Agronomy Journal最新文献

Optimizing nitrogen (N) management in cotton (Gossypium hirsutum L.) production across diverse environments in the southeastern United States remains a challenge. We examined cotton yield responses to N fertilization on multiple commercial farms with different management histories in four physiographic regions of South Carolina. Field experiments were conducted using a randomized complete block design with four N rates (0, 45, 90, and 135 kg ha⁻¹) replicated three times at 50 trials from 2021 to 2023. Field management varied by previous crop, type of tillage, water regime, and history of conservation practices. Cotton lint yield was responsive to N fertilization in 52% of the trials. Economic optimum N rate (EONR) had an interquartile range of 0–135 kg ha⁻¹, with 68% of trials having values <78 kg ha⁻¹ (below the recommended rate). The physiographic region influenced EONR (p < 0.05), with higher EONR values at Coastal Plains and Sandhills compared to the Piedmont region, reflecting differences in soil types and the history of management. Sites with long-term conservation practices had greater yield without N input, higher relative yields, and lower N factor (fertilizer N required per unit of lint) than conventionally managed sites. These sites exhibited greater residual soil N content, thereby reducing N fertilizer requirements. Current-season management had varying impacts, and tillage primarily influenced how efficiently cotton used N (affecting EONR and N factor), while water regime affected yield potential indices (control, maximum, and profit-maximizing yield) as well as EONR. These findings emphasize the need for site-specific N recommendations that should consider physiographic characteristics, current-season management practices, and the long-term history of conservation practices. This study provides a foundation for developing more sustainable and efficient N management practices for cotton production.

Despite the potential to improve nutrient cycling, weed suppression, and system resilience, mixed-species cover crops remain underutilized in organic irrigated systems. This study evaluated the influence of cover crop diversity and associated weeds on biomass production (both cover crops and weeds), as well as carbon (C) and nitrogen (N) acquisition, and weed suppression. Three summer cover crop–carrot rotation cycles (2018–2019, 2019–2020, and 2021–2022) were established on a clay-textured soil in a 50-ha organic pivot-irrigated field in Alberta. Cover crops included a polyculture (POLY) and monoculture of mustard (MUST; white [Sinapsis alba L.] and brown [Brassica juncea (L.) Czern.]), buckwheat (BWHT, Fagopyrum esculentum Moench), faba bean (FABA; Vicia faba L.), and a no-cover control (CONT). Cover crop performance varied by species and year. POLY consistently produced the highest biomass (up to 2.79 Mg ha⁻¹) and, along with BWHT, achieved the greatest weed suppression (62%–72%), while FABA and MUST were least effective. FABA had the highest N concentration (27–32 g kg⁻¹) and lowest C:N ratios (13–16), whereas BWHT had the highest C:N ratios (21–36). C and N uptake were generally greater in POLY (up to 1.20 Mg C ha⁻¹; 74 kg N ha⁻¹) and lowest in FABA or MUST, with POLY and BWHT accounting for the largest share of total biomass nutrient uptake (53%–69%). Overall, these findings demonstrate that cover crop performance is highly context-dependent, with POLY and BWHT offering more consistent benefits in biomass production, weed suppression, and nutrient acquisition, and highlight the complementary role of weeds in nutrient cycling.

Biomass sorghum [Sorghum bicolor (L.) Moench] is an alternative biofuel feedstock to maize [Zea mays (L.)]. One advantage of biomass sorghum over maize is relatively lower nitrogen (N) requirement and its ability to tolerate late planting or fit into double cropping systems. To evaluate the most economic rate of N (MERN) for biomass sorghum in the Mid-Atlantic region, a 3-year (2017, 2018, and 2019) field trial was conducted at two locations (Holland and Hare) in Southeastern Virginia. Treatments were two planting dates (early [EP] versus late [LP]) and seven N rates (0, 56, 112, 168, 224, 280, and 336 kg ha⁻¹) conducted in six environments. Data on dry matter yield of biomass sorghum, plant height, stem diameter, susceptibility to foliar diseases, and stalk lodging were recorded. Between the two planting dates, EP had 52%, 19%, and 16% higher dry matter, plant height, and stem diameter, respectively, compared to LP. However, LP exhibited lower disease pressure in four of 6 site-years and lodging severity likely in response to weather conditions. Nitrogen rates between 112 and 224 kg ha⁻¹ significantly improved dry matter, plant height, and stem diameter, with lower disease and lodging severity. At the MERN of 123 kg ha⁻¹, dry matter yield (20.66 Mg ha⁻¹), plant height (454 cm), disease (61%), and lodging severity (34%) were least as compared to other treatments. Application of N at 123 kg ha⁻¹ can provide the highest economic return while reducing the potential for N loss in the Mid-Atlantic region.

