Abstract
Background
Suboptimal water and nutrient availability are primary constraints in global agriculture. Root anatomy plays key roles in soil resource acquisition. In this article we summarize evidence that root anatomical phenotypes present opportunities for crop breeding.
Scope
Root anatomical phenotypes influence soil resource acquisition by regulating the metabolic cost of soil exploration, exploitation of the rhizosphere, the penetration of hard soil domains, the axial and radial transport of water, and interactions with soil biota including mycorrhizal fungi, pathogens, insects, and the rhizosphere microbiome. For each of these topics we provide examples of anatomical phenotypes which merit attention as selection targets for crop improvement. Several cross-cutting issues are addressed including the importance of phenotypic plasticity, integrated phenotypes, C sequestration, in silico modeling, and novel methods to phenotype root anatomy including image analysis tools.
Conclusions
An array of anatomical phenes have substantial importance for the acquisition of water and nutrients. Substantial phenotypic variation exists in crop germplasm. New tools and methods are making it easier to phenotype root anatomy, determine its genetic control, and understand its utility for plant fitness. Root anatomical phenotypes are underutilized yet attractive breeding targets for the development of the efficient, resilient crops urgently needed in global agriculture.
Similar content being viewed by others
Introduction
A better understanding of resource capture by plant roots is important because water and nutrient availability limit plant growth in the majority of terrestrial ecosystems. In natural ecosystems, improved understanding of this topic will expand our knowledge of key factors driving the productivity and function of these systems and will be useful in mitigating the increasingly severe consequences of global climate change and human encroachment. In managed ecosystems, such insight would create opportunities to sustain productivity despite environmental degradation and increasing population pressure. This is most clearly evident in the case of crop production. In rich nations, intensive fertilization and irrigation of crops is costly, damages the environment, depletes limited resources, and is unsustainable (Lynch 2007, 2019). In developing nations, low crop yields caused by drought and low soil fertility are primary constraints to food security, economic development, and political stability (Lynch 2007, 2019). These challenges are intensifying because of population growth, soil degradation, depletion of freshwater resources, and global climate change (Oldeman 1992; St. Clair and Lynch 2010; Mbow et al. 2019). We urgently need better crops and cropping systems that can sustain adequate yields with less demand for fertilizers and irrigation, while sustaining or improving soil fertility (Lynch 2007, 2019). Resource capture by plant roots is closely linked to soil exploration, and therefore carbon sequestration from the atmosphere, which is a promising avenue to mitigate global climate change (Kell 2011; 2012, Lynch and Wojciechowski 2015). Improved understanding of soil resource capture by plant roots is therefore an important component of the grand challenge of the twenty-first century: how to sustain 10B people while reversing environmental degradation.
While improved understanding of soil resource capture has manifold benefits, it would be directly useful in the breeding of more resource-efficient, stress-tolerant crops. The identification of traits improving soil resource capture is needed for the development of ideotypes for specific environments, for the deployment of specific traits in breeding programs (phenotypic selection), and when possible, for the use of marker-assisted or genotypic selection in molecular breeding (Lynch 2019). The large number of root traits affecting soil resource capture, and their genetic and mechanistic complexity, means that it is highly improbable to select optimal phenotypes on the basis of coarse metrics of plant performance such as yield under stress (Lynch 2019). While breeding programs that directly employ root phenotypes for improved water and nutrient capture are rare, they have been successful when attempted (e.g. Burridge et al. 2019).
In this perspective we provide an overview of root anatomical phenotypes that are potential targets to improve soil resource capture by crops. We do not attempt a comprehensive review of a very large topic, but rather highlight promising breeding targets based on the magnitude of potential benefits given natural phenotypic variation present in crops (rather than mutant studies for example), as evaluated in realistic environments, and discuss knowledge gaps and future prospects.
Soil exploration
Anatomy regulates the metabolic cost of soil exploration
The availability of water and nutrients in soil varies greatly in time and space and is often unpredictable (Lynch 2018). Soil exploration is therefore a primary challenge in plant biology. Since roots and their symbionts are heterotrophic, biomass allocation to roots reduces allocation to photosynthetic tissues, which can limit overall plant growth. This is especially true under conditions of edaphic stress, which in the case of the three primary soil resources—water, nitrogen (N), and phosphorus (P)—increases resource allocation to roots relative to shoots. For example, root maintenance respiration accounted for up to 72% of the growth reduction caused by suboptimal potassium (K) availability in maize plants in silico, and up to 38% of the growth reduction caused by suboptimal N or P availability (Postma and Lynch 2011b). The metabolic cost of soil exploration can be analyzed from the perspective of any limiting resource such as P, N, energy, or water, but is most often analyzed in the context of C fluxes and budgets, which are easier to measure than energy analogs and capture respiratory costs more readily than other currencies such as P, N, or water. More comprehensive microeconomic analyses can encompass opportunity costs, risk, and competition within and among organs and organisms (Lynch 2015). In the context of soil exploration, analysis of resource efficiency in terms of the costs of root elongation, root depth, or volume of soil explored is often useful. In accord with microeconomic theory, a plant that can acquire a limiting soil resource at reduced metabolic cost would benefit by being able to acquire more of the limiting resource as well as by having greater availability of internal resources to allocate to competing plant functions, such as the growth of photosynthetic tissue, resource storage, and reproduction.
Anatomy is a primary determinant of the metabolic costs of root construction and maintenance. Some tissues are more metabolically demanding than others. For example, mature xylem vessels and some sclerenchyma cells are dead, in contrast with xylem parenchyma or phloem companion cells which are highly active. Cell walls, cytoplasm, and vacuole have very different construction and maintenance costs. Living cell types have varying proportions of polysaccharides, protein, and nucleic acids. Some cells like cortical parenchyma are relatively expendable while others like phloem cells are critical for root function. Anatomical features like aerenchyma regulate oxygen availability and thereby respiration. By determining the proportion of living and dead cells, highly active vs. less active cells, cell composition and oxygen availability, root anatomy is a key determinant of the metabolic costs of soil exploration.
Reducing cortical burden increases soil exploration
Root cortical parenchyma is often ephemeral and has variable dimensions, suggesting that it may be reduced without loss of critical functions. Reduced metabolic costs of cortical tissue may be especially useful in monocots, which have a persistent cortex, unlike dicots, in which the cortex is destroyed in secondary growth (Postma and Lynch 2011a; Strock and Lynch 2020) (see "Secondary growth in dicotyledonous species" in this article). Jaramillo et al. (2013) measured this ‘cortical burden’ as living cortical area (LCA, i.e. transversal root cortical area minus aerenchyma area and intercellular air space), and showed that LCA is highly correlated with root respiration, and reduced LCA is associated with greater drought tolerance among contrasting maize phenotypes (Jaramillo et al. 2013). Several anatomical phenes (‘phene’ is a fundamental unit of the phenotype, as opposed to phene aggregates, sensu (York et al. 2013)) may reduce LCA, thereby reducing the metabolic cost of soil exploration, including root cortical aerenchyma (RCA), root cortical senescence (RCS), and cortical cell file number (CCFN) (Lynch 2019).
Root cortical aerenchyma (RCA) is caused by programmed cell death of cortical parenchyma, resulting in air-filled lacunae (Fig. 1). Although RCA has been primarily researched for its role in oxygenation of root tissue under hypoxia (Jackson et al. 1985), constitutive RCA formation is common in grasses. In addition to hypoxia, RCA is induced by a range of abiotic stresses (Jackson et al. 1985), including drought (Zhu et al. 2010a; Chimungu et al. 2015b), heat (Hu et al. 2014), and suboptimal availability of N (Saengwilai et al. 2014), P (Fan et al. 2007; Galindo-Castañeda et al. 2018), and S (Bouranis et al. 2003). RCA formation under edaphic stress could be adaptive by reducing the metabolic costs of soil exploration by converting living cortical parenchyma into air space, thereby reducing root nutrient content and respiration. RCA formation also reduces the radial transport of water and nutrients to the stele (Fan et al. 2007; Hu et al. 2014; Bo et al. 2014). Reduced radial transport of water may not be disadvantageous in dry soils since the majority of water uptake occurs in lateral roots (Schneider and Lynch 2018) and younger root tissue before RCA develops. Reduced radial transport offers potential benefits of parsimonious water capture under drought, which would conserve soil water for future use, and enforce more efficient use of water via reduced leaf growth and stomatal aperture. Likewise, under nutrient stress, reduced radial nutrient transport of mature root axes with RCA may not be detrimental since most nutrient capture occurs by younger root tissues and lateral roots. In silico analysis found substantial fitness benefits for RCA in maize growing in soils with suboptimal availability of N, P and K, via reduced root respiration as well as nutrient reallocation from cortical tissue (Postma and Lynch 2011a). The benefits of RCA for P capture were greater in maize than bean (Postma and Lynch 2011b), showing the importance of a persistent root cortex in monocots, as opposed to dicots, which lose their root cortex through secondary growth (Strock et al. 2018). In silico results were confirmed in empirical studies in the field and in greenhouse mesocosms under suboptimal N and P availability, where RCA formation among contrasting maize phenotypes was associated with reduced root respiration, greater root growth, greater N and P capture, better shoot nutrient status under nutrient stress, and hence greater photosynthesis, growth, and yield (Saengwilai et al. 2014; Galindo-Castañeda et al. 2018). Similar benefits were observed for RCA formation under drought stress, where greater RCA formation among contrasting maize lines was associated with reduced root respiration, greater rooting depth, better shoot water status, leaf photosynthesis, plant growth, and yield (Fig. 2; Zhu et al. 2010a). These results were supported by analysis of maize yields under natural drought environments in Malawi, which found greater yields in high RCA landraces than in low RCA landraces (Chimungu et al. 2015b). A recent study associated greater RCA with drought adaptation in specific phenotypic clusters of diverse maize inbreds (Klein et al. 2020).
Comparison of maize (Zea mays) and common bean (Phaseolus vulgaris) root cross-sections highlighting differences in the anatomical arrangement between monocotyledonous and dicotyledonous species. Dicot roots are characterized by having a vascular cambium (lateral meristem) that produces new xylem and phloem continuously through secondary growth, thereby destroying primary tissues like the epidermis, cortex, and endodermis. Contrastingly, most monocots lack a lateral meristem and have a persistent cortex that encircles a central stele containing a fixed number of metaxylem and phloem. All cross-sections are at the same scale. Scale bar = 0.5 mm
Phenotypic variation in maize for root cortical aerenchyma (RCA, a), cortical cell file number (CCFN, b) and cortical cell size (CCS, c). (d) Under water stress, genotypes with greater RCA have less respiration (nmol CO2 s–1 cm–1), deeper rooting (a, cm roots at 40–50 cm soil depth; b, c, D95, which is the depth in cm attained by the 95th percentile of roots), and greater yield (g per plant), as did genotypes with reduced CCFN (e) and greater CCS (f). Data shown are means ± SE (n = 3 or 4). Means with different letters are significantly different (P ≤ 0.05). Redrawn from Lynch (2018)
Root cortical senescence (RCS) is similar to RCA in being formed via programmed cell death but differs in having more restricted taxonomic distribution, having been reported in the Poaceae, including principal cereal crops such as wheat, barley, rye, and oat, and in causing entire loss of the cortex instead of the formation of discrete lacunae as in RCA (Schneider and Lynch 2018) (Fig. 3). As with RCA, loss of cortical parenchyma by RCS reduces root respiration and nutrient content as well as radial water and nutrient transport (Schneider et al. 2017b). In silico analysis showed that these effects would be beneficial for barley plants growing with suboptimal availability of N, P, and K (Schneider et al. 2017a). As with RCA, reduced radial water transport in older axes caused by RCS may not be detrimental under drought because such root segments are not normally active in water transport, although further research is needed (Schneider and Lynch 2018).
Schematic of RCS and soil resource capture. In edaphic stress, plants with RCS have greater root length, reduced root respiration, and reduced radial water and nutrient uptake. Greater root growth in plants with RCS is driven by savings in metabolic costs of root tissue. Reduced radial water and nutrient transport of axial root tissue after RCS has small effects on total plant nutrient uptake, as lateral roots do not form RCS and perform the majority of root nutrient and water uptake. From Schneider and Lynch (2018)
Another avenue to reduced cortical burden is simply by reducing the number of parenchyma cells in the cortex, as shown in maize, which displays substantial phenotypic variation for the number of cortical cell files in nodal roots (CCFN, Fig. 2). Among contrasting maize phenotypes under drought stress, reduced CCFN was associated with reduced root respiration, greater rooting depth, better water capture from deep soil, better shoot water status, leaf photosynthesis, growth, and yield (Lynch et al. 2014). In silico analysis suggests similar benefits under suboptimal availability of N, P, and K (Yang et al. 2020).
RCA, RCS, and CCFN all affect living cortical area- the symplastic area of the cortex as observed in cross sections. An alternative avenue to reduced cortical burden without concomitant reduction of root diameter is by enlarging cortical cell size (CCS, Fig. 2), since larger cells have proportionately greater vacuole/cytoplasm volume, given that the cytoplasm is much more metabolically active than the vacuole. Among contrasting maize phenotypes under drought stress, greater CCS was associated with reduced root respiration, greater rooting depth, better water capture from deep soil, better shoot water status, leaf photosynthesis, growth, and yield (Chimungu et al. 2014a). In silico analysis suggests comparable benefits under suboptimal availability of N, P, and K (Yang et al. 2020). Larger CCS in wheat grown in compacted soils reduced root respiration by ~ 50% and improved penetration of hard soils (Colombi et al. 2019).
Taken as whole, the fact that RCA, RCS, CCFN, and CCS all improve the capture of soil resources supports the proposal that anatomical phenotypes that reduce the metabolic costs of soil exploration, by reducing nutrient content and respiration, promote greater soil exploration and therefore are beneficial under drought and low soil fertility. It is noteworthy that comparable benefits were observed in maize for greater RCA, reduced CCFN and larger CCS under drought despite the fact that these three phenes are under distinct genetic and developmental regulation (Chimungu et al. 2014a, b, 2015a, b; Lynch et al. 2014) (Fig. 2). Benefits of RCA for N (a mobile resource) and P (an immobile resource) capture in low fertility soil are congruent with benefits for water capture under drought. Comparable benefits were observed in the field, in greenhouse mesocosms with simplified soil biota, and in silico, which is a highly simplified environment that serves to test the adequacy of a logic model.
Secondary growth in dicotyledonous species
In dicotyledonous species, secondary growth causes thickening of roots as they age and develop (Fig. 4). Radial expansion is a result of cellular divisions that occur within the vascular cambium and cork cambium (or phellogen) (Fig. 1; Evert and Eichhorn 2006). The deposition of secondary tissues produced by these cambia ultimately cause the destruction of the primary root tissues (epidermis, cortex, and endodermis) (Dickison 2008). The formation of these secondary tissues includes metaxylem vessels that are produced centripetally (inside) and phloem centrifugally (outside) to the vascular cambium, while a protective tissue called phellem is produced centrifugally to the cork cambium (Sanio 1873; Larson 1994; Evert and Eichhorn 2006; Smetana et al. 2019). In annual dicotyledonous crops like Phaseolus species, most of the root thickening from the production of these secondary tissues is driven by the production of metaxylem elements and parenchyma centripetally to the vascular cambium (Strock and Lynch 2020). These dramatic anatomical changes that occur via secondary development effectively shift the functional role of a root from soil resource capture to axial transport of water and nutrients (Fig. 4; McCully 1999a; Steudle 2000; Strock et al. 2018). Specifically, the destruction of the primary tissues and deposition of heavily lignified and suberized secondary tissues decrease the absorptive capacity of roots as they age while the production of metaxylem increases capacity for axial conductance (Bouma et al. 2001; Volder et al. 2005; Guo et al. 2008; Rewald et al. 2011). From a functional perspective, this restriction of radial transport may serve an important role in preserving the integrity of the vasculature under drought by hydraulically isolating older root segments from drying surface horizons and preventing leakage and air seeding through pit membranes (Sperry and Saliendra 1994; Hacke and Sperry 2001; Zwieniecki et al. 2002; Cuneo et al. 2016). Additionally, the production of these secondary tissues serves to provide mechanical support for the growing shoot and increase resistance to edaphic herbivores and pathogens (Eissenstat 1992; Valenzuela-Estrada et al. 2008; Gerrienne and Gomez 2011; Hoffman and Tomescu 2013).
Modified from Strock and Lynch (2020)
Diagram summarizing the relationships between secondary growth of roots and soil resource acquisition, metabolic costs, and interactions with soil organisms. Images of cross-sections from roots of common bean (Phaseolus vulgaris). All cross-sections are at the same scale. Scale bar = 0.5 mm.
As the heavily lignified and suberized periderm is developed during secondary growth, radial transport of water and nutrients restricted, and the periderm also plays a significant role in protecting the root from biotic stress (Eissenstat 1992; Guo et al. 2008; Valenzuela- Estrada et al. 2008; Rewald et al. 2011). Deposition of suberin in this secondary tissue is a key component in inhibiting penetration by soil pathogens such as Phytophthora (Lulai and Corsini 1998; Valenzuela-Estrada et al. 2011; Machado et al. 2013), and in Malus domestica the intensity of pathogen colonization in roots was closely linked to the senescence and loss of the cortex (Emmett et al. 2014). Secondary growth also impairs the formation of mycorrhizae. In Vitis ssp., root age significantly affects formation of arbuscular mycorrhizae, where younger roots have more arbuscules and older roots have more vesicles and/ or spores (Vukicevich et al. 2019). Under phosphorus deficit, secondary growth of P. vulgaris roots is suppressed, thereby prolonging AM (Strock et al. 2018). Valenzuela-Estrada et al. (2008) similarly observed in Vaccinium ssp. that roots with greater radial growth had less mycorrhizal colonization.
In most plants, activity of the vascular cambium is indeterminate, suggesting that the process of secondary growth is regulated by homeostatic mechanisms (Tomescu and Groover 2019). While the constitutive nature of secondary growth in dicot roots suggests that this process increases fitness in most environments, a significant level of plasticity in the meristematic activity of the vascular cambium does afford the capacity to respond to the environment (Brewer et al. 2013; Strock and Lynch 2020). In some environments, root secondary development can hinder overall plant growth as radial expansion increases root metabolic and construction costs. Specifically, as secondary growth progresses, the metabolic (i.e. carbon, nutrient and energy) costs of producing and maintaining root length increase, and it has been proposed that suppression of secondary growth in some environments may be an adaptive strategy to improve the metabolic efficiency of soil exploration (Lynch 1995, 2007; Lynch and Brown 2008; De la Riva and Lynch 2010; Strock et al. 2018; Strock and Lynch 2020). Allocation of resources to greater total root length rather than radial thickening facilitates greater exploration of soil domains where resources are more abundant. Even small changes in the density of root tissue can have significant effects on the soil volume explored per unit of carbon invested (Ma et al. 2018). For example, under P deficit, suppression of secondary growth is associated with greater root elongation, increased soil exploration and greater phosphorus acquisition (Strock et al. 2018).
Reallocation of resources within a plant is a hallmark adaptive response to nutrient stress (Fohse et al. 1988), and further investigation into the effect of nutrient and water limitation on secondary growth of roots is warranted. While the influence of radial thickening of roots on metabolic and construction costs is obvious, because secondary growth affects multiple aspects of root function, the utility of suppressing this developmental process could be limited to specific environments. Thin roots with a low tissue density are more metabolically efficient in soil exploration, but have less hydraulic conductance, root longevity, and ability to penetrate strong soils (Bengough et al. 2006; Strock and Lynch 2020). Targeted studies exploring how abiotic and biotic factors affect this process, as well as the relevance of secondary growth in roots to fitness of annual dicotyledonous crop species under stress, are needed. Interactions between root secondary growth, edaphic conditions and soil resource acquisition may have significant effects on plant fitness. Specifically, the implications of secondary growth for resource capture, axial transport, metabolic costs and interactions with soil organisms in roots of annual crops are important research foci that warrant investigation (Strock and Lynch 2020).
Thicker cortical cell walls/apoplastic phenes
The primary cell wall is constructed during cell division and is extended during cell expansion (Cosgrove 1999, 2005; Höfte and Voxeur 2017; McQueen-Mason and Cosgrove 1995; Zhong et al. 2019). In roots, secondary cell walls are deposited in mature cells depending on the cell type, e.g. xylem tracheids have thicker secondary cell walls as compared to cortical parenchyma (Zhong et al. 2019) and secondary walls occupy most of the apoplastic volume in mature roots. Secondary cell walls are mainly composed of cellulose, hemicellulose, lignin, and pectin (Somssich et al. 2016; Zhong et al. 2019). Dicots have higher pectin percentage while in monocots the role of pectin is replaced by glucoronoarabinoxylan (Carpita 1996; Carpita and Gibeaut 1993; Jarvis et al. 1988; Riboulet et al. 2008). Because cell walls are rich in carbohydrate, they require significant initial carbon and energy investment, but because they have low metabolic activity, are not costly to maintain. We propose that the maintenance cost of the cell walls would be much less than the cost of maintaining a similar volume of living cell lumen. Therefore, cell wall volume and composition may influence the metabolic costs of soil exploration, by analogy with root cortical phenotypes (see "Reducing cortical burden increases soil exploration").
Root hairs
Root hairs are subcellular outgrowths of root epidermal cells that are present in nearly all land plants (Fig. 5). Their role in nutrient acquisition, soil adhesion, and microbe interaction has been postulated for nearly a century (Comber 1922). Early reports indicate that a single rye plant could have as many as 4 billion root hairs, leading to an increase in surface area of 400 m2 (Dittmer 1937). Root hairs have long been known to play an important role in nutrient uptake, especially phosphate, as found through modeling and empirical studies (Bouldin 1961; Nye 1966; Barley and Rovira 1970; Bhat and Nye 1974; Itoh and Barber 1983). As phosphate is immobile in soil and the soluble phosphate pool is slowly replenished, a root must access new pools of phosphate by coming into contact with soil which has not been recently depleted of phosphate (Barber 1995). New root growth into these areas can be costly, but root hair growth has low carbon costs and can allow for an increase in the size of the depletion zone at little cost to the plant (Bates and Lynch 2000). Potassium is also immobile in soil, though to a lesser extent than phosphate, and root hairs contribute to uptake in a similar fashion (Jungk 2001). Similarly, uptake of zinc in barley was inhibited in a hairless mutant (Genc et al. 2007).
