Introduction

Due to the scarcity of water in arid and semi-arid regions, future climatic changes will significantly affect water management and sustainable development. Consequently, the crucial factor in achieving optimal crop performance is the efficient use of water in agricultural production, utilizing it only when necessary and preventing unnecessary water waste (Kuśmierek-Tomaszewska et al. 2019). Especially in semi-arid zones, this scarcity is more pronounced, where there is a high evaporative demand and limited winter rainfall. Water-saving irrigation techniques must be encouraged to improve the long-term sustainability of irrigation water sources. Drip irrigation is considered one of the most advanced irrigation technologies, leading to significant water savings. This technology contributes to the horizontal expansion of cultivated areas and helps achieve the desired efficiency (Ahmed 2023). Most researchers focus on enhancing sugar beet adaptability to challenging environments, ensuring sustainable and high-yield production (Mishra et al. 2023). Deficit irrigation (DI) is considered one of the most important techniques for conserving irrigation water in arid and semi-arid regions, where water scarcity is a major concern. It also helps improve water productivity (WP) by allowing the root system to expand and access soil water more effectively. Efficiently utilizing irrigation water enhances water productivity without compromising crop yield (Geerts and Raes 2009; Chai et al. 2016; Trout and DeJonge 2018; Abu-Ellail et al. 2019; Nilahyane et al. 2020).

Sugar beet is an important crop for Egyptian farmers because it serves as a reliable source of income. Withholding irrigation significantly decreases sugar and root yields more than normal irrigation treatment (Abu-Ellail and El-Mansoub 2020). Drought stress has a direct effect on plant length and root characteristics, such as length and diameter, of sugar beet plants. The application of deficit irrigation with 75% of field capacity under a drip irrigation system in sandy soil was found to be the optimal soil water content for achieving maximum root yield and sucrose percentage (Abd El-All and Makhlouf 2017). Root yield and sugar yield were significantly affected by drought stress. There are varieties that can be introduced to farmers for cultivation in water-scarce conditions (Abbas et al. 2018; Abu-Ellail et al. 2021). Factor scores represent the values of the underlying constructs used to identify an individual's placement or ranking on the factors. Therefore, it is recommended to use this information to determine how factor scores differ between varieties (DiStefano et al. 2009; Yong and Pearce 2013). Rajabi et al. (2023) utilized factor analysis to identify and select factors with eigenvalues greater than 1, the variance of each factor was expressed as a percentage, indicating its significance in interpreting the overall variations in the sugar beets data. The current study addresses water management by providing information that can help farmers in sugar beet fields save water and increase root and sugar productivity in our country, which is important to avoid future negative consequences of the Ethiopian dam on the Nile River (Fig. 1). To achieve the goal of water security, the objective of this study was to assess the impact of various levels of deficit irrigation on sugar yield, as well as on certain morphological and quality characteristics of sugar beet. Additionally, the study aimed to rank ten different sugar beet varieties under full irrigation (100%) and different levels of deficit irrigation (75% and 50%), using factor analysis scores as selection criteria for the varieties.

Fig. 1
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Water management in sugar beet fields to achieve the best result of root and sugar yields under different levels of deficit irrigation (75%, and 50%) with statistical tools

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Materials and Methods

Study Location and Soil Analysis

The field experiment was implemented in a private farm at Wadi El-Natrun region located in the western desert (17.98 m above the sea, latitude 30° 23′ 19.89′′ N and longitude 30° 21′ 41.06′′ E), El-Beheira Governorate, Egypt. The study was performed during two winter growing seasons 2021/2022 and 2022/2023 to estimate the response of ten imported monogerm sugar beet varieties (Table 1) to deficit irrigation under the drip system. The experimental soil was prepared by chisel plow (two passes) and furrowed at 80 cm. Sugar beet seeds were sown manually in hills at a distance of 20 cm on the 1st and 10th of October for two seasons, respectively. Harvesting was carried out manually 210 days after sowing for both seasons. All agricultural practices for all treatments were accomplished in accordance with scientific recommendations. The experimental site was characterized as sandy soil; some characteristics of the soil and irrigation water are shown in Table 2 and 3.

