Agronomy Journal最新文献

Optimizing corn (Zea mays L.) relative maturity (RM) is an important management practice to maximize yield. First frost-free date in spring, last frost-free date in fall, season length, and total growing degree days (GDDs) are important information that can help RM choice. The objectives of this work were to determine optimum corn RM for high yield across the United States and assess growing season length and cumulative GDD based on different frost probability thresholds. Corn yield data from 30 states across the United States between 2014 and 2023 were collected and spatial analysis was performed to predict the optimum RM in unobserved locations. Historical weather data were used to identify growing season characteristics at the county level. The highest yielding RM ranged between 78 units in North Dakota and 118 in the southern states. Anticipated growing season length can be affected by frost definition (minimum temperature threshold) and the degree of risk aversion of farmers, which can affect RM choice. Overall results suggest that informed decision to choose optimum RM requires knowledge of spring first and fall last frost-free dates, growing season length, and total GDD for different frost scenarios. The results in this study can be useful to corn farmers who seek information about optimum RM hybrid in their region and to all farmers who seek information about the growing season characteristics in their region. Future work examining planting date and RM interactions can further aid in optimizing such important decisions.

Cover crop mixtures combine species from different functional groups to optimize specific agronomic goals and address resource concerns. This study investigated four summer cover crop mixtures, specifically examining their establishment, growth, biomass production, and overall species suitability within the mix. Mix 1 was a grass-only blend comprising four grass species. Mix 2 included two grasses, one legume, and one nonlegume broadleaf. Mix 3 consisted of two grasses and two legumes, while Mix 4 contained two legumes and two nonleguminous broadleaf plants. Sorghum-sudangrass (Sorghum bicolor × S. bicolor var. sudanense) and pearl millet (Pennisetum glaucum L.) were the main biomass contributors in Mixes 1, 2, and 3, with an average share of 98.4%, 87.7%, and 81.6%, respectively. Mix 1 had less than 12% plant population establishment due to the poor emergence of foxtail (Setaria italica L.) and proso millet (Panicum miliaceum L.). Mixes 2, 3, and 4 had the greatest plant population densities. Mix 4, which did not include any grass species, produced the least biomass; sunn hemp (Crotalaria juncea L.) was the greatest biomass contributor in this mix, accounting for 71.5% of the biomass. Overall, mixes that contained grasses and legumes performed better in terms of establishment success and biomass production. Soil moisture availability during establishment was a crucial factor for the emergence and establishment success of summer mixes, especially for small-seeded species. Mixes 2 and 3, containing grasses and legumes, produced the greatest biomass and can be a valuable addition to rotations in the southern region.

There is a growing body of research on the impact of climate change on cotton production, yet limited information exists on the specific effects of heat stress on cotton yield parameters. This study conducted a meta-analysis to quantify the impact of heat stress on key cotton (Gossypium) yield parameters, including lint yield, boll weight, boll number, boll retention, and seed yield. A systematic search across ScienceDirect, Web of Science, and Google Scholar yielded 62 articles, of which 43 met the inclusion criteria. Using OpenMEE software, the research applied a random effects model to generate pooled effect estimates at a 95% confidence interval, with subgroup analyses performed to assess variability across key moderators. The results showed a significant overall reduction in all cotton yield parameters due to heat stress. Subgroup analysis revealed that the magnitude of these effects varied depending on factors such as country of study, type of heat stress (day/night and combined), growth stage, and experimental conditions (field vs. controlled environment), with notable heterogeneity. Heat stress significantly reduced cotton lint yield in regions such as the United States and the United Kingdom, whereas China showed no statistically significant effect. These findings underscore the importance of regional climatic conditions and agronomic practices in influencing cotton's response to heat stress. Consequently, further investigation is recommended in regions where significant reductions were observed and in areas with limited empirical data. Expanding research on long-term adaptation strategies, such as heat-tolerant cultivars and optimized management practices, will be critical for mitigating heat stress impacts on cotton production.