Importance of root hairs and rhizosheaths in improving nutrient uptake and plant performance. A) Scanning electron micrograph of root hair less mutant (Rht-1). B) Scanning electron micrograph of wild type – B73, compare the density and length of root hairs with Rht-1. C) None to bare minimum rhizosheath formation on the Rht-1 root and D) Root hairs promoting rhizosheath formation in wild type B73. Increased rhizosheath formation improves nutrient uptake e.g. P, Zn and improves stress tolerance e.g. drought
The advantage of increased root hair length and density for phosphate acquisition has been shown in a number of species, through both the use of mutant studies and analysis of natural phenotypic variation (Gahoonia and Nielsen 1997, 2004; Gahoonia et al. 2001; Bates and Lynch 2001; Zhu et al. 2005; Nestler and Wissuwa 2016). The longevity of an individual root hair, generally thought to be active for less than 48 h, is a trait that has been studied less, and its contribution to nutrient acquisition is not as well understood but could be beneficial in specific soil conditions (Brown et al. 2013). In addition to being beneficial for nutrient acquisition, root hairs are also highly responsive to their surrounding environment. Root hairs of multiple species, including Arabidopsis and maize, become longer and denser under P stress (Foehse and Jungk 1983; Bates and Lynch 2000; Ma et al. 2001a, b; Zhu et al. 2010a, b; Vejchasarn et al. 2016; Giri et al. 2018). In silico analysis showed that increased root hair length and density (and in Arabidopsis, the position and geometry of their initiation) are synergistic for P capture, i.e. their benefits for P capture are much greater in combination than in isolation (Ma et al. 2001b). Other nutrient stresses, including iron (Müller and Schmidt 2004), manganese (Wei Yang et al. 2008), ammonium (Liu and von Wirén 2017), and nitrate (Canales et al. 2017) alter root hair length and/or density. The root hair growth response is rapid in response to low P (Bhosale et al. 2018; Janes et al. 2018). The majority of our understanding of root hair growth and P responses derives from problematic artificial growth systems (Nestler et al. 2016; Hanlon et al. 2018) using Arabidopsis, which has a unique root hair formation pattern and is non-mycorrhizal (Pemberton et al. 2001; Dolan 2017).
Root hairs have also been implicated in the acquisition of water and mobile soil resources. Recent work has shown that root hairs reduce the drop in matric potential at the root surface, leading to increased water uptake (Carminati et al. 2017). Increased root hair length and density enhanced water acquisition in barley in droughted field conditions, conferring a yield advantage (Marin et al. 2020). The specifics by which root hairs impact water acquisition are confounded by multiple factors, including differences in water uptake at different times of day (Carminati et al. 2017), differences in osmotic potential at the root surface due to nutrient concentration (Carminati et al. 2017), and differences in evaporative demand (Dodd and Diatloff 2016). The role of root hairs in water uptake is directly related to rhizosheath formation (Rhizosheaths). Further understanding of the interplay of root hairs and rhizosheaths is necessary to understand how water uptake and soil contact occurs at the root surface. Root hair length and density are both increased under low nitrogen availability in maize (Gaudin et al. 2011). In Arabidopsis, different accessions have differential root hair length and density responses to nitrogen conditions dependent on the form (ammonia versus nitrate) (Vatter et al. 2015). However, no work has yet shown a direct link between root hair traits and nitrogen acquisition. Investigation of root hair traits in leguminous species such as soybean, alfalfa, pea or bean may be further complicated by rhizobial symbiosis, as the root hair is the starting point for these interactions (Ibáñez et al. 2017).
In addition to their direct benefits for soil resource capture, root hairs contribute to the formation of rhizosheaths (see "Rhizosheaths") and have been proposed as being important for the penetration of root axes into hard soil (see "Anatomical phenes that improve adaptation to soil mechanical impedance").
Many studies investigating the functional role of root hairs have been completed using root hairless mutants, such as brb in barley and rth1-rth6 in maize. Though these allow for targeted experimental design, they fail to consider pleiotropic effects of the genetic mutation and the complex roles of root hairs in maintaining a normal plant-soil interface. In maize, rth1 has short root hairs, but a dwarf phenotype (Wen and Schnable 1994). The rth3 mutant in maize lacks root hairs, has no obvious aberrant shoot phenotypes, but has greatly reduced yield (Hochholdinger et al. 2008). The rth3 mutant has altered root system architecture, forming many more fine roots (Klamer et al. 2019). The brb mutant lacks apoplastic barriers (Burke et al. 2020), which could greatly alter patterns of hydraulic flow and nutrient uptake as compared to its wildtype counterpart, and has altered root architecture (Dodd and Diatloff 2016). The brb mutant can effectively replace root hairs with mycorrhizal interaction (Jakobsen et al. 2005), though the complexities of this relationship across species and in naturally varying populations is less well understood (Maherali 2014). A different set of mutants in barley that alter root hair formation and growth have been isolated, though these have not been studied extensively in terms of nutrient responses or acquisition (Chmielewska et al. 2014). One of the isolated mutants, rhs1.a, had pleiotropic growth effects, similar to what had been seen with rth1 in maize (Chmielewska et al. 2014). Root hairs, mycorrhizae, and rhizosphere development may all have overlapping roles in nutrient acquisition at the root surface, but our standard methods by which we study these relationships may currently be lacking. Using the hairless rth3 mutant of maize, Kumar et al. (2019) found plants had increased mycorrhizal colonization, presumably to increase P acquisition in the absence of hairs. The rth3 plants also had more fine lateral roots, indicating that these mutations can impact the entire root architectural system and are not solely isolated to root hairs. As root hairs are only one mechanism by which plants obtain nutrients from soil, they must be considered within this larger context. Exploiting natural variation in crop plants, including bean, maize, and rice may allow for targeted selection and improvement in the field, as well as a more nuanced understanding of how natural variation for root hair phenotypes contributes to resource capture (Brown et al. 2013; Lynch 2019; Burridge et al. 2019).
Rhizosheaths
Rhizosheaths are sheaths of small soil aggregates adhered to an immature root surface (Fig. 5; McCully 1999b). Rhizosheaths form up to 5 cm basipetal to the root tip (depending on the root elongation rate) and this zone can be 15–30 cm long (McCully 1999b; St. Aubin et al. 1986; Watt et al. 1994). They are generally identified by carefully excavating roots from soil and then shaking the loose soil, with remaining soil adhering to roots being considered rhizosheath (McCully 1999b). Rhizosheaths were first reported in desert taxa (Wullstein and Pratt 1981) but now have been reported in many mesophytic grass taxa (Bailey and Scholes 1997; Duell and Peacock 1985) including principal crops like wheat (Basirat et al. 2019; James et al. 2016), barley (Haling et al. 2014), rice (Zhang et al. 2020), maize (McCully 1999b; St. Aubin et al. 1986), foxtail millet (Liu et al. 2018) and sorghum (Duell and Peacock 1985).
Mucilage released by epidermal cells and border cells along with root hairs play major roles in the formation of rhizosheaths (McCully 1999b). Mucilage released by the border cells is believed to first act as a lubricant for tip growth and assists rhizosheath development (Watt et al. 1994). Alternate wetting and drying of mucilage give rise to its important adhesive properties (Watt et al. 1993, 1994), which leads to adherence of soil aggregates to roots as well to each other (Fig. 5B). Selecting for mucilage phenes is challenging because not much is known about the genetics of mucilage secretion that can be directly applied in breeding (Vermeer and McCully 1982).
Root hair length is related to rhizosheath size to different degrees in different species; however, root hair presence is required for the maximum expression of the rhizosheath (Haling et al. 2014; George et al. 2014; Delhaize et al. 2015; Brown et al. 2017) although root hair length may not improve rhizosheath mass (Brown et al. 2017). In contrast, other studies in wheat (Haling et al. 2010) and barley (Brown et al. 2012) showed that root hair length improves rhizosheath mass. The link between root hair length and rhizosheath formation deserves further investigation. Increasing the size of the rhizosheath may contribute to increased water uptake and resistance to soil drying (Choi and Cho 2019; Basirat et al. 2019). Root hairs and rhizosheaths improve plant performance under low phosphorus conditions (Brown et al. 2013; Nielsen et al. 1998; Zhu et al. 2010a, b), aluminum stress (Delhaize et al. 2015, 2012), combined low P and drought stress (Brown et al. 2012), and assist in associative nitrogen fixation (Bergmann et al. 2009). Root hairs release exudates, including phosphatases, that mineralize phosphate and promote interactions with soil microbes (Holz et al. 2017, 2020; McKay Fletcher et al. 2020). The extent to which a plant can capture P from surrounding soil is greater than the individual contributions of either root hairs or rhizosphere formation, indicating a synergistic relationship between the two components (Holz et al. 2020). This highlights the importance of root hairs for rhizosheath formation and function, reinforcing their potential value as selection targets for crop improvement (Lynch et al. 2014).
Other major functions of the rhizosheath include providing a habitat for microorganisms (Vermeer and McCully 1982) and improved acquisition of nutrients like zinc (Nambiar 1976). It is also known to help plants better tolerate acidic soils (Delhaize et al. 2015, 2012), and mechanical stress (Haling et al. 2014, 2013). Most of these functions are attributed to the rhizosheath’s property of maintaining contact between the soil and roots (Fig. 5C). The exact mechanism by which the rhizosheath can improve plant performance is poorly understood. For example, the mucilage in the rhizosheath improves water holding capacity of this zone (Watt et al. 1993; Young 1995) and reduces the risk of an air gap between soil and roots (McCully 1995; Walker et al. 2003), suggesting a role of the rhizosheath in improving plant performance under drought stress, first proposed over a century ago (Price 1911). Recent research has shown that wheat cultivars with greater rhizosheath formation had sustained transpiration rates under drought stress as compared to genotypes with less rhizosheath formation (Basirat et al. 2019). The observation that xylem vessels in the rhizosheath zone are still alive and are not conductive (McCully 1999b) suggests that one benefit may be the maintenance of hydration of the growing root tip and surrounding soil. It has been proposed that greater length of the immature vessel zone may increase the length of rhizosheath and thereby affect plant performance under abiotic stress (Lynch et al. 2014). This merits investigation.
Anatomical phenes that improve adaptation to soil mechanical impedance
Soil mechanical impedance limits root growth and elongation, soil quality, and crop production globally (Whalley et al. 2005; Lipiec et al. 2012; Bengough et al. 2011). Root phenotypes that are able to overcome impedance have an advantage in water and nutrient capture at depth, improving plant performance in edaphic stress (Barraclough and Weir 1988; Ishaq et al. 2001; Lynch 2018). Physical soil properties influence mechanical impedance including soil water content, texture, bulk density, and overburden pressure due to depth (Gao et al. 2015; Vanhees et al. 2020). In most soils, soil strength and therefore mechanical impedance increases with decreasing water content (Whalley et al. 2005), and is therefore synergistic with water deficit stress (Bengough et al. 2011). Soil compaction causes impedance by increasing soil bulk density while reducing porosity and pore connectivity (Chen et al. 2014a) and therefore increases the risk of hypoxia by reducing hydraulic conductivity and air permeability (Chen et al. 2014a). In addition, in soils with limited well-connected macropores, root growth may further compact the rhizosphere (Lucas et al. 2019a). Root phenes that place roots in deeper soil strata may also aid in the avoidance of soil hardening in drying topsoil (Lynch 2013). Roots have innate characteristics that enable them to penetrate hard soils. Roots that are less likely to buckle, provide root tips better anchorage, or better locate biopores and cracks in the soil may be advantageous in environments with mechanical impedance (Whiteley et al. 1982). In hard soils, maize increased the proportion of coarse roots (Vanhees et al. 2021b) and roots were larger in diameter (Lucas et al. 2019a). In maize, deeper-rooting plants in hard soils were associated with increased cortical cell file number, greater mid-cortical cell area at node three and greater crown root cortical aerenchyma formation at node four (Vanhees et al. 2020), and the formation of multiseriate cortical sclerenchyma (Schneider et al. 2021). Intraspecific variation in root penetration ability has been observed in maize (Bushamuka and Zobel 1998; Chimungu et al. 2015a), lupin (Chen et al. 2014b), rice (Yu et al. 1995; Price et al. 2000), cotton (Taylor and Kasperbauer, 1999), wheat (Kubo et al. 2006; Botwright Acuña et al. 2007), soybean (Bushamuka and Zobel 1998), and common bean (Rivera et al. 2019). Genetic diversity for penetration of hard soils gives potential for trait discovery.
Root diameter
Root anatomical phenes influence penetration ability in impeded soils (Vanhees et al. 2020). For example, cortical cell thickness, cortical cell count, cortical cell wall area, and stele diameter are all associated with increased root penetration and bend strength (Fig. 6; Chimungu et al. 2015a). Generally, thicker roots have greater penetration ability in hard soils as they are more resistant to buckling and deflection (Whiteley et al. 1982; Jin et al. 2013). Root thickening in response to impedance involves both changes in the underlying tissues and cellular structures in both the cortex and stele. In response to compaction, the formation of coarse roots, addition of cell layers (Colombi et al. 2019) or the expansion of cortical cells (Atwell and Russell 1989; Colombi and Walter 2017; Colombi et al. 2019; Vanhees et al. 2021a, b) have been observed. In wheat, root cross-sectional area, stele and cortical area, root cortical aerenchyma, and cortical cell size and file number were plastic in response to impedance, and these responses were genotype and root class specific (Colombi and Walter 2017). Classically, radial expansion in response to mechanical impedance has been assumed to enhance soil penetration. However, recent studies have demonstrated that root thickening is not associated with rooting depth in compacted soils (Vanhees et al. 2020). Ethylene may signal the root to radially thicken in response to compaction and may act as a stop signal for axial root growth (Vanhees et al. 2021a). Compacted soil reduces ethylene diffusion and therefore increases the concentration of ethylene near root tissues. A signalling cascade triggered by the accumulation of ethylene may impede root growth through hard soil (Pandey et al. 2021).
Roots with a greater root diameter, greater stele area, many cortical cell files, small cortical cells in the outer cortex, and a small root tip radius to length ratio enhance root penetration in hard soils
In addition to radial thickening rendering roots more resistant to buckling, it has also been speculated that thickening may facilitate root anchorage to enable root penetration in strong soils. The anchorage of roots may be accomplished by friction of soil particles and maturing tissues through the production of root hairs and lateral roots behind the zone of elongation. Root anchorage may support the maximum growth pressure (i.e. growth force exerted by the root per unit cross-sectional area), which is largely driven by turgor pressure in the expanding cells at the root elongation zone, to force the root tip further into strong soils (Bengough et al. 2011; Lynch and Wojciechowski 2015). Radial thickening of the root through an increase in the number of cell files, cell size, or cell wall thickening is speculated to relieve stress from the root tip by deforming the soil near the root tip allowing penetration into compacted soil (Atwell 1993; Smith 2007). When a root encounters impeded soil, radial thickening occurs within the elongation zone and the elongation zone becomes shorter (Bengough et al. 2006). In response to mechanical impedance, the cell walls in the axial direction of the elongation zone stiffen and increase tension (Bengough et al. 2006). The elongation zone shortens upon mechanical impedance presumably due to decreased cell wall extensibility in the axial direction while the local growth rate is maintained at the apical end of the elongation zone (Bengough et al. 2006; Spollen and Sharp 1991). Upon exposure to mechanical impedance, root diameter may increase up to twofold due to radial expansion of cortical cells caused by microfibril reorientation in the primary cell wall (Veen 1982). This smaller elongation zone under mechanical impedance will produce shorter cells with a larger diameter (Bengough et al. 2006; Colombi et al. 2019). Increased root diameter in response to impedance (Atwell 1993; Pfeifer et al. 2014; Colombi and Walter 2015) may be accompanied by decreases in cell division (Clark et al. 2003) and therefore root elongation (Atwell 1993; Smith 2007). Therefore, increasing penetration resistance results in decreased root elongation (Colombi et al. 2019; Vanhees et al. 2020). Root thickening is often considered to be adaptive, however, increased root diameters are associated with greater energy costs for root elongation and growth and may be node-dependent (Yang et al. 2019; Vanhees et al. 2020; Colombia et al. 2019). Root thickening has been primarily observed on small, seedling roots. However, in maize, thinner (seedling) roots may have a greater propensity to thicken when compared to younger, thicker roots of older plants. As roots from younger nodes are innately thicker, these roots may experience less impedance stress than thinner, older roots. Root thickening is node-specific, dependent on root anatomy, and may be obscured by allometric effects. In future studies it will be important to distinguish between the utility of innately thicker roots that have the capability to grow under mechanical impedance and roots that thicken as a reaction to mechanical impedance.
Studies of mechanically impeded soils in controlled growth conditions often involve repacking soil in pots, which not only changes the soil bulk density but also significantly changes the soil structure including pore size and continuity. Altering soil structure, and therefore pore characteristics and air permeability can have significant effects on root growth (Lipiec and Hatano 2003). In dense repacked soils, roots have a limited ability to locate existing macropores and soil aeration was reduced (Lucas et al. 2019a). Soils with a high bulk density (> 1.60 g cm−3) did not limit root growth in the field, but limited root growth in repacked soils (Lucas et al. 2019b). In the field highly connected pore systems enable roots to bypass zones of high mechanical impedance (Colombi et al. 2017b; Stirzaker et al. 1996). Soil structure including pore size and connectivity should be considered as an important mechanism for deep rooting in hard soils. Soil structure disruption in repacked soils should also be considered when interpreting results from controlled experiments.
Root tip
For a root to penetrate soil, it requires pressure to expand the cavity in the soil and to overcome the frictional resistance between the root and the soil. The cavity expansion pressure is primarily determined by the shape of the root tip, its rate of penetration, and soil mechanical properties. Generally, more narrowly pointed root tips are more efficient in cylindrical deformation of soil, whereas more blunt root tips have less efficient spherical-like soil deformation (Bengough et al. 1997). In hard soils, a smaller root tip radius to length ratio was associated with greater root elongation rates by reducing root penetration stress (Fig. 6). However, root tips do not become more acute in response to mechanical impedance (Colombi et al. 2017a). Changes in the mechanical properties around the root tip including hydraulic or water release properties of the rhizosphere may occur through root mucilage or other rhizodeposits (Read et al. 2003; Whalley et al. 2005; Carminati et al. 2010). In addition, rhizodeposits may also interact with charged clay particles at the root tip to alter viscosity (Barré and Hallett 2009). A better understanding of mucilage and exudate interaction with the soil at the root tip will be important to understand root penetration in impeded soils. In addition, the frictional resistance between the root and the soil may account for up to 80% of the total penetration resistance (Bengough et al. 1997). However, the frictional resistance between the root and soil may be reduced through lubrication by border cells and mucilage production (Bengough et al. 2011) which largely explains why penetrometer resistance is typically five times greater than root penetration resistance (Bengough and Mullins 1990). Under increasing mechanical impedance roots produce more border cells and mucilage to better facilitation root penetration (Barber and Gunn 1974; Iijima et al. 2000).
Multiseriate cortical sclerenchyma
Sclerenchyma are complexes of thick, lignified cell walls that enable plant organs to withstand stretching, bending, and pressure strains (Evert and Eichhorn 2006). The size and composition of peripheral cortical cell files have been shown to be important for soil penetration (Lux et al. 2010; Chimungu et al. 2015a). Outer cortical tissues in roots may consist of a hypodermis in several cortical cell files and centripetally developed internal sclerenchyma layers (Lux et al. 2010). Multiseriate Cortical Sclerenchyma (MCS) is characterized by small cells in the outer cortex that have thick cell walls impregnated with lignin, and has utility in environments with greater mechanical impedance (Schneider et al. 2021). MCS is genetically controlled and displays variation in several Poaceae species including maize, wheat, barley, and sorghum. In maize and wheat, MCS enhanced cortical tensile strength and bending force of the root tip which increased penetration in mechanically impeded soils (Fig. 7). Greater penetration ability in strong soils enabled greater root depth distribution and greater shoot biomass in compacted soils.
A) Multiseriate cortical sclerenchyma (MCS) is characterized by small cells with thick cell walls in outer cortical cells. Genotypes with MCS have a B) greater root tensile stress, C) penetration ability in compacted soils, and therefore a D) greater plant performance in compacted soils when compared to genotypes with no MCS. Penetration ratio is measured as the ratio of the number of roots penetrating the hard layer to the number of roots reaching the hard layer per plant. Data is summarized from Schneider et al. (2021)
Roots with MCS have greater lignin concentration. Lignification is associated with mechanical support, water transport through xylem, and defense against pests and microorganisms (Boudet 2000). Lignin is primarily deposited in secondarily thickened cell walls rendering them rigid and impervious and improving the mechanical strength of the cell wall (Janssen 2000). Lignin concentrations are elevated in several root tissues including the endodermis, exodermis, and hypodermis. In barley, compacted soils increased root lignin concentrations (Scippa et al. 2008; Bingham et al. 2010; Bingham and Bengough 2003). Increases in lignin concentration are associated with increased root tensile strength and therefore penetration of hard soils (Zhang et al. 2014; Chimungu et al. 2015a).
It will be important to understand phenotypes that are capable of penetration under dynamic stresses, for example water deficit in compacted soils. A strategy for water capture in compacted soils may be to develop MCS for greater penetration ability and subsequently greater root depth or exploit paths with reduced resistance including cracks and biopores.