Table 1 Origin of ten imported monogerm sugar beet varieties used in this study.
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Table 2 Mechanical analyses, bulk density, field capacity, wilting point, and available water also the chemical properties of experimental soil
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Table 3 Chemical analysis of irrigation water at the experimental site during a combined two growing seasons (2021/2022 and 2022/2023)
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Irrigation System Components

The irrigation system consisted of a submersible pump with a discharge of 60 m3/h, driven by an electric engine. This pump extracts groundwater and sends it to the mainline cross-control unit. The control unit includes a backflow prevention device, pressure gauges, a steel disk filter, and a control valve. Mainline with a 110-mm-diameter made from polyvinyl chloride (PVC) was used to carry water from the pump to other components of the irrigation network. Sub-mainlines with a diameter of 75 mm are made from high-density polyethylene (HDPE) and connected to the mainline using a 3′′ ball valve. Manifold lines with a diameter of 63 mm, made of HDPE, were connected to the sub-mainline using a 2′′ ball valve and pressure gauge. Inline emitter laterals (GR) with a 16-mm inner diameter and a length of 25 m made of low-density polyethylene (LDPE) were used. The laterals are connected to the manifold by a clamp saddle measuring 63 mm × 1/2′′. The emitters are classified as long-path emitters with a flow cross-section diameter of 0.7 mm. They have a discharge rate of 4.0 L/h at an operating pressure of 100 Kilopascal (kPa) and a distance of 20 cm between emitters. The coefficient of variation for the emitter manufacturer was less than 0.05, and the Christiansen uniformity coefficient (CU) for the lateral lines was classified as excellent (CU = 90%) according to Rowan et al. (2013). Irrigation system components and treatment distribution are shown in Fig. 2.

Fig. 2
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Experimental layout and treatments distribution

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Crop Evapotranspiration

Crop evapotranspiration for sugar beet plants in the Wadi El-Natrun region were calculated by the software program CROPWAT version 8.0 based on the agro-climatological data for the experimental site which was collected by the Agricultural Climate Station at Wadi El-Natrun as shown in Table 4 attributions to the Penman–Monteith formula, explained by (Allen et al. 1998) as follow:

$${\text{ET}}_{{\text{c}}} = {\text{ ET}}_{{\text{o}}} * \, K_{{\text{c}}}$$
Table 4 Agro-climatologically data for the experimental site at Wadi El-Natrun station
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In which: ETc is crop evapotranspiration (mm/day), ETo is reference evapotranspiration (mm/day), and Kc is crop coefficient values for sugar beet crop. The growing season was divided into four stages initial (I), development (D), mid-season (M), and late-season (L). The duration (days) and crop coefficient for every stage are shown in Fig. 3.

Fig. 3
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Growing stages and crop coefficient for sugar beet crop

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Seasonal Applied Water

The applied water was calculated according to Vermeiren and Jopling (1984) as follows:

$$A= \frac{{{\text{ET}}}_{{\text{c}}}* {K}_{{\text{r}}}*T}{{E}_{a} (1-{\text{LR}})}$$

In which: Kr is reduction coefficient, which depends on a ground cover. As the spacing between drip lines is less than 1.8 m. A value of 1.0 was applied, T is irrigation period (day), Ea is drip irrigation efficiency (a value of 0.85 was applied), and LR is leaching requirement (a value of 10% was applied). The values of Kr and LR were mentioned by Abd El-All and Makhlouf (2017)

At harvest, ten plants were randomly selected from each plot cleaned and topped to determine the following characteristics in both seasons:

Growth traits (1) Root diameter (cm). (2) Top fresh weight/plant (g). (3) Root fresh weight/plant (g).

Yield quality traits At harvesting, a sample of ten roots was taken at random from each plot and cleaned to determine the following traits in both seasons.

  1. (1)

    Sucrose percentage was determined by using sacharometer lead acetate extract of fresh macerated roots according to Carruthers and Oldfield (1961).

