109-30 Characterizing Soybean Maturity and Seed Yield Using Optimized Phenotyping with Canopy Reflectance.

Poster Number 535

See more from this Division: C01 Crop Breeding & Genetics
See more from this Session: Crop Breeding and Genetics: II (includes student competition)
Monday, November 3, 2014
Long Beach Convention Center, Exhibit Hall ABC
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Brent Christenson1, William T. Schapaugh Jr.1, P.V. Vara Prasad2, Nan An1 and Allan K Fritz1, (1)Kansas State University, Manhattan, KS
(2)Kansas State University, Kansas State University, Manhattan, KS
Genotyping and phenotyping technologies that increase genetic material and efficiency of breeding programs are essential for increased genetic gains. Canopy reflectance measurements may provide a logical solution. The objectives of this study were: 1) to determine if canopy reflectance is useful in characterizing soybean maturity and seed yield; 2) build maturity and yield estimation models for use as screening tools; 3) determine which wavebands and indice combinations contribute most to soybean maturity and yield estimation; and 4) determine how growth stage affects effects maturity and yield estimation modeling. Canopy reflectance, maturity, and seed yield were measured on 20 maturity group III (MGIII) and 20 maturity group IV (MGIV) soybean cultivars released from 1923 to 2010. Measurements were conducted on six irrigated and water-stressed environments in 2011 and 2012. Spectral band regions significantly contributing to seed yield estimation were selected through partial least squares regression. Maturity and yield estimation models were created using selected band regions and vegetation indices calculated from those band regions. Significant differences were detected between cultivars, environments, and cultivar × environment interactions for maturity, yield, and band regions. Maturity estimation models were created using the visible, red edge, and near-infrared portions of the spectrum as well as NDVI and water index ratios. Yield estimation models using the red edge and near-infrared portions as well as the visible NDVI indices, explained much of the variation in seed yield among genotypes. No differences were detected between waveband and indice created models for goodness of fit on validation data. No significant trend was found for specific growth stages contributing to yield estimation modeling or water regimes; however, later growth stages and environmental means were more accurate for maturity estimation than individual observations. Maturity and seed yield estimation models using canopy reflectance measurements may be a useful selection tool in breeding programs.
See more from this Division: C01 Crop Breeding & Genetics
See more from this Session: Crop Breeding and Genetics: II (includes student competition)