Agronomy Journal最新文献

Pigeonpea productivity can be enhanced by optimally matching the physiology of genotypes to environmental conditions. Information on crop responses to the environment has been lacking for the short-duration pigeonpea genotypes, which are being trialed to develop the Australian pigeonpea industry. The objective of this study was to examine the dynamics of productivity in relation to radiation use efficiency (RUE) and its influence on yield partitioning. Seven field trials, employing three pigeonpea [Cajanus cajan (L.). Millsp.] genotypes, were established at the Gatton Campus, the University of Queensland, Australia, in 2017/2018 and 2018/2019 summer seasons. The study reveals that leaf area development, influenced by growing environment, genotypes, and their interactions, were the key factors for the differences in leaf area duration and RUE. Pigeonpea planted in December had higher seasonal (1.11 g MJ⁻¹) as well as reproductive (0.71 g MJ⁻¹) RUE, resulting in significant differences in total dry matter (TDM) and grain yield (GY). GY was positively associated with seasonal RUE (R² = 0.62), and the relationship was stronger (R² = 0.83) for the reproductive phase (RUE_(R)). The positive association between GY and RUE_(R) suggested that maintaining optimum leaf area during the grain filling period is crucial to achieve higher productivity. Variations in GY were related to amount and rate of TDM accumulation before flowering (R² = 0.51 and R² = 0.53, respectively). Hence, achieving greater TDM before flowering was determinant for achieving higher productivity. The present study provided updated information on dynamics of productivity that will enable more comprehensive modelling of pigeonpea adaptation under subtropical conditions.

Nitrogen (N) fertilizer management in rice (Oryza sativa L.) varies with production practices. In drill-seeded, delayed-flood production systems, the most common production practice in Louisiana N fertilizer is applied at two application timings. The first application timing is just before the permanent flood is established. The second application is at midseason. Nitrogen fertilization before flooding is critical for maximum N uptake, nitrogen recovery efficiency (NRE), and yield. Field experiments were conducted from 2017 to 2020 to evaluate N timing effects on N uptake, NRE, and rice yield. The rice cultivar CL153 was drill-seeded into a stale seedbed at a seed rate of 85 kg ha⁻¹. Fertilizer-N was applied utilizing multiple application timings and rates adding up to a seasonal rate of 155 kg ha⁻¹ across treatments. A single N application 1-day before flooding significantly increased grain yield in all trials, ranging from 8523 kg ha⁻¹ in 2019 to 11,322 kg ha⁻¹ in 2018. Compared to post-flood applications, preflood N increased plant height, N uptake, and NRE. Split N application rates and timings after flooding did not impact rice yield or its agronomics, such as height, aboveground biomass, and time of heading. NRE and yield were significantly correlated (r = 0.805; p < 0.001). Our results indicated that a single N application before flooding has the potential to be an alternative option for N management in the drill-seeded, delayed-flood rice system.

Mali is among Africa's three biggest cotton (Gossypium hirsutum L.)-producing countries, and cotton growing is the principal driving force behind Mali's agricultural sector. Cotton production is rainfed on small-scale family farms as a commercial crop alongside staple crops grown for subsistence. Cultivar choice, planting date, and planting density are critical elements for seed cotton yield that should be optimized. This study aimed to understand the interactions between planting dates and planting densities for the optimal production of four cotton cultivars in Mali. Two trials were set up in two seasons at the Finkolo and N'Tarla research stations. A split-plot design with four replications was used, with planting dates (early and delayed by 3 weeks) as the main plots and planting density (41,666; 83,333; and 166,666 plants/ha) and cultivar (Malian NTA MS334, Togolese STAM 129A, Australian SIOKRA L23, and Brazilian BRS 293) as the subplots. In 2021, seed cotton yield was 1263 kg/ha for early planting versus 361 kg/ha for late planting. Medium and high planting densities produced the same yield level, higher than the low planting density. Regardless of the planting density, early plantings' average capsular weight and seed index were higher than those of late plantings. The African cultivars (STAM 129A and Malian cultivar NTA MS334) were the most productive. Due to significant interactions on fiber percentage and to optimize cotton yields in Mali, planting should be early, with planting densities higher than 41,666 plants/ha, and either of the African cultivars tested should be used.