  2. (2)

    Impurities of juice (K and Na) and Alpha-amino-N concentrations were estimated according to Browen and Lilliand (1964).

  3. (3)

    Sucrose loss to molasses (SLM %) was determined according to Devillers (1988).

  4. (4)

    Extractable Sugar % = Sucrose % − SLM% − 0.6 (Dexter et al. 1967).

Yield At harvesting, the guarded ridges of sugar beet in each plot were up-rooted, topped, cleaned, and weighed to determine.

  1. (1)

    Root yield (ton/fed): Calculated from root weight of experimental unit, then converted to ton/fed.

  2. (2)

    Sugar yield (ton/fed) = Root yield (ton/fed) × Extractable sugar %/100.

Proline content (µ moles/g leaf fresh weight) Proline was extracted from the leaves of plants after 30 days after planting and estimated using the ninhydrin method according to Bates et al. (1973).

Estimation of Seasonal Applied Water

The total applied water for three water regimes for two growing seasons based on the irrigation program was estimated. Water regime was applied as a percentage of Crop evapotranspiration (ETc) as follows: full irrigation 100% ETc and two deficit irrigation (DI) 75% and 55% ETc. Full irrigation was applied for all treatments during the initial stage to obtain the highest possible germination rate.

Water Productivity

Water productivity (WP) expresses the ratio of a certain yield to the seasonal applied water in kg m−3. Water productivity for root and sugar yields was estimated based on (Michael 1997):

$${\text{WP}}_{{\text{root or sugar yield}}} = \frac{{{\text{Root or sugar yield }}({\text{kg}}/{\text{fed}}.)}}{{{\text{Total applied water }}\left( {{\text{m}}^{3} /{\text{fed}}.} \right)}}$$

Statistical Analysis

The experimental design was a randomized complete block design (RCBD) with three replications. Overall irrigation and seasons (six experiments) data for each observed trait were subjected to combined analysis of variance (ANOVA) in RCBD. At first, the data were tested for normal distribution and variance homogeneity, so the Kolmogorov–Simirnov normality test was applied for all the variables prior to the combined analysis to test the homogeneity of individual error terms (Levene 1960; Kozak and Piepho 2018). Which, the data skipped the tests; subsequently, the analysis of variance (ANOVA) procedure was carried out. Crossbar plots were depicted to easily visualize the summary of interaction between ten varieties of sugar beet and three irrigation treatments across two seasons with the help of the R-statistical software using “ggplot” package.

The second step was to compute an exploratory factor analysis (EFA) to estimate the factor coefficients which were used to obtain factor scores for each genotype (Sharma 1996; Grice 2001), since the aim of the research is to discover the behavior of the ten varieties of sugar beet under different levels of drought stress, to classify these varieties for stress tolerance under Egyptian environmental conditions.

Results and Discussion

Selection of appropriate varieties and effective irrigation water management are two crucial factors for ensuring the sustainable use of water resources in Egypt, especially in light of the current challenges posed by water scarcity and climate change. Under field conditions, the categorization of sugar beet varieties' response to drought stress in Egypt has only been investigated in a few studies.

Growing Conditions

The field was irrigated before sowing with 336 m3 of water per fed−1 in order to prepare the soil and ensure proper germination. After sowing, irrigation was scheduled for three events per week. Full irrigation (100% ETc.) was applied during the initial stage for 30 days, followed by deficit irrigation. Irrigation was stopped seven days before harvesting. Seasonal applied water for three different water regimes was calculated and listed in Table 5, considering a long growing season. Seasonal applied water for three water regimes, 100% ETc., 75% ETc., and 55% ETc., were 2226.6, 1799.0, and 1456.9 m3 fed−1, respectively, for the first season. For the second season, the values were 2293.7, 1842.9, and 1482.3 m3 fed−1, respectively.

Table 5 Seasonal applied water under different water regimes for sugar beet crop, (m3/fed)
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The highest monthly water application occurred in March for the first season and in April for the second season. Deficit treatments (75% and 55%, ETc.) saved irrigation water compared to the full irrigation treatment (100%, ETc.) by 19.2% and 34.6%, respectively, in the first season, and by 19.7% and 35.4%, respectively, in the second season. The results are in line with those obtained by (EL-Darder et al. 2017), who revealed that the drip irrigation systems with 80% irrigation water requirement had a highly significant effect on all morphological and quality traits for both seasons of the sugar beet crop.

