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Precision nitrogen management of wheat. A review

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Abstract

Conventional farming has led to extensive use of chemicals and, in turn, to negative environmental impacts such as soil erosion, groundwater pollution and atmosphere contamination. Farming systems should be more sustainable to reach economical and social profitability as well as environmental preservation. A possible solution is to adopt precision agriculture, a win–win option for sustaining food production without degrading the environment. Precision technologies are used for gathering information about spatial and temporal differences within the field in order to match inputs to site-specific field conditions. Here we review reports on the precision N management of wheat crop. The aims are to perform an investigation both on approaches and results of site-specific N management of wheat and to analyse performance and sustainability of this agricultural practice. In this context, we analysed literature of the last 10–15 years. The major conclusions are: (a) before making N management decisions, both the measurement and understanding of soil spatial variability and the wheat N status are needed. Complementary use of different sensors has improved soil properties assessment at relatively low cost; (b) results show the usefulness of airborne images, remote and proximal sensing for predicting crop N status by responsive in-season management approaches; (c) red edge and near-infrared bands can penetrate into higher vegetation fraction of the canopy. These narrowbands better estimated grain yield, crop N and water status, with R 2 higher than 0.70. In addition, different hyperspectral vegetation indices accounted for a high variability of 40–75 % of wheat N status; (d) various diagnostic tools and procedures have been developed in order to help wheat farmers for planning variable N rates. In-season adjustments in N fertilizer management can account for the specific climatic conditions and yield potential since less than 30 % of spatial variance could show temporal stability; (e) field studies in which sensor-based N management systems were compared with common farmer practices showed high increases in the N use efficiency of up to 368 %. These systems saved N fertilizers, from 10 % to about 80 % less N, and reduced residual N in the soil by 30–50 %, without either reducing yields or influencing grain quality; (f) precision N management based on real-time sensing and fertilization had the highest profitability of about $5–60 ha−1 compared to undifferentiated applications.

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References

  • Abbott LK, Murphy DV (2007) What is soil biological fertility? In: Abbott LK, Murphy DV (eds) Soil biological fertility—a key to sustainable land use in agriculture. Springer, pp 1–15. ISBN:978-1-4020-6619-1

  • Adamchuk V (2011) On-the-go soil sensors—are we there yet? In: Proceeding of the second global workshop on proximal soil sensing—Montreal, pp 160–163

  • Adamchuk VI, Hummel JW, Morgan MT, Upadhyaya SK (2004) On-the-go soil sensors for precision agriculture. Comput Electron Agric 44:71–91. doi:10.1016/j.compag.2004.03.002

    Article  Google Scholar 

  • Adamchuk VI, Viscarra Rossel RA, Sudduth KA, Lammers PS (2011) Sensor fusion for precision agriculture. In: Thomas C (ed) Sensor fusion—foundation and applications. InTech. ISBN:978-953-307-446-7

  • Ammann K (2009) Why farming with high tech methods should integrate elements of organic agriculture. New Biotechnol 25:378–388. doi:10.1016/j.nbt.2009.06.933

    Article  CAS  Google Scholar 

  • Aparicio N, Villegas D, Casadesus J, Araus JL, Royo C (2000) Spectral vegetation indices as nondestructive tools for determining durum wheat yield. Agron J 92:83–91

    Article  Google Scholar 

  • Arnall DB, Tubaña BS, Holtz SL, Girma K, Raun WR (2009) Relationship between nitrogen use efficiency and response index in winter wheat. J Plant Nutr 32:502–515. doi:10.1080/01904160802679974

    Article  CAS  Google Scholar 

  • Arslan S, Colvin TS (2002) Grain yield mapping: yield sensing, yield reconstruction, and errors. Precis Agric 3:135–154

    Article  Google Scholar 

  • Babar MA, Reynolds MP, van Ginkel M, Klatt AR, Raun WR, Stone ML (2006) Spectral reflectance indices as a potential indirect selection criteria for wheat yield under irrigation. Crop Sci 46:578–588. doi:10.2135/cropsci2005.0059

    Article  Google Scholar 

  • Bannayan M, Crout NMJ, Hoogenboom G (2003) Application of the CERES-Wheat model for within-season prediction of winter wheat yield in the United Kingdom. Agron J 95:114–125

    Article  Google Scholar 

  • Barnes EM, Clarke TR, Richards SE (2000) Coincident detection of crop water stress, nitrogen status and canopy density using ground based multispectral data. In: Robert PC, Rust RH, Larson WE (eds) Proceedings of the 5th international conference on precision agriculture. American Society of Agronomy, Madison, Unpaginated CD

    Google Scholar 

  • Basso B, Cammarano D, Grace PR, Cafiero G, Sartori L, Pisante M, Landi G, De Franchi S, Basso F (2009) Criteria for selecting optimal nitrogen fertilizer rates for precision agriculture. Ital J Agron 4:147–158. doi:10.4081/ija.2009.4.147

    Google Scholar 

  • Basso B, Cammarano D, Troccoli A, Chen D, Ritchie JT (2010) Long-term wheat response to nitrogen in a rainfed Mediterranean environment: field data and simulation analysis. Eur J Agron 33:132–138. doi:10.1016/j.eja.2010.04.004

