Soybean (Glycine max [L.] Merr.) is a major crop cultivated in the United States, and it is well adapted to different latitudes and weather conditions. However, grain yield variability of rainfed soybean across early and late sowing dates and among maturity groups (MGs) has not been well evaluated in the southeastern United States. This study uses crop variety trials and soil reports to calibrate the CROPGRO-Soybean model and then assesses yield variability for different sowing dates and MGs across sites within the southeastern United States. After model calibration and evaluation, soybean yield was simulated across 36 yr at eight sites for 16 sowing dates and three cultivars from MGs V, VI, and VII. The results show that the model accurately simulated soybean yield for MGs across different soil types, where the root mean square error (RMSE) across cultivars ranged from 423 to 589 kg ha −1 and across sites ranged from 219 to 684 kg ha −1 . This facilitated the assessment of sowing date effects on yield variability, where simulations showed high yields for sowing dates from April to May, but with higher variability for April sowing dates and low grain yield for sowing dates in July. Our approach successfully illustrates the use of soil reports and crop variety trials to assess the best sowing dates and MGs for soybean production in this region.Abbreviations: DSSAT, Decision Support System for Agrotechnology Transfer; DUL, drained upper limit; EMFL, photothermal days between plant emergence and flower appearance; FLSD, photothermal days between first flower and first seed; FLSH, photothermal days between first flower and first pod; IQR, inter-quartile range; LFMAX, maximum leaf photosynthetic rate; MG, maturity group; PODUR, time required to reach final pod load under optimal conditions; SAT, saturated water-holding limit; SDPDV, average seeds per pod under standard growing conditions; SDPM, photothermal days between first seed and physiological maturity; SFDUR, seed filling duration for a pod cohort at standard growth conditions; SLPF, soil fertility factor; WSS, Web Soil Survey; WTPSD, weight per seed.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.