Agronomy Journal最新文献

Plant growth regulators can enhance row crop productivity and nutrient use efficiency. We conducted 2 year field experiments (2020–2021) in the North Central China Plain (NCP) to evaluate a foliar ethephon-chlormequat chloride (ECC) and nitrogen (N) fertilizer rates (0, 60, 120, and 240 kg N ha⁻¹) on sorghum (Sorghum Bicolor (L.) Moench) yield and nitrogen use efficiencies (NUEs). The control treatment (CK) received a foliar water spray. ECC increased sorghum yield by an average of 4.5%, 5.9%, and 4.7% under 60, 120, and 240 kg ha⁻¹, respectively, relative to CK across 2 experimental years. Moreover, ECC significantly (p < 0.05) increased sorghum root biomass, root to shoot ratio, leaf nitrate reductase activity, chlorophyll content, and nitrogen uptake, thereby improving both nitrogen uptake efficiency and agronomic efficiency. Sorghum yield increased significantly with nitrogen application up to 120 kg ha⁻¹, with no additional yield gain beyond this rate. Nitrogen uptake increased with higher nitrogen rates up to 240 kg ha⁻¹, whereas nitrogen agronomic efficiency declined when nitrogen fertilization exceeding 60 kg ha⁻¹ in both experimental years. Overall, foliar spraying ECC at five-leaf stage, combined with 120 kg N ha⁻¹, achieved high sorghum yield and improved NUE in the NCP.

Zimdahl, R. L. (2025). Survey of deans of agriculture. Agronomy Journal, 117, e70216. https://doi.org/10.1002/agj2.70216

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This study calibrated and validated the Crop Environment Resource Synthesis-wheat model within Decision Support System for Agrotechnology Transfer to assess climate change impacts and evaluate adaptation strategies under various emission scenarios in Central Oromia, Ethiopia. Field data from three consecutive growing seasons (2021/22–2023/24) were used to calibrate the model's genetic coefficients, while 2024/25 data served for validation. Calibration results showed strong agreement with observed data, with normalized root mean square error RMSEn below 10% for all variables. Validation across stations produced R² values between 0.74 and 0.97 and RMSEn from 2.89% to 19.77%, confirming the model's reliability in simulating wheat (Triticum aestivum L.) growth and yield. Using the validated model, climate change impacts were evaluated under baseline (1991–2022) and future scenarios (SSP4.5 and SSP8.5 for the 2050s and 2080s). Simulations indicated notable cultivar- and location-specific yield responses, with most stations showing declines under SSP8.5 by the 2080s. At Degem, yield reductions of 9.75%–38.85% were projected for the Triticum aestivum L. ‘Wane’ cultivar under SSP8.5. Bishoftu showed declines for both Wane and Dendea, particularly under SSP8.5 in the 2080s, while Fitche recorded a 2.66%–6.5% decrease for Wane in the same period. Adaptation analysis under SSP8.5 revealed that delayed planting improved Wane performance at Degem, and late-maturing cultivars were better suited to Degem and Fitche. However, at Bishoftu, neither planting adjustments nor cultivar selection mitigated yield losses, underscoring the need for integrated adaptation approaches. Future studies should incorporate multi-model comparisons, broader adaptation options, and socioeconomic considerations to ensure sustainable wheat production in Central Oromia under climate change.

Pennycress (Thlaspi arvense) and camelina [Camelina sativa (L.) Crantz] are winter oilseed crops that can be implemented in cropping systems of the US Midwest region. Incorporating winter oilseed crops into the cropping system offers ecosystem and productivity benefits when the ground is otherwise fallow. However, adding a new crop into an established cropping system may increase pest or pathogen risk. Pennycress and camelina have been identified as a host and non-host, respectively, of the soybean cyst nematode (SCN, Heterodera glycines), a devastating soybean pathogen. The objective of this experiment was to investigate whether adding winter pennycress or camelina to a soybean–corn rotation affected SCN population density. The experiment was a two-level facorial with a split-plot design that included SCN-susceptible and SCN-resistant soybean varieties as main plots and oilseed crops (pennycress, camelina, and fallow) as subplots conducted at three field locations in Minnesota. Throughout the study, the SCN-susceptible soybean treatment significantly increased SCN population density when compared to the SCN-resistant soybean treatment. There was no measurable effect on SCN population density when camelina or pennycress was included as a winter oilseed crop. The results indicate that camelina or pennycress can be grown as winter oilseed cover crops in the soybean–corn rotations without significant risk to soybean production concerning SCN in Minnesota.