    Article  Google Scholar 

  • Basso B, Ritchie JT, Cammarano D, Sartori L (2011) A strategic and tactical management approach to select optimal N fertilizer rates for wheat in a spatially variable field. Eur J Agron 35:215–222. doi:10.1016/j.eja.2011.06.004

    Article  Google Scholar 

  • Batchelor WD, Basso B, Paz JO (2002) Examples of strategies to analyze spatial and temporal yield variability using crop models. Eur J Agron 18:141–158

    Article  Google Scholar 

  • Biermacher JT, Epplin FM, Wade Brorsen B, Solie JB, Raun WR (2006) Maximum benefit of a precise nitrogen application system for wheat. Precis Agric 7:193–204. doi:10.1007/s11119-006-9017-6

    Article  Google Scholar 

  • Biermacher JT, Brorsen BW, Epplin FM, Solie JB, Raun WR (2009) The economic potential of precision nitrogen application with wheat based on plant sensing. Agric Econ 40:397–407. doi:10.1111/j.1574-0862.2009.00387.x

    Article  Google Scholar 

  • Blondlot A, Gate P, Poilvé H (2005) Providing operational nitrogen recommendations to farmers using satellite imagery. In: Stafford JV (ed) Precision agriculture 2005. Uppsala, Sweden, pp 345–352

    Google Scholar 

  • Bocchi S, Castrignanó A (2007) Identification of different potential production areas for corn in Italy through multitemporal yield map analysis. Field Crop Res 102:185–197. doi:10.1016/j.fcr.2007.03.012

    Article  Google Scholar 

  • Bongiovanni R, Lowenberg-Deboer J (2004) Precision agriculture and sustainability. Precis Agric 5:359–387

    Article  Google Scholar 

  • Booltink HWG, van Alphen BJ, Batchelor WD, Paz JO, Stoorvogel JJ, Vargas R (2001) Tools for optimizing management of spatially variable fields. Agric Syst 70:445–476

    Article  Google Scholar 

  • Boyer CN, Brorsen BW, Solie JB, Raun WR (2011) Profitability of variable rate nitrogen application in wheat production. Precis Agric 12:473–487. doi:10.1007/s11119-010-9190-5

    Article  Google Scholar 

  • Broge NH, Mortensen JV (2002) Deriving green crop area index and canopy chlorophyll density of winter wheat from spectral reflectance data. Remote Sens Environ 81:45–57

    Article  Google Scholar 

  • Bundy LG, Andraski TW (2004) Diagnostic tests for site-specific nitrogen recommendations for winter wheat. Agron J 96:608–614

    Article  Google Scholar 

  • Carr PM, Carlson GR, Jacobsen JS, Nielson GA, Skogley EO (1991) Farming soils, not fields: a strategy for increasing fertiliser profitability. J Prod Agric 4:57–61

    Google Scholar 

  • Cartelat A, Cerovic ZG, Goulas Y, Meyer S, Lelarge C, Prioul JL, Barbottin A, Jeuffroy MH, Gate P, Agati G, Moya I (2005) Optically assessed contents of leaf polyphenolics and chlorophyll as indicators of nitrogen deficiency in wheat (Triticum aestivum L.). Field Crop Res 91:35–49. doi:10.1016/j.fcr.2004.05.002

    Article  Google Scholar 

  • Cassman KG (1999) Ecological intensification of cereal production systems: yield potential, soil quality, and precision agriculture. In: Proc. Natl. Acad. Sci. USA 96, Colloquium Paper, pp 5952–5959

  • Castrignanò A, Buttafuoco G, Pisante M, Lopez N (2006) Estimating within-field variation using a nonparametric density algorithm. Environmetrics 17:465–481

    Article  CAS  Google Scholar 

  • Castrignanò A, Buttafuoco G, Troccoli A, Colecchia SA, Di Bitetto V, Pisante M, Basso F, Cafiero G, Cammarano D, Basso B (2008) Multivariate geostatistical analysis for delineation of management zones using crop index. In: Proceedings of the Int. Conf. on Agricultural Engineering, Hersonissos. Crete Isle, Greece. Unpaginated CD ROM

  • Castrignanò A, Wong MTF, Stelluti M, De Benedetto D, Sollitto D (2012) Use of EMI, gamma-ray emission and GPS height as multi-sensor data for soil characterization. Geoderma 175–176:78–89. doi:10.1016/j.geoderma.2012.01.013

    Article  CAS  Google Scholar 

  • Christensen LK, Rodriquez D, Belford R, Sadras V, Rampant P, Fisher P (2005) Temporal prediction of nitrogen status in winter wheat under the influence of water deficiency using spectral and thermal information. Crop variability and resulting management effects. In: Stafford JV (ed) Precision agriculture. Wageningen Academic Publisher, 209–216

  • Dang YP, Pringle MJ, Schmidt M, Dalal RC, Apan A (2011) Identifying the spatial variability of soil constraints using multi-year remote sensing. Field Crop Res 123:248–258. doi:10.1016/j.fcr.2011.05.021