Anatomical phenes for transport
Metaxylem
Xylem vessels are responsible for the bulk of axial transport of water and nutrients through the root system. Xylem vessels are located within the root stele, which is enclosed by the pericycle with a single layer of endodermis and the Casparian band that restricts the radial movement of water and nutrients (Evert and Eichhorn 2006). Throughout root development, two types of xylem vessels are formed: the narrow protoxylem vessels, which are first differentiated in immature root tissues, and the larger metaxylem vessels that provide greater capacity for axial transport as the root matures (Evert and Eichhorn 2006). In monocotyledonous species lacking secondary growth, the axial transport capacity of the root is fixed following the maturation of metaxylem beyond the elongation zone. These metaxylem vessels provide the majority of axial transport capacity in the root system with smaller contributions from the protoxylem (Evert and Eichhorn 2006; Carlquist 2012). In contrast, through secondary growth, roots of dicotyledonous species have the capacity for continued production of xylem, thereby augmenting axial transport capacity throughout their phenology (Fig. 1; Evert and Eichhorn 2006; Strock and Lynch 2020).
The capacity for axial transport through the root is largely determined by the number and size of xylem vessels, and substantial intra- and inter-specific variation for root vasculature phenotypes has been reported in several agronomically important species (Fig. 8A-D; Purushothaman et al. 2013; Kadam et al. 2015; Oyiga et al. 2020; Klein et al. 2020; Strock et al. 2021). Genetic variation for xylem vessel size and number is probably linked to other physiological components of water transport, and in turn, can have significant implications on water use strategies (Fig. 8E-G; Sperry and Saliendra 1994; Gallardo et al. 1996; Purushothaman et al. 2013). This concept is reflected in the geographic distribution of many species, where plants with a larger transport capacity (i.e. many, large xylem vessels) tend to be endemic to environments with wet, humid conditions while plants with a smaller transport capacity (e.g. fewer, narrower xylem vessels) are distributed in more xeric environments (Tyree et al. 1994; Purushothaman et al. 2013).
Modified from Strock et al. (2021)
Comparison of common bean (Phaseolus vulgaris) (A, B) and maize (Zea mays) (C, D) root cross-sections highlighting genetic variation within each of these species for the number and size of xylem vessels. All cross-sections are at the same scale. Scale bar = 0.5 mm. (E–G) This variation in xylem number and size affects axial hydraulic conductance capacity of the root system and can relate to differences in net transpiration rate (mmol m−2 s − 1) of common bean (Phaseolus vulgaris) and tepary bean (Phaseolus acutifolius) accessions with contrasting conductance under terminal drought stress at 13 (E), 27 (F), and 41 days after planting (G). Values shown are mean ± SE. Comparisons are made using ANOVA and Tukey's HSD across species and phenotypic groups within each timepoint. * indicates significant species differences and † indicates significant phenotypic differences at α ≤ 0.05.
The Hagen-Poiseuille formula demonstrates that the axial flow rate of water through a conduit is proportional to the fourth power of its radius, thus small increases in metaxylem radii translate to substantial increases in axial conductance capacity (Lewis and Boose 1995; Hacke et al. 2017). Roots with few, narrow xylem vessels have reduced capacity for axial transport and therefore require a larger water potential gradient between the soil and atmosphere to transport an equivalent volume of water as roots with many, wider xylem vessels. Several studies have linked improved drought tolerance to root phenotypes where metaxylem are narrower (Richards and Passioura 1989; Abd Allah et al. 2010; Purushothaman et al. 2013; Klein et al. 2020) and more abundant (de Souza et al. 2013; Oyiga et al. 2020; Klein et al. 2020). This may be because narrow vessels that restrict axial transport capacity improve water use efficiency by simultaneously reducing the overall shoot size and limiting transpiration by reducing stomatal conductance (Lynch et al. 2014; Vadez et al. 2014). Narrow root metaxylem that restrict net water use may be beneficial under terminal drought by limiting water use early in the growing season, thereby increasing the availability of water during reproductive growth (Zaman-Allah et al. 2011; Feng et al. 2016). Metering water transport in environments with limited water availability may also help moderate desiccation of root tips and the surrounding rhizosphere, thereby allowing continued soil exploration later in the season (Richards and Passioura 1989; Vadez 2014; Lynch et al. 2014; Strock et al. 2021).
In Phaseolus species with shallow root length distribution, fewer, narrower root metaxylem vessels were associated with superior plant water status under terminal drought, suggesting adaptation to drought through a strategy of conserving soil water (Fig. 8A, B, E–G; Strock et al. 2021). Computer modeling of maize root systems also revealed that roots with reduced hydraulic conductance were associated with water saving behavior while roots with greater conductance enabled a high initial transpiration rate that decreased rapidly as soil moisture was depleted (Leitner et al. 2014). However, severely diminished flow rates of small vessels may risk limiting maximum yield potential or relative growth rate in non-stress conditions (Wahl and Ryser 2000). Nevertheless, in Australia where wheat is grown on stored soil water, a narrowing in the metaxylem of seminal roots was related to greater wheat yields under drought with no yield penalty under optimal watering (Richards and Passioura 1989), possibly because of compensating conductance by nodal roots.
In addition to improving water use efficiency, narrow root metaxylem are also more resistant to hydraulic dysfunction from cavitation (Hacke and Sperry 2001; Sperry et al. 2006), a common occurrence in dry soils where there is greater tension of xylem sap. High rates of drought-induced cavitation can greatly impair biomass accumulation (Williams et al. 1997; Gitz et al. 2015) and is a direct cause of mortality in trees (Barigah et al. 2013). Though cavitation has been observed in the roots of herbaceous annuals (McCully et al. 1998) and has been shown to weaken the overall hydraulic system of non-resilient species (Hacke et al. 2001), it is unclear whether cavitation significantly hinders productivity of annual crops. Because drought-induced cavitation results from air-seeding at the interconduit pits, the pit membrane anatomy, such as the pit pore size or total pit area, may play a more direct role in vulnerability to cavitation than xylem vessel diameter (Wheeler et al. 2005; Hacke et al. 2006; Sperry et al. 2006).
While narrower metaxylem vessels that meter water use may be adaptive under water-limited conditions, restricted axial transport can also have ancillary effects on acquisition of other soil resources. Suppressed extraction of water from the rhizosphere may reduce nutrients delivered via transpiration-driven mass flow (Chapman et al. 2012; Lynch 2019). Therefore, it may be advantageous to couple the restrictive root metaxylem phenotype with augmented ion uptake kinetics (Kelly and Barber 1991; York et al. 2016) and root architectural phenotypes that optimize root foraging in resource-rich soil domains. The ‘steep, cheap and deep’ ideotype would improve N capture by facilitating deeper root growth (Lynch 2013) whereas Mg and Ca acquisition would be aided by root architectures optimized for topsoil foraging (Lynch 2019). In contrast, acquisition of nutrients bound to soil constituents and taken up by diffusion, like P and K, is less affected by restricting water extraction. Their uptake is more dependent on root architectural phenotypes that maximize exploration in the topsoil where these resources are more bioavailable (Lynch and Brown 2001; Ho et al. 2005; Lynch 2011, 2019).
Axial transport phenes may affect hydraulic lift, the phenomenon in which root redistribute water from deep stores to the drier shallow layers overnight to be reabsorbed by shallow roots during the day (Caldwell and Richards 1989; Dawson 1993). Hydraulic lift has been observed in multiple species as a mechanism that facilitates favorable edaphic conditions for sustained mineral nutrient availability, fine root longevity, and microbial processes in the rhizosphere, particularly under water-limited conditions (Caldwell et al. 1998). While root abundance, root diameter, and root volume were positively correlated with increased water availability spurred by hydraulic lift, and in turn improved drought tolerance, in greenhouse-grown maize (Wan et al. 2000), the contributions of root anatomy have not yet been shown. Theoretically, root transport phenes that accommodate high axial hydraulic conductance and greater efflux from the roots (e.g. numerous or wide metaxylem vessels) may encourage hydraulic lift to occur but at a potential cost to daytime drought tolerance. Genotypic variation in hydraulic lift prevalence has been observed (Wan et al. 2000), which suggests that hydraulic lift may offer opportunities for crop improvement.
Radial transport
Cell wall modifications and anatomical phenes can restrict the radial movement of water, nutrients, and gases into the root. The exodermis, hypodermis, and endodermis are often embedded with suberin and/or lignin which regulate the movement of water and ions, primarily though reducing apoplastic transport (Steudle 2000; Colmer 2003; Enstone et al. 2003; Schreiber et al. 2005). The amount of suberin in roots typically is negatively correlated with water uptake in maize (Zimmermann et al. 2000), water and Ca, Mn, and Zn in Arabidopsis (Baxter et al. 2009), and radial oxygen loss in rice (Kotula et al. 2009). Edaphic stress can induce cell wall modifications. For example, water-stressed rice roots had enhanced endodermal suberization and most drought-tolerant genotypes had greater endodermal suberization (Henry et al. 2012), and increased lignification (Hazman and Brown 2018). Intraspecific variation in the degree of suberization and lignification in roots of many species suggest a potential for breeding for stress-tolerant crops. However, we need to better understand the environmental and genetic factors that influence the development of apoplastic barriers.
Other root anatomical phenes can also influence radial water transport and the development of apoplastic barriers. For example, increased cortical width caused by a greater number of cortical cell files and/or an increase in cortical cell size reduces radial conductance (Heymans et al. 2020b). Root cortical senescence is a type of programmed cell death in the cortex of several temperate grain species. Senescence of cortical tissue is accompanied by increased suberization of the endodermis and a reduction in nutrient and water transport (Schneider et al. 2017b, 2020a, b, c). Similarly, the formation of root cortical aerenchyma may have similar functions in reducing radial and water transport. Root cortical aerenchyma formation in maize reduced radial nutrient transport (Hu et al. 2014; Heymans et al. 2020b) and root hydraulic conductivity (Fan et al. 2007).
In water-limited environments, reduced radial hydraulic conductivity may be advantageous by conserving soil water throughout the growth season, a strategy known as “water banking” (Feng et al. 2016). Under water deficit, a reduced hydraulic conductivity may prevent desiccation of mature roots and the root tip and surrounding soil for continued root elongation. Root phenes like root cortical senescence and root cortical aerenchyma, may promote water banking by reducing water flow from the root to soil and enhanced suberization by reduce radial water loss from older root tissue. Root phenotypes that prevent desiccation of the root tip and surrounding soil may also be beneficial in strong soils, such as delayed xylem maturation, increased suberization of the endodermis, or hydraulic isolation of rhizosheaths (Lynch and Brown 2012; Lynch 2018).
Root anatomy and biotic interactions
Mycorrhizas
Arbuscular mycorrhizae (AM) are wide-spread symbioses between Glomeromycota fungi and plant roots (Smith and Read 2008). By creating a hyphal network outside of the root tissue, AM can expand the soil volume explored by a plant increasing nutrient uptake for at least 15 cm beyond the root surface (Jansa et al. 2003). AM trigger the expression of aquaporins in root tissue under water-limiting conditions, thereby increasing water uptake under drought (Bárzana et al. 2014). Plant defense response is also triggered during the symbiosis formation (Pozo and Azcon-Aguilar 2007). Furthermore, AM help maintain soil aggregate stability (Rillig and Mummey 2006). Thus, the promotion of the symbiosis is considered a beneficial practice in agriculture (Smith and Smith 2011) with overall positive growth response when inoculated plants are compared to non-inoculated controls in greenhouse (Gerlach et al. 2015) and field (Hijri 2016) conditions. Nevertheless, the effects of inoculation with spores or infective mycelia of AM on plant growth range from positive to negative (Kaeppler et al. 2000; Sawers et al. 2017) and are accentuated under abiotic stress. Mycorrhizal inoculum is abundant in normal soil. Therefore, practical applications of AM in intensive agriculture have been questioned (Ryan and Graham 2018). Mycorrhizal symbiosis has potential to promote plant growth but the multifactorial nature of this interaction makes it challenging to design AM-based applications to promote plant growth under contrasting agronomic conditions (Smith and Smith 2011). Hence, more research is needed to find possible factors that may consistently affect colonization rates and benefits from the symbiosis.
It is well established that fine, young roots have increased active AM colonization compared to lignified, coarse and older roots within the same plant (Brundrett et al. 1996; Guo et al. 2008; Smith and Read 2008). Such changes are linked to the anatomy of each root class (Guo et al. 2008). However, the effect of anatomical variation within the same root class between related plant species on AM has been in general overlooked. Root cortical aerenchyma and a continuous sclerenchymatic ring in the outer cortex was associated with decreased AM colonization in related palm species (Dreyer et al. 2010). A multispecies study in which three root anatomical traits, namely proportion of root length with a suberized hypodermis, distribution of hypodermal passage cells, and the proportion of root volume that is intercellular air space were quantified in parallel with AM under low phosphorus, revealed that none of these traits were significantly correlated to AM colonization, suggesting that this relation might be species-specific (Sharda and Koide 2010). Mycorrhizal colonization was absent in pioneer roots of trees (Acer, Juglans, Liriodendron, and Populus), which in comparison with fibrous roots with AM, have more layers of hypodermis, a smaller percentage of putative passage cells and more protoxylem clusters than fibrous roots of similar age in the same plants (Zadworny and Eissenstat 2011).
Few studies address the associations of intraspecific variation for root anatomy and the AM symbiosis. Reduced living tissue and increased root cortical aerenchyma were correlated with AM colonization in inbred maize lines grown in the greenhouse and field, but the opposite pattern and a correlation between AM and root diameter were found in field-grown hybrids (Fig. 9; Galindo-Castañeda et al. 2019). When AM colonization in common beans was compared under high and low P conditions, colonization was greater in basal root segments vs. apical root segments under low P, and the opposite was found for high P (Strock et al. 2018). A better understanding of possible AM-tradeoffs of root anatomical phenotypes would be facilitated by comparative analyses of AM in plants from the same species with contrasting levels of aerenchyma, root hair length and density, lignification of cortical layers, cortical cell size, etc. Moreover, the relationship between axial and lateral root anatomy would be crucial for the understanding of AM associations given that lateral roots host the most active part of the symbiosis. From a physiological perspective, the relative contribution of the symbiosis versus the root phenotype itself for soil resource capture would reveal the real importance of one or the other mechanism to improve plant growth under stress. Experimental systems where AM colonization can be controlled, and where both the measurement of root anatomy and AM colonization is measured in parallel with soil resource capture will facilitate further research efforts focused on untangling the relative contributions of root traits and AM. Such a system needs to be further developed, but mesocosm systems in combination with microscopy and laser ablation tomography are promising approaches to study this bipartite phenomenon. Mutants that do not form AM are useful but may display other phenotypic differences from wildtype plants because of pleiotropy. Complementation with gene expression and metabolic profiling would help in understanding the hierarchy of events that take place when roots use both symbionts and root phene states to cope with abiotic stress.
Relationships between maize root anatomy and fungal colonization as found by Galindo-Castañeda et al. (2019). A. i. Root cortical aerenchyma was negatively correlated with mycorrhizal colonization (AMC) and inversely correlated with F. verticilliodes colonization in greenhouse-grown inbred maize lines. ii. Cell size was directly correlated with AMC, and inversely correlated with root rots in field-grown maize hybrids. iii. Plants with reduced cortical cell file numbers had reduced root rots in field-grown maize hybrids. B. i. Relationship of AMC and percent aerenchyma area (P = 0.030, R2 = 0.443, n = 4) in greenhouse-grown inbred maize lines under suboptimal P conditions. ii. Three‐dimensional scatterplot of F. verticillioides colonization with the root anatomical phene aggregates living cortical area (LCA) and percent of the cortex that is living cortical area (perXSisLCA) in greenhouse-grown inbred maize lines. The plane is the linear fit of the model F. verticillioides concentration = LCA + perXSisLCA (P = 0.002, R2 = 0.881, n = 4). Red intensity relates to the LCA coordinates, with red in the lowest values and black in the highest values. C. Tridimensional reconstructions of a root segments colonized by AM, highlighting arbuscules (yellow) and aerenchyma lacunae (green). Roots collected in 4-weeks old maize plants growing in the greenhouse. i. Front of the segment before rotation showing the cross-section. ii. Front and side view of the reconstruction in which the root tissue was faded and the aerenchyma channels and arbuscular networks are shown (Photos by Tania Galindo Castañeda)
Pathogens
Root pathogens cause substantial yield losses in global agriculture (Stirling et al. 2016). Therefore, the study of the interactions of root anatomy with pathogen colonization is of great interest in plant breeding programs targeting root anatomical traits. The selection of specific root phenotypes linked to improved soil resource acquisition should not compromise root resistance to pathogens. Very few studies have examined associations between natural phenotypic variation for root anatomy and root pathogens. Root cortical aerenchyma has been studied as a possible factor that could affect pathogen colonization in root tissues. For example, the colonization by the fungal pathogens Cochliobolus sativum in spring wheat (Deacon and Lewis 1982), and Phialophora oraminicola in Kentucky bluegrass (Smiley and Giblin 1986) was favored in plants with increased RCA. On the contrary, safflower plants with increased RCA had reduced colonization of Phytophthora cryptogea (Atwell and Heritage 1994). In a recent study, fungal colonization of maize nodal roots by Fusarium verticilliodes was reduced in plants with increased living cortical area in greenhouse-grown inbreds, and root rots were positively correlated with cortical cell file number and inversely correlated with cortical cell size in field-grown hybrids (Fig. 9; Galindo-Castañeda et al. 2019). Possible mechanisms that may explain these observations are linked to the availability of apoplastic space where pathogens spread. In roots with a relatively greater apoplastic space (for example in cortex with smaller cell size and many cortical cell files) pathogens may encounter more avenues to spread. However, this may be modified when the apoplastic space, especially in the outer layers of the cortex, is sealed by suberization or lignification (Garrett 1981).
Pathogen susceptibility across different root classes in perennial species has been explored and could be used as reference or for examination of grasses or annual species. For example, in a study of apple rootstocks and the multi-species disease apple replant disease, roots in primary development and transitioning to secondary development had the greatest pathogen abundance (Emmett et al. 2014). It is also recognized that precocious suberization of the endodermis might prevent fungal colonization, and that tylosis could be linked to pathogen colonization resistance (Garrett 1981). Questions remain open on whether interactions in trees are also found in annual crops.
Rhizosphere microbiome
Microorganisms inhabiting the rhizosphere have the potential of promoting plant growth by increasing P and N availability (Richardson et al. 2009). Therefore, it has been proposed that the rhizosphere microbiome is a promising avenue to facilitate nutrient uptake under abiotic stress in crops (Compant et al. 2019). New approaches in plant breeding targeting root phenes should consider the effects of selecting for specific root phenotypes on the composition and functions of the rhizosphere microbiome. How root anatomy would affect the rhizosphere microbiome, and how the microbiome would affect root anatomy was until very recently generally unknown, and remains a topic to be researched in crops.
Traits that are directly linked to abiotic stress response have been recently studied in the context of microbial associations in the rhizosphere. Maize inbreds grown in the field with contrasting aerenchyma formation under nitrogen-limiting conditions were studied for their rhizosphere bacterial composition using amplicons of the 16s RNA genes. Plants with augmented aerenchyma showed significantly different bacterial communities compared to low-aerenchyma plants and the changes were nitrogen-level dependent (Galindo-Castañeda et al. 2018). Root-hair defective mutants had a distinct, more simplified procaryotic community in the rhizosphere, compared to wild-type barley lines (Robertson-Albertyn et al. 2017). Genes involved in root development (initiation and emergence of lateral roots, root hair length, root morphogenesis) were linked to microbiome traits in field-grown Arabidopsis (Bergelson et al. 2019). The regulatory network that controls endodermal suberization of Arabidopsis was linked to the composition of the root microbiome (endosphere and rhizosphere included), and microbes induced differences in the levels of endodermis suberization, which at the same time was linked to nutrient content (Salas-González et al. 2021). For the third and fourth mentioned studies, how these processes occur in agricultural-relevant species such as cereals or legumes remains to be discovered. It is noteworthy that Arabidopsis root anatomy and microbial associations might greatly differ from crops, and therefore, the mechanisms involved in orchestrating microbiome and root anatomy in such different soil environments need further exploration. Nevertheless, recent results indicate that the microbial composition of the rhizosphere is coordinated by both the root and the microbial community, and that interkingdom dialog and feedbacks shape the capabilities of the plant to absorb nutrients and cope with nutrient stress. Consequently, breeding efforts targeting root anatomy to improve soil resource capture, as well as the development of biostimulants, should consider microbial tradeoffs and microbial-root feedbacks that could modify or be modified by the microbe-root environment as determined by root anatomy.
Insects
Root interactions with arthropods and nematodes have significant impacts on soil resource capture, plant performance and yield. Plants are generally less tolerant of root herbivory compared to shoot herbivory since damage to roots can dramatically reduce water and nutrient uptake, open opportunities for pathogen infection, and increase susceptibility to lodging (Zvereva and Kozlov 2012). We hypothesize that resistance to these pests not only encompasses the commonly cited signaling response and plant defense biomolecules, but likely also involves physical components of root anatomy (Fig. 10). Although widely studied at the molecular and ecological scales (Meihls et al. 2012; Moore and Johnson 2017), the interactions between these soil organisms and root anatomy may have reciprocal effects but have been largely neglected in the literature (Strock et al. 2019b).
(A, B) Three-dimensional reconstruction of a wheat (Triticum aestivum L.) root segment that contains a cereal cyst nematode (Heterodera avenae) and feeding site. The central metaxylem is highlighted in green, the nematode in red, and the feeding site in dark blue. (C, D) Three-dimensional reconstruction of the western corn rootworm (Diabrotica virgifera virgifera) feeding on a maize (Zea mays) crown root from a V3 stage plant, 4 d after inoculation with neonates. Modified from Strock et al. (2019a, b)
Where the interface between plants and insects has been examined at the anatomical scale, significant interactions have been reported. For example, Levin et al. (2021) found that cyst nematodes formed feeding sites adjacent to the central metaxylem in wheat (Triticum aestivum L.) roots, and resistance to nematodes was associated with physical separation of feeding sites and metaxylem vessels (Fig. 10A, B). Examination of root anatomy has also revealed that the allocation of defensive compounds is concentrated in specific tissues within the root (van Dam 2009). Hol et al. (2003) found that the root cortex of S. jacobaea had five times the concentration of pyrrolizidine alkaloids compared to the central cylinder. Similarly, McCully et al. (2008) found that glucosinolates were highly concentrated in the cell layers just beneath the outermost periderm layer in Brassica napus roots. This accumulation of defensive compounds in superficial cell layers likely serves to shield root vasculature from damage thereby preventing the disruption to axial transport of water and nutrients (van Dam 2009).
