Evaluating grain yield in spring wheat with canopy spectral reflectance

Crop Science

Volumn 55, Issue 5, 2015, Pages 1881-1890

  Bowman, B C ^a   Chen, J ^a   Zhang, J ^a   Wheeler, J ^a   Wang, Y ^a   Zhao, W ^a   Nayak, S ^a   Heslot, N ^b   Bockelman, H ^c   Bonman, J M ^c  

^a UNIVERSITY OF IDAHO   (United States)

^b Department of Molecular Biology and Genetics   (United States)

^c Small Grains and Potato Germplasm Research Unit   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

TRITICUM AESTIVUM;

EID: 84939556532     PISSN: 0011183X     EISSN: 14350653     Source Type: Journal    
DOI: 10.2135/cropsci2014.08.0533     Document Type: Article

References (49)

1. Aparicio, N., D. Villegas, J. Casadesus, J.L. Araus, and C. Royo. 1999. Spectral vegetation indices as nondestructive tools for determining durum wheat yield. Agron. J. 92:83–91.
2. Araus, J.L. 2002. Plant breeding and drought in C3 cereals: What should we breed for? Ann. Bot. (Lond.) 89:925–940. doi:10.1093/aob/mcf049
3. Araus, J., and J. Cairns. 2014. Field high-throughput phenotyping: The new crop breeding frontier. Trends Plant Sci. 19:52–61. doi:10.1016/j.tplants.2013.09.008
4. Arbuckle, J.G., L.S. Prokopy, T. Haigh, J. Hobbs, T. Knoot, C. Knutson, A. Loy, A.S. Mase, J. McGuire, L.W. Morton, J. Tyndall, and M. Widhalm. 2013. Climate change beliefs, concerns, and attitudes toward adaptation and mitigation among farmers in the Midwestern United States. Clim. Change 117:943–950. doi:10.1007/s10584-013-0707-6
5. Babar, M.A., M.P. Reynolds, M. Van Ginkel, R. Klatt, W.R. Raun, and M.L. Stone. 2006a. Spectral reflectance indices as a potential indirect selection criteria for wheat yield under irrigation. Crop Sci. 46:578. doi:10.2135/cropsci2005.0059
6. Babar, M.A., M.P. Reynolds, M. Van Ginkel, R. Klatt, W.R. Raun, and M.L. Stone. 2006b. Spectral reflectance to estimate genetic variation for in-season biomass, leaf chlorophyll, and canopy temperature in wheat. Crop Sci. 46:1046. doi:10.2135/cropsci2005.0211
7. Babar, M.A., M. Van Ginkel, R. Klatt, B. Prasad, and M.P. Reynolds. 2006c. The potential of using spectral reflectance indices to estimate yield in wheat grown under reduced irrigation. Euphytica 150:155–172. doi:10.1007/s10681-006-9104-9
8. Blackburn, G.A. 1999. Relationships between spectral reflectance and pigment concentrations in stacks of deciduous broadleaves. Remote Sens. Environ. 70:224–237. doi:10.1016/S0034-4257(99)00048-6
9. Brenchley, R., M. Spannagl, M. Pfeifer, G.L.A. Barker, R.D. Amore, A.M. Allen, N. McKenzie, M. Kramer, A. Kerhornou, D. Bolser, S. Kay, D. Waite, M. Trick, I. Bancroft, Y. Gu, N. Huo, M.C. Luo, S. Sehgal, B. Gill, S. Kianian, O. Anderson, P. Kersey, J. Dvorak, W.R. McCombie, A. Hall, K.F.X. Mayer, K.J. Edwards, M.W. Bevan, N. Hall, and R. D’Amore. 2012. Analysis of the bread wheat genome using whole-genome shotgun sequencing. Nature 491:705–710. doi:10.1038/nature11650
10. Cabrera-Bosquet, L., J. Crossa, J. Von Zitzewitz, M.D. Serred, and L. Araus. 2012. High-throughput phenotyping and genomic selection: The frontiers of crop breeding converge genomic selection: A step forward. J. Integr. Plant Biol. 54:312–320. doi:10.1111/j.1744-7909.2012.01116.x
11. Cavanagh, C.R., S. Chao, S. Wang, B.E. Huang, S. Stephen, S. Kiani, K. Forrest, C. Saintenac, G.L. Brown-Guedira, A. Akhunova, D. See, G. Bai, M. Pumphrey, L. Tomar, D. Wong, S. Kong, M. Reynolds, M.L. da Silva, H. Bockelman, L. Talbert, J.A. Anderson, S. Dreisigacker, S. Baenziger, A. Carter, V. Korzun, P.L. Morrell, J. Dubcovsky, M.K. Morell, M.E. Sorrells, M.J. Hayden, and E. Akhunov. 2013. Genome-wide comparative diversity uncovers multiple targets of selection for improvement in hexaploid wheat landraces and cultivars. Proc. Natl. Acad. Sci. USA 110:8057–8062. doi:10.1073/pnas.1217133110