Mean Performance

In the current study, the most interesting objective was to examine the interaction effect between ten varieties of sugar beet and three irrigation treatments, full irrigation (100%) and two levels of deficit irrigation (75% and 50%), across two seasons. Therefore, it would be graphically displayed and discussed, regardless of the main effects. All studied factors (genotypes and irrigation) were fixed, except for seasons, which were considered random factors. The results of the combined analysis of variance showed that the studied varieties differed significantly for all the traits examined, including growth traits, juice quality, yields, and water productivity. These differences were observed when the varieties were tested under three different conditions: control 100% (full irrigation), moderate stress 75%, and severe stress 55%. Results were depicted by crossbar plots (Figs. 4, 5a, b, and 6) to easily visualize the effect of the interaction between varieties and irrigation on the previously mentioned traits. These results are in line with those obtained by Abu-Ellail et al. (2021) and Hoffman et al. (2011), who evaluated various sugar beet varieties under different water stress treatments.

Fig. 4
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Interaction between ten sugar beet varieties (1–10) and drought stress (full irrigation (Ctrl), 75% and 55%) for growth traits, where dark and thick circles express the mean variety around the grand mean (thick line)

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Fig. 5
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a Interaction between ten sugar beet varieties (1–10) and drought stress (full irrigation (Ctrl), 75% and 55%) on juice quality traits and proline concentration, where dark and thick circles display the mean variety around the grand mean (thick line). b Interaction between ten sugar beet varieties (1–10) and drought stress (full irrigation (Ctrl), 75% and 55%) on juice quality traits (impurities), where dark and thick circles display the mean variety around the grand mean (thick line)

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Fig. 6
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Interaction between ten sugar beet varieties (1–10) and drought stress (full irrigation (Ctrl), 75% and 55%) on yields and water productivity, where dark and thick circles display the mean variety around the grand mean (thick line)

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Response of Plant Growth Traits to Drought Stress

Results showed that the root diameter (cm), root weight (g/fed), and top weight (g/fed) varied and reduced in most of the varieties under drought conditions (75% and 55%) compared to the control condition (Fig. 4). Higher root diameter values were recorded by Farida-KWS (V1), followed by Stikhiyn (V6) and Smart Seza-KWS (V2). The remaining varieties had lower values than the general average under control conditions (Fig. 4). However, at 75% drought conditions, Stikhiyn (V6) had the largest root diameter, followed by Symbool (V5) and Volua (V9). The remaining varieties had mean values of root diameter lower than the overall average. The results obtained under controlled conditions (55%) indicated that varieties Klara (V10) and Volua (V9) had the highest root diameter. The remaining varieties, including BTS 3880 (V7), Perfekta (V4), BTS 3740 (V8), and Stikhiyn (V6) also scored values above the grand average means. On the other hand, varieties Farida-KWS (V1), Smart Seza-KWS (V2), Smart Meyra KWS (V3), and Symbool (V5) recorded root diameters lower than the grand means (Fig. 4).

Water stress affects the formation of sugar beet yield, with the root system being the primary organ responsible for plant water uptake. Khozaei et al. (2020) and Ober and Sharp (2007) found that the variation in root size was primarily due to differences in irrigation schedules, climate conditions, sugar beet varieties, and measurement techniques. Sugar beet growth can be described by the root diameter, as this parameter is closely related to the root weight (Hoffmann 2017). The recorded differences among the studied varieties showed that some were sensitive to water stress, while others were moderately tolerant and resistant to water stress (Fig. 4).