Although spatiotemporal patterns of structural compounds have not been well characterized in roots, localized incorporation of lignin, cellulose, suberin, and callose can provide physical barriers to herbivory (Meihls et al. 2012; Moore and Johnson 2017). Incorporation of mineral compounds like silica and calcium oxalate into anatomical features may also reduce the accessibility and digestibility of root tissues to these pests. For example, Riedell and Kim (1990) found that the suberized and lignified secondary cell walls of the endodermis and exodermis in maize roots act as a barrier to discourage larval feeding of western corn rootworm on maize roots (Fig. 10C, D). Similarly, Castano-Duque et al. (2017) found an association between the cutting resistance of maize roots and the intensity of western corn rootworm feeding on the cortex. Johnson et al. (2010) found that roots with greater lignin concentration and fracture toughness had delayed penetration by wireworms. In line with these observations, the deposition of lignin and suberin during secondary growth of dicotyledonous species (Strock and Lynch 2020) and multiseriate cortical sclerenchyma in monocotyledonous species (Schneider et al. 2021) would likely confer resistance to edaphic pests.
To our knowledge, targeted selection of root anatomical traits for resistance to root herbivory has yet to be utilized in breeding programs, but nevertheless, indirect selection for anatomical phenotypes conferring resistance to root herbivores may occur. For example, breeding programs for resistance to western corn rootworm consider the phenotype of reduced lodging (Castano-Duque et al. 2017). Overall, while the sparse literature on the interface between root anatomy and herbivory is likely attributed to experimental limitations, novel research techniques like laser ablation tomography have recently opened up opportunities for investigating this scale of plant–insect interactions (Strock et al. 2019b). Investigation into how root herbivores interact with root anatomy would not only provide a great contribution in our understanding of how these pests affect root health and development, but also aid in the advancement of designing integrated systems of pest management.
Cross cutting issues
Plasticity
Phenotypic plasticity is the ability of the organism to alter its phenotype in response to the environment. Plasticity of root phenes is heritable and genetically controlled and is a widespread and important phenomenon for strategic capture of nutrients and water (Schneider et al. 2020a; Schneider and Lynch 2020). However, plasticity is not necessarily a characteristic of an organism as a whole, but rather a characteristic of a specific phene and may be adaptive, maladaptive, or neutral in regard to fitness. A number of root phenes express phenotypic plasticity. For example, metaxylem number, root cortical aerenchyma, stele diameter, root angle, lateral branching density and length, and cortical cell size and file number are plastic in response to drought (Schneider et al. 2020a, b; Niones et al. 2013; Price et al. 2017). In drought, many of these adaptive plastic responses were associated with deeper rooting, yield stability, and improved plant performance (Niones et al. 2012; Wasson et al. 2012; Sandhu et al. 2016). However, the duration and the spatiotemporal conditions of phenotypic expression influence its utility. It has been speculated that plasticity is an adaptive mechanism for crop ancestors in natural ecosystems with highly variable and fluctuating environments (Schneider and Lynch 2020). However, a plastic response may be maladaptive in high-input agroecosystems with greater water and nutrient availability and reduced biotic stress (Lynch 2018). The fitness landscape of root phenotypic plasticity is complex and dependent on many variables including the environment and management practices.
Integrated anatomical phenotypes
While individual root anatomical phenes affect the metabolic costs of soil exploration, root penetration into strong soils, the radial and axial transport of soil resources, and interactions with soil organisms, efforts to conceptualize the interaction among multiple components of root anatomy can provide even greater insight into strategies of soil resource capture (Asfaw et al. 2012; York et al. 2013). The effects of root phenotypes on soil resource capture are multifaceted over space and time, and we must embrace this complexity to better define the fitness optima in which specific root phenotypes are advantageous. Investigation of the broader interactions among multiple phenes, or integrated phenotypes, that affect soil resource acquisition, transport, and utilization may reveal synergistic (i.e. greater than the additive effects of individual phene states) or antagonistic (i.e. less than additive effects on plant performance) relationships among different components of the root system (Lynch 2019). For instance, at the single phene scale, large cortical cells have been linked to improved tolerance to water deficit stress (Chimungu et al. 2014a) and low P availability (Galindo-Castañeda et al. 2018) by reducing the metabolic burden of cortical tissue maintenance (Jaramillo et al. 2013). Coupling large cortical cells with fewer cortical cell files has been suggested as a synergistic combination to facilitate deeper rooting (Lynch 2013), but may have an antagonistic effect on root penetration of hard soil. Focusing on integrated phenotypes may also reveal multiple phene combinations that result in similar fitness outcomes in a given environment (Rangarajan et al. 2018; Strock et al. 2019a; Klein et al. 2020), which presents breeders with several novel targets for crop improvement.
The sheer number of possible combinations resulting from the interactions of multiple phenes in multiple states in multiple phenotypic and environment contexts is a challenge for empirical research, but is well suited to in silico analysis. In silico approaches also permit the analysis of phenotypes that do not exist in nature. For example, use of the functional-structural plant model SimRoot identified substantial synergism among root hair length, density, epidermal patterning, and point of initiation for P capture in Arabidopsis (Ma et al. 2001b). Low P availability regulates these phenes in this species in a coordinated manner that increases P capture 3.7 fold greater than their additive effects, demonstrating substantial morphological synergy. SimRoot analysis also showed that the utility of RCA for nutrient capture depends on other root phenes and environmental factors (Postma and Lynch 2011a). On low-phosphorus soils, the utility of RCA was 2.9 times greater in plants with increased lateral branching density than in plants with normal branching. On low-nitrate soils, the utility of RCA formation was 56% greater in coarser soils with high nitrate leaching.
Though the inherent complexity of integrated phenotypes lends itself to evaluation in silico, it is possible to exploit the natural diversity that exists in some species to identify integrated phenotypes that are valuable in the field. For example, using a diverse collection of maize inbreds, Klein et al. (2020) identified three integrated phenotypes composed of root anatomical phenes that centered on likely drought survival strategies: enabling the exploration of a larger soil volume by reallocating internal resources to greater root construction (increased root cortical aerenchyma production, larger cortical cells, fewer cortical cell files), restricting uptake of water to conserve soil moisture (reduced hydraulic conductance, narrow metaxylem vessels), and improving penetrability of hard, dry soils (thick roots with a larger proportion of stele, and smaller distal cortical cells). Of the groups of root phenotypes identified in the panel, the root systems of those with improved performance contained at least one of the identified integrated phenotypes.
Beyond the integration within multiple anatomical components, integrated root phenotypes combining root anatomy with other factors affecting soil resource capture (root system architecture, shoot architecture, phenology) should be carefully considered. For example, the integrated effect of root system architecture, which affects root length distribution in the soil profile, and xylem morphology, which affects axial transport, influences water use under drought. Both synergistic and antagonistic interactions between metaxylem phenotypes and root architecture have been observed in two species of Phaseolus under water limitation (Strock et al. 2020). A synergistic interaction between highly conductive xylem morphology and deep root architecture in P. acutifolius demonstrated the utility of efficient axial transport for supporting growth when water is more available at depth. A less-conductive xylem phenotype within this species had an antagonistic interaction with deeper roots by reducing the capacity for transport of water to the growing shoot under stress. Complementarity between the low-conductance xylem phenotypes and shallow root architecture in P. vulgaris revealed the utility of restricting water uptake to conserve soil water usage (Strock et al. 2020). These observations indicate that xylem phenotypes integrate with root system depth to influence water use.
Interactions of root anatomy and root architecture are also important for nutrient capture. For example, long root hairs and shallow root growth angles are synergistic for P capture in common bean (Miguel et al. 2015). Compared with short-haired, deep-rooted phenotypes, long root hairs increased shoot biomass under phosphorus stress by 89%, while shallow roots increased shoot biomass by 58%. The additive benefits of these two phene states would therefore be 147%, however genotypes with both long root hairs and shallow roots had 298% greater biomass accumulation than short-haired, deep-rooted phenotypes, a synergistic combination twice as large as their additive effects. As another example, it has been proposed that RCA may have important interactions with architectural phenes increasing root depth, by alleviating hypoxia (Lynch and Wojciechowski 2015).
Trait synergisms and tradeoffs may also exist with contrasting root phenotypes originating from different root classes. For example, in soils with a high mechanical impedance, it may be beneficial for lateral roots to be highly responsive to ethylene acting as a stop signal for root growth upon reaching hard soils. This would enable more metabolic resources to be invested in axial roots, which are typically innately thicker and therefore greater ability to penetrate hard soils. The investment of metabolic resources in different root classes may interact to influence plant growth. Potential synergisms and tradeoffs between root and leaf phenotypes likely exist but presently are not well understood. While roots are directly responsible for the acquisition of soil resources, leaves have important effects on the utilization of these resources. Research attention toward understanding how these organs interact is essential for further optimizing plant fitness under limited resource availability. The optimal combination of both below- and above-ground anatomy, or potential trade-offs of acquisition and utilization strategies under varying water and N availability are poorly understood. While important synergistic effects among root phenes have been identified, the concept of aggregating multiple phenes into an integrated phenotype is not widely appreciated. However, because root and shoot development are regulated by many shared genes and signaling pathways, anatomical phenotypes in these organs may be correlated through pleiotropy or close linkage (Byrne et al. 2003; Laux et al. 2004; Chen and Lübberstedt 2010; Seago and Fernando 2013). If the anatomy of leaves has strong relationships with that of roots, collection of leaf samples may serve as an important tool in reducing labor and time required for excavating, washing, and collecting root samples in anatomical screening for below-ground traits.
Although few studies have directly addressed phene synergism and the value of integrated anatomical phenotypes, it is likely that root anatomical phenes have many important interactions with each other, with root architecture, with the shoot phenotype, and with the environment. This represents an implicit challenge to the reductionist paradigm of modern plant biology.
Carbon sequestration
In terrestrial ecosystems, soils serve as the largest reservoir of carbon, storing two times more than the atmosphere and three times more than the vegetation it supports (Post et al. 1982; Kell 2011, 2012). Despite holding such vast reserves, soils possess great capacity for further carbon retention, providing an important opportunity for combating climate change. A significant portion of plant photosynthate is deposited through roots, directly adding carbon to soil through growth, exudation, and associations with edaphic organisms (Lambers et al. 2002; Farrar et al. 2003; Jones et al. 2004). Root growth is particularly important for carbon sequestration since carbon from roots has 2.4 times longer residence time in the soil compared to carbon derived from above-ground tissues (Rasse et al. 2005). Consequently, root anatomical composition may have a significant effect on the capacity for plants to sequester atmospheric CO2 in soil. For example, genetic variation for the deposition of lignin and suberin in roots may greatly impact plant capacity for carbon sequestration. This concept is highlighted in a meta-analysis by Poirier et al. (2018) where root suberin content was identified as one of the most influential promoters of soil organic matter stabilization. Thicker cell walls also may be a potential selection criterion for carbon sequestration. Carbon sequestration with thicker cell walls would depend on the composition; for example lignin degrades much slower as compared to hemicellulose and cellulose (Berg and McClaugherty 2003; Kögel-Knabner 2002; Yue et al. 2016). Additionally, root anatomy phenotypes that improve the metabolic efficiency of soil foraging and improve growth of above-ground biomass may, through allometry, produce greater overall root mass and augment the sequestration of carbon in soil. Since the residence time of carbon in soil is largely a function of plant allocation to roots, and their vertical distribution, root anatomical phenotypes that facilitate deeper rooting would sequester atmospheric CO2 more effectively than plants with a shallow distribution of root length (Lynch and Wojciechowski 2015; Jobbagy and Jackson 2000; Kell 2011, 2012). Finally, root anatomical traits that modify root exudation or interactions with the rhizosphere community may further contribute to the total quantity of carbon added to the soil. Research to understand the potential that genetic variation in root anatomy has for below-ground carbon storage will only become more critical as climate change progresses.
Modelling root anatomy and resource capture
With advancement in molecular, imaging, and computational technologies, numerous mechanistic models (mathematical or computational) focusing on different aspects of plant biology have been developed, ranging from molecular and cellular biology through organs, organisms, to ecosystems, with physical structure in two or more dimensions. These models have been useful in identifying and filling knowledge gaps, quantitatively testing current paradigms, testing novel hypotheses, predicting system behavior for scenarios that are not accessible in-vivo, and designing incisive experiments to make useful discoveries and performing studies when laboratory experiments are difficult or impossible (Hodgman and Ajmera 2015; Marshall-Colon et al. 2017; Benes et al. 2020).
Evaluating the impact of variation in root anatomy on soil resource capture and identifying carbon and resource-efficient root anatomical phenotypes would be invaluable for developing improved crop varieties, as discussed in previous sections. However, such studies are extremely difficult as the number of combinations to be evaluated exceeds the capacity of empirical research. Thus, in silico evaluation becomes essential. Computational morphodynamics (Chickarmane et al. 2010) is one such approach, wherein tissue or organ scale models could either be considered as a continuum or multicellular structure, depending on the question of interest and the available computational capabilities. Under this paradigm, the functional-structural model—SimRoot (now, OpenSimRoot) (Lynch et al. 1997; Postma et al. 2017) can be classed as the only continuum model for root anatomy (Fig. 11A, Bi). Over the last three decades, SimRoot models have been successfully implemented for different crop species to represent various anatomical phenotypes such as root hairs, root diameter, root cortical aerenchyma, root cortical senescence, cortical cell size and cell file number, xylem size and number; and their impact on soil resource capture and plant carbon economy. These models enabled the functional evaluations of different anatomical phenotypes and their combinations under edaphic stress. It is noteworthy that these findings would have been difficult or impossible to attain with empirical approaches.
Paradigms for modeling root anatomy. Panel A depicts OpenSimRoot simulation of maize root system at 40 days after germination. Color gradient highlights root cortical aerenchyma (RCA) formation, with red denoting the greatest proportion of RCA and dark blue denoting lack of RCA. Panel B depicts nutrient uptake dynamics across a root segment in continuum and multicellular models. Panel C highlights simulation outputs of various multicellular root anatomy models namely, MECHA, OpenAlea and RootSlice. Subpanel B(i) schematically illustrates nutrient and water uptake, flux and transport across a cylindrical root segment implemented in a continuum model like OpenSimRoot, CRootBox (Schnepf et al. 2018), R‐SWMS (Javaux et al. 2008), Root system models (Doussan et al. 1998, 2006). Water dynamics are defined by kr and kx denoting radial and axial hydraulic conductivity. Nutrient uptake kinetics are defined by the Michaelis–Menten kinetic parameters Imax and km denoting maximum nutrient uptake rate and affinity of transporter, respectively. Subpanel B(ii) schematically illustrates radial and axial flux of water and nutrients across a root segment in a multicellular model. The water and nutrient flow via symplastic (Sym; dash-red arrow) and apoplastic (Apo; black arrow) routes through root tissues, namely epidermis (Ep), exodermis (Ex), cortex (Co), endodermis (En), casparian strip (Cs) and pericycle (Pe), eventually entering xylem (Xy) and transported (axially) across the plant. Subpanel C(i) depicts MECHA simulation of water flux across the cell membranes in a cross section of a mature primary root of pearl millet. Blue indicates water entering a cell, red indicates water leaving a cell (image was generated via MECHA webtool—https://mecharoot.github.io). Subpanel C(ii) depicts OpenAlea simulation of cytoplasmic phosphate (CytoPi) distribution across an aerenchymatous rice root cross section. Red and dark blue in the scale bar depict highest and zero phosphate level, respectively. Sections of the root with aerenchyma have lower CytoPi level (light green to ocean blue) than sections with intact cortical cells (yellow). Strings of cortical cells and fluid-filled channels flanking lacunae reduce barriers to inward flow of Pi, thus increasing its uptake and lowering CytoPi levels in the outer cells. Subpanel C(iii) depicts a RootSlice simulation showing a 3D maize root cross section with RCA (white space) across the red colored cortex. Epidermis, pericycle and phloem are denoted in shades of blue, xylem, companion cells and pith are depicted in orange yellow, and green, respectively
Continuum models like SimRoot have computational and conceptual advantages but lack precise multicellular topologies required to evaluate the influence of cellular/supracellular features (e.g. cell size/number/volume, cell wall, aerenchyma, casparian strip, membrane transporters, etc.) on tissue or organ scale behavior (e.g. resource acquisition, storage, flux, and transport) (Fig. 11B.ii). Multicellular modelling frameworks capturing root anatomy include MECHA (Couvreur et al. 2018, Fig. 11C.i) OpenAlea (Pradal et al. 2008, Fig. 11C.ii), and RootSlice (in development, Fig. 11C.iii). These frameworks use a standard programming language (e.g. java, python or C + +) to couple model components and implement realistic root anatomies extracted from microscopy images (discussed in "Image analysis"). Most existing multicellular root anatomical models are focused at capturing developmental aspects (Band et al. 2012; Rutten and Ten Tusscher 2019). Only a few multicellular models of root anatomy have the capabilities to capture uptake dynamics involving water (Couvreur et al. 2018) and phosphorus (Ajmera 2016). Furthermore, to date no functional-structural model exists capturing soil resource acquisition and transport with explicit implementation of cellular and supracellular morphometry of the root. Though capabilities for capturing various features of root anatomy exist in many of the available modelling frameworks, including MECHA, OpenAlea, and RootSlice, their implementations are being awaited. Case studies highlighting the current capabilities of these modelling frameworks are briefly discussed below.
Root hydraulic conductivity is one of the key drivers regulating water uptake dynamics and is therefore a potential target for breeding drought tolerant crops. However, quantifying root hydraulic properties, particularly radial conductivity, and the array of factors influencing it, involves extremely complicated and error-prone procedures. To address this challenge, a two-dimensional Model of Explicit Cross-Section Hydraulic Anatomy, MECHA, was developed (Fig. 11C.i; Couvreur et al. 2018). The model can—a) estimate water flow across walls, membranes, and plasmodesmata of each individual cell; b) quantify contribution of different passages on water flow across the root, including intercellular spaces, xylem poles and passage cells, and c) predict its radial hydraulic conductivity. Certainly, MECHA offers a convenient approach to probe and cross-validate experimental root hydraulic studies.
A typical mature rice root has a distinctive cortical aerenchyma consisting of lacunae with spoke-like structures connecting the outer cell layers with the stele (Fig. 13A.iv). It has been proposed that if aerenchyma lacunae are lined or filled with aqueous solution, they would allow smooth passage for nutrients to flow across the cortex with minimal resistance (Drew and Saker 1986; van der Weele et al. 1996; Ranathunge et al. 2003; Vadez 2014). A 2D multicellular temporal OpenAlea model (Band et al. 2012) of phosphate uptake and flux across realistic rice root cross-section shows agreement with this hypothesis (Fig. 11C.ii; Ajmera 2016).
The cortex occupies a large part of the cross-sectional area of a root and its features vary across genotypes and environments. To evaluate the influence of variation in these phenotypes on its underlying rhizoeconomics, a 3D static functional-structural root anatomy modelling platform has been developed named RootSlice (unpublished, Fig. 11C.iii). In an initial study using the basal cross-sections of the maize roots, the model quantitatively showed the impact of cell wall thickness on cellular metabolic demand and apoplastic conductance. This model enables the quantification of rhizoeconomic variables for the different cylindrical root segments of varying class and age implemented in plant-scale models like OpenSimRoot. Such integrative compatibility opens avenues for investigating relationships between root architecture, anatomy, and soil resource availability.
Methods for studying root anatomy
One of the major limitations in exploring and utilizing root anatomical traits is the challenge of high-throughput phenotyping. Traditional methods like preparing a root cross section by hand and visualizing it with light microscopy are relatively inexpensive and a good starting point, but are limited because they may alter anatomical phenotypes and also because these methods are relatively slow and thus discourage exploration of root anatomical traits on a larger scale such as diversity panels, multi-species groups, mapping populations and breeding material, etc.. High-throughput phenotyping is needed for direct phenotypic selection, which is accessible to breeding programs without access to sophisticated genotyping capabilities, and for the discovery of genetic markers for marker- assisted breeding, which is especially important for quantitative traits like most root phenes. Therefore, high-throughput phenotyping of root anatomy progress from basic research to applied breeding. Several methods have recently become available that may be suitable for high throughput phenotyping of root anatomy.
LAT (Laser ablation tomography)
LAT (Laser Ablation Tomography) is a novel imaging technique that permits high-throughput, three-dimensional quantitative and qualitative analysis of root anatomy (Fig. 1; Chimungu et al. 2015a, b; Hall et al. 2019; Saengwilai et al. 2014; Strock et al. 2019b, 2018). The original LAT system utilizes a pulsed UV laser coupled with a galvanometer that forms a laser ablation plane by scanning the beam rapidly along a line of a defined width. The sample is mounted on a software-controlled stage that slowly moves it into the ablation plane while being imaged using a high-resolution camera equipped with a macro lens. Full color or even multi-spectrum scans of root samples at 0.1 mm to 1 cm spatial scale and \(\mu\)m level resolution can be acquired. LAT 2.0 is a newer version of LAT 1.0 and is equipped with superior laser physics permitting athermal ablation, hyper spectral imaging, and robotic sample processing. LAT 2.0 offers finer control over the laser power, faster sample processing speed and semi-automated handling of samples. Sample processing and imaging requires 1–2 min. The application of LAT for studies of root anatomy provides both volumetric quantification and qualitative tissue differentiation based on composition-specific autofluorescence. For three-dimensional visualization of specific features in samples, LAT scans are assembled into three dimensional stacks and compiled into three dimensional reconstructions. These three-dimensional reconstructions can be then used for volumetric measurements of different features e.g. three dimensional quantification of percent aerenchyma in maize (Galindo-Castañeda et al. 2018), xylem anatomy in beans (Strock et al. 2021), mycorrhizae colonization of maize and bean roots (Strock et al. 2018; Galindo-Castañeda et al. 2019), and root infection by nematodes in barley (Strock et al. 2019b; Levin et al. 2021). LAT can also be used for differentiating tissue features differing in their composition based on their autofluorescence spectra after UV excitation (Strock et al. 2019b). Hyperspectral imaging on the LAT 2.0 system can potentially help discern different tissue compounds such as lignin, xylan, and suberin. More details about LAT can be found at https://plantscience.psu.edu/research/labs/roots/methods/laser-ablation-tomography. Other techniques like vibratomes coupled by imaging with light microscopy are also an alternative to hand sectioning (Verhertbruggen et al. 2017).
