Abstract
Farmers in North Dakota and Northern Minnesota did not have a model to predict when their soybean (Glycine max L. Merr.) crop will be mature. Soybean plants need to be mature before the first fall freeze. The objectives of this study were to estimate needed accumulated growing degree days (AGDD) for adapted soybean maturity groups (MG) to reach maturity (R8). Research was conducted during 2007–2012 at northern, central, and southern North Dakota, to develop a model to predict the soybean maturity date based on accumulated GDDs and to verify the model using field research data from 2013 to 2015. Based on 1816 data points a regression analysis was performed which predicted that 1666, 1862, 2030 AGDD (with a 50°F base temperature) were needed to reach maturity for 00.7, 0.4, and 1.0 MG soybean cultivars, respectively.The predicted values were used to create a model that allows producers to select the MG of their cultivar, date of planting, and the nearest North Dakota Agricultural Weather Network (NDAWN) station. The output provides the predicted maturity date, as well as the average first day of occurrence of select threshold temperatures (36°, 32° and 28°F) at 50% probability level. This model will help growers to judge the risks of certain frost occurring before the selected cultivar's projected maturity date. The projected maturity date is based on two parts. The first part is the observed period from the planting date to the date the model is queried and is based on daily maximum and minimum temperatures. The second part is the forecast period that is based on normal (1981–2010 average) daily maximum and minimum temperatures from the queried date through the end of the select growing season. The growing degree days (GDD) values are accumulated from the planting date through the end of season based on these daily maximum and minimum temperatures. Input into the model should be for adapted MG soybean for the region and for planting dates between May 15 and 31. Farmers and agriculturist in North Dakota and northwest Minnesota can use the model before planting to determine if a MG would mature before the frost with varying temperature thresholds and monitor the accumulation of GDD and development of the crop during the season and estimated date of maturity.
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