Alfalfa (Medicago sativa L.) is a perennial legume grown as a forage crop worldwide. More than 3 million ha of forage alfalfa is in production either as monoculture or alfalfa-based mixtures stands in Canada. Future climate change impacts on alfalfa forage production should be investigated for potential adaptation opportunities that can leverage the beneficial climate conditions to improve yields. Our objective is to explore alfalfa growth and production under the projected future climate change in Canada using an ensemble modeling approach. Three crop models were used to simulate alfalfa growth at 61 locations across Canada using climate scenarios from five global climate models under three shared socioeconomic pathways (SSPs). Under SSP3-7.0, temperatures are projected to increase by 1.8°C in 2030s, 3.1°C in 2050s, and 4.4°C in 2070s, with a respective increases of 31, 52, and 75 mm in annual precipitation compared to the baseline (1985–2014). The increased temperatures led to an extended growing season for alfalfa, which enabled additional harvests and shifts in crop growth dynamics. Under rainfed conditions, forage dry matter yield is projected to increase by about 1600 kg ha⁻¹ in 2030s, 3000 kg ha⁻¹ in 2050s, and 3600 kg ha⁻¹ in 2070s averaged across locations. This increase is mainly due to a greater number of harvests and improved photosynthetic efficiency from elevated CO₂ under future climate change. However, at some locations in the Canadian Prairies, rainfed yield gains are considerably smaller due to precipitation deficits incurred under future conditions.

This study evaluated the effects of sowing dates, spacing, and mulching on baby corn (Zea mays L.) production and assessed the predictive performance of the AquaCrop model using field trials conducted during winter and kharif 2022 at Tamil Nadu Agricultural University, Coimbatore. Early sowing (January 21 and June 15) combined with closer spacing (60 × 20 cm) and paddy straw mulching enhanced growth attributes, growth rates, intercepted PAR (>56%), radiation use efficiency (>0.50 g MJ⁻¹) and physiological parameters (photosynthetic rate: 15.5 µmol CO₂ m⁻² s⁻¹; stomatal conductance: 0.34 mol H₂O m⁻² s⁻¹; transpiration rate: 3.82 mmol H₂O m⁻² s⁻¹), resulting in higher total yields despite wider spacing (60 × 30 cm) producing larger cob attributes. The AquaCrop model accurately simulated biomass and yield across planting dates (R² > 0.95). Increased plant density improved leaf area index (3.89 and 4.36 in winter and kharif), contributing to greater productivity. Overall, AquaCrop serves as an effective decision-support tool for optimizing baby corn management under varied field conditions.

Winter wheat (Triticum aestivum L.) growers are exploring intensive management strategies aimed at overcoming yield plateaus and improving profitability. The interactive effects of starter fertilizer (SF) and late-season nitrogen (LN) with multiple fungicide applications under intensive management remain unclear. This study evaluated the influence of fertilizer and fungicide strategies on grain yield, protein content, straw yield, and disease assessment. Treatments were arranged in a full-factorial, randomized complete block design with four replications, including two SF rates, five fungicide timing strategies, and two LN rates applied at Feekes 7. Trials were conducted from 2021 to 2023 in Lansing, MI, following silage corn (SC) or soybean (SB), for 4 site-years. SF increased grain yield by 35% and 34% in SC 2022 and SC 2023, respectively. LN improved grain yield only in 2022, with increases of 14% (SB 2022) and 4% (SC 2022). Grain protein concentration responded to SF × LN interaction by increasing with LN when SF was applied but decreasing with SF alone in SC 2023. Across site-years, LN consistently increased protein content (0.7%–0.8%). Fungicide effects were limited, with FK 5–7, 9, and 10.5.1 treatments increasing straw yield by 50% when combined with LN. Results emphasize the potential for intensive management to effectively narrow yield gaps with SF and LN improving yield and grain protein content, while fungicide benefits were minimal under low disease pressure. Further research with greater disease pressure is needed to refine nutrient–fungicide interactions and optimize management strategies for sustainable yield gains.

The aim of this study was to evaluate the effectiveness of the Agricultural Production Systems sIMulator (APSIM) model in estimating yield and yield gaps for winter-sown wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.) in Alborz Province, Iran. Initially, the APSIM-Wheat and APSIM-Barley sub-models (version 7.1) were parameterized for the target cultivars, and model performance was evaluated under a variety of conditions. Model calibration and validation required meteorological data, regional agronomic management approaches, and cultivar-specific genetic coefficients. These data were gathered over a 4-year period, with both field and on-farm components. Two-year field experiments were conducted to calibrate the model at the Atomic Energy Organization farm (2014–2015) and the University of Tehran's Faculty of Agriculture (2016–2017), using a randomized complete block design with 12 treatments (six wheat and six barley cultivars) and three replications. Under optimal conditions, wheat and barley in Alborz Province might produce average grain yields of 10,800 and 10,350 kg/ha, respectively. The yield gap research found that the wheat yield gap at levels 1–4 was 18.5%, 14.9%, 26.5%, and 18.3%, respectively, while the barley yield gap was 29.5%, 3.1%, 24.0%, and 23.7%. Irrigation schedule, total water use, and sowing date were key management factors that influenced yield gaps. The data indicate that using the best agronomic practices can greatly increase productivity and resource efficiency. Furthermore, the APSIM model has been shown to be an effective tool for crop management prediction, scenario analysis, and informed decision-making.

