Core Ideas: Soybean phenology predictions allow producers to schedule management decisions. Phenology can be predicted for a location and maturity group from temperature and photoperiod. Predictions from 2776 locations were generated for the US Midsouth. An interactive map displays predicted dates of flowering, beginning seed fill, and physiological maturity. Eco-physiology models can predict soybean [Glycine max (L.) Merrill] development by describing daily development as a function of temperature, photoperiod, and cultivar sensitivity to these environmental conditions. However, these models require calibration with field data and a skilled user, limiting their agronomic application and adoption. We developed an interactive forecasting tool (SoyStage) using algorithms and previously calibrated coefficients from DSSAT-CROPGRO-Soybean. SoyStage predicts dates of first flower, beginning seed fill, and physiological maturity for emergence dates ranging from 14 March to 27 June in 7-d intervals, maturity groups (MGs) 3.2 to 6.7 in one-half MG increments, and 2776 locations across the US Midsouth based on weather data from 1981 to 2016. Predictions from SoyStage agreed well with field observed phenological stages monitored at 27 site-years (RMSE ≤ 7.2 d). SoyStage can be accessed through the internet, requiring minimal inputs and predicting phenology for a wide range of locations, MGs, and emergence dates.
|Number of pages||4|
|Journal||Agricultural and Environmental Letters|
|State||Published - 2019|
Bibliographical noteFunding Information:
The authors gratefully acknowledge partial support for this research from the United Soybean Board and the Midsouth Soybean Board.
© 2019 The Authors
ASJC Scopus subject areas
- Agronomy and Crop Science
- Soil Science
- Management, Monitoring, Policy and Law