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Engineering Nitrogen Utilization in Crop Plants pp 121–139Cite as

Tackling Nitrogen Use Efficiency in Cereal Crops Using High-Throughput Phenotyping

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Abstract

Nitrogen use efficiency involves a complex set of plant processes which are heavily influenced by the environment . This chapter explores a suite of new technologies which can be, and in some cases have been, brought to bear in order to categorize and improve the nitrogen use efficiency of cereals . A combination of high-throughput phenotyping , in controlled environments as well as the field, should enable scientists to better capitalize on the expanding genetic knowledge around the downstream pathways of NUE and make more progress in delivering high NUE crops . In this chapter, modern phenomics is explored, with a focus on those technologies which can give more insight into the determinants of yield and NUE.

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References

  • Abiko T, Wakayama M, Kawakami A, Obara M, Kisaka H, Miwa T, Aoki N, Ohsugi R (2010) Changes in nitrogen assimilation, metabolism, and growth in transgenic rice plants expressing a fungal NADP (H)-dependent glutamate dehydrogenase (gdhA). Planta 232(2):299–311

    Article  CAS  PubMed  Google Scholar 

  • Agrama HAS, Zakaria AG, Said FB, Tuinstra M (1999) Identification of quantitative trait loci for nitrogen use efficiency in maize. Mol Breeding 5(2):187–195

    Article  Google Scholar 

  • Al-Tamimi N, Brien C, Oakey H, Berger B, Saade S, Ho YS, Schmöckel SM, Tester M, Negrão S (2016) Salinity tolerance loci revealed in rice using high-throughput non-invasive phenotyping. Nature Commun 7:13342

    Article  Google Scholar 

  • An D, Su J, Liu Q, Zhu Y, Tong Y, Li J, Jing R, Li B, Li Z (2006) Mapping QTLs for nitrogen uptake in relation to the early growth of wheat (Triticum aestivum L.). Plant Soil 284(1–2):73–84

    Article  CAS  Google Scholar 

  • Andrade-Sanchez P, Gore MA, Heun JT, Thorp KR, Carmo-Silva AE, French AN, Salvucci ME, White JW (2013) Development and evaluation of a field-based high-throughput phenotyping platform. Funct Plant Biol 41(1):68–79

    Article  Google Scholar 

  • Araus JL, Cairns JE (2014) Field high-throughput phenotyping: the new crop breeding frontier. Trends Plant Sci 19(1):52–61

    Article  CAS  PubMed  Google Scholar 

  • Babar MA, van Ginkel M, Klatt AR, Prasad B, Reynolds MP (2006) The potential of using spectral reflectance indices to estimate yield in wheat grown under reduced irrigation. Euphytica 150(1):155–172

    Article  Google Scholar 

  • Barraclough PB, Howarth JR, Jones J, Lopez-Bellido R, Parmar S, Shepherd CE, Hawkesford MJ (2010) Nitrogen efficiency of wheat: genotypic and environmental variation and prospects for improvement. Eur J Agron 33(1):1–11

    Article  CAS  Google Scholar 

  • Billiau K, Sprenger H, Schudoma C, Walther D, Köhl KI (2012) Data management pipeline for plant phenotyping in a multisite project. Funct Plant Biol 39(11):948–957

    Article  Google Scholar 

  • Borrell A, Hammer G, Van Oosterom E (2001) Stay-green: a consequence of the balance between supply and demand for nitrogen during grain filling? Ann Appl Biol 138(1):91–95

    Article  Google Scholar 

  • Brauer EK, Rochon A, Bi YM, Bozzo GG, Rothstein SJ, Shelp BJ (2011) Reappraisal of nitrogen use efficiency in rice overexpressing glutamine synthetase. Physiol Plant 141(4):361–372

    Article  CAS  PubMed  Google Scholar 

  • Brien CJ, Berger B, Rabie H, Tester M (2013) Accounting for variation in designing greenhouse experiments with special reference to greenhouses containing plants on conveyor systems. Plant Methods 9(1):5

    Article  PubMed  PubMed Central  Google Scholar 

  • Brown TB, Cheng R, Sirault XR, Rungrat T, Murray KD, Trtilek M, Furbank RT, Badger M, Pogson BJ, Borevitz JO (2014) TraitCapture: genomic and environment modelling of plant phenomic data. Curr Opin Plant Biol 18:73–79