    Article  Google Scholar 

  • De Benedetto D, Castrignanò A, Sollitto D, Modugno F, Buttafuoco G, lo Papa G (2012) Integrating geophysical and geostatistical techniques to map the spatial variation of clay. Geoderma 171–172:53–63. doi:10.1016/j.geoderma.2011.05.005

    Article  Google Scholar 

  • Delin S, Lindén B, Berglund K (2005) Yield and protein response to fertilizer nitrogen in different parts of a cereal field: potential of site-specific fertilization. Eur J Agron 22:325–336. doi:10.1016/j.eja.2004.05.001

    Article  Google Scholar 

  • Dellinger AE, Schmidt JP, Beegle DB (2008) Developing nitrogen fertilizer recommendations for corn using an active sensor. Agron J 100:1546–1552. doi:10.2134/agronj2007.0386

    Article  CAS  Google Scholar 

  • Diacono M, Montemurro F (2010) Long-term effects of organic amendments on soil fertility. A review. Agron Sustain Dev 30:401–422. doi:10.1051/agro/2009040

    Article  CAS  Google Scholar 

  • Diacono M, Troccoli A, Girone G, Castrignanò A (2011) Field-scale variability and homogeneous zone delineation for some qualitative parameters of durum wheat semolina in Mediterranean environment. World J Agr Sci 7:286–290

    Google Scholar 

  • Diacono M, Castrignanò A, Troccoli A, De Benedetto D, Basso B, Rubino P (2012) Spatial and temporal variability of wheat grain yield and quality in a Mediterranean environment: a multivariate geostatistical approach. Field Crop Res 131:49–62. doi:10.1016/j.fcr.2012.03.004

    Article  Google Scholar 

  • Drissi R, Goutouly J-P, Forget D, Gaudillere J-P (2009) Nondestructive measurement of grapevine leaf area by ground normalized difference vegetation index. Agron J 101:226–231. doi:10.2134/agronj2007.0167

    Article  Google Scholar 

  • Ehlert D, Schmerler J, Voelker U (2004) Variable rate nitrogen fertilisation of winter wheat based on a crop density sensor. Precis Agric 5:263–273

    Article  Google Scholar 

  • Eitel JUH, Long DS, Gessler PE, Smith AMS (2007) Using in-situ measurements to evaluate the new RapidEye™ satellite series for prediction of wheat nitrogen status. Int J Remote Sens 28:4183–4190. doi:10.1080/01431160701422213

    Article  Google Scholar 

  • Erdle K, Mistele B, Schmidhalter U (2011) Comparison of active and passive spectral sensors in discriminating biomass parameters and nitrogen status in wheat cultivars. Field Crop Res 124:74–84. doi:10.1016/j.fcr.2011.06.007

    Article  Google Scholar 

  • Fairchild DS (1988) Soil information system for farming by kind of soil. In: Proceedings, International interactive workshop on soil resources: their inventory, analysis and interpretations for use in the 1990’s. University of Minnesota, St Paul, MN, USA, pp159–164

  • FAO (1995) Integrated plant nutrition system. FAO Fertilizer and Plant Nutrition Bulletin 12, Rome

  • Fava F, Colombo R, Bocchi S, Meroni M, Sitzia M, Fois N, Zucca C (2009) Identification of hyperspectral vegetation indices for Mediterranean pasture characterization. Int J Appl Earth Obs Geoinf 11:233–243. doi:10.1016/j.jag.2009.02.003

    Article  Google Scholar 

  • Ferguson RB, Lark RM, Slater GP (2003) Approaches to management zone definition for use of nitrification inhibitors. Soil Sci Soc Am J 67:937–947

    Article  CAS  Google Scholar 

  • Fiez TE, Miller BC, Pan WL (1994) Assessment of spatially variable nitrogen fertilizer management in winter wheat. J Prod Agric 7:86–93

    Google Scholar 

  • Fitzgerald GJ, Lesch SM, Barnes EM, Luckett WE (2006a) Directed sampling using remote sensing with a response surface sampling design for site-specific agriculture. Comput Electron Agric 53:98–112. doi:10.1016/j.compag.2006.04.003

    Article  Google Scholar 

  • Fitzgerald GJ, Rodriguez D, Christensen LK, Belford R, Sadras VO, Clarke TR (2006b) Spectral and thermal sensing for nitrogen and water status in rainfed and irrigated wheat environments. Precis Agric 7:233–248

    Article  Google Scholar 

  • Fitzgerald G, Rodriguez D, O’Leary G (2010) Measuring and predicting canopy nitrogen nutrition in wheat using a spectral index—the canopy chlorophyll content index (CCCI). Field Crop Res 116:318–324. doi:10.1016/j.fcr.2010.01.010

    Article  Google Scholar 

  • Florin MJ, McBratney AB, Whelan BM (2009) Quantification and comparison of wheat yield variation across space and time. Eur J Agron 30:212–219. doi:10.1016/j.eja.2008.10.003

    Article  Google Scholar 

  • Flowers M, Weisz R, Heiniger R, Osmond D, Crozier C (2004) In-season optimization and site-specific nitrogen management for soft red winter wheat. Agron J 96:124–134

    Article  Google Scholar 

  • Franzen DW, Hopkins DH, Sweeney MD, Ulmer MK, Halvorson AD (2002) Evaluation of soil survey scale for zone development of site specific nitrogen management. Agron J 94:381–389

