Corn and Soybean Rotation under Reduced Tillage Management: Impacts on Soil Properties, Yield, and Net Return

A 4-yr field study was conducted from 2007 to 2010 at Stoneville, MS to examine the effects of rotating corn and soybean under reduced tillage conditions on soil properties, yields, and net return. The six rotation systems were continuous corn (CCCC), continuous soybean (SSSS), corn-soybean (CSCS), soybean-corn (SCSC), soybean-soybean-cornsoybean (SSCS), and soybean-soybean-soybean-corn (SSSC). Field preparation consisted of disking, subsoiling, disking, and bedding in the fall of 2005. After the fall of 2006, the raised beds were refurbished each fall after harvest with no additional tillage operations to maintain as reduced tillage system. The surface 5 cm soil from continuous soybean had higher pH than continuous corn in all four years. Unlike pH, total carbon and total nitrogen were higher in continuous corn compared to continuous soybean. Delta 15N tended to be higher in continuous corn compared to continuous soybean. Fatty acid methyl ester (FAME) indicated minor changes in soil microbial community in relation to cropping sequence, however there was a significant shift in rhizosphere community depending on crop. Corn yield increased every year following rotation with soybean by 16%, 31%, and 15% in 2008, 2009, and 2010, respectively, compared to continuous corn. As a result, net returns were higher in rotated corn compared with continuous corn. This study demonstrated that alternating between corn and soybean is a sustainable practice with increased net returns in corn.

Quantifying and Validating Soybean Seed Emergence Model as a Function of Temperature

Developing a model for soybean seed emergence offers a tool producers could use for planting date options and in predicting seedling emergence. In this study, temperature effects on soybean seed emergence were quantified, modeled, and validated. The data for seed emergence model development was generated at varying temperatures, 20°C/12°C, 25°C/17°C, 30°C/22°C, 35°C/27°C, and 40°C/32°C, on two soybean cultivars, Asgrow AG5332 and Progeny P 5333 RY. Time for 50% emergence (t50%) was recorded, and seed emergence rate (SER) was estimated as reciprocal to time at each temperature in both the cultivars. No differences were observed between the cultivars in their response to temperature. A quadratic model (QM) best described the relationship between t50% and SGR and temperature (R2 = 0.93). Two sets of experiments were conducted to validate the model. In Experiment 1, 17 time-series planting date studies with the same cultivars were used by utilizing diurnal and seasonal changes in temperature conditions. In the second experiment, sunlit growth chambers with 3 different day/night temperatures, low—20°C/12°C, optimum—30°C/22°C, and high—40°C/32°C, and 64 soybean cultivars belonging MG III, IV, and V, were used. Air temperature and t50 were recorded, and SGR was estimated in all experiments. No differences were recorded among the cultivars for t50% and SGR, but differences were observed among seeding date and temperature experiments. We tested QM and traditionally used Growing Degree Days models against the data collected in validation experiments. Both the model simulations predictions agreed closely with the observed data. Based on model statistics, R2, root mean square errors (RMSE), and comparison of observations and predictions to assess model performance, the QM model performed better than the GDD model for soybean seed emergence under a wide range of cultivars and environmental conditions.