    Article  CAS  PubMed  Google Scholar 

  • Burger J, Geladi P (2006) Hyperspectral NIR imaging for calibration and prediction: a comparison between image and spectrometer data for studying organic and biological samples. Analyst 131(10):1152–1160

    Article  CAS  PubMed  Google Scholar 

  • Burns IG (1980) Influence of the spatial distribution of nitrate and the uptake of N by plants: a review and a model for rooting depth. J Soil Sci 31:155–173

    Article  CAS  Google Scholar 

  • Cabrera-Bosquet L, Fournier C, Brichet N, Welcker C, Suard B, Tardieu F (2016) High-throughput estimation of incident light, light interception and radiation-use efficiency of thousands of plants in a phenotyping platform. New Phytol 212(1):269–281

    Article  CAS  PubMed  Google Scholar 

  • Campbell MT, Du Q, Liu K, Brien CJ, Berger B, Zhang C, Walia H (2017) A comprehensive image-based phenomic analysis reveals the complex genetic architecture of shoot growth dynamics in rice (Oryza sativa). Plant Genome 10(2)

    Google Scholar 

  • Campbell MT, Knecht AC, Berger B, Brien CJ, Wang D, Walia H (2015) Integrating image-based phenomics and association analysis to dissect the genetic architecture of temporal salinity responses in rice. Plant Physiol 168(4):1476–1489

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Chapman S, Merz T, Chan A, Jackway P, Hrabar S, Dreccer M, Holland E, Zheng B, Ling T, Jimenez-Berni J (2014) Pheno-copter: a low-altitude, autonomous remote-sensing robotic helicopter for high-throughput field-based phenotyping. Agronomy 4

    Google Scholar 

  • Chen D, Neumann K, Friedel S, Kilian B, Chen M, Altmann T, Klukas C (2014) Dissecting the phenotypic components of crop plant growth and drought responses based on high-throughput image analysis. Plant Cell 26(12):4636–4655

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Cho Y-G, Kang H-J, Lee J-S, Lee Y-T, Lim S-J, Gauch H, Eun M-Y, McCouch SR (2007) Identification of quantitative trait loci in rice for yield, yield components, and agronomic traits across years and locations all rights reserved. no part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. permission for printing and for reprinting the material contained herein has been obtained by the publisher. Crop Sci 47(6):2403–2417

    Article  Google Scholar 

  • Cormier F, Foulkes J, Hirel B, Gouache D, Moenne-Loccoz Y, Le Gouis J (2016) Breeding for increased nitrogen-use efficiency: a review for wheat (T.aestivum L.). Plant Breed 135(3):255–278

    Article  CAS  Google Scholar 

  • Cormier F, Le Gouis J, Dubreuil P, Lafarge S, Praud S (2014) A genome-wide identification of chromosomal regions determining nitrogen use efficiency components in wheat (Triticum aestivum L.). Theor Appl Genet 127(12):2679–2693

    Article  CAS  PubMed  Google Scholar 

  • Crain JL, Wei Y, Barker J, Thompson SM, Alderman PD, Reynolds M, Zhang N, Poland J (2016) Development and deployment of a portable field phenotyping platform. Crop Sci 56(3):965–975

    Article  Google Scholar 

  • Deery D, Jimenez-Berni J, Jones H, Sirault X, Furbank R (2014) Proximal remote sensing buggies and potential applications for field-based phenotyping. Agronomy 4(3):349

    Article  Google Scholar 

  • Dhugga KS, Waines J (1989) Analysis of nitrogen accumulation and use in bread and durum wheat. Crop Sci 29(5):1232–1239

    Article  Google Scholar 

  • Ding L, Wang KJ, Jiang GM, Biswas DK, Xu H, Li LF, Li YH (2005) Effects of nitrogen deficiency on photosynthetic traits of maize hybrids released in different years. Ann Bot 96(5):925–930

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Dueck T, van Ieperen W, Taulavuori K (2016) Light perception, signalling and plant responses to spectral quality and photoperiod in natural and horticultural environments. Environ Exp Bot 121:1–3

    Article  Google Scholar 

  • Ecarnot M, Compan F, Roumet P (2013) Assessing leaf nitrogen content and leaf mass per unit area of wheat in the field throughout plant cycle with a portable spectrometer. Field Crops Res 140:44–50