A comprehensive understanding of the interaction between genotype and environment at the local level, coupled with the development of effective management strategies, is imperative to meet the demand for maize (Zea mays) in Santa Catarina, Brazil, and elsewhere. This study estimated maize yield potential, water-limited yield potential, and yield gaps in the state. The study also identified the key biophysical and management factors contributing to yield gaps. The nine buffer zones selected encompass 63% of the total cultivated area dedicated to maize production. To ensure the appropriate balance between the quantity of data utilized and the representativeness of the study area, the Hybrid-Maize model and the method developed by the Global Yield Gap Atlas were employed. In the 2020–2021 and 2021–2022 agricultural years, surveys were conducted in 293 fields. A comparative analysis between high and low yields, in conjunction with regression tree analyses, enables the identification of management practices that warrant investment to elevate average yields and approach values approximating 75% of water-limited yield potential. The results indicated that the yield potential of maize in Santa Catarina is 17.4 Mg ha⁻¹, while the water-limited yield potential is 14.7 Mg ha⁻¹. Therefore, the attainable yield gap was estimated to be 4.0 Mg ha⁻¹. The primary management practices that constrain maize yield were identified, including the population of established plants, the rate of potassium fertilization, the sowing date, and the interval between lime applications. Improvements to these practices will enable an increase of 1.0 million Mg in the current crop area.

Cover crop mixes offer many benefits, including the management of herbicide-resistant weeds. In Southern cropping systems, summer mixes, planted after cash crop harvest and terminated by frost, can be valuable for effective weed management. In this 3-year study, four summer mixes were evaluated for their impact on weed suppression and the establishment of subsequent cash crops. Mix 1 had four grasses; mix 2 had two grasses, one legume, and one non-leguminous broadleaf; mix 3 had two grasses and two legumes; and mix 4 had two legumes and two non-leguminous broadleaves. Mixes 1, 2, and 3 produced the greatest biomass, thus offering the highest post-harvest weed suppression (>80% reduction in weed biomass) and moderate early-summer weed suppression, compared to fallow. The summer grasses sorghum-sudangrass (Sorghum bicolor × S. bicolor var. sudanense) and pearl millet (Pennisetum glaucum L.) were effective contributors to biomass production and weed suppression. Mix 4, with no grass component, still had a 54% reduction in weed biomass compared to the weedy check control. The corn and grain sorghum planted into the terminated legume mix plots showed enhanced growth, with none of the mixes negatively impacting these cash crops. In mixes 2 and 3 that contained legumes, corn plants were 18% taller on average and had 29% greater early-season plant biomass than the weed-free check. Overall, the findings suggest that summer mixtures, particularly those dominated by grasses, provide substantial weed suppression, with grass–legume combinations offering additional benefits to early cash crop performance.

Nitrogen (N) use efficiency on claypan soils is often low; therefore, adopting effective management practices is crucial for increasing corn (Zea mays L.) productivity and maximizing economic returns. The objective of this 4-year field study (2019–2022) was to evaluate the impact of anhydrous ammonia (AA) with or without a nitrification inhibitor (nitrapyrin) on corn productivity, grain quality, partial factor productivity (PFP), and economic returns across different topographic positions (shoulder, backslope, and footslope) within a landscape. Averaged over the years, AA + nitrapyrin treatment had over 6.4% yield advantage compared to AA alone. Grain N removal was 11 kg ha⁻¹ higher and PFP was 3.6 units higher with AA + nitrapyrin compared to AA treatment. Although the expected net returns with nitrapyrin were lower at the footslope and higher at the shoulder position, the incremental yields, economic yield difference, and net economic gains at the footslope were consistently greater than those at the backslope and shoulder. Averaged over site-years, the footslope position generated higher net economic gains ($200.07 ha⁻¹), which were $46.04 and $125.37 ha⁻¹ higher than the backslope and shoulder positions, respectively. These findings emphasize the importance of site-specific N management with nitrapyrin for optimizing yields, enhancing nutrient use efficiency, and maximizing economic returns under varying landscapes.