12. Federer, W.T., and D. Raghavarao. 1975. On augmented designs biometrics. Biometrics 31:29–35.
13. Fedoroff, N. V, D.S. Battisti, R.N. Beachy, P.J.M. Cooper, D. A Fischhoff, C.N. Hodges, V.C. Knauf, D. Lobell, B.J. Mazur, D. Molden, M.P. Reynolds, P.C. Ronald, M.W. Rosegrant, P.A. Sanchez, A. Vonshak, and J.K. Zhu. 2010. Radically rethinking agriculture for the 21st century. Science 327:833–834. doi:10.1126/science.1186834
14. Feng, W., Y. Zhu, Y. Tian, W. Cao, X. Yao, and Y. Li. 2011. Monitoring leaf nitrogen accumulation in wheat with hyper-spectral remote sensing. Acta Ecol. Sin. 28:23–32.
15. Feuillet, C., P. Langridge, and R. Waugh. 2008. Cereal breeding takes a walk on the wild side. Trends Genet. 24:24–32. doi:10.1016/j.tig.2007.11.001
16. Fischer, R. 2011. Wheat physiology: A review of recent developments. Crop Pasture Sci. 62:95–114. doi:10.1071/CP10344
17. Fischer, R.A., and G.O. Edmeades. 2010. Breeding and cereal yield progress. Crop Sci. 50:S85–S98. doi:10.2135/cropsci2009.04.0225
18. Foulkes, M.J., G.A. Slafer, W.J. Davies, P.M. Berry, R. Sylvester- Bradley, P. Martre, D.F. Calderini, S. Griffiths, and M.P. Reynolds. 2011. Raising yield potential of wheat. III. Optimizing partitioning to grain while maintaining lodging resistance. J. Exp. Bot. 62:469–486. doi:10.1093/jxb/erq300
19. Graybosch, R.A., and C.J. Peterson. 2010. Genetic improvement in winter wheat yields in the great plains of North America, 1959–2008. Crop Sci. 50:1882–1890. doi:10.2135/cropsci2009.11.0685
20. Gutierrez, M., M.P. Reynolds, and A.R. Klatt. 2010a. Association of water spectral indices with plant and soil water relations in contrasting wheat genotypes. J. Exp. Bot. 61:3291–3303. doi:10.1093/jxb/erq156
21. Gutierrez, M., M.P. Reynolds, W.R. Raun, M.L. Stone, and A.R. Klatt. 2010b. Spectral water indices for assessing yield in elite bread wheat genotypes under well-irrigated, water-stressed, and high-temperature conditions. Crop Sci. 50:197–214. doi:10.2135/cropsci2009.07.0381
22. Hansen, P. 2002. Predicting grain yield and protein content in winter wheat and spring barley using repeated canopy reflectance measurements and partial least squares regression. J. Agric. Sci. 139:307–318. doi:10.1017/S0021859602002320
23. Inoue, Y., and M.S. Moran. 1998. Remote sensing modeling analysis of spectral measurements in paddy field for predicting rice growth and yield based on a simple crop simulation model. Plant Prod. Sci. 1:269–279. doi:10.1626/pps.1.269
24. Li, P., J. Chen, and P. Wu. 2011. Agronomic characteristics and grain yield of 30 spring wheat genotypes under drought stress and nonstress conditions. Agron. J. 103:1619–1628. doi:10.2134/agronj2011.0013
25. Malcolm, S., E. Marshall, M. Aillery, P. Heisey, M. Livingston, and K. Day-rubenstein. 2012. Agricultural adaptation to a changing climate: Economic and environmental implications vary by U.S. region. USDA–ERS, Econ. Res. Rep. No. EER-136. USDA, Econ. Res. Serv., Washington, DC.
26. McCaig, T.N., and I. Romagosa. 1989. Measurement and use of excised-leaf water status in wheat. Crop Sci. 29:1140–1145. doi:10.2135/cropsci1989.0011183X002900050008x
27. Penuelas, J., I. Filella, C. Biel, L. Serrano, and R. Savé. 1993. The reflectance at the 950–970 nm region as an indicator of plant water status. Int. J. Remote Sens. 14:1887–1905. doi:10.1080/01431169308954010
28. Penuelas, J., J. Llusia, J. Pinol, and I. Filella. 1997a. Photochemical reflectance index and leaf photosynthetic radiation-use-efficiency assessment in Mediterranean trees. Int. J. Remote Sens. 18:2863–2868. doi:10.1080/014311697217387
29. Penuelas, J., J. Pinol, R. Ogaya, and I. Filella. 1997b. Estimation of plant water concentration by the reflectance Water Index WI (R900/R970). Int. J. Remote Sens. 18:2869–2875. doi:10.1080/014311697217396