    Article  Google Scholar 

  • Echarte L, Rothstein S, Tollenaar M (2008) The response of leaf photosynthesis and dry matter accumulation to nitrogen supply in an older and a newer maize hybrid all rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher. Crop Sci 48(2):656–665

    Article  CAS  Google Scholar 

  • Eitel JUH, Magney TS, Vierling LA, Brown TT, Huggins DR (2014) LiDAR based biomass and crop nitrogen estimates for rapid, non-destructive assessment of wheat nitrogen status. Field Crops Res 159:21–32

    Article  Google Scholar 

  • Evenson RE, Gollin D (2003) Assessing the impact of the green revolution, 1960 to 2000. Science 300(5620):758–762

    Article  CAS  PubMed  Google Scholar 

  • Fageria NK, Baligar VC (2005) Enhancing nitrogen use efficiency in crop plants. In: Donald LS (ed) Advances in agronomy. Academic Press, pp. 97-185

    Google Scholar 

  • Fan X, Tang Z, Tan Y, Zhang Y, Luo B, Yang M, Lian X, Shen Q, Miller AJ, Xu G (2016) Overexpression of a pH-sensitive nitrate transporter in rice increases crop yields. Proc Natl Acad Sci 113(26):7118–7123

    Article  CAS  PubMed  Google Scholar 

  • Fischer R, Wall P (1976) Wheat breeding in Mexico and yield increases

    Google Scholar 

  • Fischer RA (2011) Wheat physiology: a review of recent developments. Crop Pasture Sci 62(2):95–114

    Article  Google Scholar 

  • Forde BG, Clarkson DT (1999) Nitrate and ammonium nutrition of plants: physiological and molecular perspectives. Adv Bot Res 30:1–90

    Article  CAS  Google Scholar 

  • Foulkes M, Sylvester-Bradley R, Scott R (1998) Evidence for differences between winter wheat cultivars in acquisition of soil mineral nitrogen and uptake and utilization of applied fertilizer nitrogen. J Agric Sci 130(01):29–44

    Article  Google Scholar 

  • Foulkes MJ, Hawkesford MJ, Barraclough PB, Holdsworth MJ, Kerr S, Kightley S, Shewry PR (2009) Identifying traits to improve the nitrogen economy of wheat: Recent advances and future prospects. Field Crops Res 114(3):329–342

    Article  Google Scholar 

  • Furbank RT, Tester M (2011) Phenomics–technologies to relieve the phenotyping bottleneck. Trends Plant Sci 16(12):635–644

    Article  CAS  PubMed  Google Scholar 

  • Gallais A, Hirel B (2004) An approach to the genetics of nitrogen use efficiency in maize. J Exp Bot 55(396):295–306

    Article  CAS  PubMed  Google Scholar 

  • Garnett T, Conn V, Kaiser BN (2009) Root based approaches to improving nitrogen use efficiency in plants. Plant Cell Environ 32(9):1272–1283

    Article  CAS  PubMed  Google Scholar 

  • Garnett T, Conn V, Plett D, Conn S, Zanghellini J, Mackenzie N, Enju A, Francis K, Holtham L, Roessner U, Boughton B, Bacic A, Shirley N, Rafalski A, Dhugga K, Tester M, Kaiser BN (2013) The response of the maize nitrate transport system to nitrogen demand and supply across the lifecycle. New Phytol 198(1):82–94

    Article  CAS  PubMed  Google Scholar 

  • Garnett T, Plett D, Heuer S, Okamoto M (2015) Genetic approaches to enhancing nitrogen-use efficiency (NUE) in cereals: challenges and future directions. Funct Plant Biol 42(10):921–941

    Article  CAS  Google Scholar 

  • Garnett T, Rebetzke G (2013) Improving crop nitrogen use in dryland farming. Improving water and nutrient-use efficiency in food production systems. Wiley. pp 123–144

    Google Scholar 

  • Golzarian M, Frick R, Rajendran K, Berger B, Roy S, Tester M, Lun D (2011) Accurate inference of shoot biomass from high-throughput images of cereal plants. Plant Methods 7

    Google Scholar 

  • Good AG, Johnson SJ, De Pauw M, Carroll RT, Savidov N, Vidmar J, Lu Z, Taylor G, Stroeher V (2007) Engineering nitrogen use efficiency with alanine aminotransferase. Botany 85(3):252–262