Phenotyping root hairs
Phenotyping for root hair length and density can easily done using a light or stereoscopic microscope, inexpensive LED pocket microscopes, or even the unaided eye (Vieira et al. 2008; Zhu et al. 2010b; Miguel et al. 2015). Root hairs can be phenotyped using seedlings germinated on germination paper or, for best representation of actual conditions, in roots extracted from soil. Root samples from soil should be harvested with care so that root hair phenotypes are not altered by the sampling method. After harvesting and washing root hairs can be stained with dyes like Toluidine blue and imaged using a light microscope. Given the intraspecific variation for root hair phenotypes and their importance for soil resource capture, they should be phenotyped routinely in crop improvement programs.
Non-destructive imaging
Certain anatomical features can be better phenotyped with non-destructive methods such as confocal microscopy, two-photon microscopy, and micro-CT etc. (Fig. 12). Confocal microscopy has been widely used to image root anatomical features of model organisms such as Arabidopsis and Brachypodium (Fig. 12A) (Hepler and Gunning 1998; Pollastri et al. 2012). Due to the small size of roots of these species, phenes like cortical cell size, cortical cell file number, cortical cell length, aerenchyma area etc. can be phenotyped non-destructively. But for phenotyping thicker root segments (> 200 um) e.g. in maize, simple confocal microscopes can only provide data about the epidermal cells or a few of the outer cortical cells depending on the cell diameter. Two-photon or multiphoton microscopes can image up to 1 mm into the tissue without compromising resolution (Mizuta et al. 2015), but this would not work for tissues thicker than 1 mm (Fig. 12B). Another benefit of using confocal or multiphoton microscopy is that organelles can be imaged by using different organelle specific dyes or probes (Spence and Johnson 2010; Giovanni et al. 2017). In-vivo imaging in growing medium of some root anatomical features such as root diameter etc. is possible using micro-CT (Fig. 12C; Wang et al. 2017; Teramoto et al. 2020). It is worth mentioning that all these methods, within their limits, can be used to faithfully construct root anatomical features but it most cases the time required to image samples, and the cost and complexity of these instruments, limits their application in crop breeding. We also acknowledge that there are other less common techniques for phenotyping root anatomy such as light sheet fluorescence microscopy, but we have discussed only the most used ones in this review.
Image analysis
Image processing and analysis are a major bottleneck for plant phenotyping. Broadly, it involves visualization, quantification, and management of the generated image dataset. Fundamentally, analyzing a micro-scale tissue image involves segmentation or delineation of cell walls against the background to extract the corresponding cellular morphometry. Accuracy and automation are the key attributes for the advancement of image analysis tools. For micro-scale plant phenotyping and non-invasive imaging, automation becomes vital as it requires quantification of subcellular and cellular morphometry over different spatiotemporal scales, often in 3D, from images with varying scales and depths. For more details and perspective on plant image analysis, readers are directed to several excellent reviews (e.g. Dhondt et al. 2013; Minervini et al. 2015; Bassel and Smith 2016; Lobet 2017; Legland et al. 2018; Zhao et al. 2019).
In recent years, various image analysis approaches and computational tools have been developed to evaluate microscopic root images from hand sections, paraffin or vibratome slices, laser ablation tomography (Fig. 13A.i, iv), fluorescence imaging and μ-CT. These tools can be classed as manual, semi-automated, and automated. Manual tools involved subjective evaluation of images and are most useful for low-throughput applications. Traditionally, ImageJ—an open-source platform (Schindelin et al. 2012; Rueden et al. 2017; Rasband 2015; http://imagej.net/), has been extensively used for manual and batch automation routines for image analysis via native macros or developing new plugins (Arena et al. 2017). On the other hand, semi-automated tools necessitate user feedback for individual images for accurate results. RootScan (Fig. 13A.ii; Burton et al. 2012), CellSeT (Fig. 13A.iii; Pound et al. 2012), PHIV-RootCell (Fig. 13A.vi; Lartaud et al. 2015) are semi-automated tools to evaluate root anatomy. An automated image analysis tool is expected to assess images and get accurate results with just a ‘single-click’. RootAnalyzer (Chopin et al. 2015), DL-RootAnatomy (Wang et al. 2020) and RootScan3D (unpublished) are advanced fully automated tools for extracting anatomical metrics from root section images. DL-RootAnatomy and RootScan3D implement machine learning approaches to recognize and quantify the different anatomical root features. In machine learning approaches, initial image inputs and supervision are required for training the algorithms. Furthermore, open-source tools such as GRANAR (Heymans et al. 2020a) and CellSeT (Pound et al. 2012) allow digitalization of root anatomical networks (Fig. 13B), which can then be used for the development of multi-cellular models of root anatomy (Fig. 11C). However, there are significant differences in the processing time required by these tools, such that GRANAR (Fig. 13B.i, iii) requires seconds while CellSeT (Fig. 13B.ii, iv) could require hours to process root cross-section images with a thousand cells.
Visualization of maize and rice root cross sections processed with various image analysis tools. Panel A (i, iv) highlights raw cross section images of mature maize and rice roots from laser ablation tomography. Panel A (ii, iii, v, vi) depicts anatomical features in the raw images quantified by different semi-automated image analysis tools such RootScan, CellSeT, MIPAR and PHIV-RC (RootCell). Panel B (i, iii) depicts digitalized anatomical network for mature maize and rice roots generated by GRANAR. Panel B (ii, iv) features structured network of cells in matured maize and rice roots extracted using CellSeT from raw image in Panel A (i, iv)
Various other plant image analysis tools, including for micro-scale, can be found in an online database (http://plant-image-analysis.org) (Lobet et al. 2013). This manually curated database enables the users to find suitable tools for their image datasets. In addition, commercial tools such as Avizo (VSG Inc., Burlington, MA, USA) and MIPAR™ (Sosa et al. 2014; Fig. 13A.v) are also being used for processing root section images and accurate quantification of different anatomical phenes (Hazman and Brown 2018; Strock et al. 2019b; Klein et al. 2020; Schneider et al. 2020a, b, c; Levin et al. 2021). There is significant progress being made in the arena of plant image processing and analysis at multiple scales. Given the challenges, AI based approaches are the way forward for the advancement of crop phenotyping.
Future prospects
As we show here, an array of anatomical phenes have substantial importance for the acquisition of water and nutrients from the soil, and natural genotypic variation for these phenotypes in crop plants provides attractive breeding targets for the development of more efficient, resilient crops. High-throughput phenotyping platforms, such as LAT accompanied by AI-assisted image analysis, are increasingly available, and in many cases are suitable for plants grown in soil and in the field, which is important since many anatomical phenes respond to environmental conditions. The expression and utility of many of these phenotypes may be restricted to specific taxa. For example, reduced secondary growth as a mechanism to expand soil exploration and nutrient capture is not relevant to monocots, which lack secondary growth. In contrast, root cortical senescence has only been observed in cereal crops. The fact that not all plant taxa display all anatomical phenotypes of interest represents a constraint for the relevance of model organisms that dominate elite plant biology research. The genetic control of many if not most of these phenotypes is likely to be highly quantitative. This poses a challenge for the gene-centric paradigm of elite plant biology. Crop breeding programs still rely heavily on phenotypic selection however. This is especially true in developing nations, which have urgent need of more resource-efficient crops but may lack the resources needed for molecular breeding approaches such as genomic selection, although such tools are increasingly powerful and inexpensive. Phenotypic selection for anatomical traits has been facilitated by the advent by inexpensive portable microscopes accessible to even the most rudimentary breeding programs.
A more challenging bottleneck is our incomplete understanding of the fitness landscape of root anatomical phenotypes. In some cases, such as that of long, dense root hairs, a phenotype appears to afford multiple fitness advantages with no obvious tradeoffs. In other cases, such as metaxylem vessel diameter, the fitness landscape is highly dependent on the environment and the background phenotype. The number of potentially interesting scenarios, given multiple states of multiple phenes in multiple environments, exceeds the capacity of empirical research. Furthermore, very few research efforts or even research communities encompass the range of relevant factors, including soil chemistry, physics, and microbiology, biotic and abiotic stressors, weather variability, crop management, etc. As we argue here, this complexity calls for greater emphasis on in silico approaches capable of spanning multiple spatiotemporal scales and multiple plant and environmental factors. However, the current organization of elite plant research, which supports and rewards success in narrow subfields, is not well suited to address this challenge. As an example that is relevant in the context of this article, very few elite plant biologists have expertise in soil science, and many do not employ natural soils at all, or if they do use real soil, make no effort to generalize their results across contrasting soil taxa. Few research efforts focused on drought also consider P stress, although these constraints commonly occur together in global agriculture. For that matter, few studies of plant response to abiotic stress also consider biotic stress factors. Such efforts are difficult to fund, conduct, and publish in modern plant science. They are what is needed to address global challenges. As a research community we need to reach beyond narrow disciplinary boundaries, dogma, and tribalism, and be willing to support and publish transdisciplinary, integrative research addressing the complexity of real world systems, and we need to train young scientists how to do this, if we are to fully exploit the remarkable potential of root anatomical phenotypes to address the two primary challenges of the twenty-first century: how to sustain 10B people in a degraded environment, and how to sustain and improve the natural resource base for future generations.
Dedication
We dedicate this article to Kathleen M Brown on the occasion of her retirement. In a career spanning over 40 years she has been a model of research excellence, integrity and dedication. Her spirit of selfless service, quest for the truth, and personal kindness has inspired generations of students and scholars.
Change history
20 April 2022
A Correction to this paper has been published: https://doi.org/10.1007/s11104-022-05416-2
Abbreviations
- AM:
-
Arbuscular Mycorrhizas
- CCS:
-
Cortical Cell Size
- CCFN:
-
Cortical Cell File Number
- LCA:
-
Living Cortical Area
- MCS:
-
Multiseriate Cortical Sclerenchyma
- RCA:
-
Root cortical aerenchyma
- RCS:
-
Root cortical senescence
References
Abd Allah AA, Badawy SA, Zayed BA, El. Gohary AA (2010) The role of root system traits in the drought tolerance of rice (Oryza sativa L.). International Journal of Agricultural and Biological Sciences 1:83–87
Ajmera I (2016) A systems study of nutrient uptake in plants. PhD thesis, University of Nottingham
Arena ET, Rueden CT, Hiner MC, Wang S, Yuan M, Eliceiri KW (2017) Quantitating the cell: turning images into numbers with ImageJ. Wiley Interdiscip Rev Dev Biol 6:e260
Asfaw A, Gurum F, Alemayehu F, Rezene Y (2012) Analysis of multi-environment grain yield trials in mung bean Vigna radiata (L.) Wilczek based on GGE biplot in southern Ethiopia. J Agric Sci Technol 14:389–398
Atwell BJ (1993) Response of roots to mechanical impedance. Environ Exp Bot 33:27–40
Atwell BJ, Russell S (1989) Physiological responses of lupin roots to soil compaction. In Structural and Functional Aspects of Transport in Roots (pp. 251–255). Springer, Dordrecht
Atwell B, Heritage A (1994) Reduced susceptibility of roots of safflower to Phytophthora cryptogea after prior adaptation of roots to hypoxic conditions. Aust J Bot 42(1):29–36. https://doi.org/10.1071/BT9940029
Bailey C, Scholes M (1997) Rhizosheath occurrence in South African grasses. South African j Bot 63:484–490. https://doi.org/10.1016/S0254-6299(15)30803-6
Band LR, Fozard JA, Godin C, Jensen OE, Pridmore T, Bennett MJ, King JR (2012) Multiscale systems analysis of root growth and development: modeling beyond the network and cellular scales. Plant Cell 24:3892–3906
Barber D, Gunn K (1974) The effect of mechanical forces on the exudation of organic substances by the roots of cereal plants grown under sterile conditions. New Phytol 73:39–45
Barber SA (1995) Soil nutrient bioavailability: a mechanistic approach. John Wiley and Sons
Barigah TS, Charrier O, Douris M, Bonhomme M, Herbette S, Améglio T, Fichot R, Brignolas F, Water CH (2013) Water stress-induced xylem hydraulic failure is a causal factor of tree mortality in beech and poplar. Ann Bot 112:1431–1437
Barley KP, Rovira AD (1970) The influence of root hairs on the uptake of phosphate. Commun Soil Sci Plant Anal 1:287–292
Barraclough PB, Weir AH (1988) Effects of a compacted subsoil layer on root and shoot growth, water use and nutrient uptake of winter wheat. J Agric Sci 110:207–216
Barré P, Hallett PD (2009) Rheological stabilization of wet soils by model root and fungal exudates depends on clay mineralogy. Eur J Soil Sci 60:525–538
Bárzana G, Aroca R, Bienert GP, Chaumont F, Ruiz-Lozano JM (2014) New insights into the regulation of aquaporins by the arbuscular mycorrhizal symbiosis in maize plants under drought stress and possible implications for plant performance. Mol Plant Microbe Interact 27:349–363
Basirat M, Mousavi SM, Abbaszadeh S, Ebrahimi M, Zarebanadkouki M (2019) The rhizosheath: a potential root trait helping plants to tolerate drought stress. Plant Soil 445:565–575
Bassel GW, Smith RS (2016) Quantifying morphogenesis in plants in 4D. Curr Opin Plant Biol 29:87–94
Bates TR, Lynch JP (2000) The efficiency of Arabidopsis thaliana (Brassicaceae) root hairs in phosphorus acquisition. Am J Bot 87:964–970
Bates TR, Lynch JP (2001) Root hairs confer a competitive advantage under low phosphorus availability. Plant Soil 236:243–250
Baxter I, Hosmani PS, Rus A, Lahner B, Borevitz JO, Muthukumar B, Mickelbart MV, Schreiber L, Franke RB, Salt DE (2009) Root suberin forms an extracellular barrier that affects water relations and mineral nutrition in Arabidopsis. PLoS Genet 5:e1000492
Benes B, Guan K, Lang M, Long SP, Lynch JP, Marshall-Colón A, Peng B, Schnable J, Sweetlove LJ, Turk MJ (2020) Multiscale computational models can guide experimentation and targeted measurements for crop improvement. Plant J 103:21–31
Bengough A, Mullins C (1990) Mechanical impedance to root growth: a review of experimental techniques and root growth responses. J Soil Sci 41:341–358
Bengough AG, Bransby MF, Hans J, McKenna SJ, Roberts TJ, Valentine TA (2006) Root responses to soil physical conditions; growth dynamics from field to cell. J Exp Bot 57:437–447. https://doi.org/10.1093/jxb/erj003
Bengough AG, McKenzie BM, Hallett PD, Valentine TA (2011) Root elongation, water stress, and mechanical impedance: A review of limiting stresses and beneficial root tip traits. J Exp Bot 62:59–68
Bengough AG, Mullins CE, Wilson G (1997) Estimating soil frictional resistance to metal probes and its relevance to the penetration of soil by roots. Eur J Soil Sci 48:603–612
Berg B, McClaugherty C (2003) Plant litter. Springer, Berlin Heidelberg
Bergelson J, Mittelstrass J, Horton MW (2019) Characterizing both bacteria and fungi improves understanding of the Arabidopsis root microbiome. Sci Rep 9(1):1–1
Bergmann D, Zehfus M, Zierer L, Smith B, Gabel M (2009) Grass rhizosheaths: associated bacterial communities and potential for nitrogen fixation. West North Am Nat 69:105–114. https://doi.org/10.3398/064.069.0102
Bhat KKS, Nye PH (1974) Diffusion of phosphate to plant roots in soil. Plant Soil 41:383–394
Bhosale R, Giri J, Pandey BK, Giehl RF, Hartmann A, Traini R, Truskina J, Leftley N, Hanlon M, Swarup K, Rashed A (2018) A mechanistic framework for auxin dependent Arabidopsis root hair elongation to low external phosphate. Nat Commun 9
Bingham IJ, Bengough AG (2003) Morphological plasticity of wheat and barley roots in response to spatial variation in soil strength. Plant Soil 250:273–282
Bingham IJ, Bengough AG, Rees RM (2010) Soil compaction-N interactions in barley: Root growth and tissue composition. Soil Tillage Res 106:241–246
Bo Hu, Henry A, Brown KM, Lynch JP (2014) Root cortical aerenchyma inhibits radial nutrient transport in maize (Zea mays L.). Ann Bot 113:181–189
Botwright Acuña TL, Pasuquin E, Wade LJ (2007) Genotypic differences in root penetration ability of wheat through thin wax layers in contrasting water regimes and in the field. Plant Soil 301:135–149
Boudet AM (2000) Lignins and lignification: Selected issues. Plant Physiol Biochem 38:81–96
Bouldin DR (1961) Mathematical description of diffusion processes in the soil-plant system. Soil Sci Soc Am J 25:476–480
Bouma TJ, Yanai RD, Elkin AD, Hartmond U, Flores-Alva DE, Eissenstat DM (2001) Estimating age-dependent costs and benefits of roots with contrasting life span: comparing apples and oranges. New Phytol 150:685–695. https://doi.org/10.1046/j.1469-8137.2001.00128.x
Bouranis DL, Chorianopoulou SN, Siyiannis VF, Protonotarios VE, Hawkesford MJ (2003) Aerenchyma formation in roots of maize during sulphate starvation. Planta 217:382–391
Brewer PB, Koltai H, Beveridge CA (2013) Diverse roles of strigolactones in plant development. Mol Plant 6:18–28. https://doi.org/10.1093/mp/sss130
Brown LK, George TS, Dupuy LX, White PJ (2013) A conceptual model of root hair ideotypes for future agricultural environments: what combination of traits should be targeted to cope with limited P availability? Ann Bot 112:317–330
Brown LK, George TS, Neugebauer K, White PJ (2017) The rhizosheath – a potential trait for future agricultural sustainability occurs in orders throughout the angiosperms. Plant Soil 418:115–128. https://doi.org/10.1007/s11104-017-3220-2
Brown LK, George TS, Thompson JA, Wright G, Lyon J, Dupuy L, Hubbard SF, White PJ (2012) What are the implications of variation in root hair length on tolerance to phosphorus deficiency in combination with water stress in barley (Hordeum vulgare)? Ann Bot 110:319–328. https://doi.org/10.1093/aob/mcs085
Brundrett MC, Bougher N, Dell B, Grove T, Malajczuk N (1996) Working with mycorrhizas in forestry and agriculture. Canberra: Australian Centre for International Agricultural Research
Burke S, Sadaune E, Rognon L, Fontana A, Jourdrin M, Fricke W (2020) A redundant hydraulic function of root hairs in barley plants grown in hydroponics. Funct Plant Biol. https://doi.org/10.1071/FP20287
Burridge JD, Findeis JL, Jochua CN, Miguel MA, Mubichi-Kut FM, Quinhentos ML, Xerinda SA, Lynch JP (2019) A case study on the efficacy of root phenotypic selection for edaphic stress tolerance in low-input agriculture: Common bean breeding in Mozambique. Field Crops Res 244:107612
Burton A, Williams M, Lynch JP, Brown K (2012) RootScan: Software for high-throughput analysis of root anatomical traits. Plant Soil 357:189–203
Bushamuka V, Zobel R (1998) Differential genotypic and root type penetration of compacted soil layers. Crop Sci 38:776–781
Byrne ME, Kidner CA, Martienssen RA (2003) Plant stem cells: Divergent pathways and common themes in shoots and roots. Curr Opin Genet Dev 13:551–557. https://doi.org/10.1016/j.gde.2003.08.008
