Winter cover crops (WCCs) provide agronomic and environmental benefits, although their impacts on subsequent crop yields have been reported to vary across regions, soils, or under different farm practices. To address the variability in response, previous qualitative and quantitative reviews have summarized the overall yield effects of WCCs. However, the results from such reviews need constant revision as new research is published and interest in the conservation benefits of WCCs increases. Here, we update a previous meta-analysis of WCC effects on corn (Zea mays) yields, which summarized peer-reviewed research from the United Sates and Canada that was published between 1965 and 2004. Our updated data set (1965 to 2015) comprises 268 observations from 65 studies conducted in different regions of the United States and Canada, and includes information about the management practices utilized (i.e., WCC species, nitrogen [N] fertilization, termination date, tillage, etc.). The effect-size was the response ratio (RR), defined as corn yield following WCCs relative to yield after no cover crop (NC). As in the previous meta-analysis, our results showed a neutral to positive contribution of WCCs to corn yields. On average, grass WCCs neither increased nor decreased corn yields, although corn grown for grain yielded relatively higher than silage corn after grass WCCs. Legume WCCs resulted in subsequent higher corn yields by 30% to 33% when N fertilizer rates were low or the tillage system shifted from conventional tillage (CT) to no-tillage (NT). Mixture WCCs increased corn yields by 30% when the cover crop was late terminated (zero to six days before subsequent corn). Evidence of 65 years of research showed that uncertainty around the RR has decreased and corn yield response to WCCs has stabilized over time. Our results suggest that benefits of WCCs do not result in reduced corn productivity if properly managed.

Despite the active promotion of cover crops as a key conservation practice, their adoption is very limited. We developed a series of partial budgets based on a statewide survey of Iowa farmers to evaluate the changes in net returns resulting from the incorporation of cover crops into a corn or soybean production system. The average net returns to cover crop use for farmers who did not use cover crops for grazing livestock or forage were consistently negative across different planting and termination methods, tillage practices, and experience levels. Only farmers who used cover crops for grazing livestock or forage and received cost-share payments tended to derive net positive returns from cover crop use. Our results can be used as benchmarks for current or potential cover croppers and for ground-truthing agricultural and conservation policy design.

Maize system impacts of cover crop management decisions: A simulation analysis of rye biomass response to planting populations in Iowa, U.S.A.

No abstract

Time to maturity (TTM) is an important trait in soybean breeding programs. However, soybeans are a relatively new crop in Africa. As such, TTM information for soybeans is not yet as well defined as in other major producing areas. Multi-environment trials (METs) allow breeders to analyze crop performance across diverse conditions, but also pose statistical challenges (e.g., unbalanced data). Modern statistical methods, e.g., generalized additive models (GAMs), can flexibly smooth a range of responses while retaining observations that could be lost under other approaches. We leveraged 5 years of data from an MET breeding program in Africa to identify the best geographical and seasonal variables to explain site and genotypic differences in soybean TTM. Using soybean cycle features (e.g., minimum temperature, daylength) along with trial geolocation (longitude, latitude), a GAM predicted soybean TTM within 10 days of the average observed TTM (RMSE = 10.3; x = 109 days post-planting). Furthermore, we found significant differences between cultivars (p < 0.05) in TTM sensitivity to minimum temperature and daylength. Our results show potential to advance the design of maturity systems that enhance soybean planting and breeding decisions in Africa.