    CAS  Google Scholar 

  • Good AG, Shrawat AK, Muench DG (2004) Can less yield more? Is reducing nutrient input into the environment compatible with maintaining crop production? Trends Plant Sci 9(12):597–605

    Article  CAS  Google Scholar 

  • Gu R, Duan F, An X, Zhang F, von Wirén N, Yuan L (2013) Characterization of AMT-mediated high-affinity ammonium uptake in roots of maize (Zea mays L.). Plant Cell Physiol 54(9):1515–1524

    Google Scholar 

  • Han M, Okamoto M, Beatty PH, Rothstein SJ, Good AG (2015) The genetics of nitrogen use efficiency in crop plants. Annu Rev Genet 49:269–289

    Article  CAS  PubMed  Google Scholar 

  • Hawkesford MJ (2017) Genetic variation in traits for nitrogen use efficiency in wheat. J Exp Bot 68(10):2627–2632

    Article  CAS  PubMed  Google Scholar 

  • Heap JW, McKay AC (2009) Managing soil-borne crop diseases using precision agriculture in Australia. Crop Pasture Sci 60(9):824–833

    Article  Google Scholar 

  • Hogewoning SW, Trouwborst G, Maljaars H, Poorter H, van Ieperen W, Harbinson J (2010) Blue light dose–responses of leaf photosynthesis, morphology, and chemical composition of Cucumis sativus grown under different combinations of red and blue light. J Exp Bot 61(11):3107–3117

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Holman F, Riche A, Michalski A, Castle M, Wooster M, Hawkesford M (2016) High throughput field phenotyping of wheat plant height and growth rate in field plot trials using UAV based remote sensing. Remote Sens 8(12):1031

    Article  Google Scholar 

  • Honsdorf N, March TJ, Berger B, Tester M, Pillen K (2014) High-throughput phenotyping to detect drought tolerance QTL in wild barley introgression lines. PLoS ONE 9(5):e97047

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Howitt SM, Udvardi MK (2000) Structure, function and regulation of ammonium transporters in plants. Biochimica et Biophysica Acta (BBA). Biomembranes 1465(1):152–170

    Article  CAS  Google Scholar 

  • Kamprath EJ, Moll RH, Rodriguez N (1982) Effects of nitrogen fertilization and recurrent selection on performance of hybrid populations of corn. Agron J 74(6):955–958

    Article  Google Scholar 

  • Keeney DR (1982) Nitrogen management for maximum efficiency and minimum pollution. Nitrogen in agricultural soils. Madison, Wisconsin USA: American Society of Agronomy, pp 605–649

    Google Scholar 

  • Kokaly RF (2001) Investigating a physical basis for spectroscopic estimates of leaf nitrogen concentration. Remote Sens Environ 75(2):153–161

    Article  Google Scholar 

  • Krajewski P, Chen DJ, Cwiek H, van Dijk ADJ, Fiorani F, Kersey P, Klukas C, Lange M, Markiewicz A, Nap JP, van Oeveren J, Pommier C, Scholz U, van Schriek M, Usadel B, Weise S (2015) Towards recommendations for metadata and data handling in plant phenotyping. J Exp Bot 66(18):5417–5427

    Article  CAS  PubMed  Google Scholar 

  • Ladha JK, Tirol-Padre A, Reddy CK, Cassman KG, Verma S, Powlson DS, van Kessel C, de B. Richter D, Chakraborty D, Pathak H (2016) Global nitrogen budgets in cereals: a 50-year assessment for maize, rice, and wheat production systems. Sci Rep 6:19355

    Google Scholar 

  • Le Gouis J, Béghin D, Heumez E, Pluchard P (2000) Genetic differences for nitrogen uptake and nitrogen utilisation efficiencies in winter wheat. Eur J Agron 12(3–4):163–173

    Article  Google Scholar 

  • Léran S, Varala K, Boyer J-C, Chiurazzi M, Crawford N, Daniel-Vedele F, David L, Dickstein R, Fernandez E, Forde B, Gassmann W, Geiger D, Gojon A, Gong J-M, Halkier BA, Harris JM, Hedrich R, Limami AM, Rentsch D, Seo M, Tsay Y-F, Zhang M, Coruzzi G, Lacombe B (2014) A unified nomenclature of nitrate transporter 1/peptide transporter family members in plants. Trends Plant Sci 19(1):5–9