Caldwell MM, Dawson TE, Richards JH (1998) Hydraulic lift: consequences of water efflux from roots of plants. Oecologia 113:151–161
Caldwell MM, Richards JH (1989) Hydraulic lift: water efflux from upper roots improves effectiveness of water uptake by deep roots. Oecologia 79:1–5. https://doi.org/10.1007/BF00378231
Canales J, Contreras-López O, Álvarez JM, Gutiérrez RA (2017) Nitrate induction of root hair density is mediated by TGA1/TGA4 and CPC transcription factors in Arabidopsis thaliana. Plant J 92:305–316
Carlquist S (2012) Monocot xylem revisited: new information, new paradigms. Bot Rev 78:87–153
Carminati A, Moradi AB, Vetterlein D, Vontobel P, Lehmann E, Weller U, Vogel HJ, Oswald SE (2010) Dynamics of soil water content in the rhizosphere. Plant Soil 332:163–176
Carminati A, Passioura JB, Zarebanadkouki M, Ahmed MA, Ryan PR, Watt M, Delhaize E (2017) Root hairs enable high transpiration rates in drying soils. New Phytol. https://doi.org/10.1111/nph.14715
Carpita NC (1996) Structure and biogenesis of the cell walls of grasses. Annu Rev Plant Physiol Plant Mol Biol 47:445–476. https://doi.org/10.1146/annurev.arplant.47.1.445
Carpita NC, Gibeaut DM (1993) Structural models of primary cell walls in flowering plants: Consistency of molecular structure with the physical properties of the walls during growth. Plant J 3:1–30. https://doi.org/10.1111/j.1365-313X.1993.tb00007.x
Castano-Duque L, Loades KW, Tooker JF, Brown KM, Williams WP, Luthe DS (2017) A maize inbred exhibits resistance against western corn rootwoorm, Diabrotica virgifera virgifera. J Chem Ecol 43:1109–1123. https://doi.org/10.1007/s10886-017-0904-2
Chapman N, Miller AJ, Lindsey K, Whalley WR (2012) Roots, water, and nutrient acquisition: let’s get physical. Trends Plant Sci 17:701–710
Chen G, Weil RR, Hill RL (2014a) Effects of compaction and cover crops on soil least limiting water range and air permeability. Soil Tillage Res 136:61–69
Chen Y, Lübberstedt T (2010) Molecular basis of trait correlations. Trends Plant Sci 15:454–461. https://doi.org/10.1016/j.tplants.2010.05.004
Chen YL, Palta J, Clements J, Buirchell B, Siddique KHM, Rengel Z (2014b) Root architecture alteration of narrow-leafed lupin and wheat in response to soil compaction. F Crop Res 165:61–70
Chickarmane V, Roeder AH, Tarr PT, Cunha A, Tobin C, Meyerowitz EM (2010) Computational morphodynamics: a modeling framework to understand plant growth. Annu Rev Plant Biol 61:65–87
Chimungu JG, Brown KM, Lynch JP (2014a) Large root cortical cell size improves drought tolerance in maize. Plant Physiol 166:2166–2178. https://doi.org/10.1104/pp.114.250449
Chimungu JG, Brown KM, Lynch JP (2014b) Reduced root cortical cell file number improves drought tolerance in maize. Plant Physiol 166:1943–1955. https://doi.org/10.1104/pp.114.249037
Chimungu JG, Loades KW, Lynch JP (2015a) Root anatomical phenes predict root penetration ability and biomechanical properties in maize (Zea mays). J Exp Bot 66:3151–3162
Chimungu JG, Maliro MF, Nalivata PC, Kanyama-Phiri G, Brown KM, Lynch JP (2015b) Utility of root cortical aerenchyma under water limited conditions in tropical maize (Zea mays L.). F Crop Res 171:86–98. https://doi.org/10.1016/j.fcr.2014.10.009
Chmielewska B, Janiak A, Karcz J, Guzy-Wrobelska J, Forster BP, Nawrot M, Rusek A, Smyda P, Kedziorski P, Maluszynski M, Szarejko I (2014) Morphological, genetic and molecular characteristics of barley root hair mutants. J Appl Genet 55(4):433–447
Choi HS, Cho HT (2019) Root hairs enhance Arabidopsis seedling survival upon soil disruption. Sci Rep 9:1–10. https://doi.org/10.1038/s41598-019-47733-0
Chopin J, Laga H, Huang CY, Heuer S, Miklavcic SJ (2015) RootAnalyzer: a cross-section image analysis tool for automated characterization of root cells and tissues. PLoS One 10:9–e0137655
Clark L, Whalley W, Barraclough P (2003) How do roots penetrate strong soil? Plant Soil 255:93–104
Colmer TD (2003) Long-distance transport of gases in plants: A perspective on internal aeration and radial oxygen loss from roots. Plant, Cell Environ 26:17–36
Colombi T, Herrmann AM, Vallenback P, Keller T (2019) Cortical cell diameter is key to energy costs of root growth in wheat. Plant Physiol 180:2049–2060. https://doi.org/10.1104/pp.19.00262
Colombi T, Kirchgessner N, Walter A, Keller T (2017a) Root tip shape governs root elongation rate under increased soil strength. Plant Physiol 174:2289–2301
Colombi T, Braun S, Keller T, Walter A (2017b) Artificial macropores attract crop roots and enhance plant productivity on compacted soils. Sci Total Environ 574:1283–1293. https://doi.org/10.1016/j.scitotenv.2016.07.194
Colombi T, Walter A (2015) Root responses of triticale and soybean to soil compaction in the fi eld are reproducible under controlled conditions. Funct Plant Biol 43:114–128
Colombi T, Walter A (2017) Genetic diversity under soil compaction in wheat: Root number as a promising trait for early plant vigor. Front Plant Sci 8:1–14
Comber NM (1922) The availability of mineral plant food. J Agric Sci 12:363–369
Compant S, Samad A, Faist H, Sessitsch A (2019) A review on the plant microbiome: ecology, functions, and emerging trends in microbial application. J Adv Res 19:29–37
Cosgrove DJ (1999) Enzymes and other agents that enhance cell wall extensibility. Annu Rev Plant Biol 50:391–417. https://doi.org/10.1146/annurev.arplant.50.1.391
Cosgrove, DJ (2005) Growth of the plant cell wall. Nat Rev Mol Cell Biol 6(11):850–61.https://doi.org/10.1038/nrm1746
Couvreur V, Faget M, Lobet G, Javaux M, Chaumont F, Draye X (2018) Going with the flow: Multiscale insights into the composite nature of water transport in roots. Plant Physiol 178:1689–1703. https://doi.org/10.1104/pp.18.01006
Cuneo IF, Knipfer T, Brodersen CR, McElrone AJ (2016) Mechanical failure of fine root cortical cells initiates plant hydraulic decline during drought. Plant Physiol 172:1669–1678. https://doi.org/10.1104/pp.16.00923
Dawson TE (1993) Hydraulic lift and water use by plants: implications for water balance, performance and plant-plant interactions. Oecologia 95:565–574. https://doi.org/10.1007/BF00317442
De la Riva LM, Lynch JP (2010) Root etiolation as a strategy for phosphorus acquisition in common bean. Master’s dissertation, Pennsylvania State University
de Souza TC, de Castro EM, Magalhães PC, Lino LD, Alves ET, de Albuquerque PE (2013) Morphophysiology, morphoanatomy, and grain yield under field conditions for two maize hybrids with contrasting response to drought stress. Acta Physiologiae Plantarum. 1;35(11):3201–11
Deacon JW, Lewis SJ (1982) Natural senescence of the root cortex of spring wheat in relation to susceptibility to common root rot (Cochliobolus sativus) and growth of a free-living nitrogen-fixing bacterium. Plant Soil 66(1):13–20. https://doi.org/10.1007/BF02203397
Delhaize E, James RA, Ryan PR (2012) Aluminium tolerance of root hairs underlies genotypic differences in rhizosheath size of wheat (Triticum aestivum) grown on acid soil. New Phytol 195:609–619. https://doi.org/10.1111/j.1469-8137.2012.04183.x
Delhaize E, Rathjen TM, Cavanagh CR (2015) The genetics of rhizosheath size in a multiparent mapping population of wheat. J Exp Bot 66:4527–4536. https://doi.org/10.1093/jxb/erv223
Dhondt S, Wuyts N, Inzé D (2013) Cell to whole-plant phenotyping: the best is yet to come. Trends Plant Sci 18(8):428–439
Dickison WC (2008) Integrative plant anatomy. Academic Press, San Diego
Dittmer HJ (1937) A quantitative study of the roots and root hairs of a winter rye plant (Secale Cereale). Am J Bot 24:417–420
Dodd IC, Diatloff E (2016) Enhanced root growth of the brb (bald root barley) mutant in drying soil allows similar shoot physiological responses to soil water deficit as wild-type plants. Funct Plant Biol. https://doi.org/10.1071/FP15303
Dolan L (2017) Root hair development in grasses and cereals (Poaceae). Curr Opin Genet Dev 45:76–81
Doussan C, Pagès L, Vercambre G (1998) Modelling of the hydraulic architecture of root systems: an integrated approach to water absorption: Model description. Ann Bot 81(2):213–223
Doussan C, Pierret A, Garrigues E, Pages L (2006) Water uptake by plant roots: II - Modelling of water transfer in the soil root-system with explicit account of flow within the root system - Comparison with experiments. Plant Soil 283(1–2):99–117
Drew M, Saker L (1986) Ion Transport to the Xylem in Aerenchymatous Roots of Zea mays L. J Exp Bot 37(174):22–33
Dreyer B, Morte A, López JÁ, Honrubia M (2010) Comparative study of mycorrhizal susceptibility and anatomy of four palm species. Mycorrhiza 20(2):103–115. https://doi.org/10.1007/s00572-009-0266-x
Duell RW, Peacock GR (1985) Rhizosheaths on Mesophytic Grasses 1. Crop Sci 25:880–883. https://doi.org/10.2135/cropsci1985.0011183x002500050036x
Eissenstat DM (1992) Costs and benefits of constructing roots of small diameter. J Plant Nutr 15:763–782. https://doi.org/10.1080/01904169209364361
Emmett B, Nelson EB, Kessler A, Bauerle TL (2014) Fine-root system development and susceptibility to pathogen colonization. Planta 239(2):325–340. https://doi.org/10.1007/s00425-013-1989-7
Enstone DE, Peterson CA, Ma F (2003) Root endodermis and exodermis: structure, function, and responses to the environment. J Plant Growth Regul 21:335–351
Evert RF, Eichhorn SE (2006) Esau’s plant anatomy: Meristems, cells, and tissues of the plant body—their structure, function and development, 3rd edn. John Wiley and Sons, Hoboken
Fan M, Bai R, Zhao X, Zhang J (2007) Aerenchyma formed under phosphorus deficiency contributes to the reduced root hydraulic conductivity in maize roots. J Integr Plant Biol 49:598–604
Farrar J, Hawes M, Jones D, Lindow S (2003) How roots control the flux of carbon to the rhizosphere. Ecology 84:827–837
Feijó JA, Moreno N (2002) Imaging plant cells by two-photon excitation. Protoplasma 223(1):1–32
Feng W, Lindner H, Robbins NE, Dinneny JR (2016) Growing out of stress: the role of cell- and organ-scale growth control in plant water-stress responses. Plant Cell 28:1769–1782
Foehse D, Jungk A (1983) Influence of phosphate and nitrate supply on root hair formation of rape, spinach and tomato plants. Plant Soil 74:359–368
Fohse D, Claassen N, Jungk A (1988) Phosphorus efficiency of plants.1. External and internal P requirement and P uptake efficiency of different plant species. Plant Soil 110:101–109. https://doi.org/10.1007/bf02143545
Gahoonia TS, Nielsen NE (1997) Variation in root hairs of barley cultivars doubled soil phosphorus uptake. Euphytica 98:177–182
Gahoonia TS, Nielsen NE (2004) Barley genotypes with long root hairs sustain high grain yields in low-P field. Plant Soil 262:55–62
Gahoonia TS, Nielsen NE, Joshi PA, Jahoor A (2001) A root hairless barley mutant for elucidating genetic of root hairs and phosphorus uptake. Plant Soil 235:211–219
Galindo-Castañeda T, Brown KM, Kuldau GA, Roth GW, Wenner NG, Ray S, Schneider H, Lynch JP (2019) Root cortical anatomy is associated with differential pathogenic and symbiotic fungal colonization in maize. Plant, Cell Environ 42(11):2999–3014. https://doi.org/10.1111/pce.13615
Galindo-Castañeda T, Brown KM, Lynch JP (2018) Reduced root cortical burden improves growth and grain yield under low phosphorus availability in maize. Plant Cell Environ 1–14
Gallardo M, Eastham J, Gregory PJ, Turner NC (1996) A comparison of plant hydraulic conductances in wheat and lupins. J Exp Bot 47:233–239
Gao K, Chen F, Yuan L, Zhang F, Mi G (2015) A comprehensive analysis of root morphological changes and nitrogen allocation in maize in response to low nitrogen stress. Plant, Cell Environ 38:740–750
Garrett SD (1981) CHAPTER 9 – Root-infecting fungi. In S. D. Garrett (Ed.), Soil Fungi and Soil Fertility (Second Edition) (pp. 124–140): Pergamon
Gaudin AC, Mcclymont SA, Holmes BM, Lyons E, Raizada MN (2011) Novel temporal, fine-scale and growth variation phenotypes in roots of adult-stage maize (Zea mays L.) in response to low nitrogen stress. Plant Cell Environ 34:2122–2137
Genc Y, Huang CY, Langridge P (2007) A study of the role of root morphological traits in growth of barley in zinc-deficient soil. J Exp Bot 58:2775–2784
George TS, Brown LK, Ramsay L, White PJ, Newton AC, Bengough AG, Russell J, Thomas WT (2014) Understanding the genetic control and physiological traits associated with rhizosheath production by barley (Hordeum vulgare). New Phytol 203:195–205. https://doi.org/10.1111/nph.12786
Gerlach N, Schmitz J, Polatajko A, Schlüter U, Fahnenstich H, Witt S, Bucher M (2015) An integrated functional approach to dissect systemic responses in maize to arbuscular mycorrhizal symbiosis. Plant, Cell Environ 38(8):1591–1612. https://doi.org/10.1111/pce.12508
Gerrienne P, Gonez P (2011) Early evolution of life cycles in embryophytes: A focus on the fossil evidence of gametophyte/sporophyte size and morphological complexity. J Syst Evol 49:1–16. https://doi.org/10.1111/j.1759-6831.2010.00096.x
Giovanni S, Renna L, Federica B (2017) Plant cell vacuoles: staining and fluorescent probes. J Chem Inf Model 110:1689–1699
Giri J, Bhosale R, Huang G, Pandey BK, Parker H, Zappala S, Yang J, Dievart A, Bureau C, Ljung K, Price A (2018) Rice auxin influx carrier OsAUX1 facilitates root hair elongation in response to low external phosphate. Nat Commun 9:1408
Gitz DC III, Baker JT, Lascano RJ (2015) Relating xylem cavitation to gas exchange in cotton. Am J Plant Sci 6:1742–1751
Guo D, Xia M, Wei X, Chang W, Liu Y, Wang Z (2008) Anatomical traits associated with absorption and mycorrhizal colonization are linked to root branch order in twenty-three Chinese temperate tree species. New Phytol 180(3):673–683. https://doi.org/10.1111/j.1469-8137.2008.02573.x
Hacke UG, Sperry JS (2001) Functional and ecological xylem anatomy. Perspectives in Plant Ecology Evolution and Systematics 4:97–115. https://doi.org/10.1078/1433-8319-00017
Hacke UG, Sperry JS, Wheeler JK, Castro L (2006) Scaling of angiosperm xylem structure with safety and efficiency. Tree Physiol 26:689–701
Hacke UG, Spicer R, Schreiber SG, Plavcova L (2017) An ecophysiological and developmental perspective on variation in vessel diameter. Plant, Cell Environ 40:831–845. https://doi.org/10.1111/pce.12777
Hacke UG, Stiller V, Sperry JS, Pittermann J, McCulloh KA (2001) Cavitation fatigue. Embolism and refilling cycles can weaken the cavitation resistance of xylem. Plant Physiol 125:779–786
Haling RE, Brown LK, Bengough AG, Valentine TA, White PJ, Young IM, George TS (2014) Root hair length and rhizosheath mass depend on soil porosity, strength and water content in barley genotypes. Planta 239:643–651. https://doi.org/10.1007/s00425-013-2002-1
Haling RE, Brown LK, Bengough AG, Young IM, Hallett PD, White PJ, George TS (2013) Root hairs improve root penetration, root–soil contact, and phosphorus acquisition in soils of different strength. J Exp Bot 64:3711–3721. https://doi.org/10.1093/jxb/ert200
Haling RE, Richardson AE, Culvenor RA, Lambers H, Simpson RJ (2010) Effect of lime on root growth, morphology and the rhizosheath of cereal seedlings growing in an acid soil. Plant Soil 327:199–212. https://doi.org/10.1007/s11104-009-0047-5
Hall B, Lanba A, Lynch JP (2019) Three-dimensional analysis of biological systems via a novel laser ablation technique. J Laser Appl 31:022602. https://doi.org/10.2351/1.5108633
Hanlon MT, Ray S, Saengwilai P, Luthe D, Lynch JP, Brown KM (2018) Buffered delivery of phosphate to Arabidopsis alters responses to low phosphate. J Exp Bot 69:1207–1219
Hazman M, Brown KM (2018) Progressive drought alters architectural and anatomical traits of rice roots. Rice 11:62. https://doi.org/10.1186/s12284-018-0252-z
Henry A, Mabit L, Jaramillo RE, Cartagena Y, Lynch JP (2012) Land use effects on erosion and carbon storage of the Río Chimbo watershed, Ecuador. Plant Soil 367:477–491
Hepler PK, Gunning BES (1998) Confocal fluorescence microscopy of plant cells. Protoplasma 201:121–157
Heymans A, Couvreur V, LaRue T, Paez-Garcia A, Lobet G (2020a) GRANAR, a computational tool to better understand the functional importance of monocotyledon root anatomy. Plant Physiol 182(2):707–720
Heymans A, Couvreur V, Lobet G (2020b) Connecting the dots between root cross-section images and modelling tools to create a high-resolution root system hydraulic maps in Zea mays. bioRxiv 12.15.422825. https://doi.org/10.1101/2020.12.15.422825
Hijri M (2016) Analysis of a large dataset of mycorrhiza inoculation field trials on potato shows highly significant increases in yield. Mycorrhiza 26(3):209–214
Ho MD, Rosas JC, Brown KM, Lynch JP (2005) Root architectural tradeoffs for water and phosphorus acquisition. Funct Plant Biol 32:737–748
Hochholdinger F, Wen TJ, Zimmermann R, Chimot-Marolle P, Costa Da, e Silva O, Bruce W, Lamkey KR, Wienand U, Schnable PS, (2008) The maize (Zea mays L.) roothairless3 gene encodes a putative GPI-anchored, monocot-specific, COBRA-like protein that significantly affects grain yield. Plant J 54:888–898
Hodgman TC, Ajmera I (2015) The successful application of systems approaches in plant biology. Prog Biophys Mol Biol 117(1):59–68
Hoffman LA, Tomescu AMF (2013) An early origin of secondary growth: Franhueberia gerriennei gen. et sp nov from the lower Devonian of Gaspe (Quebec, Canada). Am J Bot 100:754–763. https://doi.org/10.3732/ajb.1300024
Höfte H, Voxeur A (2017). Plant Cell Walls. https://doi.org/10.1016/j.cub.2017.05.025
Hol WHG, Vrieling K, van Veen JA (2003) Nutrients decrease pyrrolizidine alkaloid concentrations in Senecio jacobaea. New Phytol 158:175–181
Holz M, Zarebanadkouki M, Carminati A, Becker JN, Spohn M (2020) The effect of root hairs on rhizosphere phosphatase activity. J Plant Nutr Soil Sci 183:382–388
Holz M, Zarebanadkouki M, Kuzyakov Y, Pausch J, Carminati A (2017) Root hairs increase rhizosphere extension and carbon input to soil. Ann Bot. https://doi.org/10.1093/aob/mcx127
Hu B, Henry A, Brown KM, Lynch JP (2014) Root cortical aerenchyma inhibits radial nutrient transport in maize (Zea mays). Ann Bot 113:181–189
Ibáñez F, Wall L, Fabra A (2017) Starting points in plant-bacteria nitrogen-fixing symbioses: intercellular invasion of the roots. J Exp Bot 68:1905–1918
Iijima M, Griffiths B, Bengough AG (2000) Sloughing of cap cells and carbon exudation from maize seedling roots in compacted sand. New Phytol 145:477–482
Ishaq M, Ibrahim M, Hassan A, Saeed M, Lal R (2001) Subsoil compaction effects on crops in Punjab, Pakistan: II. Root growth and nutrient uptake of wheat and sorghum. Soil Tillage Res 60:153–161
Itoh S, Barber SA (1983) Phosphorus uptake by six plant species as related to root Hairs1. Agron J 75:457–461
Jackson MB, Fenning TM, Drew MC, Saker LR (1985) Stimulation of ethylene production and gas-space (aerenchyma) formation in adventitious roots of Zea mays L. by small partial pressures of oxygen. Planta 165:486–492
Jakobsen I, Chen B, Munkvold L, Lundsgaard T, Zhu YG (2005) Contrasting phosphate acquisition of mycorrhizal fungi with that of root hairs using the root hairless barley mutant. Plant Cell Environ 28:928–938
James RA, Weligama C, Verbyla K, Ryan PR, Rebetzke GJ, Rattey A, Richardson AE, Delhaize E (2016) Rhizosheaths on wheat grown in acid soils: phosphorus acquisition efficiency and genetic control. J Exp Bot 67:3709–3718. https://doi.org/10.1093/jxb/erw035
Janes G, von Wangenheim D, Cowling S, Kerr I, Band L, French AP, Bishopp A (2018) Cellular patterning of Arabidopsis roots under low phosphate conditions. Front Plant Sci 9:735
Jansa J, Mozafar A, Frossard E (2003) Long-distance transport of P and Zn through the hyphae of an arbuscular mycorrhizal fungus in symbiosis with maize. Agronomie 23(5–6), 481–488. Retrieved fromhttps://doi.org/10.1051/agro:2003013
Janssen J (2000) Designing and building with bamboo. International Network for Bamboo and Rattan (INBAR). Beijing. China Tech Rep 20
Jaramillo RE, Nord EA, Chimungu JG, Brown KM, Lynch JP (2013) Root cortical burden influences drought tolerance in maize. Ann Bot 112:429–437. https://doi.org/10.1093/aob/mct069
Jarvis MC, Forsyth W, Duncan HJ (1988) A survey of the pectic content of nonlignified monocot cell walls. Plant Physiol 88:309–314. https://doi.org/10.1104/pp.88.2.309
Javaux M, Schröder T, Vanderborght J, Vereecken H (2008) Use of a three-dimensional detailed modeling approach for predicting root water uptake. Vadose Zone J 7:1079–1088
Jin K, Shen J, Ashton RW, Dodd IC, Parry MAJJ, Whalley WR (2013) How do roots elongate in a structured soil? J Exp Bot 64:4761–4777
