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Modeling Soybean Growth for Crop Management

G. G. Wilkerson, J. W. Jones, K. J. Boote, K. T. Ingram, J. W. Mishoe·1983·Transactions of the ASAE

Abstract

ABSTRACT Asoybean (Glycine max (L.) Merr.) crop growth simulation model (SOYGRO) was developed to aid farm managers in making irrigation and pest management decisions. Non-linear first order differential equations describe dry matter rates of change, accumulation and depletion of protein pools, and changes in shell and seed numbers. Two data sets from defoliation and irrigation experiments were used for calibration and validation of the model. The model responds well to drought and defoliation stresses for two test cases. Sensitivity analyses of SOYGRO revealed that simulated yield was most sensitive to changes in gross photosynthesis and growth respiration. The sensitivity of simulated yield to changes in model parameters was increased by the occurrence of either water or defoliation stress.

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Metadata

Authors
Wilkerson, G. G., Jones, J. W., Boote, K. J., Ingram, K. T., & Mishoe, J. W.
Venue
Transactions of the ASAE
Published
1983
Volume
26
Issue
1
Pages
0063-0073
ISSN
  • 0001-2351 (ISSN-L)
  • 2151-0059
OpenAlex
W2056148320
Cited by
244
References
0
FWCI
7.34
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Modeling Soybean Growth for Crop Management. https://app.cochat.ai/papers/10.13031/2013.33877
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Wilkerson, G. G., Jones, J. W., Boote, K. J., Ingram, K. T., & Mishoe, J. W. (1983). Modeling Soybean Growth for Crop Management. Transactions of the ASAE. https://doi.org/10.13031/2013.33877

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.