    Article  CAS  PubMed  Google Scholar 

  • Lin M, Huybers P (2012) Reckoning wheat yield trends. Environ Res Lett 7(2):024016

    Article  Google Scholar 

  • Lovett GM, Burns DA, Driscoll CT, Jenkins JC, Mitchell MJ, Rustad L, Shanley JB, Likens GE, Haeuber R (2007) Who needs environmental monitoring? Front Ecol Environ 5(5):253–260

    Article  Google Scholar 

  • Ludewig U, Neuhäuser B, Dynowski M (2007) Molecular mechanisms of ammonium transport and accumulation in plants. FEBS Lett 581(12):2301–2308

    Article  CAS  PubMed  Google Scholar 

  • Martre P, Porter JR, Jamieson PD, Triboï E (2003) Modeling grain nitrogen accumulation and protein composition to understand the sink/source regulations of nitrogen remobilization for wheat. Plant Physiol 133(4):1959–1967

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Max JFJ, Schurr U, Tantau H-J, Mutwiwa UN, Hofmann T, Ulbrich A (2012) Greenhouse cover technology. horticultural reviews. Wiley, pp 259–396

    Google Scholar 

  • McAllister CH, Beatty PH, Good AG (2012) Engineering nitrogen use efficient crop plants: the current status. Plant Biotechnol J 10(9):1011–1025

    Article  CAS  PubMed  Google Scholar 

  • Meng R, Saade S, Kurtek S, Berger B, Brien C, Pillen K, Tester M, Sun Y (2017) Growth curve registration for evaluating salinity tolerance in barley. Plant Methods 13(1):18

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Mickelson S, See D, Meyer FD, Garner JP, Foster CR, Blake TK, Fischer AM (2003) Mapping of QTL associated with nitrogen storage and remobilization in barley (Hordeum vulgare L.) leaves. J Exp Bot 54(383):801–812

    Article  CAS  PubMed  Google Scholar 

  • Moll R, Kamprath E, Jackson W (1982) Analysis and interpretation of factors which contribute to efficiency of nitrogen utilization. Agron J 74(3):562–564

    Article  Google Scholar 

  • Muraya MM, Chu J, Zhao Y, Junker A, Klukas C, Reif JC, Altmann T (2017) Genetic variation of growth dynamics in maize (Zea mays L.) revealed through automated non-invasive phenotyping. Plant J 89(2):366–380

    Article  CAS  PubMed  Google Scholar 

  • Neilson EH, Edwards A, Blomstedt C, Berger B, Møller BL, Gleadow R (2015) Utilization of a high-throughput shoot imaging system to examine the dynamic phenotypic responses of a C4 cereal crop plant to nitrogen and water deficiency over time. J Exp Bot eru526

    Google Scholar 

  • Ortiz-Monasterio R, Sayre K, Rajaram S, McMahon M (1997) Genetic progress in wheat yield and nitrogen use efficiency under four nitrogen rates. Crop Sci 37(3):898–904

    Article  Google Scholar 

  • Parent B, Shahinnia F, Maphosa L, Berger B, Rabie H, Chalmers K, Kovalchuk A, Langridge P, Fleury D (2015) Combining field performance with controlled environment plant imaging to identify the genetic control of growth and transpiration underlying yield response to water-deficit stress in wheat. J Exp Bot 66(18):5481–5492

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Passioura JB (2006) The perils of pot experiments. Funct Plant Biol 33(12):1075–1079

    Article  Google Scholar 

  • Peñuelas J, Filella I (1998) Visible and near-infrared reflectance techniques for diagnosing plant physiological status. Trends Plant Sci 3(4):151–156

    Article  Google Scholar 

  • Peoples M, Freney J, Mosier A, Bacon P (1995) Minimizing gaseous losses of nitrogen. Nitrogen fertilization in the environment, pp. 565–602

    Google Scholar 

  • Plett D, Toubia J, Garnett T, Tester M, Kaiser BN, Baumann U (2010) Dichotomy in the NRT  Gene Families of Dicots and Grass Species. PLoS ONE 5(12):e15289

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Poorter H, Fiorani F, Pieruschka R, Wojciechowski T, Putten WH, Kleyer M, Schurr U, Postma J (2016) Pampered inside, pestered outside? Differences and similarities between plants growing in controlled conditions and in the field. New Phytol 212(4):838–855