    Article  Google Scholar 

  • Godwin RJ, Miller PCH (2003) A review of the technologies for mapping within-field variability. Biosyst Eng 84:393–407. doi:10.1016/S1537-5110(02)00283-0

    Article  Google Scholar 

  • Godwin RJ, Wood GA, Taylor JC, Knight SM, Welsh JP (2003a) Precision farming of cereal crops: a review of a six year experiment to develop management guidelines. Biosyst Eng 84:375–391. doi:10.1016/S1537-5110(03)00031-X

    Article  Google Scholar 

  • Godwin RJ, Richards TE, Wood GA, Welsh JP, Knight SM (2003b) An economic analysis of the potential for precision farming in UK cereal production. Biosyst Eng 84:533–545. doi:10.1016/S1537-5110(02)00282-9

    Article  Google Scholar 

  • Guastaferro F, Castrignanò A, De Benedetto D, Sollitto D, Troccoli A, Cafarelli B (2010) A comparison of different algorithms for the delineation of management zones. Precis Agric 11:600–620. doi:10.1007/s11119-010-9183-4

    Article  Google Scholar 

  • Haboudane D, Miller JR, Tremblay N, Zarco-Tejada PJ, Dextraze L (2002) Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application in precision agriculture. Remote Sens Environ 81:416–426. doi:10.1016/j.rse.2003.12.013

    Article  Google Scholar 

  • Havlin JL, Heiniger RW (2009) A variable-rate decision support tool. Precis Agric 10:356–369. doi:10.1007/s11119-009-9121-5

    Article  Google Scholar 

  • Havránková J (2007) The evaluation of ground based remote sensing systems for canopy nitrogen management in winter wheat. PhD Thesis. Cranfield University at Silsoe

  • Heege HJ, Reusch S, Thiessen E (2008) Prospects and results for optical systems for site-specific on-the-go control of nitrogen-top-dressing in Germany. Precis Agric 9:115–131. doi:10.1007/s11119-008-9055-3

    Article  Google Scholar 

  • Houlès V, Guérif M, Mary B (2007) Elaboration of a nitrogen nutrition indicator for winter wheat based on leaf area index and chlorophyll content for making nitrogen recommendations. Eur J Agron 27:1–11. doi:10.1016/j.eja.2006.10.001

    Article  CAS  Google Scholar 

  • Humphreys MT, Raun WR, Martin KL, Freeman KW, Johnson GV, Stone ML (2004) Indirect estimates of soil electrical conductivity for improved prediction of wheat grain yield. Commun Soil Sci Plan 35:2639–2653. doi:10.1081/LCSS-200030421

    Article  CAS  Google Scholar 

  • Iqbal J, Thomasson JA, Jenkins JN, Owens PR, Whisler FD (2005) Spatial variability analysis of soil physical properties of alluvial soils. Soil Sci Soc Am J 69:1338–1350. doi:10.2136/sssaj2004.0154

    Article  CAS  Google Scholar 

  • Isaaks EH, Srivastava RM (1989) Applied geostatistics. Oxford University Press, New York

    Google Scholar 

  • James IT, Godwin RJ (2003) Soil, water and yield relationships in developing strategies for the precision application of nitrogen fertiliser to winter barley. Biosyst Eng 84:467–480. doi:10.1016/S1537-5110(02)00284-2

    Article  Google Scholar 

  • Jenny H (1941) Factors of soil formation. McGraw-Hill, New York

    Google Scholar 

  • Johnson CK, Mortensen DA, Wienhold BJ, Shanahan JF, Doran JW (2003) Site-specific management zones based on soil electrical conductivity in a semiarid cropping system. Agron J 95:303–315

    Article  Google Scholar 

  • Kitchen NR, Sudduth KA, Drummond ST, Scharf PC, Palm HL, Roberts DF, Vories ED (2010) Ground-based canopy reflectance sensing for variable-rate nitrogen corn fertilization. Agron J 102:71–84. doi:10.2134/agronj2009.0114

    Article  CAS  Google Scholar 

  • Komatsuzaki M, Ohta H (2007) Soil management practices for sustainable agro-ecosystems. Sustain Sci 2:103–120. doi:10.1007/s11625-006-0014-5

    Article  Google Scholar 

  • Ladha JK, Pathak H, Krupnik TJ, Six J, van Kesse C (2005) Efficiency of fertilizer nitrogen in cereal production: retrospects and prospects. Adv Agron 87:85–156. doi:10.1016/S0065-2113(05)87003-8

    Article  CAS  Google Scholar 

  • Ladoni M, Bahrami HA, Alavipanah SK, Norouzi AA (2010) Estimating soil organic carbon from soil reflectance: a review. Precis Agric 11:82–99. doi:10.1007/s11119-009-9123-3

    Article  Google Scholar 

  • Large EC (1954) Growth stages in cereals. Plant Pathol 3:128–129

    Article  Google Scholar 

  • Lark RM (1998) Forming spatially coherent regions by classification of multivariate data: an example from the analysis of maps of crop yield. Int J Geogr Inf Sci 12:83–98