Efficient nitrogen (N) management is critical for improving nitrogen use efficiency (NUE) and sustaining corn (Zea mays L.) yields. We evaluated summer cover crops planted after winter wheat (Triticum aestivum L.) to quantify biomass, N content, soil N dynamics, and subsequent corn performance under rainfed conditions in eastern Nebraska. Across 2 site-years (2020–2021 and 2023–2024), eight CC treatments were tested, including six legumes, one grass, one legume mixture, and two no-CC controls. Cover crop biomass ranged from 760 kg ha⁻¹ (cereal rye (Secale cereale L.), Austrian winter pea (Pisum sativum arvense L.)) to 8630 kg ha⁻¹ (sunn-hemp (Crotalaria juncea L.), legume mixture). Hairy vetch (Vicia villosa L.) and soybean (Glycine max (L.) Merr.) had high biomass N accumulation (176 and 188 kg N ha⁻¹, respectively) due to biological N-fixation. Hairy vetch significantly increased soil nitrate-N availability by 154% (preplant) and 111% (in-season) compared to the no-N and cereal rye controls. Corn yield improved significantly (p < 0.001) following legume CCs, with hairy vetch, sunn-hemp, and forage-pea (Pisum sativum L.) outperforming other species. Legumes increased corn yield by 2.50 Mg ha⁻¹ (2021) and 2.23 Mg ha⁻¹ (2024) compared to the N control treatment, contributing 29 and 44 kg ha⁻¹ of grain N, respectively. Apparent N credits from legumes ranged from 32 to 99 kg N ha⁻¹. In contrast, cereal rye reduced yield and N uptake, indicating net N immobilization. These results support legume CCs as a viable strategy to enhance NUE in rainfed corn systems.

Summer pak choi (Brassica chinensis L.) farming is difficult due to insect pressure. The preventive and physiological benefits of insect-proof netting with mesh sizes 20, 40, and 80 on pak choi cultivation were investigated in summer. We found that 20, 40, and 80 mesh nets significantly reduced insect activity (p < 0.05). Aphid populations decreased by 50.84% (20-mesh) and up to 80% (40/80-mesh), whereas Pieris rapae and Plutella xylostella infestations were completely eliminated (100% reduction) in 40- and 80-mesh nets. The net treatments increased shoot weight by 63.94%–67.91%, root weight by 52.63%–52.94%, and total biomass by 63.11%–66.67% over the uncovered control. The nets increased chlorophyll content (65.29%–67.25%) and improved antioxidant enzyme activity (superoxide dismutase, glutathione peroxidase: 85.51–104.38 µmol/min/mg protein; catalase: 41.16–55.62 µmol/min/mg protein) (p < 0.05). Magnesium and potassium concentrations increased by 117%–118% and 106%–121% over the uncovered control, respectively. The statistics show that insect-proof nets provide effective protection against key monitored pests and improve physiological performance in summer pak choi cultivation, with the 40-mesh net providing the best overall pest exclusion and growth promotion.

Plant tissue testing is an effective tool for diagnosing crop nutritional status; however, critical tissue-potassium (K) concentrations have not been established for modern cotton (Gossypium hirsutum L.) cultivars. We aimed to define critical leaf- and petiole-K concentrations at various growth stages for optimal cotton production. Nine fertilizer-K rate (0–187 kg K ha⁻¹) trials were conducted in a randomized complete block design on silt loam soils with very low to above optimum soil-test K in Arkansas, during 2023 and 2024. Leaf and petiole samples were collected from first square through the beginning of boll and fiber maturation, to quantify tissue-K concentrations. At maturity, cotton lint yield was measured. Lint yield was significantly affected by K fertilization (p ≤ 0.10) in seven out of nine trials, where the unfertilized control yield was 35%–79% of the yield-maximizing fertilizer-K rates (56, 75, and 112 kg K ha⁻¹). Leaf- and petiole-K concentrations increased with increasing K availability (soil or fertilization). Tissue-K concentrations peaked at first square and declined throughout cotton reproductive development. Critical leaf- and petiole-K concentrations to maximize yield were 11.1 and 47.3 g K kg⁻¹ at first square, 10.3 and 48.0 g K kg⁻¹ at first flower, and decreased to 5.1 and 7.5 g K kg⁻¹ at eight weeks after first flower, respectively. Petiole-K concentrations had a stronger relationship with relative yield than leaf-K (R² range of 0.31–0.65 for petioles and 0.19–0.53 for leaves). Our results suggest petioles are more accurate for monitoring cotton K nutrition, and growth-stage-specific critical K concentrations are key for accurately assessing cotton K nutritional status.