    Article  CAS  PubMed  Google Scholar 

  • Quraishi UM, Abrouk M, Murat F, Pont C, Foucrier S, Desmaizieres G, Confolent C, Riviere N, Charmet G, Paux E (2011) Cross-genome map based dissection of a nitrogen use efficiency ortho-metaQTL in bread wheat unravels concerted cereal genome evolution. Plant J 65(5):745–756

    Article  CAS  PubMed  Google Scholar 

  • Rajcan I, Tollenaar M (1999) Source: sink ratio and leaf senescence in maize: II. Nitrogen metabolism during grain filling. Field Crops Res 60(3):255–265

    Article  Google Scholar 

  • Raun WR, Johnson GV (1999) Improving nitrogen use efficiency for cereal production. Agron J 91(3):357–363

    Article  Google Scholar 

  • Ray DK, Mueller ND, West PC, Foley JA (2013) Yield trends are insufficient to double global crop production by 2050. PLoS ONE 8(6):e66428

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Ray DK, Ramankutty N, Mueller ND, West PC, Foley JA (2012) Recent patterns of crop yield growth and stagnation. 3:1293

    Google Scholar 

  • Rebetzke GJ, Chenu K, Biddulph B, Moeller C, Deery DM, Rattey AR, Bennett D, Barrett-Lennard EG, Mayer JE (2012) A multisite managed environment facility for targeted trait and germplasm phenotyping. Funct Plant Biol 40(1):1–13

    Article  Google Scholar 

  • Rebetzke GJ, Jimenez-Berni JA, Bovill WD, Deery DM, James RA (2016) High-throughput phenotyping technologies allow accurate selection of stay-green. J Exp Bot 67(17):4919–4924

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Sadras VO, Richards RA (2014) Improvement of crop yield in dry environments: benchmarks, levels of organisation and the role of nitrogen. J Exp Bot 65(8):1981–1995

    Article  CAS  PubMed  Google Scholar 

  • Sankaran S, Khot LR, Carter AH (2015) Field-based crop phenotyping: multispectral aerial imaging for evaluation of winter wheat emergence and spring stand. Comput Electron Agric 118:372–379

    Article  Google Scholar 

  • Shaw R, Lark RM, Williams AP, Chadwick DR, Jones DL (2016) Characterising the within-field scale spatial variation of nitrogen in a grassland soil to inform the efficient design of in-situ nitrogen sensor networks for precision agriculture. Agr Ecosyst Environ 230:294–306

    Article  Google Scholar 

  • Sinclair TR (1998) Historical changes in harvest index and crop nitrogen accumulation. Crop Sci 38(3):638–643

    Article  Google Scholar 

  • Sun J, Shi S, Gong W, Yang J, Du L, Song S, Chen B, Zhang Z (2017) Evaluation of hyperspectral LiDAR for monitoring rice leaf nitrogen by comparison with multispectral LiDAR and passive spectrometer. 7:40362

    CAS  Google Scholar 

  • Sylvester-Bradley R, Kindred DR (2009) Analysing nitrogen responses of cereals to prioritize routes to the improvement of nitrogen use efficiency. J Exp Bot 60(7):1939–1951

    Article  CAS  PubMed  Google Scholar 

  • Tanger P, Klassen S, Mojica JP, Lovell JT, Moyers BT, Baraoidan M, Naredo MEB, McNally KL, Poland J, Bush DR, Leung H, Leach JE, McKay JK (2017) Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice. 7:42839

    CAS  Google Scholar 

  • Thomas H, Smart CM (1993) Crops that stay green1. Ann Appl Biol 123(1):193–219

    Article  Google Scholar 

  • Ugarte CC, Trupkin SA, Ghiglione H, Slafer G, Casal JJ (2010) Low red/far-red ratios delay spike and stem growth in wheat. J Exp Bot 61(11):3151–3162

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Van Herwaarden A, Farquhar G, Angus J, Richards R, Howe G (1998a) ‘Haying-off’, the negative grain yield response of dryland wheat to nitrogen fertiliser. I. Biomass, grain yield, and water use. Aust J Agric Res 49(7):1067–1081

    Article  Google Scholar 

  • van Herwaarden AF, Angus JF, Richards RA, Farquhar GD (1998b) ‘Haying-off’, the negative grain yield response of dryland wheat to nitrogen fertiliser—II. Carbohydrate and protein dynamics. Aust J Agric Res 49(7):1083–1093

