Light Interception as a Yield-Loss Prediction Tool for Defoliation-Induced Yield Loss in Soybean

Abstract

Predicting yield loss from defoliating agents such as insects, diseases, and hail is an important objective for commercial soybean [Glycine max (L.) Merr.] production. Because of its association with canopy photosynthetic rate, light interception has potential use as a yield‐loss prediction tool for defoliation‐induced yield loss. Our objective was to review data from previous defoliation research to generate regression models relating relative yield [(yielddefol / yieldcontrol) × 100] to reduced relative light interception (LI) [(1 − LIdefol / LIcontrol) × 100]. Regression models were developed for the flowering/pod formation period, and for the early, mid, and late seed filling periods. Highly correlated (R2 = 0.74 to 0.95) linear and quadratic regression models were generated relating relative yield to relative light interception reduction. Validation of these models was done using independent studies from Iowa, Alabama, and Louisiana. Observed and predicted relative yields were highly linearly correlated (R2 = 0.93) in a 1:1 linear relationship having a zero y‐intercept, thus demonstrating that our models were robust yield‐loss prediction tools for defoliation‐induced yield loss. Use of these tools as economic thresholds for insecticide application was also discussed and compared with other economic threshold methods (insect counts and percent defoliation).

Quantitative characterization of proximate sensing canopy traits in the SoyNAM population

“…Previous studies have suggested that soybean grain yield is controlled by the amount of LI during specific developmental growth periods (Board & Kahlon, 2012; Board et al., 2011), and that dissection of highly quantitative traits into more heritable components helps reveal genetic and physiological mechanisms that account for trait variability, as well as their influence on grain yield (Tardieu & Tuberosa, 2010). To evaluate these concepts as they pertain to LI, we divided total CIPAR into two periods encompassing the vegetative (CIPARv) and reproductive (CIPARr) periods of soybean growth.…”

“…Despite the importance of canopy LI for optimizing soybean growth and grain yield, the majority of canopy LI studies have explored grain yield variation in soybean subjected to various planting densities and row spacing configurations, and have done so with great success (Board & Harville, 1992; Board et al., 1992; De Bruin & Pedersen, 2009; Edwards, Purcell, & Karcher, 2005; Purcell et al., 2002; Shibles & Weber, 1965; Wells, 1991). Studies have also shown the ability to develop accurate models using measurements of LI obtained during specific developmental periods to predict grain yield, stress‐induced grain yield reduction, and total dry matter (Board & Kahlon, 2012; Board et al., 2011).…”

Partial and total defoliation during the filling period affected grain industrial and nutraceutical quality in soybean

“…This, in turn, matches the maximum rate of dry matter and the main components of soybean grain accumulation. 6 Noticeably, even when the incident or intercepted solar radiation has been widely used as a strong explanatory variable for defoliation-induced yield loss in soybean, 7,[17][18][19][20] less was explored in terms of grain chemical composition modifications. A few studies have provided some evidence of associations between the incident or intercepted solar radiation and protein, oil, and fatty acid composition, mainly involving shading experiments.…”

“…16 Several research studies have identified that reduced light interception accounted for most of the yield loss in response to defoliation, not only in single-crop 7,17,18 but also in double-crop soybean systems. 19 Moreover, Board et al 20 developed a prediction tool for defoliation-induced yield loss in soybean based on this mechanistic crop parameter. While effects of light interception decrease due to defoliation on soybean grain yield have been widely studied, little is known about its effects on grain chemical composition with special emphasis on nutraceuticals.…”

“…Several research studies have identified that reduced light interception accounted for most of the yield loss in response to defoliation, not only in single‐crop 7,17,18 but also in double‐crop soybean systems 19 . Moreover, Board et al 20 . developed a prediction tool for defoliation‐induced yield loss in soybean based on this mechanistic crop parameter.…”