    Article  Google Scholar 

  • Lark RM (2001) Some tools for parsimonious modelling and interpretation of within-field variation of soil and crop systems. Soil Till Res 58:99–111

    Article  Google Scholar 

  • LaRuffa JM, Raun WR, Phillips SB, Solie JB, Stone ML, Johnson GV (2001) Optimum field element size for maximum yield in winter wheat using variable nitrogen rates. J Plant Nutr 24:313–325

    Article  CAS  Google Scholar 

  • Li J, Heap AD (2008) A review of spatial interpolation methods for environmental scientists. Geoscience Australia, Record 2008/23, 137 pp

  • Li F, Miao Y, Zhang F, Cui Z, Li R, Chen X, Zhang H, Schroder J, Raun WR, Jia L (2009) In-season optical sensing improves nitrogen-use efficiency for winter wheat. Soil Sci Soc Am J 73:1566–1574. doi:10.2136/sssaj2008.0150

    Article  CAS  Google Scholar 

  • Li F, Miao Y, Hennig SD, Gnyp ML, Chen X, Jia L, Baret G (2010) Evaluating hyperspectral vegetation indices for estimating nitrogen concentration of winter wheat at different growth stages. Precis Agric 11:335–357. doi:10.1007/s11119-010-9165-6

    Article  Google Scholar 

  • Li Y, Efatmaneshnik M, Dempster AG (2012) Attitude determination by integration of MEMS inertial sensors and GPS for autonomous agriculture applications. Gps Solut 16:41–52. doi:10.1007/s10291-011-0207-y

    Article  Google Scholar 

  • Liang HX, Zhao CJ, Huang WJ, Li, LY, Wang JH, Ma YH (2005) Variable-rate nitrogen application algorithm based on canopy reflected spectrum and its influence on wheat. In: Proceedings of international society for optical engineering. Bellingham, WA, pp 522–530

  • Lichtfouse E, Navarrete M, Debaeke P, Souchère V, Alberola C, Ménassieu J (2009) Agronomy for sustainable agriculture. A review. Agron Sustain Dev 29:1–6. doi:10.1051/agro:2008054

    Article  Google Scholar 

  • Link J, Batchelor WD, Graeff S, Claupein W (2008) Evaluation of current and model-based site-specific nitrogen applications on wheat (Triticum aestivum L.) yield and environmental quality. Precis Agric 9:251–267. doi:10.1007/s11119-008-9068-y

    Article  Google Scholar 

  • Liu XJ, Ju XT, Zhang FS, Chen XP (2003) Nitrogen recommendation for winter wheat using N-min test and rapid plant tests in North China Plain. Commun Soil Sci Plan 34:2251–2539. doi:10.1081/CSS-120024785

    Google Scholar 

  • Liu L, Wang J, Bao Y, Huang W, Ma Z, Zhao C (2006) Predicting winter wheat condition, grain yield and protein content using multi–temporal EnviSat–ASAR and Landsat TM satellite images. Int J Remote Sens 27:737–753. doi:10.1080/01431160500296867

    Article  Google Scholar 

  • Lobell DB, Asner GP, Ortiz-Monasterio JI, Benning TL (2003) Remote sensing of regional crop production in the Yaqui Valley, Mexico: estimates and uncertainties. Agric Ecosyst Environ 94:205–220

    Article  Google Scholar 

  • Long DS, Engel R, Carlson GR (2000) Method for precision nitrogen management in spring wheat: II. Implementation. Precis Agric 2:25–38

    Article  Google Scholar 

  • Martinon V, Fadailli EM, Evain S, Zecha C (2011) Multiplex: an innovative optical sensor for diagnosis, mapping and management of nitrogen on wheat. In: Stafford JV (ed) Precision agriculture 2011. Ampthill, UK, pp 547–561

    Google Scholar 

  • McBratney AB, Mendonça Santos ML, Minasny B (2003) On digital soil mapping. Geoderma 117:3–52

    Article  Google Scholar 

  • Meyer-Aurich A, Weersink A, Gandorfer M, Wagner P (2010) Optimal site-specific fertilization and harvesting strategies with respect to crop yield and quality response to nitrogen. Agric Syst 103:478–485. doi:10.1016/j.agsy.2010.05.001

    Article  Google Scholar 

  • Miao Y, Mull DJ, Batchelor WD, Paz JO, Robert PC, Wiebers M (2006) Evaluating management zone optimal nitrogen rates with a crop growth model. Agron J 98:545–553. doi:10.2134/agronj2005.0153

    Article  Google Scholar 

  • Miao Y, Stewart BA, Zhang F (2011) Long-term experiments for sustainable nutrient management in China. A review. Agron Sustain Dev 31:397–414. doi:10.1051/agro/2010034

    Article  Google Scholar 

  • Mistele B, Schmidhalter U (2008) Estimating the nitrogen nutrition index using spectral canopy reflectance measurements. Europ J Agronomy 29:184–190. doi:10.1016/j.eja.2008.05.007

    Article  CAS  Google Scholar 

  • Montemurro F (2009) Different nitrogen fertilization sources, soil tillage, and crop rotations in winter wheat: effect on yield, quality, and nitrogen utilization. J Plant Nutr 32:1–18. doi:10.1080/01904160802530979

