Ground-based digital imaging as a tool to assess soybean growth and yield

Crop Science

Volumn 54, Issue 4, 2014, Pages 1756-1768

  Hoyos Villegas, V ^a,b   Houx, J H ^a   Singh, S K ^a   Fritschi, F B ^a  

^a UNIVERSITY OF MISSOURI   (United States)

^b MICHIGAN STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84903186940     PISSN: 0011183X     EISSN: 14350653     Source Type: Journal    
DOI: 10.2135/cropsci2013.08.0540     Document Type: Article

References (48)

1. Adamsen, F.G., P.J. Pinter, E.M. Barnes, R.L. LaMorte, G.W. Wall, S.W. Leavitt, and B.A. Kimball. 1999. Measuring wheat senescence with a digital camera. Crop Sci. 39:719-724. doi:10.2135/cropsci1999.0011183X003900030019x
2. Araus, J.L., J. Casadesus, and J. Bort. 2001. Recent tools for the screening of physiological traits determinig yield. In: M.P. Reynolds, J.I. Ortiz-Monasterio, and A. McNab, editors, Application of physiology in wheat breeding. CIMMYT, Mexico, DF. p. 59-77.
3. Araus, J.L., G.A. Slafer, M.P. Reynolds, and C. Royo. 2002. Plant breeding and drought in C3 cereals: What should we breed for? Ann Bot 89: 925-940.
4. Araus, J.L., G.A. Slafer, C. Royo, and M.D. Serret. 2008. Breeding for yield potential and stress adaptation in cereals. Crit. Rev. Plant Sci. 27:377-412. doi:10.1080/07352680802467736
5. Ball, R.A., L.C. Purcell, and E.D. Vories. 2000. Optimizing soybean plant population for a short-season production system in the southern USA. Crop Sci 40: 757-764.
6. Berger, B., B. Parent, and M. Tester. 2010. High-throughput shoot imaging to study drought responses. J. Exp. Bot. 61:3519-3528 doi:10.1093/jxb/erq201
7. Boyer, J.S. 1982. Plant productivity and environment. Science 218:443-448. doi:10.1126/science.218.4571.443
8. Buschmann, C., G. Langsdorf, and H.K. Lichtenthaler. 2000. Imaging of the blue, green, and red fluorescence emission of plants: An overview. Photosynthetica 38:483-491. doi:10.1023/A:1012440903014
9. Casadesus, J., Y. Kaya, J. Bort, M.M. Nachit, J.L. Araus, S. Amor, G. Ferrazzano, F. Maalouf, M. Maccaferri, V. Martos, H. Ouabbou, and D. Villegas. 2007. Using vegetation indices derived from conventional digital cameras as selection criteria for wheat breeding in water-limited environments. Ann. Appl. Biol. 150:227-236. doi:10.1111/j.1744-7348.2007.00116.x
10. Cooper, M., S. Rajatasereekul, B. Somrith, S. Sriwisut, S. Immark, C. Boonwite, A. Suwanwongse, S. Ruangsook, P. Hanviriyapant, P. Romyen, P. Porn-uraisanit, E. Skulkhu, S. Fukai, J. Basnayake, and D.W. Podlich. 1999. Rainfed lowland rice breeding strategies for Northeast Thailand II. Comparison of intrastation and interstation selection. Field Crops Res. 64:153-176. doi:10.1016/S0378-4290(99)00057-X
11. Fehr, W.R., C.E. Caviness, D.T. Burmood, and J.S. Penningt. 1971. Stage of development descriptions for soybeans, Glycine-Max (L) Merrill. Crop Sci 11: 929-931.
12. Furbank, R.T., and M. Tester. 2011. Phenomics-Technologies to relieve the phenotyping bottleneck. Trends Plant Sci. 16:635-644. doi:10.1016/j.tplants.2011.09.005
13. Golzarian, M.R., R.A. Frick, K. Rajendran, B. Berger, S. Roy, M. Tester, and D.S. Lun. 2011. Accurate inference of shoot biomass from high-throughput images of cereal plants. Plant Methods 7:2-11. doi:10.1186/1746-4811-7-2
14. Granier, C., L. Aguirrezabal, K. Chenu, S.J. Cookson, M. Dauzat, P. Hamard, J.-J. Thioux, G. Rolland, S. Bouchier-Combaud, A. Lebaudy, B. Muller, T. Simonneau, and F. Tardieu. 2006. PHENOPSIS, an automated platform for reproducible phenotyping of plant responses to soil water deficit in Arabidopsis thaliana permitted the identification of an accession with low sensitivity to soil water deficit. New Phytol. 169:623-635. doi:10.1111/j.1469-8137.2005.01609.x
