Dry matter accumulation predictors for optimal yield in soybean

Identification of predictors for soybean [Glycine max (L.) Merr.] optimal yield (4500 kg ha(-1) for Louisiana growing conditions) would help farmers identify profitability and aid in determination of environmental factors limiting crop yield. Since environmental influences on yield act mainly through effects on total dry matter (TDM) accumulation during the emergence to R5 period (R5 = start of seed filling), TDM at R1 (first flowering) and TDM at R5 are promising predictors for optimal yield. Thus, the main objective of this study was to determine if TDM(R1) and TDM(R5) can be used as predictors for optimal yield. A secondary objective was to analyze relationships between yield components, TDM, and yield to explain why certain TDM levels can serve as predictors for optimal yield. Data for this study were collected from previous studies containing a variety of cultural treatments (planting dates, row spacings, plant populations, and waterlogging stress) conducted near Baton Rouge, LA (30 degrees N Lat) between 1987 to 1996 and combined to make a single data set. The data represent a wide range of yield, yield component, and TDM values across which regression analyses were conducted to achieve our objectives. The study indicated that 200 g m(-2) and 600 g m(-2) at R1 and R5, respectively, were valid predictors for optimal yield. Environmental effects on yield were regulated by node and reproductive node number per area, pod number per area, and seed number per area. These yield components responded to TDM at R1 and R5 in a fashion similar to that shown for yield, thus supporting the use of TDM at R1 and R5 as predictors for optimal yield.