U.S. cereal rye winter cover crop growth database.

Winter cover crop performance metrics (i.e., vegetative biomass quantity and quality) affect ecosystem services provisions, but they vary widely due to differences in agronomic practices, soil properties, and climate. Cereal rye (Secale cereale) is the most common winter cover crop in the United States due to its winter hardiness, low seed cost, and high biomass production. We compiled data on cereal rye winter cover crop performance metrics, agronomic practices, and soil properties across the eastern half of the United States. The dataset includes a total of 5,695 cereal rye biomass observations across 208 site-years between 2001-2022 and encompasses a wide range of agronomic, soils, and climate conditions. Cereal rye biomass values had a mean of 3,428 kg ha-1, a median of 2,458 kg ha-1, and a standard deviation of 3,163 kg ha-1. The data can be used for empirical analyses, to calibrate, validate, and evaluate process-based models, and to develop decision support tools for management and policy decisions.

Climate trends and soybean production since 1970 in Mississippi: Empirical evidence from ARDL model.

Studying historical response of crops to weather conditions at a finer scale is essential for devising agricultural strategies tailored to expected climate changes. However, determining the relationship between crop and climate in Mississippi (MS) remains elusive. Therefore, this research attempted to i) estimate climate trends between 1970 and 2020 in MS during the soybean growing season (SGS) using the Mann-Kendall and Sen slope method, ii) calculate the impact of climate change on soybean yield using an auto-regressive distributive lag (ARDL) econometric model, and iii) identify the most critical months from a crop-climate perspective by generating a correlation between the detrended yield and the monthly average for each climatic variable. Specific variables considered were maximum temperature (Tmax), minimum temperature (Tmin), diurnal temperature range (DTR), precipitation (PT), carbon dioxide emissions (CO2), and relative humidity (RH). All required diagnostic-tests i.e., pre-analysis, post-analysis, model-sensitivity, and assessing the models' goodness-of-fit were performed and statistical standards were met. A positive trend in Tmin (+0.25 °C/decade), and a negative trend in DTR (-0.18 °C/decade) was found. Although Tmax, PT, and RH showed non-significant trends, numerical changes were noted as +0.11 °C/decade, +3.03 mm/decade, and -0.06 %/decade, respectively. Furthermore, soybean yield was positively correlated with Tmin (in June and September), PT (in July and August), and RH (in July), but negatively correlated with Tmax (in July and August) and DTR (in June, July, and August). Soybean yield was observed to be significantly reduced by 18.11 % over the long-term and by 5.51 % over the short-term for every 1 °C increase in Tmax. With every unit increase in Tmin and CO2 emissions, the yield of soybeans increased significantly by 7.76 % and 3.04 %, respectively. Altogether, soybeans in MS exhibited variable sensitivity to short- and long-terms climatic changes. The results highlight the importance of testing climate-resilient agronomic practices and cultivars that encompass asymmetric sensitivities in response to climatic conditions of MS.

Dataset of historic and modern bread and durum wheat cultivar performance under conventional and reduced tillage with full and reduced irrigation.

Conservation agriculture (CA) is an agronomic management system based on zero tillage and residue retention. Due to its potential for climate change adaptation through the reduction of soil erosion and improved water availability, CA is becoming more important in many regions of the world. However, increased bulk density and large amounts of crop residues may be a constraint for early plant establishment. This holds especially true under irrigated production areas with high yield potential. Genotype × tillage effects on yield are not well understood and it is unclear whether tillage should be an evaluation factor in breeding programs. Fourteen CIMMYT bread (Triticum aestivum) and thirteen durum (Triticum turgidum) wheat genotypes, created between 1964 and 2011, were tested for yield and agronomic performance at CIMMYT's experimental station near Ciudad Obregon, Mexico, during nine seasons. The genotypes were subjected to different tillage and irrigation treatments which consisted of conventional and permanent raised beds with full and reduced irrigation. The dataset includes traits collected during the growing period (days to emergence, days to flowering, maturity, plant height, NDVI, days from flowering to maturity, grain production rate) and at harvest (yield, harvest index, thousand grain weight, spikes/m², grains/m², test weight) and weather data (daily minimum and maximum temperature, rainfall). Six years of data of 26 genotypes were published along with the Honsdorf et al. (2018) paper in Field Crops Research (DOI: s10.1016/j.fcr.2017.11.011). This updated dataset includes three additional seasons of data (harvest years 2016 to 2018) and an additional bread wheat genotype (Borlaug100).

Ammonia emissions from field-simulated cattle defecation and urination.

Atmospheric ammonia (NH(3)) is a concern because of its environmental impact. The greatest contribution to atmospheric NH(3) comes from agricultural sources. This study quantified NH(3) volatilization from cattle defecation and urination on pasture under field conditions in Auburn, Alabama. Treatments consisted of beef feces, dairy feces, dairy urine, and a control. The experiment was conducted during four seasons from June 2003 to April 2004. Fresh feces or urine was applied onto grass swards, and NH(3) volatilization was measured up to 14 d after application using an inverted chamber method. Dairy urine was the only significant source of NH(3). Ammonia nitrogen (N) loss differed among seasons, ranging from 1.8% in winter to 20.9% during the warmer summer months. Cumulative volatilization was best described in this experiment by the equation % NH(3)-N loss = N(max) (1 - e(-ct))(i). The highest rate of NH(3) volatilization generally occurred within 24 h. This study suggests that NH(3) volatilization from cattle urine on pasture is significant and varies with season, whereas NH(3) volatilization from cattle feces is negligible.