In other words, the moderate stress of 75% and severe stress of 55% in the drought class have caused a change in the ranking of the varieties in terms of root yield as the stress level increases. However, Fig. 4 shows that the control environment presented a high mean for root weight recorded by varieties, namely Farida-KWS (V1), Klara (V10), and Volua (V9). On the other hand, the remaining varieties showed low means of root weight. Varieties 5, 6, 2, 9, 4, and 10 (Symbool, Stikhiyn, Smart Seza-KWS, Klara, Perfekta, and Volua, respectively) scored the highest root weight under water stress conditions (75%). However, under stress conditions of 55%, varieties 10, 9, and 7 (Klara, Volua, and BTS-3880, respectively) achieved the highest mean point for root weight (Fig. 4).

With regard to the top weight trait, varieties number 2, 4, 3, and 1 (Smart Seza-KWS, Perfekta, Smart Meyra-KWS, and Farida-KWS, respectively) recorded the highest mean values in the controlled environment. At 75% conditions, varieties 2, 1, and 4 (Smart Seza -KWS, Farida-KWS, and Perfekta, respectively) recorded the highest top weight, while varieties 5 and 6 recorded the lowest top weight. However, variety 7 (BTS 3880) exhibited the highest yield under stress conditions, with a top weight of 55%. On the other hand, varieties Volua (V9) and Klara (V10) had the lowest top weight. A lower root weight at the end can likely be attributed to a larger increase in aboveground growth during later stages, which cannot be determined solely by an increase in root diameter (Abu-Ellail et al. 2021; Hoffmann et al. 2021). Therefore, it can be concluded that water stress has a strong impact on root yield. This result confirms previous observations obtained by Ebmeyer et al. (2021) and Ebmeyer and Hoffmann (2022). They mentioned that a high correlation has been observed between increasing root diameter and increasing root weight. Islam et al. (2020) reported that drought stress had a negative impact on sugar beet growth and dry matter accumulation. This could be attributed to the reduced production of plant biomass. Our current study also revealed a detrimental effect of water stress on the growth and dry matter accumulation of sugar beet, particularly in the following varieties: Farida-KWS, Smart Meyra-KWS, Smart Seza-KWS, Perfekta, and BTS-3880, respectively. This negative impact could be attributed to the reduced production of plant biomass under water deficits of 75% and 55%.

Influence of Drought Stress on Juice Quality Traits and Proline Concentration

Sucrose % (SC) reduced under drought conditions of 75% and 55%, compared to the control condition of 100% for most of the tested varieties (Fig. 5a). The varieties 9, 10, 6, 5, and 4 exhibited the highest sucrose percentage concentration, with means greater than the mean of the control condition (Fig. 5a). On the other hand, the remaining varieties had sucrose percentage concentration means lower than that of the control treatment (100%). At deficit conditions (75%), varieties 5, 6, 9, and 10 (Symbool, Stikhiyn, Volua, and Klara, respectively) achieved the highest concentration of sucrose, while the two varieties 10 and 9 (Klara and Volua) were recorded as highest sucrose concentration at deficit conditions of 55%. The studied varieties exhibited the same behavior in terms of extractable sugar percentage, similar to sucrose (Fig. 5a). Results reported that varieties 5, 6, 4, and 3 recorded a high concentration of proline at (75%) stress conditions, while varieties 10 and 9 (Klara and Volua) only exhibited a high concentration at (55%) stress conditions. Thus, proline is considered the most important organic solute and can play a key role in regulating enzyme activities. It can also be an important component of cell wall proteins, which is why varieties with higher proline content are considered more resistant to water stress.

