Effects of Corn Stalks and Urea on N2O Production from Corn Field Soil

Returning corn stalks to the field is an important and widely used soil management practice which is conducive to the sustainable development of agriculture. In this study, the effects of corn stalks and urea on N2O production in corn field soil were investigated through a 21-day incubation experiment. This study showed that increasing amounts of urea added to soil with a history of corn cultivation leads to increasing overall N2O emissions, by increasing both the intensity and the duration of emissions. Although N2O production was affected primarily by urea-derived NH4+-N and NO3−-N, its main source was native soil nitrogen, which accounted for 78.5 to 94.5% of N2O. Returning corn stalk residue to the field reduced the production of N2O, and the more urea was applied, the stronger the effect of corn residue on reducing N2O emissions. Combining the application of corn stalks and urea could reduce the concentration of NH4+-N and NO3−-N derived from urea, and then reduce the substrate required for N2O production in nitrification and denitrification processes. In addition, the combined application of corn stalks and urea could effectively inhibit the abundance of key N2O-producing genes AOA amoA, nirS and nirK.

Field-Scale Spatial and Temporal Soil Water Variability in Irrigated Croplands

HighlightsThe greatest heterogeneity in soil water was observed at 30-60 cm depth in a corn field and 0-15 cm in a cotton field.Spatiotemporal soil water variability did not increase with increasing soil water in all soil layers in both croplands during the growing season.Water excess and water stress locations were identified in both fields. A single, temporally stable location was identified in each field, which can be used for precise uniform irrigation.Knowledge of variability and stability in soil water can be useful in determining the number and location of sensors to install in crop fields to assist irrigation scheduling decisions.Abstract. This study investigated the spatiotemporal variability and temporal stability of soil water at various depths in two croplands sown in corn and cotton during the 2018 growing season in the Tennessee Valley Region (TVR) of northern Alabama. Classical statistics and relative difference approaches were used to analyze soil water data in this study. In the corn field, the 30-60 cm depth showed the greatest variability, while the cotton field showed the greatest variability at 0-15 cm depth. A decreasing trend was noticed between mean soil water and coefficient of variation for all depths in the cotton field and at 30-60 cm depth in the corn field. However, convex upward, exponential decreasing, or no trends were found between mean soil water and standard deviation at different depths in both fields. The temporal stability analysis showed one representative sensor (S8 in corn and S1 in cotton) for the entire soil profile in both fields. Different statistical tests, i.e., Spearman’s correlation (rs), Nash-Sutcliffe efficiency (NSE), coefficient of determination (R2), etc., were used to reduce uncertainty or increase confidence in the performance of representative sensors. Among various field attributes, topography in corn and soil properties in cotton were determined as significant factors responsible for soil water variability. Crop evapotranspiration (ETc) showed significant negative weak and moderate correlations with soil water in the corn and cotton fields, respectively. However, the mean air temperature showed a significant positive correlation with soil water in the corn field and a significant negative correlation in the cotton field. Solar radiation had a significant negative correlation with soil water in the cotton field and a non-significant correlation in the corn field. Accumulated growing degree days (accGDD) showed a significant negative correlation with soil water in the corn field and a positive correlation in the cotton field. This study gives insights into soil water variability, provides useful information about temporal stability, and identifies significant factors for precision uniform irrigation scheduling. Keywords: Corn, Cotton, Croplands, Growing season, Irrigation, Soil water, Spatial and temporal variability, Temporal stability.