30. Pingali, P.L. 2012. Green revolution: Impacts, limits, and the path ahead. Proc. Natl. Acad. Sci. USA 109:12302–12308. doi:10.1073/pnas.0912953109
31. Prasad, B., B.F. Carver, M.L. Stone, M.A. Babar, W.R. Raun, and A.R. Klatt. 2007a. Genetic Analysis of Indirect Selection for Winter Wheat Grain Yield Using Spectral Reflectance Indices. Crop Sci. 47:1416–1425. doi:10.2135/cropsci2006.08.0546
32. Prasad, B., B.F. Carver, M.L. Stone, M.A. Babar, W.R. Raun, and A.R. Klatt. 2007b. 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
33. Raun, W., J. Solie, and G. Johnson. 2001. In-season prediction of potential grain yield in winter wheat using canopy reflectance. Agron. J. 93:131. doi:10.2134/agronj2001.931131x
34. Ray, D.K., N.D. Mueller, P.C. West, and J.A. Foley. 2013. Yield trends are insufficient to double global crop production by 2050. PLoS ONE 8:E66428. doi:10.1371/journal.pone.0066428
35. Reynolds, M., J. Foulkes, R. Furbank, S. Griffiths, J. K ing, E. Murchie, M. Parry and G. Slafer. 2012. Achieving yield gains in wheat. Plant Cell Environ. 35:1799–1823. doi:10.1111/j.1365-3040.2012.02588.x
36. Reynolds, M., M.J. Foulkes, G.A. Slafer, P. Berry, M.A.J. Parry, J.W. Snape, and W.J. Angus. 2009. Raising yield potential in wheat. J. Exp. Bot. 60:1899–1918. doi:10.1093/jxb/erp016
37. Rostoks, N., L. Ramsay, K. MacKenzie, L. Cardle, P.R. Bhat, M.L. Roose, J.T. Svensson, N. Stein, R.K. Varshney, D.F. Marshall, A. Graner, T.J. Close, and R. Waugh. 2006. Recent history of artificial outcrossing facilitates whole-genome association mapping in elite inbred crop varieties. Proc. Natl. Acad. Sci. USA 103:18656–18661. doi:10.1073/pnas.0606133103
38. SAS Institute. 2013. JMP version 11. SAS Inst. Inc., Cary, NC
39. Stamp, P., and R. Visser. 2012. The twenty-first century, the century of plant breeding. Euphytica 186:585–591. doi:10.1007/s10681-012-0743-8
40. Teal, R., B. Tubana, and K. Girma. 2006. In-season prediction of corn grain yield potential using normalized difference vegetation index. Agron. J. 98:1488–1494. doi:10.2134/agronj2006.0103
41. Tucker, C., and P. Sellers. 1986. Satellite remote sensing of primary production. Int. J. Remote Sens. 7:1395–1416. doi:10.1080/01431168608948944
42. Wei, F., Z. Yan, T. Yongchao, C. Weixing, Y. Xia, and L. Yingxue. 2008. Monitoring leaf nitrogen accumulation in wheat with hyper-spectral remote sensing. Acta Ecol. Sci. 28:23–32. doi:10.1016/S1872-2032(08)60018-9
43. Wright, D., V. Rasmussen, R. Ramsey, D. Baker, and J. Ellsworth. 2004. Canopy reflectance estimation of wheat nitrogen content for grain protein management. GIScience Remote Sens. 41:287–300. doi:10.2747/1548-1603.41.4.287
44. Wright, D., and G. Ritchie. 2003. Managing grain protein in wheat using remote sensing. Online J. Sp. Commun. 3(1992).
45. Van Ginkel, M., and D. Calhoun. 1998. Plant traits related to yield of wheat in early, late, or continuous drought conditions. Euphytica 100:109–121.
46. Xue, L., W. Cao, W. Luo, T. Dai, and Y. Zhu. 2004. Monitoring leaf nitrogen status in rice with canopy spectral reflectance. Agron. J. 96:135–142. doi:10.2134/agronj2004.0135
47. Zhang, J., J. Chen, B.C. Bowman, K. O’Brian, J. Marshall, and J.M. Bonman. 2014. Association mapping of Hagberg falling number in hard white spring wheat. Crop Sci. 54:1243–1252. doi:10.2135/cropsci2013.08.0551
48. Zhao, D., K. Raja Reddy, V.G. Kakani, J.J. Read, and G.A. Carter. 2003. Corn (Zea mays L.) growth, leaf pigment concentration, photosynthesis and leaf hyperspectral reflectance properties as affected by nitrogen supply. Plant Soil 257:205–218. doi:10.1023/A:1026233732507
49. Zhu, Y., X. Yao, Y. Tian, X. Liu, and W. Cao. 2008. Analysis of common canopy vegetation indices for indicating leaf nitrogen accumulations in wheat and rice. Int. J. Appl. Earth Obs. Geoinf. 10:1–10. doi:10.1016/j.jag.2007.02.006