    Article  CAS  Google Scholar 

  • Montemurro F, Maiorana M, Ferri D, Convertini G (2006) Nitrogen indicators, uptake and utilization efficiency in a maize and barley rotation cropped at different levels and sources of N fertilization. Field Crop Res 99:114–124. doi:10.1016/j.fcr.2006.04.001

    Article  Google Scholar 

  • Montemurro F, Convertini G, Ferri D (2007) Nitrogen application in winter wheat grown in Mediterranean conditions: effects on nitrogen uptake, utilization efficiency, and soil nitrogen deficit. J Plant Nutr 30:1681–1703. doi:10.1080/01904160701615541

    Article  CAS  Google Scholar 

  • Montemurro F, Maiorana M, Convertini G, Fornaro F (2008) Cropping systems: the role of continuous cropping, crop rotation, leguminous crops and catch crop in Mediterranean conditions. In: Berklian YU (ed) Crop rotation, Chapter 6. Nova Science Publishers, Inc. ISBN 978-1-60692-100-5

  • Morris KB, Martin KL, Freeman KW, Teal RK, Girma K, Arnall DB, Hodgen PJ, Mosali J, Raun WR, Solie JB (2006) Mid-season recovery from nitrogen stress in winter wheat. J Plant Nutr 29:727–745. doi:10.1080/01904160600567066

    Article  CAS  Google Scholar 

  • Mulla DJ, Bhatti AU, Hammond MW, Benson JA (1992) A comparison of winter wheat yield and quality under uniform versus spatially variable fertilizer management. Agric Ecosystems Environ 38:301–311

    Article  Google Scholar 

  • Mullen RW, Freeman KW, Raun WR, Johnson GV, Stone ML, Solie JB (2003) Identifying an in-season response index and the potential to increase wheat yield with nitrogen. Agron J 95:347–351

    Article  Google Scholar 

  • Mzuku M, Khosla R, Reich R, Inman D, Smith F, MacDonald L (2005) Spatial variability of measured soil properties across site-specific management zones. Soil Sci Soc Am J 69:1572–1579. doi:10.2136/sssaj2005.0062

    Article  CAS  Google Scholar 

  • Pierce FJ (1995) If (condition) then (action). ag/INNOVATOR 3,4

  • Pierce FJ, Nowak P (1999) Aspects of precision agriculture. Adv Agron 67:1–85

    Article  Google Scholar 

  • Pitman MG, Läuchli A (2002) Global impact of salinity and agricultural ecosystems. In: Läuchli A, Lüttge U (eds) Salinity: environment–plants–molecules. Kluwer Academic Publishers, Netherlands, pp 3–20

    Google Scholar 

  • Plant RE (2001) Site-specific management: the application of information technology to crop production. Comput Electron Agric 30:9–29

    Article  Google Scholar 

  • Prasad B, Carver BF, Stone ML, Babar MA, Raun WR, Klatt AR (2007) Potential use of spectral reflectance indices as a selection tool for grain yield in winter wheat under Great Plains conditions. Crop Sci 47:1426–1440. doi:10.2135/cropsci2006.07.0492

    Article  Google Scholar 

  • Raun WR, Solie JB, Johnson GV, Stone ML, Lukina EV, Thomason WE, Schepers JS (2001) In-season prediction of potential grain yield in winter wheat using canopy reflectance. Agron J 93:131–138

    Article  Google Scholar 

  • Raun WR, Sollie JB, Johnson GV, Stone ML, Mullen RW, Freeman KW, Thomason WE, Lukina EV (2002) Improving nitrogen use efficiency in cereal production with optical sensing and variable rate application. Agron J 94:815–820

    Article  Google Scholar 

  • Raun WR, Solie JB, Stone ML, Martin KL, Freeman KW, Mullen RW, Zhang H, Schepers JS, Johnson GV (2005) Optical sensor-based algorithm for crop nitrogen fertilization. Commun Soil Sci Plan 36:2759–2781. doi:10.1080/00103620500303988

    Article  CAS  Google Scholar 

  • Raun WR, Solie JB, Taylor RK, Arnall DB, Mack CJ, Edmonds DE (2008) Ramp calibration strip technology for determining midseason nitrogen rates in corn and wheat. Agron J 100:1088–1093

    Article  CAS  Google Scholar 

  • Ray SS, Singh JP, Panigrahy S (2010) Use of hyperspectral remote sensing data for crop stress detection: ground-based studies. International Archives of Photogrammetry, Remote Sensing and Spatial Information Science, XXXVIII, Part 8, Kyoto Japan

  • Robert PC (2002) Precision agriculture: a challenge for crop nutrition management. Plant Soil 247:143–149

    Article  CAS  Google Scholar 

  • Roberts DC, Brorsen BW, Taylor RK, Solie JB, Raun WR (2010) Replicability of nitrogen recommendations from ramped calibration strips in winter wheat. Precis Agric. doi:10.1007/s11119-010-9209-y

  • Robertson M, Isbister B, Maling I, Oliver Y, Wong M, Adams M, Bowden B, Tozer P (2007) Opportunities and constraints for managing within-field spatial variability in Western Australian grain production. Field Crop Res 104:60–67. doi:10.1016/j.fcr.2006.12.013