On the contrary, variety number 1 (Farida-KWS) showed the lowest concentration value of proline, indicating that this variety is sensitive to water deficits of 75% and 55%. Ghaffari et al. (2019) stated that the foliar application of proline was effective in improving water stress tolerance, particularly in sugar beet. Proline application plays a beneficial role in mitigating the detrimental effects of water stress. Proline accumulation is a crucial metabolite that increases in sugar beets when they are exposed to water stress. It is a reliable indicator of the current stress levels in plants, as the proline level decreases after the stress is relieved and the plant recovers (Ghaffari et al. 2021). Additionally, Islam et al. (2020) found that the accumulation of proline provides valuable evidence of stress in sugar beet. Proline can also function as a signaling molecule, influencing mitochondrial functions, cell proliferation, and the expression of stress-tolerant genes. On the basis of the results in Fig. 5b, varieties 5, 6, 9, and 10 exhibited similar behavior, which was lower than the grand mean values in terms of impurities such as sucrose loss to molasses % (SLM), potassium (K), sodium chloride (Na), and alpha-amino-N (N) under control, semi-controlled (75%), and deficit (55%) environments, while the rest of the varieties showed results opposite to the previous results. Campbell (2002) stated that the quality of sugar beet depends not only on the sucrose concentration of harvested roots but also on the concentration of naturally occurring soluble constituents of the root, known as impurities, which hinder the extraction of sucrose during regular factory operations. The increase in sucrose concentration was mainly attributed to a rise in root yield, coupled with a decrease in impurities (Hoffman et al. 2011). Low impurity concentrations and/or high sucrose concentrations were important factors in selecting varieties under drought conditions (75% and 55%). The production and accumulation of sucrose in plants can help mitigate the adverse effects of water stress (Khoyerdi et al. 2016).

Drought Stress and the Response of Yield, Water-Productivity Trait

Data in Fig. 6 summarize the mean and variability in yields and water productivity, including traits, root yield (ton/fed) (RY), sugar yield (ton/fed) (SY), water productivity of root yield (WP root yield), and water productivity of sugar yield (WP sugar yield). These traits differed significantly between the irrigated and non-irrigated treatments. Increasing sugar ratios were reported with decreasing irrigation water quantities in arid climatic conditions (Li et al. 2019). It was determined that there is a linear relationship between crop water consumption and sugar beet root yield under semi-arid and arid climatic conditions. Based on the results of Fig. 6, varieties 5, 6, 9, and 10 (Symbool, Stikhiyn, Klara, and Volua, respectively) exhibited the highest root yield and water productivity of root yield under favorable conditions. Varieties 6, 5, and 1 (Stikhiyn, Symbool, and Farida-KWS, respectively) recorded the highest root yield and water productivity of root yield under unfavorable conditions (75%). However, under unfavorable conditions (55% humidity), only varieties 10 and 9 (Klara and Volua) exhibit high water consumption in order to achieve a high root yield, surpassing the grand mean (Fig. 6). Varieties 6 and 5 followed closely, even under unfavorable conditions (75%). Varieties 9, 10, 6, and 5 recorded higher water productivity for sugar yield under unfavorable conditions (55%) compared to the overall average, resulting in higher sugar yield. Topak et al. (2016) reported significant effects of different irrigation treatments on water productivity (WP) values of sugar beet and indicated the highest WP value for a 50% water deficit. Decreasing root yields were observed with increasing water deficits (Fig. 6). Yetik and Candogan (2022) found that cultivating sugar beets using the full drip irrigation method in sub-humid climate conditions is recommended for achieving the highest yields of roots and sugar. In situations where water resources are limited, it may be advisable to implement an irrigation strategy that includes a 33% reduction in water usage. This approach, combined with the use of high water productivity values, can help maximize the efficiency of irrigation water application. Thus, the varieties with higher water productivity of root yield and water productivity of sugar yield under drought conditions may be considered moderately tolerant plants, as their means were close to the grand mean, such as Symbool and Stikhiyn at 75% water deficit. Klara, Volua, and BTS-3740 may be considered drought-tolerant plants at a 55% water deficit.

Examination of the relationship between these attributes and the subsequent identification of attributes that are highly correlated with high yield at low cost can help in selecting superior species for cultivation in water-stressed conditions. For this purpose, the aforementioned attributes were identified as effective in terms of selecting for high sugar yield and root yield under water stress conditions. Water productivity of sugar yield, water productivity of root yield, and proline activity play a vital role in plant defense mechanisms by maintaining balance within the plant. It is important to mention that water productivity of sugar yield, root yield, and proline is reliable physiological indices that can be used to evaluate the drought tolerance of specific varieties (Ebmeyer et al. 2021). Recent studies have indicated that water consumption is closely linked to the growth rate and decreases during later growth phases, even when water is readily available (Ebmeyer et al. 2021). Ebmeyer and Hoffmann (2022) emphasize that the growth rate of sugar beet determines its water demand.