The United States is experiencing longer crop growing season in most states, which could afford producers the opportunity to diversify into double-cropping (DC) and cover crop systems rather than the predominant summer and winter fallow systems. Thus, this study evaluated DC and cover crops effects on wheat (Triticum aestivum L.), cotton (Gossypium hirsutum L.), and soybean (Glycine max) yield under conventional tillage (CT) and no-tillage (NT). Summer cover crops (SCCs) were sunn hemp (Crotolaria juncea L.) and sorghum sudangrass (Sorghum bicolor), while winter cover crops (WCCs) were Austrian winter pea (Pisum sativum) and wheat. Cropping systems were wheat-fallow (W-F), wheat-cotton (W-C), wheat-soybean (W-S), W-SCC, WCC-C, F-C, WCC-S, and F-S. Tillage effect on crop yields varied across years. In 2021, wheat yield in CT of W-C, W-F, and W-SCC (2831, 2689, and 2646 kg ha⁻¹) significantly differed from NT of W-S (1720 kg ha⁻¹). No significant tillage effect was observed on cotton lint yield between W-C and WCC-C. For soybean, in 2020, the CT of W-S and WCC-S significantly outyielded the NT of W-S and WCC-S. Cropping system effect on wheat yield between W-S and W-SCC (1419 and 1987 kg ha⁻¹) was significant in 2020 due to low stand counts in W-SCC arising from the thick SCC biomass. Cotton lint yield in WCC-C outyielded W-C in all 3 years but was not significant. Soybean grain yield in W-S was consistently higher than in WCC-S, though not significant. Cotton lint and soybean grain yield in the fallow systems were the least. Overall, in a short term, crop yield in DC and cover crop systems were similar.

Surfactants are commonly employed in sand-based turfgrass systems to address soil water repellency, which often results in the formation of preferential flow channels leading to non-uniform wetting patterns. While the influence of soil moisture on nutrient dynamics is well documented, the potential of surfactants to improve N uptake remains poorly understood. A 2-year study was conducted on ‘Celebration’ bermudagrass [Cynodon dactylon (L.)] fairway to better understand the interaction between fertility programs (296 or 586 kg N ha⁻¹ year⁻¹ from ammonium sulfate and 564 kg N ha⁻¹ year⁻¹ primarily from a controlled-release N fertilizer) and surfactant rate and frequency (3.2 L ha⁻¹ every 14 or 28 days, or at 6.4 L ha⁻¹ every 28 days) on turfgrass performance, leaf N content, and soil moisture. Overall, no significant interaction was observed between surfactant treatment and fertility program. During the dry season (November to May), fertility programs influenced turfgrass performance parameters with higher N rates consistently leading to improvements in visual quality, normalized difference vegetation index, percent green cover, and dark green color index; however, no differences were observed during the rainy season (June to October). Surfactants showed no effect on turfgrass performance but led to minimal increase in leaf N content from 3.72% to 3.85%. All surfactant treatments reduced water drop penetration time at 0 cm. Moreover, surfactant treatments applied every 28 days regardless of the rate exhibited a higher volumetric water content compared to those applied every 14 days. Surfactant applications might not be an economically feasible strategy to improve leaf N content in South Florida well-watered bermudagrass fairways.

Dairy manure applications are a common practice in Idaho potato (Solanum tuberosum L.) production, however the impacts on tuber yield and quality are not well understood. Our objectives were to determine (1) how repeated dairy manure applications impact soil properties and plant nutrient uptake, and (2) how these changes influence plant nutrient interactions, tuber yield, and quality. Stockpiled dairy manure was fall-applied over a 6-year period to two adjacent potato production fields in Kimberly, ID. Eight treatments included application frequency (annual and biennial), manure application rate (18, 36, and 52 Mg ha⁻¹ application⁻¹ [dry weight basis]), fertilizer-only, and a non-amended control. Manure treatments were supplemented with fertilizer to prevent nutrient-limiting conditions. Compared to fertilizer treatments, mean soil organic matter, total N, and K were greater for annual manure by 53%, 47%, and 426%, and biennial manure by 24%, 23%, and 199%, respectively. For annual applications only, mean soil nitrate, P, and electrical conductivity were greater than fertilizer treatments by 247%, 431%, and 222%, respectively. Manure promoted P and K luxury consumption with increasing application rate and frequency. Foliage Ca, Mg, Zn, Mn, and Cu correlated negatively against foliage K, potentially due to cation competition and translocation disruption. Annual applications decreased mean tuber specific gravity from 1.078 to 1.073, which may be attributed to saline-sodic conditions and delayed maturity from late-season N mineralization. Our findings suggest that biennial manure applications may prevent specific gravity issues. Agronomic parameters related to N, K, and soluble salts should be closely monitored in these systems.