Conservation management practices have the potential to mitigate the negative impacts of conventional row crop agriculture on soil health. However, these practices can increase costs without consistent improvements in yield. A field study was conducted to evaluate the ability of different combinations of conservation practices to improve soil health indicators and crop yield after 4 years in a silty Mississippi Delta soil. Treatments included all combinations of the following: (1) till or no-till, (2) winter cover crop (CC; winter pea; Pisum sativum var. arvense) or no cover crop (NC), and (3) monoculture cotton (Gossypium hirsutum L.), monoculture sorghum (Sorghum bicolor), or cotton–sorghum (CotSor) rotation. After 4 years, CC increased soil organic matter by 12% and microbial biomass carbon (MBC) by 16% on average compared to NC, and also enhanced activities linked with organic matter breakdown, phosphorus (P)-cycling, and general hydrolytic activity. Monoculture sorghum and CotSor rotation also increased MBC and soil activities compared to cotton monoculture, likely due to greater sorghum plant residues left behind after harvest compared to cotton. Both CC and rotation consistently increased sorghum yield, while CC effects on cotton yield were inconsistent, and tillage had no impact on yield. These results suggest that sorghum is more responsive to conservation management practices than cotton. Incorporating sorghum in rotation or adding a winter cover crop are both viable options for alleviating the deleterious effects of cotton on soil health indicators, with the potential to improve yields in select crops.

Alfalfa (Medicago sativa L.) is essential for the US livestock industry and provides critical ecosystem services. However, a 30%–50% gap in forage harvested persists between farmers and research fields. This study surveyed 24 farmers in the US Midwest managing 38 alfalfa fields to identify practices that maximize forage harvested. Most fields were seeded in spring under vertical tillage, primarily for haylage. Fields with more than three cuts and those harvested for haylage or silage showed greater forage harvested (yield). Previous crop, type of tillage, interval between cuts, organic management, forage use, manure, sulfur (S), and potassium (K) application in the seeding year were associated with alfalfa forage harvested. Inputs in the established stand, including herbicide, boron (B), and S, further influenced productivity. Conditional inference tree analysis revealed three technological groups based on alfalfa forage harvested and management. Group 1 achieved the greatest forage harvested based on more nutrient inputs, like S, and more than three cuts for haylage and silage. Group 2 had lower forage harvested, relying more on manure than fertilizers, and with similar cutting frequency. Group 3 had the lowest forage harvested, using alfalfa for hay with fewer inputs and longer cutting intervals. Despite a relatively small sample size, these findings emphasize the importance of integrated management strategies in achieving greater alfalfa forage harvested and closing the productivity gap.

Buckwheat (Fagopyrum esculentum Moench) requires minimal agrochemical inputs and delivers grains with a high nutritional profile—the perfect prerequisites for future sustainable farming. However, it is currently consumed and produced in only a few countries. The aim of this study was to investigate the potential to successfully grow buckwheat in Germany and to elaborate first insights for local breeding. Therefore, a total of 33 buckwheat varieties were tested across three locations, 3 years, and two different sowing dates. The average yield was 2.3 t ha⁻¹, ranging from 1.4 to 3.1 t ha⁻¹ across varieties. Similar yields were observed for both early and late sowing dates, and across all tested varieties. All but two of the very late-maturing common buckwheat varieties could be safely harvested in all locations also on the late sowing date. Key prerequisites to establish local breeding were met, including large genetic variation and high heritability for important agronomic traits. In summary, this study highlights the importance of variety selection and targeted breeding focusing on early-maturing buckwheat varieties, paving the way for potential double-cropping systems in Germany that use buckwheat as a second crop and significantly enhance its profitability for farmers.

The effects of biochar and nitrogen (N) fertilization on soil carbon (C) and nitrogen (N) have been primarily studied in topsoil layers (0–30 cm), leaving a gap in understanding their long-term impact on deeper soil layers. This study investigates the effects of biochar (0 (B0) and 9 t ha⁻¹ year⁻¹ (B+)) and nitrogen fertilization (0 (N0) and 300 kg N ha⁻¹ year−1 (N+)) on soil organic carbon (SOC), soil organic nitrogen (SON), microbial biomass carbon, and microbial biomass nitrogen down to 150 cm. The study was conducted over 8 years in a rice field in northwest China. Results showed that biochar application increased total SOC by 27.0% and 12.2%, with and without nitrogen fertilization, respectively. Approximately 43.5%–51.8% of SOC was stored in the top 30 cm, while significant portions were found in deeper layers, indicating substantial carbon movement beyond the surface soil. Biochar also significantly increased SON in the 105- to 150-cm depth, regardless of N fertilization. These results suggest that failing to consider deep soil layers could lead to underestimations of soil C and N storage in paddy systems. The findings highlight the importance of biochar and nitrogen fertilization for improving carbon sequestration and nutrient cycling in rice paddies, offering insights into sustainable soil management practices.