15. Griffin, J.L. 1980. Quantification of the effects of water stress on corn growth and yield. M.S. thesis. Univ. of Missouri, Columbia. p. 84.
16. Hoyos-Villegas, V., and F.B. Fritschi. 2013. Relationships among vegetation indices derived from aerial photographs and soybean growth and yield. Crop Sci. 53:2631-2642. doi:10.2135/cropsci2013.02.0126
17. Jackson, P., M. Robertson, M. Cooper, and G. Hammer. 1996. The role of physiological understanding in plant breeding; from a breeding perspective. Field Crops Res. 49:11-37. doi:10.1016/S0378-4290(96)01012-X
18. Karcher, D.E., and M.D. Richardson. 2005. Batch analysis of digital images to evaluate turfgrass characteristics. Crop Science Society of America, Madison, WI.
19. Klassen, S.P., G. Ritchie, J.M. Frantz, D. Pinnock, and B. Bugbee. 2003. Real-time imaging of ground cover: Relationships with radiation capture, canopy photosynthesis, and daily growth rate In: Digital imaging and spectral techniques: Applications to precision agriculture and crop physiology. Am. Soc. Agron, Madison, WI. p. 3-14.
20. Lafitte, R.A., A. Blum, and G. Atlin. 2003. Using secondary traits to help identify drought-tolerant genotypes. In: K.S. Fischer, R. Lafitte, S. Fukai, G. Atlin, and B. Hardy, editors, Breeding rice for drought-prone environments. IRRI, Los Baños, Philippines. p. 37.
21. Liu, J.G., and E. Pattey. 2010. Retrieval of leaf area index from top-of-canopy digital photography over agricultural crops. Agric. For. Meteorol. 150:1485-1490. doi:10.1016/j.agrformet.2010.08.002
22. Ludlow, M.M., and R.C. Muchow. 1990. A critical evaluation of traits for improving crop yields in water-limited environments. In: N.C. Brady, editor, Advances in Agronomy. Academic Press, San Diego, CA, p. 107-153.
23. Lukina, E.V., M.L. Stone and W.R. Rann. 1999. Estimating vegetation coverage in wheat using digital images. J. Plant Nut. 22: 341-350.
24. Ma, B.L., L.M. Dwyer, C. Costa, E.R. Cober, and M.J. Morrison. 2001. Early prediction of soybean yield from canopy reflectance measurements. Agron. J. 93:1227-1234. doi:10.2134/agronj2001.1227
25. Mizoue, N., and T. Masutani. 2003. Image analysis measure of crown condition, foliage biomass and stem growth relationships of Chamaecyparis obtusa. For. Ecol. Manage. 172:79-88. doi:10.1016/S0378-1127(02)00281-5
26. Monneveux, P., and J.M. Ribaut. 2006. Secondary traits for drought tolerance improvement in cereals. In: J.M. Ribaut, editor, Drought adaptation in cereals. The Haworth Press, Binghamton, NY. p. 97-143.
27. Monteith, J.L., and C.J. Moss. 1977. Climate and the efficiency of crop production in Britain. Philosophical Transactions of the Royal Society of London. Series B. Biol. Sci. 281:277-294. doi:10.1098/rstb.1977.0140
28. Montes, J.M., A.E. Melchinger, and J.C. Reif. 2007. Novel throughput phenotyping platforms in plant genetic studies. Trends Plant Sci. 12:433-436. doi:10.1016/j.tplants.2007.08.006
29. Osborne. 2005. Using multi spectral imagery to evaluate corn grown under nitrogen and drought stressed conditions J. Plant Nut. 27:1917-1929. doi:10.1081/LPLA-200030042.
30. Paruelo, J.M., W.K. Lauenroth, and P.A. Roset. 2000. Technical note: Estimating aboveground plant biomass using a photographic technique. J. Range Manage. 53:190-193. doi:10.2307/4003281