Small grains provide agronomic benefits that are critical to the success of organic production, and opportunities within local food movements create expanded markets for small grains. However, diversifying rotations with small grains can present challenges related to production, infrastructure, and markets. Here, we draw upon over two decades of integrated research and Extension efforts to support organic small grain production in the Upper Midwest, Northeast, and other regions of the United States where these crops are underutilized. Lessons learned have led to the development of guiding principles for a systems-level approach to support regional organic small grain production. Forming innovative partnerships between farmers, researchers, and end users is critical. This enables research, production, and markets to adjust to local needs, adapt to available infrastructure, and foster local grain economies. The key research challenges that lie ahead are also discussed, especially adapting organic grain production practices to regional conditions and changing climates. The systems-level approach to organic small grain research highlighted here will increase the success and resilience of organic farms across the United States and expand the adoption of organic small grain production.

The study aimed to evaluate the yield performance and stability of 10 Napier grass (Pennisetum purpureum) genotypes. A completely randomized design with three replications was used to assess these genotypes. Genotype and genotype × environment (GGE) interaction and additive main effects and multiplicative interactions (AMMI) biplot models were utilized for analysis. The combined results indicated a significant (p ≤ 0.05) impact on dry matter yield and other agronomic traits. Genotypes and environments contributed to 26.93% and 52.17% of the observed variation in dry matter yield, respectively. The GGE and AMMI biplot models identified promising genotypes based on mean dry matter yield and stability. G3, G1, and G10 genotypes were highlighted as stable with high dry matter yield across different environments compared to others, AMMI analysis also revealed that they had above-average dry matter yield, minimal deviation from the regression line (S2di), and a regression coefficient close to one, which indicated their desirability and stability. Among the 10 genotypes, these Napier grass genotypes were considered the most desirable and stable due to their characteristics. H18 had a longer vector and a small angle with average environmental axis (AEA), making it an ideal environment for selecting superior genotypes accurately. In conclusion, G3 and G1 were identified as ideal genotype candidates for broader utilization under similar environmental conditions.

Photosynthetic traits can sense and signal abiotic stress at early growth stages of mustard [Brassica juncea (L.) Czern & Coss]. The integration stress responses with multiple selection indices can select the fittest/tolerant genotypes. With this goal, a set of 210 diverse mustard genotypes were phenotyped under control and salt-stress (electrical conductivity = 12 dS m⁻¹). Significant dynamic response of the plant to salt stress with reduction for all morpho-physiological traits and genotype × treatment interaction was observed under salinity. A higher accumulation of Na⁺ was recorded in the roots, followed by shoots. A close correspondence between phenotypic coefficient of variation and genotypic coefficient of variation under control and salt stress conditions results in high heritability (h²) in broad sense. A significant negative association between shoot and root Na⁺ content and rate of photosynthesis also indicated that Na⁺ was significantly restricted in the root. This was not found to be efficient because considerable Na⁺ buildup was observed in the shoot. Multiple trait-based indices, such as membership function value of salinity tolerance, classical Smith–Hazel index, factor analysis ideotype–best linear unbiased prediction index, and multi-trait genotype-ideotype distance index, deduced CS 2009-159, CS 2009-420, CS 2009-124, and Swarn Jyoti (RH-9801) are promising for identifying salt-tolerant genotypes that can serve as donors for the development of salt-tolerant cultivars.

The pulse crop lentil (Lens culinaris Medik.) is often grown in crop rotations to provide nitrogen (N) and water benefits for subsequent crops. Lentil yields vary greatly with environmental factors and management. A reliable crop model for lentil could assist efforts to assess the effects of management practices to mitigate environmental stresses and maximize lentil yields. However, few crop models simulate the development and growth of lentil. In this study, we adapted the CSM-CROPGRO model in the Decision Support System for Agrotechnology Transfer to simulate lentil development and growth based on data collected from six experiments conducted from 2001 to 2021 globally. The initial parameter values taken from faba bean (Vicia faba L.) were modified based on reported information and analysis of observed data. Those values were fine-tuned to minimize the gaps between the simulated and observed crop attributes. The model simulated well development stages with root mean square error (RMSE) of 4 days and aboveground biomass with normalized root mean square error (nRMSE ≤ 23%). Seed yields were generally well simulated across experiments in calibration and validation (nRMSE = 19%) datasets, except for overestimation under the humid environment of Quebec in Canada, which may have resulted from excessive vegetative growth. The underlying mechanisms leading to excessive vegetative growth need to be explored further and included in the model for evaluating the adaptability of lentils to specific regions. Overall, the CSM-CROPGRO-Lentil model is ready for simulating lentil production under various scenarios, which may identify ways to improve the productivity and resiliency of cropping systems that include lentil.