Factor Analysis Score (FAS)

Factor analysis (FA) was chosen from the wide range of statistical methods to analyze data due to its multivariate statistical approach (Field 2009). Results were found to be significant for all datasets. It is understood that there is a strong correlation between characteristics, making them suitable for factor analysis (Yong and Pearce 2013). In our investigation, factor analysis (FA) was applied to explore and characterize the relationship between ten varieties of sugar beet and three water stress treatments (full irrigation 100%, 75%, and 50%). The score for a given factor is calculated by taking a linear combination of all the measures, with each measure weighted by its corresponding factor loading. Factor scores can be used to rank varieties by assigning a value of 1 to strongly positive loadings and a value of − 1 to strongly negative loadings. However, it is important to note that these factor scores will be highly collinear with the measures or attributes used to generate their rank (DeCoster 1998).

Results in Table 6, revealed that the factor scores (FS) varied among the sugar beet varieties. The varieties were ranked based on their behaviors, which differed during the three study conditions (control, 75% and 55%). To visualize these behaviors, the factor scores were plotted as a bivariate graph (Fig. 7). Thus, the varieties with higher scores under water stress conditions may be considered as tolerant plants. The highest FS was recorded from Farida-KWS variety, followed by Smart Seza-KWS and Volua, under full irrigation condition (Table 6 and Fig. 7).

Table 6 Factor score for ten varieties of sugar beet at control (100%) and stress (75% and 55%)
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Fig. 7
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Superior varieties with higher factor score at control (100%) and its behavior at drought stress (75 and 55%, respectively)

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The results indicated that the variety Stikhiyn recorded the highest factor score, followed by Symbool and Klara, under 75% water stress. At 55% water stress, the variety Klara recorded a higher factor score, followed by Volua, BTS 3740, and Symbool. The results confirmed that under severe water stress, the varieties Symbool, Stikhiyn, Volua, and Klara were distinguished as moderately tolerant and recommended for use in water stress conditions due to their better performance and higher scores. In this study, Farida-KWS, Smart Meyra KWS, Perfekta, and BTS 3880 were observed to have worse performance and the lowest scores, indicating their sensitivity to drought stress conditions. Hoffman et al. (2011) and Abu-Ellail and El-Mansoub (2020) obtained similar results using multivariate analysis to assess water stress tolerance in sugar beet. Also, these results were consistent with the findings of Rajabi et al. (2023), who utilized factor scores to evaluate yield and other agronomic traits in a group of sugar beet genotypes.

Conclusion

The results concluded that drought deficit (75% and 55%) reduced root diameter (cm), root weight (g/fed), and top weight (g/fed), also most of the juice quality traits were decreased under drought stress, while proline content was increased. Root yield (tons per fed), sugar yield (tons per fed), water productivity of root yield, and sugar yield were affected by increasing water stress. Varieties with higher water productivity can produce higher yields with the available water. Meanwhile, this study suggests that increasing the aforementioned traits and proline would be the most effective way to increase sugar yield and root yield under severe drought conditions of 55%. Finally, the moderate stress of 75% and severe stress of 55% in the drought class have caused a change in the ranking of the varieties in terms of root yield as the stress levels vary. Exploratory factor analysis was applied to investigate and describe the relationship between ten different varieties of sugar beet and three levels of water stress treatments (100%, 75%, and 50%). Generally, there was a statistically significant interaction effect on the traits of ten different varieties of sugar beet, indicating different performance under drought stress conditions (75% and 55%) compared to the full irrigation (100%) condition. Varieties Symbool, Stikhiyn, Volua, and Klara were stable, high-yielding, and recommended for use in drought stress conditions due to their moderate tolerance and relatively better performance, as well as having the highest factor scores. Hence, sugar beet breeders and agronomists should pay close attention to these parameters to enhance sugar beet productivity and quality. This can be achieved through extensive research on these traits under water stress conditions of 75% and 55%.