31. Purcell, L.C. 2000. Soybean canopy coverage and light interception measurements using digital imagery. Crop Sci. 40:834-837. doi:10.2135/cropsci2000.403834x
32. Purcell, L.C., and J.E. Specht. 2004. Physiological traits for ameliorating drought stress. In: H.R. Boerma and J.E. Specht, editors, Soybeans: Improvement, production, and uses. 3rd ed. American Society of Agronomy, Crop Science Society of America, Soil Science Society of America, Madison, WI. p. 569-620.
33. Ray, J.D., R.W. Gesch, T.R. Sinclair, and L.H. Allen. 2002. The effect of vapor pressure deficit on maize transpiration response to a drying soil. Plant Soil 239:113-121. doi:10.1023/A:1014947422468
34. Reynolds, M., and R. Tuberosa. 2008. Translational research impacting on crop productivity in drought-prone environments. Curr. Opin. Plant Biol. 11:171-179. doi:10.1016/j.pbi.2008.02.005
35. Reynolds, M.P., R.M. Trethowan, M. Van Ginkel, and S. Rajaram. 2001. Application of physiology to wheat breeding. In: M.P. Reynolds, J.I. Ortiz-Monasterio, and A. McNab, editors, Application of physiology in wheat breeding. CIMMYT, Mexico, DF. p. 2-10.
36. Richards, R.A. 1996. Defining selection criteria to improve yield under drought. Plant Growth Regul. 20:157-166. doi:10.1007/BF00024012
37. Richardson, M.D., D.E. Karcher, and L.C. Purcell. 2003. Quantifying turfgrass cover using digital image analysis. Crop Sci. 41:1884-1888. doi:10.2135/cropsci2001.1884
38. Rorie, R.L., L.C. Purcell, M. Mozaffari, D.E. Karcher, C.A. King, M.C. Marsh, and D.E. Longer. 2011. Association of "greenness" in corn with yield and leaf nitrogen concentration. Agron. J. 103:529-535.
39. Royo, C., N. Aparicio, D. Villegas, J. Casadesus, P. Monneveux, and J.L. Araus. 2003. Usefulness of spectral reflectance indices as durum wheat yield predictors under contrasting Mediterranean conditions. Int. J. Remote Sens. 24:4403-4419. doi:10.1080/0143116031000150059
40. Sakamoto, T., A.A. Gitelson, A.L. Nguy-Robertson, T.J. Arkebauer, B.D. Wardlow, A.E. Suyker, S.B. Verma, and M. Shibayama. 2012. An alternative method using digital cameras for continuous monitoring of crop status. Agric. For. Meteorol. 154:113-126. doi:10.1016/j.agrformet.2011.10.014
41. SAS. 2003. SAS User's Guide: Statistics, Version 9.1. SAS Institute, Cary, NC.
42. Seul, M., L. O'Gorman, and M.J. Sammon. 2000. Practical algorithms for image analysis: Description, examples and code. Cambridge Univ. Press, Cambridge, UK.
43. Singh, S.K., V. Hoyos-Villegas, J.H. Houx, and F.B. Fritschi. 2012. Influence of artificially restricted rooting depth on soybean yield and seed quality. Agric. Water Manage. 105:38-47. doi:10.1016/j.agwat.2011.12.025
44. SPSS. 1998. Sigma Scan Pro 5.0. SPSS Science Marketing Department, Chicago, IL.
45. Thorpe, K.R., and D.A. Dierig. 2011. Color image segmentation approach to monitor flowering in lesquerella. Industrial Crops Prod. 34:1150-1159.
46. Tsaftaris, S.A., and C. Noutsos. 2009. Plant phenotyping with low cost digital cameras and image analytics. In: I. Athanasiadis, A. Rizzoli, P. Mitkas, and J. Gómez, editors, Information Technologies in Environmental Engineering. Springer, Berlin. p. 238-251.
47. Westgate, M.E., F. Forcella, D.C. Reicosky, and J. Somsen. 1997. Rapid canopy closure for maize production in the northern US corn belt: Radiation-use efficiency and grain yield. Field Crops Res. 49:249-258. doi:10.1016/S0378-4290(96)01055-6
48. Wright, A.D., and M.E. Keener. 1982. A test of a maize growth and development model, Cornf. Agric. Syst. 9:181-197. doi:10.1016/0308-521X(82)90019-1