Jobbagy EG, Jackson RB (2000) The vertical distribution of soil organic carbon and its relation to climate and vegetation. Ecol Appl 10:423–436. https://doi.org/10.2307/2641104
Johnson SN, Hallett PD, Gillespie TL, Halpin C (2010) Below-ground herbivory and root toughness: a potential model system using lignin-modified tobacco. Physiol Entomol 35:186–191
Jones DL, Hodge A, Kuzyakov Y (2004) Plant and mycorrhizal regulation of rhizodeposition. New Phytol 163:459–480. https://doi.org/10.1111/j.1469-8137.2004.01130.x
Jungk A (2001) Root hairs and the acquisition of plant nutrients from soil. J Plant Nutr Soil Sci 164:121–129
Kadam NN, Yin X, Bindraban PS, Struik PC, Jagadish KS (2015) Does morphological and anatomical plasticity during the vegetative stage make wheat more tolerant of water deficit stress than rice? Plant Physiol 167:1389–1401
Kaeppler SM, Parke JL, Mueller SM, Senior L, Stuber C, Tracy WF (2000) Variation among maize inbred lines and detection of quantitative trait loci for growth at low phosphorus and responsiveness to arbuscular mycorrhizal fungi. Crop Sci 40(2):358–364
Kell DB (2011) Breeding crop plants with deep roots: their role in sustainable carbon, nutrient and water sequestration. Ann Bot 108:407–418. https://doi.org/10.1093/aob/mcr175
Kell DB (2012) Large-scale sequestration of atmospheric carbon via plant roots in natural and agricultural ecosystems: why and how. Philosophical Transactions of the Royal Society B-Biological Sciences 367:1589–1597. https://doi.org/10.1098/rstb.2011.0244
Kelly JM, Barber SA (1991) Magnesium uptake kinetics in loblolly pine seedlings. Plant Soil 134:227–232
Klamer F, Vogel F, Li X, Bremer H, Neumann G, Neuhäuser B, Hochholdinger F, Ludewig U (2019) Estimating the importance of maize root hairs in low phosphorus conditions and under drought. Ann Bot 124:961–968
Klein SP, Schneider HM, Perkins AC, Brown KM, Lynch JP (2020) Multiple integrated root phenotypes are associated with improved drought tolerance. Plant Physiol 183(3):1011–1025
Kögel-Knabner I (2002) The macromolecular organic composition of Plant and microbial residues as inputs to soil organic matter. Soil Biol Biochem. https://doi.org/10.1016/S0038-0717(01)00158-4
Kotula L, Ranathunge K, Schreiber L, Steudle E (2009) Functional and chemical comparison of apoplastic barriers to radial oxygen loss in roots of rice (Oryza sativa L.) grown in aerated or deoxygenated solution. J Exp Bot 60:2155–2167
Kubo K, Iwama K, Yanagisawa A, Watanabe Y, Terauchi T, Jitsuyama Y, Mikuma T (2006) Genotypic variation of the ability of root to penetrate hard soil layers among Japanese wheat cultivars. Plant Prod Sci 9:47–55
Kumar A, Shahbaz M, Koirala M et al (2019) Root trait plasticity and plant nutrient acquisition in phosphorus limited soil. J Plant Nutr Soil Sci 182:945–952
Lambers H, Juniper D, Cawthray GR et al (2002) The pattern of carboxylate exudation in Banksia grandis (Proteaceae) is affected by the form of phosphate added to the soil. Plant Soil 238:111–122. https://doi.org/10.1023/a:1014289121672
Larson PR (1994) The vascular cambium: development and structure. Springer, Berlin
Lartaud M, Perin C, Courtois B, Thomas E, Henry S, Bettembourg M, Divol F, Lanau N, Artus F, Bureau C, Verdeil JL, Sarah G, Guiderdoni E, Dievart A (2015) PHIV-RootCell: a supervised image analysis tool for rice root anatomical parameter quantification. Front Plant Sci 5:790
Laux T, Würschum T, Breuninger H (2004) Genetic regulation of embryonic pattern formation. Plant Cell 16:S190–S202. https://doi.org/10.1105/tpc.016014
Legland D, Devaux MF, Guillon F (2018) Quantitative imaging of plants: multi-scale data for better plant anatomy. J Exp Bot 69(3):343–347
Leitner D, Meunier F, Bodner G, Javaux M, Schnepf A (2014) Impact of contrasted maize root traits at flowering on water stress tolerance - A simulation study. Field Crop Res 165:125–137. https://doi.org/10.1016/j.fcr.2014.05.009
Levin KA, Tucker MR, Strock CF, Lynch JP, Mather DE (2021) Three-dimensional imaging reveals differences in the position of cyst nematode feeding sites relative to xylem vessels in susceptible and resistant wheat. Plant Cell Reports, In press
Lewis AM, Boose ER (1995) Estimating volume flow rates through xylem conduits. Am J Bot 82:1112–1116
Lipiec J, Horn R, Pietrusiewicz J, Siczek A (2012) Effects of soil compaction on root elongation and anatomy of different cereal plant species. Soil Tillage Res 121:74–81
Liu TY, Ye N, Song T, Cao Y, Gao B, Zhang D, Zhu F, Chen M, Zhang Y, Xu W, Zhang J (2018) Rhizosheath formation and involvement in foxtail millet (Setaria italica) root growth under drought stress. J Integr Plant Biol 61. https://doi.org/10.1111/jipb.12716
Liu Y, von Wirén N (2017) Ammonium as a signal for physiological and morphological responses in plants. J Exp Bot 68:2581–2592
Lobet G (2017) Image analysis in plant sciences: publish then perish. Trends Plant Sci 22(7):559–566
Lobet G, Draye X, Périlleux C (2013) An online database for plant image analysis software tools. Plant Methods 9(1):38
Lucas M, Schlüter S, Vogel HJ, Vetterlein D (2019a) Roots compact the surrounding soil depending on the structures they encounter. Sci Rep 9(1):1–3
Lucas M, Schlüter S, Vogel HJ, Vetterlein D (2019b) Soil structure formation along an agricultural chronosequence. Geoderma 350:61–72. https://doi.org/10.1016/j.geoderma.2019.04.041
Lipiec J, Hatano R (2003) Quantifcation of compaction efects on soil physical properties and crop growth. Geoderma 116:107–136. https://doi.org/10.1016/S0016-7061(03)00097-1
Lulai EC, Corsini DL (1998) Differential deposition of suberin phenolic and aliphatic domains and their roles in resistance to infection during potato tuber (Solanum tuberosum L.) wound-healing. Physiol Mol Plant Pathol 53:209–222. https://doi.org/10.1006/pmpp.1998.0179
Lux A, Luxová M, Abe J, Morita S (2010) Root cortex: structural and functional variability and responses to environmental stress. Root Res 13:117–131
Lynch J, Nielsen K, Davis R, Jablokow A (1997) SimRoot: Modelling and visualization of root systems. Plant Soil 188:139–151
Lynch JP (1995) Root architecture and plant productivity. Plant Physiol 109:7–13
Lynch JP (2007) Roots of the second green revolution. Aust J Bot 55:493–512. https://doi.org/10.1071/bt06118
Lynch JP (2011) Root phenes for enhanced soil exploration and phosphorus acquisition: tools for future crops. Plant Physiol 156:1041–1049
Lynch JP (2013) Steep, cheap and deep: an ideotype to optimize water and N acquisition by maize root systems. Ann Bot 112:347–357
Lynch JP (2015) Root phenes that reduce the metabolic costs of soil exploration: Opportunities for 21st century agriculture. Plant, Cell Environ 38:1775–1784. https://doi.org/10.1111/pce.12451
Lynch JP (2018) Rightsizing root phenotypes for drought resistance. J Exp Bot 69:3279–3292
Lynch JP (2019) Root phenotypes for improved nutrient capture: an underexploited opportunity for global agriculture. New Phytol 223:548–564
Lynch JP, Brown KM (2001) Topsoil foraging – an architectural adaptation of plants to low phosphorus availability. Plant Soil 237:225–237
Lynch JP, Brown KM (2008) Root strategies for phosphorus acquisition. In: White PJ, Hammond JP (eds) The ecophysiology of plant–phosphorus interactions. Springer, Dordrecht, pp 83–116
Lynch JP, Brown KM (2012) New roots for agriculture: exploiting the root phenome. Philos Trans R Soc Ser B 367:1598–1604
Lynch JP, Chimungu JG, Brown KM (2014) Root anatomical phenes associated with water acquisition from drying soil: targets for crop improvement. J Exp Bot 65:6155–6166
Lynch JP, Wojciechowski T (2015) Opportunities and challenges in the subsoil: pathways to deeper rooted crops. J Exp Bot 66:2199–2210
Ma Z, Bielenberg DG, Brown KM, Lynch JP (2001a) Regulation of root hair density by phosphorus availability in Arabidopsis thaliana. Plant Cell Environ 24:459–467
Ma Z, Walk TC, Marcus A, Lynch JP (2001b) Morphological synergism in root hair length, density, initiation and geometry for phosphorus acquisition in Arabidopsis thaliana: A modeling approach. Plant Soil 236:221–235
Ma ZQ, Guo DL, Xu XL, Lu MZ, Bardgett RD, Eissenstat DM, McCormack ML, Hedin LO (2018) Evolutionary history resolves global organization of root functional traits. Nature 555:94–97. https://doi.org/10.1038/nature25783
Machado A, Pereira H, Teixeira RT (2013) Anatomy and development of the endodermis and phellem of Quercus suber L. roots. Microsc Microanal 19:525–534. https://doi.org/10.1017/s1431927613000287
Maherali H (2014) Is there an association between root architecture and mycorrhizal growth response? New Phytol 204:192–200
Marin M, Feeney DS, Brown LK, Naveed M, Ruiz S, Koebernick N, Bengough AG, Hallett PD, Roose T, Puértolas J, Dodd IC (2020) Significance of root hairs for plant performance under contrasting field conditions and water deficit. Ann Bot. https://doi.org/10.1093/aob/mcaa181
Marshall-Colon A, Long SP, Allen DK, Allen G, Beard DA, Benes B, von Caemmerer S, Christensen AJ, Cox DJ, Hart JC, Hirst PM, Kannan K, Katz DS, Lynch JP, Millar AJ, Panneerselvam B, Price ND, Prusinkiewicz P, Raila D, Shekar RG, Shrivastava S, Shukla D, Srinivasan V, Stitt M, Turk MJ, Voit EO, Wang Y, Yin X, Zhu XG (2017) Crops in silico: generating virtual crops using an integrative and multi-scale modeling platform. Front Plant Sci 8:786
Mbow C, Rosenzweig C, Barioni LG, Benton TG, Herrero M, Krishnapillai M, Liwenga E, Pradhan P, Rivera-Ferre MG, Sapkota T, Tubiello FN, Xu Y (2019) Food Security. In: Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems [Shukla PR, Skea J, Calvo Buendia E, Masson-Delmotte V, Pörtner H-O, Roberts DC, Zhai P, Slade R, Connors S, van Diemen R, Ferrat M, Haughey E, Luz S, Neogi S, Pathak M, Petzold J, Portugal Pereira J, Vyas P, Huntley E, Kissick K, Belkacemi M, Malley J, (eds.)]
McCully M (1995) How do real roots work? Some new views of root structure. Plant Physiol 109:1–6
McCully ME (1999a) Root xylem embolisms and refilling. Relation to water potentials of soil, roots, and leaves, and osmotic potentials of root xylem sap. Plant Physiol 119:1001–1008. https://doi.org/10.1104/pp.119.3.1001
McCully ME (1999b) Roots in soil: Unearthing the complexities of roots and their rhizospheres. Annu Rev Plant Physiol Plant Mol Biol 50:695–718. https://doi.org/10.1146/annurev.arplant.50.1.695
McCully ME, Huang CX, Ling L (1998) Daily embolism and refilling of xylem vessels in the roots of field‐grown maize. New Phytol
McCully ME, Miller C, Sprague SJ, Huang CX, Kirkegaard JA (2008) Distribution of glucosinolates and sulphur-rich cells in roots of field-grown canola (Brassica napus). New Phytol 180:193–205
McKay Fletcher DM, Ruiz S, Dias T, Petroselli C, Roose T (2020) Linking root structure to functionality: the impact of root system architecture on citrate-enhanced phosphate uptake. New Phytol 227:376–391. https://doi.org/10.1111/nph.16554
McQueen-Mason SJ, Cosgrove DJ (1995) Expansin mode of action on cell walls: Analysis of wall hydrolysis, stress relaxation, and binding. Plant Physiol 107:87–100. https://doi.org/10.1104/pp.107.1.87
Meihls LN, Kaur H, Jander G (2012) Natural variation in maize defense against insect herbivores. Cold Spring Harb Symp Quant Biol 77:269–283
Miguel MA, Postma JA, Lynch JP (2015) Phene synergism between root hair length and basal root growth angle for phosphorus acquisition. Plant Physiol 167:1430–1439. https://doi.org/10.1104/pp.15.00145
Minervini M, Scharr H, Tsaftaris S (2015) Image analysis: the new bottleneck in plant phenotyping [Applications Corner]. IEEE Signal Process Mag 32:126–131
Mizuta Y, Kurihara D, Higashiyama T (2015) Two-photon imaging with longer wavelength excitation in intact Arabidopsis tissues. Protoplasma 252:1231–1240. https://doi.org/10.1007/s00709-014-0754-5
Moore BD, Johnson SN (2017) Get tough, get toxic, or get a bodyguard: identifying candidate traits conferring belowground resistance to herbivores in grasses. Front Plant Sci 7:1925
Müller M, Schmidt W (2004) Environmentally induced plasticity of root hair development in Arabidopsis. Plant Physiol 134:409–419
Nambiar EKS (1976) Uptake of Zn65 from dry soil by plants. Plant Soil 44:267–271. https://doi.org/10.1007/BF00016978
Nestler J, Keyes SD, Wissuwa M (2016) Root hair formation in rice (Oryza sativa L.) differs between root types and is altered in artificial growth conditions. J Exp Bot https://doi.org/10.1093/jxb/erw115
Nestler J, Wissuwa M (2016) Superior root hair formation confers root efficiency in some, but not all, rice genotypes upon P deficiency. Front Plant Sci 7:1935
Nielsen KL, Bouma TJ, Lynch JP, Eissenstat DM (1998) Effects of phosphorus availability and vesicular-arbuscular mycorrhizas on the carbon budget of common bean (Phaseolus vulgaris). New Phytol 139:647–656. https://doi.org/10.1046/j.1469-8137.1998.00242.x
Niones JM, Suralta RR, Inukai Y, Yamauchi A (2012) Field evaluation on functional roles of root plastic responses on dry matter production and grain yield of rice under cycles of transient soil moisture stresses using chromosome segment substitution lines. Plant Soil 359:107–120
Niones JM, Suralta RR, Inukai Y, Yamauchi A (2013) Roles of root aerenchyma development and its associated QTL in dry matter production under transient moisture stress in rice. Plant Prod Sci 16:205–216
Nye PH (1966) The effect of the nutrient intensity and buffering power of a soil, and the absorbing power, size and root hairs of a root, on nutrient absorption by diffusion. Plant Soil 25:81–105
Oldeman LR (1992) Global extent of soil degradation, In: ISRIC Bi-annual Report 1991–1992, pp 19–36, ISRIC, Wageningen, The Netherlands
Oyiga BC, Palczak J, Wojciechowski T, Lynch JP, Naz AA, Léon J, Ballvora A (2020) Genetic components of root architecture and anatomy adjustments to water-deficit stress in spring barley. Plant Cell Environ 43:692–711
Pan X, Ma L, Zhang Y, Wang J, Du J, Guo X (2017) Three-dimensional reconstruction of maize roots and quantitative analysis of metaxylem vessels based on X-ray micro-computed tomography. Can J Plant Sci 12;98(2):457–466
Pandey BK, Huang G, Bhosale R, Hartman S, Sturrock CJ, Jose L, Martin OC, Karady M, Voesenek LA, Ljung K, Lynch JP, Brown KM, Whalley WR, Mooney SJ, Zhang D, Bennett M (2021) Plant roots sense soil compaction through restricted ethylene diffusion. Science 371(6526):276–280
Pemberton LMS, Tsai S-L, Lovell PH, Harris PJ (2001) Epidermal patterning in seedling roots of Eudicotyledons. Ann Bot 87:649–654
Pfeifer J, Faget M, Walter A, Blossfeld S, Fiorani F, Schurr U, Nagel KA (2014) Spring barley shows dynamic compensatory root and shoot growth responses when exposed to localised soil compaction and fertilisation. Funct Plant Biol 41:581–597
Poirier V, Roumet C, Munson AD (2018) The root of the matter: Linking root traits and soil organic matter stabilization processes. Soil Biol Biochem 120:246–259. https://doi.org/10.1016/j.soilbio.2018.02.016
Pollastri S, Azzarello E, Masi E, Pandolfi C, Mugnai S (2012) Applications of confocal microscopy in the study of root apparatus. Measuring Roots: An Updated Approach. Springer, Berlin Heidelberg, pp 93–108
Post WM, Emanuel WR, Zinke PJ, Stangenberger AG (1982) Soil carbon pools and world life zones. Nature 298:156–159. https://doi.org/10.1038/298156a0
Postma JA, Kuppe C, Owen MR, Mellor N, Griffiths M, Bennett MJ, Lynch JP, Watt M (2017) OpenSimRoot: widening the scope and application of root architectural models. New Phytol 215:1274–1286
Postma JA, Lynch JP (2011a) Root cortical aerenchyma enhances the growth of maize on soils with suboptimal availability of nitrogen, phosphorus, and potassium. Plant Physiol 156:1190–1201. https://doi.org/10.1104/pp.111.175489
Postma JA, Lynch JP (2011b) Theoretical evidence for the functional benefit of root cortical aerenchyma in soils with low phosphorus availability. Ann Bot 107:829–841. https://doi.org/10.1093/aob/mcq199
Pound MP, French AP, Wells DM, Bennett MJ, Pridmore TP (2012) CellSeT: novel software to extract and analyze structured networks of plant cells from confocal images. Plant Cell 24(4):1353–1361
Pozo MJ, Azcon-Aguilar C (2007) Unraveling mycorrhiza-induced resistance. Curr Opin Plant Biol 10(4):393–398. https://doi.org/10.1016/j.pbi.2007.05.004
Pradal C, Dufour-Kowalski S, Boudon F, Fournier C, Godin C (2008) OpenAlea: a visual programming and component-based software platform for plant modelling. Funct Plant Biol 35(10):751–760
Price AH, Steele KA, Moore BJ, Barraclough PP, Clark LJA (2000) A combined RFLP and AFLP linkage map of upland rice (Oryza sativa L.) used to identify QTLs for root-penetration ability. Theor Appl Genet 100:49–56
Price SR (1911) The Roots of Some North African Desert-Grasses. New Phytol 10:328–340
Prince SJ, Murphy M, Mutava RN, Durnell LA, Valliyodan B, Shannon JG, Nguyen HT (2017) Root xylem plasticity to improve water use and yield in water-stressed soybean. J Exp Bot 66:2027–2036
Purushothaman R, Zaman-Allah M, Mallikarjuna N, Pannirselvam R, Krishnamurthy L, Gowda CLL (2013) Root anatomical traits and their possible contribution to drought tolerance in grain legumes. Plant Production Science 16:1–8
Ranathunge K, Steudle E, Lafitte R (2003) Control of water uptake by rice (Oryza sativa L.): role of the outer part of the root. Planta 217:193–205
Rangarajan H, Postma JA, Lynch JP (2018) Co-optimization of axial root phenotypes for nitrogen and phosphorus acquisition in common bean. Ann Bot 122:485–499
Rasse DP, Rumpel C, Dignac MF (2005) Is soil carbon mostly root carbon? Mechanisms for a specific stabilisation. Plant Soil 269:341–356. https://doi.org/10.1007/s11104-004-0907-y
Rasband W (2015) ImageJ. US National Institutes of Health, Bethesda, MD
Read DB, Bengough AG, Gregory PJ, Crawford JW, Robinson D, Scrimgeour CM, Young IM, Zhang K, Zhang X (2003) Plant roots release phospholipid surfactants that modify the physical and chemical properties of soil. New Phytol 157:315–326
Rewald B, Ephrath JE, Rachmilevitch S (2011) A root is a root is a root? Water uptake rates of Citrus root orders. Plant, Cell Environ 34:33–42. https://doi.org/10.1111/j.1365-3040.2010.02223.x
Riboulet C, Lefèvre B, Dénoue D, Barrière Y (2008) Genetic variation in maize cell wall for lignin content, lignin structure, p-hydroxycinnamic acid content, and digestibility in set of 19 lines at silage harvest maturity. Maydica 53:11–19
Richards RA, Passioura JB (1989) A breeding program to reduce the diameter of the major xylem vessel in the seminal roots of wheat and its effect on grain-yield in rain-fed environments. Aust J Agric Res 40:943–950. https://doi.org/10.1071/ar9890943
Richardson AE, Barea JM, McNeill AM, Prigent-Combaret C (2009) Acquisition of phosphorus and nitrogen in the rhizosphere and plant growth promotion by microorganisms. Plant Soil 321(1):305–339
Riedell WE, Kim AY (1990) Anatomical characterization of western corn rootworm damage in adventitious roots of maize. Journal of the Iowa Academy of Science 97:15–17
Rillig MC, Mummey DL (2006) Mycorrhizas and soil structure. New Phytol 171(1), 41–53. Retrieved from http://www.jstor.org.ezaccess.libraries.psu.edu/stable/3694482
Rivera M, Polanía J, Ricaurte J, Borrero G, Beebe S, Rao I (2019) Soil Compaction Induced Changes in Morpho-physiological Characteristics of Common Bean. J Soil Sci Plant Nutr 19:217–227
Robertson-Albertyn S, Alegria Terrazas R, Balbirnie K, Blank M, Janiak A, Szarejko I, Chmielewska B, Karcz J, Morris J, Hedley PE, George TS, Bulgarelli D (2017) Root hair mutations displace the barley rhizosphere microbiota. Front Plant Sci 8:1094
Rueden CT, Schindelin J, Hiner MC, DeZonia BE, Walter AE, Arena ET, Eliceiri KW (2017) Image J2: ImageJ for the next generation of scientific image data. BMC Bioinformatics 18(1):529
Rutten JP, Ten Tusscher K (2019) In silico roots: room for growth. Trends Plant Sci 24(3):250–262
Ryan MH, Graham JH (2018) Little evidence that farmers should consider abundance or diversity of arbuscula mycorrhizal fungi when managing crops. New Phytol 220:1092–1197
Saengwilai P, Nord EA, Chimungu JG, Brown KM, Lynch JP (2014) Root cortical aerenchyma enhances nitrogen acquisition from low-nitrogen soils in maize. Plant Physiol 166:726–735
Salas-González I, Reyt G, Flis P, Custódio V, Gopaulchan D, Bakhoum N, Dew TP, Suresh K, Franke RB, Dangl JL, Salt DE (2021) Coordination between microbiota and root endodermis supports plant mineral nutrient homeostasis. Science 371(6525).
