Agronomy Journal最新文献

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.

Providing accurate and precise nitrogen (N) fertilizer recommendations remains a significant challenge. To arrive at a recommendation, researchers traditionally conduct hundreds or thousands of field experiments measuring the grain yield response to varying N fertilizer rates. A statistical model is then fit to the data to calculate the agronomic optimum nitrogen rate (AONR)—the fertilizer N rate that maximizes crop yield. We evaluated the impact of excluding individual fertilizer rates on the AONR estimate and its precision using a mixed-effects quadratic-plateau model on a previously published dataset of 49 maize (Zea mays L.) fertility trials with eight N fertilizer rates. When excluding the control treatment (0 kg N ha⁻¹), the AONR deviated from the AONR calculated using all eight rates from 0 to 59 kg N ha⁻¹ for individual sites—a larger change than when any other N rate was excluded. Excluding the control treatment also caused the greatest loss in the AONR estimate precision, with an average standard error increase of +43% without the control compared to +23% for other N rates. Furthermore, our simulations confirmed these findings and showed the largest losses of accuracy and precision when the control treatment was excluded. These trends in bias and precision persisted with different simulated experimental designs. Our results demonstrate the importance of including the control treatment in N fertility trials designed to estimate the AONR. Therefore, we recommend including a control treatment for a more precise N fertilizer recommendation program, especially in on-farm research.

Future climate change is expected to have serious effects on crop production in northern Shanxi province, China. However, systematic research on the effects of future climate change on the productivity and economic returns of cropping systems is limited. Based on field observations, this study validated the Agricultural Production Systems sIMulator (APSIM) and conducted long-term scenario simulations in northern Shanxi to assess the productivity/economic return of several common cropping systems in six clusters divided by climate conditions. Results indicated the following: (1) The APSIM validation during 2022–2023 presented generally acceptable results, with normalized root mean square error of 6.4%–28.8% and Willmott agreement index of 0.800–0.978 in simulating yield and biomass. (2) Future projections offered higher yields, economic returns, higher rate of actual yield accounting for potential value (RAY), and higher rate of actual economic return accounting for potential value (RAE). (3) The RAY was higher in food crops (87.7%–99.9%) than in forages (61.3%–87.1%), while the rotations with maize (Zea mays L.) produced lower actual yield and RAY. (4) The highest actual economic returns were observed in continuous maize (34.15–45.23 × 10³ RMB 2-year⁻¹), whereas crop–forage rotations were predicted to show lower RAE. (5) High precipitation condition primarily resulted in high actual yield/economic return, while low temperature and radiation were important factors enhancing potential values. Generally, crop–forage rotations were mostly recommended in clusters with at least moderate precipitation, whereas maize and potato (Solanum tuberosum L.)-based systems were expected to thrive under high- and low-precipitation conditions, respectively.

Sugarcane (Saccharum spp. L.) is a globally important crop, and foliar fertilization can enhance plant growth, yield, and stress tolerance. However, the use of multi-nutrient complexes remains underexplored. Here, we investigated the effect of two multi-nutrient foliar fertilizer applications at vegetative stage (N, K, S, B, Cu, Mn, Mo and Zn) and at maturation stage (P, K, Mg, S and B) in 13 field experiments in the early, mid-late, and late sugarcane harvest seasons. Four treatments were compared: (i) no application of multi-nutrient foliar fertilizer (control), (ii) application at the vegetative stage of sugarcane (V), (iii) application at the maturation stage (M), and (iv) application at both the vegetative and maturation stages (VMs). Application resulted in significant gains in all biometric parameters, sugar yield, and theoretically recoverable sugars; the largest increases occurred in VM. Bagasse, straw, and energy production followed the pattern of biometric parameters and increased by averages of 7.9%, 9.7%, and 9.7% compared to the control. In early harvest sugarcane, phosphoenolpyruvate carboxylase, ribulose-1,5-bisphosphate carboxylase-oxygenase, superoxide dismutase, catalase, ascorbate peroxidase, and peroxidase activities and proline content were enhanced in M and VM, whereas hydrogen peroxide (H₂O₂) and malondialdehyde contents decreased in these treatments. In summary, multi-nutrient foliar fertilization at the VMs enhanced sugarcane growth, yield, energy production, and quality across all harvest seasons while improving photosynthetic and antioxidant enzyme activities. The results demonstrate that tailoring multi-nutrient foliar fertilizer application to the specific physiological and nutritional demands of each phenological stage can promote sugarcane development by reducing the production of stress-related molecules and enhancing carbon assimilation.