    Article  Google Scholar 

  • Virlet N, Sabermanesh K, Sadeghi-Tehran P, Hawkesford MJ (2016) Field scanalyzer: an automated robotic field phenotyping platform for detailed crop monitoring. Funct Plant Biol 44(1):143–153

    Article  Google Scholar 

  • Watanabe K, Guo W, Arai K, Takanashi H, Kajiya-Kanegae H, Kobayashi M, Yano K, Tokunaga T, Fujiwara T, Tsutsumi N, Iwata H (2017) High-throughput phenotyping of sorghum plant height using an unmanned aerial vehicle and its application to genomic prediction modeling. Front Plant Sci 8(421)

    Google Scholar 

  • Wei D, Cui K, Ye G, Pan J, Xiang J, Huang J, Nie L (2012) QTL mapping for nitrogen-use efficiency and nitrogen-deficiency tolerance traits in rice. Plant Soil 359(1–2):281–295

    Article  CAS  Google Scholar 

  • White JW, Andrade-Sanchez P, Gore MA, Bronson KF, Coffelt TA, Conley MM, Feldmann KA, French AN, Heun JT, Hunsaker DJ (2012) Field-based phenomics for plant genetics research. Field Crops Res 133:101–112

    Article  Google Scholar 

  • Wolt JD (1994) Soil solution chemistry: applications to environmental science and agriculture. Wiley

    Google Scholar 

  • Xu Y, Wang R, Tong Y, Zhao H, Xie Q, Liu D, Zhang A, Li B, Xu H, An D (2014) Mapping QTLs for yield and nitrogen-related traits in wheat: influence of nitrogen and phosphorus fertilization on QTL expression. Theor Appl Genet 127(1):59–72

    Article  CAS  PubMed  Google Scholar 

  • Yang W, Guo Z, Huang C, Duan L, Chen G, Jiang N, Fang W, Feng H, Xie W, Lian X (2014) Combining high-throughput phenotyping and genome-wide association studies to reveal natural genetic variation in rice. Nat Commun 5

    Google Scholar 

  • Yendrek C, Tomaz T, Montes CM, Cao Y, Morse AM, Brown PJ, McIntyre L, Leakey A, Ainsworth E (2016) High-throughput phenotyping of maize leaf physiology and biochemistry using hyperspectral reflectance. Plant Physiol 01447–02016

    Google Scholar 

  • Zhang X, Huang C, Wu D, Qiao F, Li W, Duan L, Wang K, Xiao Y, Chen G, Liu Q, Xiong L, Yang W, Yan J (2017) High-throughput phenotyping and QTL mapping reveals the genetic architecture of maize plant growth. Plant Physiol 173(3):1554–1564

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

Funding was received from the Australian Research Council (LP130101055, IH130200027), and the National Collaborative Research Infrastructure Strategy (NCRIS).

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Authors and Affiliations

  1. School of Agriculture, Food and Wine, Waite Research Institute, University of Adelaide, Adelaide, SA, 5064, Australia

    Nicholas John Sitlington Hansen, Darren Plett, Bettina Berger & Trevor Garnett

  2. The Plant Accelerator, Australian Plant Phenomics Facility, Waite Research Institute, University of Adelaide, Adelaide, SA, 5064, Australia

    Nicholas John Sitlington Hansen, Bettina Berger & Trevor Garnett

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  1. Nicholas John Sitlington Hansen
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Correspondence to Trevor Garnett .

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  1. Biotechnology, Monsanto Company, Chesterfield, Missouri, USA

    Ashok Shrawat

  2. Biotechnology, Monsanto Company, Chesterfield, Missouri, USA

    Adel Zayed

  3. Department of Plant, Soil and Agricultural Systems, Southern Illinois University, Carbondale, Illinois, USA

    David A. Lightfoot

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Hansen, N.J.S., Plett, D., Berger, B., Garnett, T. (2018). Tackling Nitrogen Use Efficiency in Cereal Crops Using High-Throughput Phenotyping. In: Shrawat, A., Zayed, A., Lightfoot, D. (eds) Engineering Nitrogen Utilization in Crop Plants. Springer, Cham. https://doi.org/10.1007/978-3-319-92958-3_7

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