    Article  Google Scholar 

  • Robertson MJ, Lyle G, Bowden JW (2008) Within-field variability of wheat yield and economic implications for spatially variable nutrient management. Field Crop Res 105:211–220. doi:10.1016/j.fcr.2007.10.005

    Article  Google Scholar 

  • Rodriguez D, Fitzgerald GJ, Belford R, Christensen LK (2006) Detection of nitrogen deficiency in wheat from spectral reflectance indices and basic crop eco-physiological concepts. Aust J Agric Res 57:781–789

    Article  CAS  Google Scholar 

  • SAIC (2011) Software solution enables the collection of geographic information system (GIS) data in the field without network connectivity. http://investors.saic.com/phoenix.zhtml?c=193857&p=irol-newsArticle&ID=1615653

  • Samborski SM, Tremblay N, Fallon E (2009) Strategies to make use of plant sensors-based diagnostic information for nitrogen recommendations. Agron J 101:800–816. doi:10.2134/agronj2008.0162Rx

    Article  CAS  Google Scholar 

  • Schächtl J, Huber G, Maidl FX, Stickesel E (2005) Laser-inducted chlorophyll fluorescence measurements for detecting the nitrogen status of wheat canopies. Precis Agric 6:143–156. doi:10.1007/s11119-004-1031-y

    Article  Google Scholar 

  • Seelan SK, Laguette S, Casady GM, Seielstad GA (2003) Remote sensing applications for precision agriculture: a learning community approach. Remote Sens Environ 88:157–169. doi:10.1016/j.rse.2003.04.007

    Article  Google Scholar 

  • Shahandeh H, Wright AL, Hons FM (2011) Use of soil nitrogen parameters and texture for spatially-variable nitrogen fertilization. Precis Agric 12:146–163. doi:10.1007/s11119-010-9163-8

    Article  Google Scholar 

  • Singh B, Sharma RK, Kaur J, Jat ML, Martin KL, Singh Y, Singh V, Chandna P, Choudhary OP, Gupta RK, Thind HS, Singh-J UHS, Khurana HS, Kumar A, Uppal RK, Vashistha M, Raun WR, Gupta R (2011) Assessment of the nitrogen management strategy using an optical sensor for irrigated wheat. Agron Sustain Dev. doi:10.1007/s13593-011-0005-5

  • Skjødt P (2003) Sensor based nitrogen fertilization increasing grain protein yield in winter wheat. Master thesis. (eds) Hansen PM, Jørgensen RN, Risø National Laboratory, Roskilde, Denmark. The Royal Veterinary and Agricultural University Copenhagen, Denmark

  • Song X, Wang J, Huang W, Liu L, Yan G, Pu R (2009) The delineation of agricultural management zones with high resolution remotely sensed data. Precis Agric 10:471–487. doi:10.1007/s11119-009-9108-2

    Article  Google Scholar 

  • Sripada RP, Farrer DC, Weisz R, Heiniger RW, White JG (2007) Aerial color infrared photography to optimize in-season nitrogen fertilizer recommendations in winter wheat. Agron J 99:1424–1435

    Article  CAS  Google Scholar 

  • Stafford JV (2000) Implementing precision agriculture in the 21st century. J Agric Engng Res 76:267–275

    Article  Google Scholar 

  • Stellacci AM, Castrignanò A, Diacono M, Troccoli A, Ciccarese A, Armenise E, Gallo A, De Vita P, Lonigro A, Mastro MA, Rubino P (2012) Combined approach based on principal component analysis and canonical discriminant analysis for investigating hyperspectral plant response. Ital J Agron 7:247–253. doi:10.4081/ija.2012.e34

    Google Scholar 

  • Stewart CM, McBratney AB, Skerritt JH (2002) Site-specific durum wheat quality and its relationship to soil properties in a single field in Northern New South Wales. Precis Agric 3:155–168

    Article  Google Scholar 

  • Taylor JA, McBratney AB, Whelan BM (2007) Establishing management classes for broadacre agricultural production. Agron J 99:1366–1376. doi:10.2134/agronj2007.0070

    Article  Google Scholar 

  • Thenkabail PS, Enclona EA, Ashton MS, Van Der Meer B (2004) Accuracy assessments of hyperspectral waveband performance for vegetation analysis applications. Remote Sens Environ 91:354–376. doi:10.1016/j.rse.2004.03.013

    Article  Google Scholar 

  • Thomason WE, Phillips SB, Davis PH, Warren JG, Alley MM, Reiter MS (2011) Variable nitrogen rate determination from plant spectral reflectance in soft red winter wheat. Precis Agric 12:666–681. doi:10.1007/s11119-010-9210-5

    Article  Google Scholar 

  • Tilling AK, O’Leary GJ, Ferwerda JG, Jones SD, Fitzgerald GJ, Rodriguez D, Belford R (2007) Remote sensing of nitrogen and water stress in wheat. Field Crop Res 104:77–85. doi:10.1016/j.fcr.2007.03.023

    Article  Google Scholar 

  • Tilman D, Cassman KG, Matson PA, Naylor R, Polasky S (2002) Agricultural sustainability and intensive production practices. Nature 418:671–677