We applied the reaction norm concept to assess the stability and plasticity of rice (Oryza sativa L.) grain quality traits, specifically for whole milling, chalk, and length. For that, we used 15 days of planting trials from 2021 and 2022, which included 19 commercial varieties evaluated in randomized complete block design with three replications. The analysis was conducted in two phases: first, we obtained adjusted means for each line in each trial, followed by a joint analysis to calculate broad-sense heritability and genotype-by-environment (G × E) interaction. Next, we used Finlay–Wilkinson's regression, genotype-genotype × enviroment (GGE) biplot, and environmental covariates to dissect the G × E. All analyses were performed in R using SpATS, sommer, statgenGxE, metan, EnvRtpe, caret, and snpReady packages. Furthermore, to better understand the G × E effect, we employed linear and exponential regression models. Our results revealed a higher G × E interaction for whole milling and chalk, while grain length showed a lower interaction. Notably, the specific planting days were more critical for quality traits than planting windows. We identified key environmental covariates: potential evapotranspiration and relative humidity from pre-flowering to flowering for whole milling; vapor pressure deficit and relative humidity from flowering to post-flowering for chalk; and wind speed, potential evapotranspiration, and relative temperature anomaly during various growth stages for grain length. These covariates explained ∼76% of the total variation in these traits. Reaction norm curves provided insights into genotype-specific responses to environmental factors, and the narrow-sense heritability of reaction norm components (intercept and slope) revealed “new” heritable traits to be used for stability and adaptability selection.

Despite improvements to grain yield in maize (Zea mays L.) during the Green Revolution, maize remained predominantly tall unlike other major cereals such as wheat (Triticum aestivum L.) and rice (Oryza sativa L.). Although short-statured maize (SSM) has been a topic of interest for many decades, historical efforts to introduce it commercially have remained unsuccessful. Commercial interest in SSM has recently returned mainly due to their lodging resistance, potential for high-density planting, and better in-season accessibility for pest and disease management. In this article, we conduct a systematic review to examine the limitations of past SSM hybrids in regard to genetic backgrounds and traits associated with agronomic performance, and renewed interest in SSM. Our objectives are to (i) identify the limiting factors of early SSM to understand why maize lagged behind in adopting dwarf traits compared to other cereal crops, and (ii) analyze the drivers behind renewed interest in SSM to assess its agronomic significance and potential role in future crop improvement strategies. This study analyses 45 studies and 17 patents and patent applications published between 1965 and 2024. Linear regression models were used to analyze changes in yield, height, harvest index, and lodging over time in both short and tall hybrids. Based on our review results, traits used to reduce height in maize introduced undesirable defects in plant reproductive development and architecture in early SSM hybrids. Modern improvements in SSM hybrid performance are due to less severe dwarfing traits or through concentrating trait effects away from reproductive structures.

Weeding robots are expected to decrease herbicide use on conventional farms and reduce manual labor on organic farms. A multi-objective linear programming model was used to compare the economic, environmental, and social performance of robotic and non-robotic weed control in conventional and organic sugar beet (Beta vulgaris L.) production in Bavaria, Germany. On the conventional farm, the weeding robot generated a mean gross return of €58,612 year⁻¹ compared to €57,728 year⁻¹ when using herbicide spraying. However, the mean return on total costs for the weeding robot was negative (€−2750 year⁻¹) and substantially lower than the €8663 year⁻¹ achieved with herbicide spraying. In organic farming, this technology was more profitable than non-robotic mechanical weeding, generating a mean gross return of €73,098 year⁻¹ and a mean return on total costs of €10,373 year⁻¹. The corresponding figures for non-robotic mechanical weeding were € 59,176 and €7,577 year⁻¹. The carbon emission intensity of sugar beet was comparable between weed control strategies on the conventional farm and marginally lower for robotic weeding on the organic farm. On both farms, autonomous mechanical weeding used more skilled labor due to routine supervision, field-to-field transport, and human intervention requirements. Higher skilled labor time with robotics negatively affected farmers’ work–life balance. Investment cost, supervision and human intervention requirements, technology specialization, and logistics of field operations were identified as the main barriers to adoption of the tested weeding robot. These barriers should be prioritized when developing future autonomous farm equipment.