Sandhu N, Raman KA, Torres RO, Audebert A, Dardou A, Kumar A, Henry A (2016) Rice root architectural plasticity traits and genetic regions for adaptability to variable cultivation and stress conditions. Plant Physiol 171:2562–2576
Sanio C (1873) Anatomie der gemeinen Kiefer (Pinus silvestris L.) II. Entwickelungsgeschichte der holzzellen. Jahrb Wiss Bot 9:50–128
Sawers RJ, Svane SF, Quan C, Grønlund M, Wozniak B, Gebreselassie MN, González-Muñoz E, Chávez Montes RA, Baxter I, Goudet J, Jakobsen I (2017) Phosphorus acquisition efficiency in arbuscular mycorrhizal maize is correlated with the abundance of root-external hyphae and the accumulation of transcripts encoding PHT1 phosphate transporters. New Phytol 214(2):632–643. https://doi.org/10.1111/nph.14403
Schindelin J, Arganda-Carreras I, Frise E, Kaynig V, Longair M, Pietzsch T, Preibisch S, Rueden C, Saalfeld S, Schmid B, Tinevez JY, White DJ, Hartenstein V, Eliceiri K, Tomancak P, Cardona A (2012) Fiji: an open-source platform for biological-image analysis. Nat Methods 9(7):676–682
Schnepf A, Leitner D, Landl M, Lobet G, Mai TH, Morandage S, Sheng C, Zörner M, Vanderborght J, Vereecken H (2018) CRootBox: a structural-functional modelling framework for root systems. Ann Bot 121(5):1033–1053
Schneider HM, Klein SP, Hanlon MT, Kaeppler S, Brown KM, Lynch JP (2020a) Genetic control of root anatomical plasticity in maize. Plant Genome 13:e20003
Schneider HM, Klein SP, Hanlon MT, Nord EA, Kaeppler S, Brown KM, Warry A, Bhosale R, Lynch JP (2020b) Genetic control of root architectural plasticity in maize. J Exp Bot 71:3185–3197
Schneider HM, Lynch JP (2018) Functional implications of root cortical senescence for soil resource capture. Plant Soil 423:13–26. https://doi.org/10.1007/s11104-017-3533-1
Schneider HM, Lynch JP (2020) Should root plasticity be a crop breeding target? Front Plant Sci 11:1–16
Schneider HM, Postma JA, Kochs J, Pflugfelder D, Lynch JP, van Dusschoten D (2020c) Spatio-temporal variation in water uptake in seminal and nodal root systems of barley plants grown in soil. Front Plant Sci 11:1247
Schneider HM, Postma JA, Wojciechowski T, Kuppe C, Lynch JP (2017a) Root cortical senescence improves growth under suboptimal availability of N, P, and K. Plant Physiol 174:2333–2347. https://doi.org/10.1104/pp.17.00648
Schneider HM, Wojciechowski T, Postma JA, Brown KM, Lücke A, Zeisler V, Schreiber L, Lynch JP (2017b) Root cortical senescence decreases root respiration, nutrient content, and radial water and nutrient transport in barley. Plant, Cell Environ 40:1392–1408
Schneider, HM, Strock, CF, Hanlon, MT, Vanhees, DJ, Perkins, AC, Ajmera, IB, Sidhu, HS, Mooney, SJ, Brown, KM, Lynch, JP. (2021). Multiseriate cortical sclerenchyma enhance root penetration in compacted soils. Proceedings of the National Academy of Sciences, 118(6)
Schreiber L, Franke R, Hartmann K-DD, Ranathunge K, Steudle E (2005) The chemical composition of suberin in apoplastic barriers affects radial hydraulic conductivity differently in the roots of rice (Oryza sativa L. cv. IR64) and corn (Zea mays L. cv. Helix). J Exp Bot 56:1427–1436
Scippa GS, Trupiano D, Rocco M, Di Iorio A, Chiatante D (2008) Unravelling the response of poplar (Populus nigra) roots to mechanical stress imposed by bending. Plant Biosyst 142:401–413
Seago JL, Fernando DD (2013) Anatomical aspects of angiosperm root evolution. Ann Bot 112:223–238. https://doi.org/10.1093/aob/mcs266
Sharda JN, Koide RT (2010) Exploring the role of root anatomy in P-mediated control of colonization by arbuscular mycorrhizal fungi. Botany 88(2):165–173. https://doi.org/10.1139/B09-105
Smetana O, Makila R, Lyu M, Amiryousefi A, Rodriguez FS, Wu MF, Sole-Gil A, Gavarron ML, Siligato R, Miyashima S, Roszak P, Blomster T, Reed JW, Broholm S, Mahonen AP (2019) High levels of auxin signalling define the stem-cell organizer of the vascular cambium. Nature 565: 485-+. https://doi.org/10.1038/s41586-018-0837-0
Smiley R, Giblin D (1986) Root cortical death in relation to infection of Kentucky bluegrass by Phialophora graminicola. Phytopathology 76(9):917–922. https://doi.org/10.1094/Phyto-76-917
Smith FA, Smith SE (2011) What is the significance of the arbuscular mycorrhizal colonisation of many economically important crop plants? Plant Soil 348(1):63. https://doi.org/10.1007/s11104-011-0865-0
Smith FA (2007) Plant roots. Growth, Activity and Interaction with Soils 100(1):151–152. https://doi.org/10.1093/aob/mcm099
Smith SE, Read DJ (2008) Mycorrhizal symbiosis. Academic press, New York, NY
Somssich M, Khan GA, Staffan SP (2016) Cell wall heterogeneity in root development of arabidopsis. Front Plant Sci 7:1242
Sosa JM, Huber DE, Welk B, Fraser HL (2014) Development and application of MIPAR: a novel software package for two- and three-dimensional microstructural characterization. Integrating Materials 3:123–140
Spence MT, Johnson ID (2010) The molecular probes handbook: a guide to fluorescent probes and labeling technologies. Univerza v Ljubljani, Fakulteta za farmacijo
Sperry JS, Hacke UG, Pittermann J (2006) Size and function in conifer tracheids and angiosperm vessels. Am J Bot 93:1490–1500
Sperry JS, Saliendra NZ (1994) Intra-plant and inter-plant variation in xylem cavitation in Betula-occidentalis. Plant, Cell Environ 17:1233–1241. https://doi.org/10.1111/j.1365-3040.1994.tb02021.x
Spollen WG, Sharp R (1991) Spatial distribution of turgor and root growth at low water potentials 96(2), 438–443. Plant Physiology 96(2):438–443. https://doi.org/10.1093/annbot/58.4.577
St. Aubin G, Canny MJ, McCully ME (1986) Living vessel elements in the late metaxylem of sheathed maize roots. Ann Bot 58:577–588. https://doi.org/10.1093/annbot/58.4.577
St. Clair SB, Lynch JP (2010) The opening of Pandora’s box: climate change impacts on soil fertility and crop nutrition in developing countries. Plant Soil 335:101–115
Steudle E (2000) Water uptake by roots: effects of water deficit. J Exp Bot 51:1531–1542. https://doi.org/10.1093/jexbot/51.350.1531
Stirling G, Hayden H, Pattison T, Stirling M (2016) Soil health, soil biology, soilborne diseases and sustainable agriculture: A Guide: Csiro Publishing
Stirzaker RJ, Passioura JB, Wilms Y (1996) Soil structure and plant growth: Impact of bulk density and biopores. Plant Soil 185:151–162. https://doi.org/10.1007/BF02257571
Strock CF, Burridge J, Massas ASF, Beaver J, Beebe S, Camilo SA, Fourie D, Jochua C, Miguel M, Miklas PN, Mndolwa E, Nchimbi-Msolla S, Polania J, Porch TG, Rosas JC, Trapp JJ, Lynch JP (2019a) Seedling root architecture and its relationship with seed yield across diverse environments in Phaseolus vulgaris. Field Crop Res 237:53–64. https://doi.org/10.1016/j.fcr.2019.04.012
Strock CF, Burridge JD, Niemiec MD, Brown KM, Lynch JP (2021) Root metaxylem and root architecture phenotypes interact to regulate water use under drought stress. Plant Cell Environ 44:49–67. https://doi.org/10.1111/pce.13875
Strock CF, Lynch JP (2020) Root secondary growth: an unexplored component of soil resource acquisition. Ann Bot 126:205–218. https://doi.org/10.1093/aob/mcaa068
Strock CF, Morrow de la Riva L, Lynch JP (2018) Reduction in root secondary growth as a strategy for phosphorus acquisition. Plant Physiol 176(1):691–703. https://doi.org/10.1104/pp.17.01583
Strock CF, Schneider HM, Galindo-Castañeda T, Hall BT, Van Gansbeke B, Mather DE, Roth MG, Chilvers MI, Guo X, Brown K, Lynch JP (2019b) Laser ablation tomography for visualization of root colonization by edaphic organisms. J Exp Bot 70(19):5327–5342. https://doi.org/10.1093/jxb/erz271
Taylor P, Kasperbauer MJ (1999) Genotypic variation for root penetration of a soil pan. J Sustain Agric 13:87–94
Teramoto S, Takayasu S, Kitomi Y, Arai-Sanoh Y, Tanabata T, Uga Y (2020) High-throughput three-dimensional visualization of root system architecture of rice using X-ray computed tomography. Plant Methods 16:66. https://doi.org/10.1186/s13007-020-00612-6
Tomescu AMF, Groover AT (2019) Mosaic modularity: an updated perspective and research agenda for the evolution of vascular cambial growth. New Phytol 222:1719–1735. https://doi.org/10.1111/nph.15640
Tyree MT, Davis SD, Cochard H (1994) Biophysical Perspectives of Xylem Evolution: is there a Tradeoff of Hydraulic Efficiency for Vulnerability to Dysfunction? IAWA J 15:335–360
Vadez V (2014) Root hydraulics: The forgotten side of roots in drought adaptation. Field Crop Res 165:15–24. https://doi.org/10.1016/j.fcr.2014.03.017
Vadez V, Kholova J, Medina S, Kakkera A, Anderberg H (2014) Transpiration efficiency: new insights into an old story. J Exp Bot 65:6141–6153
Valenzuela-Estrada LR, Bryla DR, Hoashi-Erhardt WK, Moore PP, Forge TA (2011) Root traits associated with phytophthora root rot resistance in red raspberry. X International Rubus and Ribes Symposium 946: 283–287.https://doi.org/10.17660/ActaHortic.2012.946.46
Valenzuela-Estrada LR, Vera-Caraballo V, Ruth LE, Eissenstat DM (2008) Root anatomy, morphology, and longevity among root orders in Vaccinium corymbosum (Ericaceae). Am J Bot 95:1506–1514. https://doi.org/10.3732/ajb.0800092
van Dam NM (2009) Belowground herbivory and plant defenses. Annu Rev Ecol Evol Syst 40:373–391
van der Weele CM, Canny MJ, McCully ME (1996) Water in aerenchyma spaces in roots. A fast diffusion path for solutes. Plant Soil 184:131–141
Vanhees D, HM Schneider, KW Loades, AG Bengough MJ Bennett, KM Brown, SJ Mooney, JP Lynch (2021) Genotypic variation in soil penetration by maize roots is negatively related to ethylene-induced thickening. bioRxiv
Vanhees D, Loades K, Bengough G, Mooney S, Lynch J (2020) Root anatomical traits contribute to deeper rooting of maize (Zea mays L.) under compacted field conditions. J Exp Bot In Press
Vanhees DJ, Loades KW, Bengough AG, Mooney SJ, Lynch JP (2021) The ability of maize roots to grow through compacted soil is not dependent on the amount of roots formed. F Crop Res 264:108013
Vatter T, Neuhäuser B, Stetter M, Ludewig U (2015) Regulation of length and density of Arabidopsis root hairs by ammonium and nitrate. J Plant Res 128:839–848
Veen BW (1982) The influence of mechanical impedance on the growth of maize roots. Plant Soil 66:101–109
Vejchasarn P, Lynch JP, Brown KM (2016) Genetic variability in phosphorus responses of rice root phenotypes. Rice 9:29
Verhertbruggen Y, Walker JL, Guillon F, Scheller HV (2017) A comparative study of sample preparation for staining and immunodetection of plant cell walls by light microscopy. Front Plant Sci 8. https://doi.org/10.3389/fpls.2017.01505
Vermeer J, Mccully ME (1982) The rhizosphere in Zea: new insight into its structure and development. Planta 156(1):45–61
Vieira RF, Carneiro JES, Lynch JP (2008) Root traits of common bean genotypes used in breeding programs for disease resistance. Pesqui Agropecu Bras 43:707–712. https://doi.org/10.1590/S0100-204X2008000600006
Volder A, Smart DR, Bloom AJ, Eissenstat DM (2005) Rapid decline in nitrate uptake and respiration with age in fine lateral roots of grape: implications for root efficiency and competitive effectiveness. New Phytol 165:493–501. https://doi.org/10.1111/j.1469-8137.2004.01222.x
Vukicevich E, Lowery DT, Eissenstat D, Hart M (2019) Changes in arbuscular mycorrhizal fungi between young and old Vitis roots. Symbiosis 78:33–42. https://doi.org/10.1007/s13199-019-00598-3
Wahl S, Ryser P (2000) Root tissue structure is linked to ecological strategies of grasses. New Phytol 148:459–471
Walker TS, Bais HP, Grotewold E, Vivanco JM (2003) Root exudation and rhizosphere biology. Plant Physiol 132:44–51
Wan C, Xu W, Sosebee RE et al (2000) Hydraulic lift in drought-tolerant and -susceptible maize hybrids. Plant Soil 219:117–126. https://doi.org/10.1023/A:1004740511326
Wang C, Li X, Caragea D, Bheemanahalli R, Jagadish SV (2020) Root Anatomy based on Root Cross-Section Image Analysis with Deep Learning. Computers and Electronics in Agriculture. 175
Wang Z, Verboven P, Nicolai B (2017) Contrast-enhanced 3D micro-CT of plant tissues using different impregnation techniques. Plant Methods 13:105. https://doi.org/10.1186/s13007-017-0256-5
Wasson AP, Richards RA, Chatrath R, Misra SC, Prasad SS, Rebetzke GJ, Kirkegaard JA, Christopher J, Watt M (2012) Traits and selection strategies to improve root systems and water uptake in water-limited wheat crops. J Exp Bot 63:3485–3498
Watt M, McCully ME, Canny MJ (1994) Formation and stabilization of rhizosheaths of Zea mays L. Effect of soil water content. Plant Physiol 106:179–186. https://doi.org/10.1104/pp.106.1.179
Watt M, Mccully ME, Jeffree CE (1993) Plant and bacterial mucilages of the maize rhizosphere: Comparison of their soil binding properties and histochemistry in a model system
Wei Yang TJ, Perry PJ, Ciani S, Pandian S, Schmidt W (2008) Manganese deficiency alters the patterning and development of root hairs in Arabidopsis. J Exp Bot 59:3453–3464
Wen T-J, Schnable PS (1994) Analyses of mutants of three genes that influence root hair Ddvelopment in Zea mays (Gramineae) suggest that root hairs are dispensable. Am J Bot 81:833–842
Whalley WR, Leeds-Harrison PB, Clark LJ, Gowing DJG (2005) Use of effective stress to predict the penetrometer resistance of unsaturated agricultural soils. Soil Tillage Res 84:18–27
Wheeler JK, Sperry JS, Hacke UG, Hoang N (2005) Inter-vessel pitting and cavitation in woody Rosaceae and other vesselled plants: a basis for a safety versus efficiency trade-off in xylem transport. Plant Cell Environ 28:800–812
Whiteley GM, Hewitt JS, Dexter AR (1982) The buckling of plant roots. Physiol Plant 54:333–342
Williams JE, Davis SD, Portwood K (1997) Xylem Embolism in Seedlings and Resprouts of Adenstoma fasciculatum after Fire. Aust J Bot 45:291–300
Wullstein LH, Pratt SA (1981) Scanning electron microscopy of rhizosheaths of Oryzopsis hymenoides. Am J Bot 68:408–419. https://doi.org/10.1002/j.1537-2197.1981.tb06379.x
Yang JT, Schneider HM, Brown KM, Lynch JP (2019) Genotypic variation and nitrogen stress effects on root anatomy in maize are node specific. J Exp Bot 70(19):5311–5325
Yang, X, M Niemiec, JP Lynch (2020) Large root cortical cells and reduced cortical cell files improve growth under suboptimal nutrient regimes. BIORXIV/2020/189514MS)
York LM, Nord EA, Lynch JP (2013) Integration of root phenes for soil resource acquisition. Front Plant Sci 4:15. https://doi.org/10.3389/fpls.2013.00355
York LM, Silberbush M, Lynch JP (2016) Spatiotemporal variation of nitrate uptake kinetics within the maize (Zea mays L.) root system is associated with greater nitrate uptake and interactions with architectural phenes. J Exp Bot 67:3763–3775
Young IM (1995) Variation in moisture contents between bulk soil and the rhizosheath of wheat (Triticum aestivum L. cv. Wembley). New Phytol 130:135–139. https://doi.org/10.1111/j.1469-8137.1995.tb01823.x
Yu L-X, Ray JD, O’Toole JC, Nguyen HT (1995) Use of wax-petrolatum layers for screening rice root penetration. Crop Sci 35:684–687
Yue K, Peng C, Yang W, Peng Y, Zhang C, Huang C, Wu F (2016) Degradation of lignin and cellulose during foliar litter decomposition in an alpine forest river. Ecosphere 7https://doi.org/10.1002/ecs2.1523
Zadworny M, Eissenstat DM (2011) Contrasting the morphology, anatomy and fungal colonization of new pioneer and fibrous roots. New Phytol 190:213–221. https://doi.org/10.1111/j.1469-8137.2010.03598.x
Zaman-Allah M, Jenkinson DM, Vadez V (2011) A conservative pattern of water use, rather than deep or profuse rooting, is critical for the terminal drought tolerance of chickpea. J Exp Bot 62:4239–4252
Zhang CB, Chen LH, Jiang J (2014) Why fine tree roots are stronger than thicker roots: The role of cellulose and lignin in relation to slope stability. Geomorphology 206:196–202
Zhang Y, Du H, Gui Y, Xu F, Liu J, Zhang J, Xu W (2020) Moderate water stress in rice induces rhizosheath formation associated with abscisic acid and auxin responses. J Exp Bot 71:2740–2751. https://doi.org/10.1093/jxb/eraa021
Zhao C, Zhang Y, Du J, Guo X, Wen W, Gu S, Wang J, Fan J (2019) Crop Phenomics: Current Status and Perspectives. Front Plant Sci 10:714
Zhong R, Cui D, Ye Z (2019) Secondary cell wall biosynthesis. New Phytol 221:1703–1723. https://doi.org/10.1111/nph.15537
Zhu J, Brown KM, Lynch JP (2010a) Root cortical aerenchyma improves the drought tolerance of maize (Zea mays L.). Plant, Cell Environ 33:740–749. https://doi.org/10.1111/j.1365-3040.2009.02099.x
Zhu J, Kaeppler SM, Lynch JP (2005) Mapping of QTL controlling root hair length in maize (Zea mays L.) under phosphorus deficiency. Plant Soil 270:299–310
Zhu J, Zhang C, Lynch JP (2010b) The utility of phenotypic plasticity of root hair length for phosphorus acquisition. Funct Plant Biol 37:313–322
Zimmermann HM, Hartmann K, Schreiber L, Steudle E (2000) Chemical composition of apoplastic transport barriers in relation to radial hydraulic conductivity of corn roots (Zea mays L.). Planta 210:302–311
Zvereva EL, Kozlov MV (2012) Sources of variation in plant responses to belowground insect herbivory: a meta-analysis. Oecologia 169:441–452
Zwieniecki MA, Thompson MV, Holbrook NM (2002) Understanding the hydraulics of porous pipes: Tradeoffs between water uptake and root length utilization. J Plant Growth Regul 21:315–323. https://doi.org/10.1007/s00344-003-0008-9
Acknowledgements
We thank Dr. Kathleen M Brown for her insightful suggestions in preparing this article.
Funding
J.P.L., H.M.S., J.S.S., and M.T.H. acknowledge support from US Department of Energy ARPA-E Award DE-AR0000821. J.P.L. and I.B.A. and acknowledge support from a grant from the Foundation for Food and Agriculture Research/Crops in Silico. J.P.L. and C.F.S. acknowledge support from a grant from the Foundation for Food and Agriculture Research/Crops of the Future Collaborative. J.P.L and S.P.K. acknowledge support from the National Institute of Food and Agriculture, U.S. Department of Agriculture (award nos. 2014–67013–21572 and 2017–67013–26192). J.P.L. acknowledges support from the National Institute of Food and Agriculture, U.S. Department of Agriculture (award number 2021–67013-33723). and the National Institute of Food and Agriculture, U.S. Department of Agriculture, Hatch project PEN04732. J.P.L. and T.G.C. acknowledge support from U.S. Department of Agriculture NESARE, (GNE13-059), and T.G.C. acknowledges support from EU project contract No.839235—ROOTPHENOBIOME MSCA-IF2018 and Fulbright Becas-Caldas Colciencias and Fulbright Becas-Caldas Colciencias.
Author information
Authors and Affiliations
Contributions
All authors contributed to the conceptual development and writing of this article.
Corresponding author
Additional information
Responsible Editor: Ismail Cakmak.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
The original version of this article was revised due to a retrospective Open Access order.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Lynch, J.P., Strock, C.F., Schneider, H.M. et al. Root anatomy and soil resource capture. Plant Soil 466, 21–63 (2021). https://doi.org/10.1007/s11104-021-05010-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11104-021-05010-y