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Predicting Soybean Relative Maturity and Seed Yield Using Canopy Reflectance
Author(s) -
Christenson Brent S.,
Schapaugh William T.,
An Nan,
Price Kevin P.,
Prasad Vara,
Fritz Allan K.
Publication year - 2016
Publication title -
crop science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.76
H-Index - 147
eISSN - 1435-0653
pISSN - 0011-183X
DOI - 10.2135/cropsci2015.04.0237
Subject(s) - canopy , normalized difference vegetation index , cultivar , yield (engineering) , maturity (psychological) , biology , reflectivity , agronomy , red edge , vegetation (pathology) , leaf area index , botany , medicine , psychology , developmental psychology , materials science , physics , optics , pathology , metallurgy
Optimized phenotyping, the observable characteristics attributed to the interaction between genotype and the environment, using canopy reflectance measurements may increase the efficiency of cultivar development. The objectives of this study were to: (i) assess canopy reflectance as a tool for predicting soybean maturity and seed yield; (ii) identify specific development stages that contribute to maturity and yield estimation; and (iii) test the stability and utility of maturity and yield estimation models across environments. Canopy reflectance, maturity, and seed yield were measured on 20 maturity group (MG) 3 and 20 MG 4 soybean cultivars released from 1923 to 2010. Measurements were conducted on six irrigated and water‐stressed environments in 2011 and 2012. Cultivar, environment, and cultivar by environment sources of variation were all significant for maturity, yield, and reflectance. Maturity estimation models were created using the visible, red edge, and near‐infrared spectrum as well as normalized difference vegetation index (NDVI) and water index ratios. Yield estimation models using the red edge, near‐infrared, and visible NDVI indices explained much of the variation in yield among genotypes. No significant trends were found for canopy reflectance data collected at specific development stages or in different water regimes contributing to more accurate yield estimation; however, later development stages (R5‐R6) were more accurate for maturity estimation due to spectral data identifying senescing vegetation. Performance of canopy reflectance models for maturity and yield accounted for a significant portion of variability among genotypes for maturity in some environments and for seed yield in most environments.