A growing demand for herbal products is an opportunity for US growers to add diversity and high value crops into current rotations. Temperate tulsi (Ocimum × africanum) is a suitable crop for increased domestic production. In this study, we assessed how harvest frequency and harvest method influenced tulsi yield, quality, and total time to harvest. We assessed three distinct methods of harvest: (1) hand harvest, (2) mechanical harvest with a small plot combine, and (3) mechanical harvest with a swather. We paired these harvest methods with two levels of harvest frequency: a single cut per season and a double cut per season. This study was replicated in 2022 and 2023. We found no significant differences in tulsi yield when comparing hand harvest to either of the mechanical methods. Hand harvest took significantly more time compared to both mechanical methods. Quality was measured as eugenol content in dried plant material. Although eugenol means were higher overall in 2023, no clear trends emerged in the effect of harvest method or harvest frequency on eugenol content. Further research should explore how other agronomic practices can affect tulsi quality. The potential extension of this research to “true” tulsi, Ocimum tenuiflorum, and the inclusion of additional agronomic factors could help us better understand and optimize domestic tulsi production.

Soils and forages of Punjab, Pakistan, have mineral concentrations that are marginal for forage plant and animal requirements, and deficiencies of Ca can lead to economic losses. The efficacy of various Ca application methods for improving plant tissue Ca concentrations and forage productivity and nutritional value is not well defined. This field study was conducted in Punjab during 2021 and 2022 with the objective of quantifying the effects of Ca biofortification using seed coating or crop fertilization on forage responses of rhodesgrass (Chloris gayana Kunth.), an important regional forage. Treatments were the factorial combinations of two seed coatings (coated with 2 g CaSO₄ kg⁻¹ seed or non-coated) and nine CaSO₄ basal or foliar applications arranged in a randomized complete block design with three replications. The nine basal/foliar application treatments were no CaSO₄ (control), basal application of 1 Mg ha⁻¹ (B1), basal application of 2 Mg ha⁻¹ (B2), foliar application at 0.5% (F0.5), foliar application at 1% (F1), and B1 + F0.5, B1 + F1, B2 + F0.5, and B2 + F1. Seed coating increased plant height (2%), tillers plant⁻¹ (13%–16%), tillers m⁻² (15%–17%), leaf area (5%–7%), and dry matter harvested (DMH; 9%–13%) over no coating. Tillers plant⁻¹ and tillers m⁻² increased with increasing basal CaSO₄ application rate. Combining greater basal and foliar rates increased plant height (5.8%–8.3%), leaf area (9.6%–10.3%), and DMH (27.0–27.6). Tissue crude protein (33.0%–40.8%), digestibility (2.3%–2.5%), calcium (88%–92%) and sulfur (60%) concentrations also increased. Calcium biofortification using CaSO₄ as a basal and foliar treatment or as seed coating improved rhodesgrass DMH and nutritive value.

Ordóñez, R. A., White, C. M., Spargo, J. T., Kaye, J. P., Ruark, M., Iqbal, J., Shapiro, C. A., Thomason, W. E., Fiorellino, N. M., Thorne, L. A., Shober, A., Grove, J. H., Hirsh, S. M., Weil, R. R., Castellano, M. J., Archontoulis, S. V., Hatfield, J. J., Lee, C. D., Quinn, D. J., … Vyn, T. J. (2025). Delta yield predicts nitrogen fertilizer requirements for corn in US production systems. Agronomy Journal, 117, e70150. https://doi.org/10.1002/agj2.70150

There was an error in Figure 2c and Figure 4. In Figure 2c, the y-axis is labeled “Delta Yield (kg ha⁻¹)” and has been updated to “Delta Yield (Mg ha⁻¹).”

In Figure 4, the x-axis is labeled “Delta Yield (kg ha⁻¹)” and has been updated to “Delta Yield (Mg ha⁻¹).”

We apologize for this error.