    Article  PubMed  CAS  Google Scholar 

  • Tremblay N, Wang Z, Cerovic ZG (2011) Sensing crop nitrogen status with fluorescence indicators. A review. Agron Sustain Dev. doi:10.1007/s13593-011-0041-1

  • Tubaña BS, Arnall DB, Holtz SL, Solie JB, Girma K, Raun WR (2008) Effect of treating field spatial variability in winter wheat at different resolutions. J Plant Nutr 31:1975–1998. doi:10.1080/01904160802403144

    Article  CAS  Google Scholar 

  • Tucker CJ (1979) Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens Environ 8:127–150

    Article  Google Scholar 

  • Vigneau N, Ecarnot M, Rabatel G, Roumet P (2011) Potential of field hyperspectral imaging as a non destructive method to assess leaf nitrogen content in wheat. Field Crop Res 122:25–31. doi:10.1016/j.fcr.2011.02.003

    Article  Google Scholar 

  • Vrindts E, Reyniers M, Darius P, De baerdemaeker J, Gilot M, Sadaoui Y, Frankinet M, Hanquet B, Destain M-F (2003) Analysis of soil and crop properties for precision agriculture for winter wheat. Biosyst Eng 85:141–152. doi:10.1016/S1537-5110(03)00040-0

    Article  Google Scholar 

  • Walley F, Yates T, van Groenigen J-W, van Kessel C (2002) Relationships between soil nitrogen availability indices, yield, and nitrogen accumulation of wheat. Soil Sci Soc Am J 66:1549–1561

    Article  CAS  Google Scholar 

  • Washmon CN, Solie JB, Raun WR, Itenfisu DD (2002) Within field variability in wheat grain yields over nine years in Oklahoma. J Plant Nutr 25:2655–2662

    Article  CAS  Google Scholar 

  • Weisz R, Heiniger R (2000) Small grain production guide 2000–01. Ext Circ. AG-580. North Carolina Coop. Ext. Serv., Raleigh

  • Welsh JP, Wood GA, Godwin RJ, Taylor JC, Earl R, Blackmore S, Knight SM (2003) Developing strategies for spatially variable nitrogen application in cereals, Part II: wheat. Biosyst Eng 84:495–511. doi:10.1016/S1537-5110(03)00003-5

    Article  Google Scholar 

  • Whelan BM, McBratney AB (2000) The “null hypothesis” of precision agriculture management. Precis Agric 2:265–279

    Article  Google Scholar 

  • Whelan BM, McBratney A (2003) Definition and interpretation of potential management zones in Australia. In: Solutions for a better environment. Proceedings of the 11th Australian Agronomy Conference, Geelong, Victoria. [CD-ROM]

  • Wong MTF, Asseng S (2006) Determining the causes of spatial and temporal variability of wheat yields at sub-field scale using a new method of upscaling a crop model. Plant Soil 283:203–215. doi:10.1007/s11104-006-0012-5

    Article  CAS  Google Scholar 

  • Wood GA, Welsh JP, Godwin RJ, Taylor JC, Earl M, Knoght SM (2003) Real-time measures of canopy size as a basis for spatially varying nitrogen applications to winter wheat son at different seed rates. Biosyst Eng 84:513–531. doi:10.1016/S1537-5110(03)00006-0

    Article  Google Scholar 

  • Xavier AC, Rudorff BFT, Moreira MA, Alvarenga BS, de Freitas JG, Salomon MV (2006) Hyperspectral field reflectance measurements to estimate wheat grain yield and plant height. Sci Agric (Piracicaba, Braz) 63:130–138

    Google Scholar 

  • Zadoks JC, Chang TT, Zonzak CF (1974) A decimal code for the growth stages of cereals. Weed Res 14:415–421

    Article  Google Scholar 

  • Zhang X, Shi L, Jia X, Seielstad G, Helgason C (2010) Zone mapping application for precision-farming: a decision support tool for variable rate application. Precis Agric 11:103–114. doi:10.1007/s11119-009-9130-4

    Article  CAS  Google Scholar 

  • Zhao C, Wang Z, Wang J, Huang W, Guo T (2011) Early detection of canopy nitrogen deficiency in winter wheat (Triticum aestivum L.) based on hyperspectral measurement of canopy chlorophyll status. New Zeal J Crop Hort 39:251–262. doi:10.1080/01140671.2011.588713

    Article  CAS  Google Scholar 

  • Zhu Y, Li Y, Feng W, Tian Y, Yao X, Cao W (2006) Monitoring leaf nitrogen in wheat using canopy reflectance spectra. Can J Plant Sci 86:1037–1046

    Article  Google Scholar 

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Acknowledgments

The authors wish to thank Prof. Louis E. Keiner, PhD Stanislaw Samborski and Prof. Urs Schmidhalter for giving us the permission to reproduce their figures in this review.

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Correspondence to Mariangela Diacono.

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Diacono, M., Rubino, P. & Montemurro, F. Precision nitrogen management of wheat. A review. Agron. Sustain. Dev. 33, 219–241 (2013). https://doi.org/10.1007/s13593-012-0111-z

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