Agronomy Journal最新文献

Although alfalfa (Medicago sativa L.) is one of the most cultivated perennial forage crops in the world, little information exists on the possibility of simulating both its growth and nutritive value. Our objectives were to evaluate and improve the performance of the STICS 10.0.0 model in simulating the biomass and leaf area index (LAI) of alfalfa grown in eastern Canada, and the performance of the equations derived from the Canadian timothy model (CATIMO) to predict three attributes of alfalfa nutritive value: neutral detergent fiber (NDF), neutral detergent fiber digestibility (NDFd), and in vitro true digestibility (IVTD) of the dry matter with STICS outputs. STICS was first calibrated, and its performance to simulate the growth of two alfalfa cultivars in spring and summer was evaluated. Leaf and stem biomass outputs from STICS were then used to calibrate and evaluate the CATIMO nutritive value equations. Twenty-four datasets were used from two cultivars (Oneida VR and Calypso) and five sites in eastern Canada. STICS succeeded in simulating the aboveground biomass (normalized root mean square error [NRMSE] ≤ 27%) and the LAI (NRMSE ≤ 21%). Taproot biomass and aboveground biomass N concentration were also sufficiently well simulated. The new parameterization and modifications of the CATIMO equations allowed the model to accurately simulate the alfalfa nutritive value with NRMSE under or equal to 15%, 11%, and 5% for NDF, NDFd, and IVTD, respectively. STICS, combined with the improved nutritive value equations, is therefore suitable to simulate alfalfa growth and nutritive value in future studies.

Double crops and cover crops can increase cropping intensity and diversity, which are associated with productive, sustainable cropping systems. However, adoption of cover crops remains low. A long-term study with a no-till, sorghum [Sorghum bicolor (L.) Moench]–soybean [Glycine max (L.) Merr.]–wheat (Triticum aestivum L.) rotation intensified with double crops or cover crops was used to evaluate the effect of fallow management and nitrogen fertilizer applications to sorghum on system productivity and net returns. The experiment was established near Manhattan, KS, in 2007 and contained all three crops every year. Treatments included fallow management between wheat and sorghum as whole plots (chemical fallow, double-crop soybean [DSB], summer legume cover crop [SL], summer non-legume cover crop [SNL], winter legume cover crop, and winter non-legume cover crop) and nitrogen fertilizer rates applied to sorghum as subplots (0, 45, 90, 135, and 180 kg ha⁻¹) in a randomized complete block with four replications. Net returns were calculated as gross revenue less input and operating costs. Across three iterations of three cycles of the rotation from 2007 through 2018, total rotation yields increased with greater nitrogen rates, but the amount required to maximize yield varied, ranging from 90 kg ha⁻¹ with DSB and SL to 180 kg ha⁻¹ with SNL. The DSB treatment with 90 kg nitrogen ha⁻¹ applied to sorghum maximized system yields and net returns. Intensifying a cropping system with double or cover crops can increase system productivity and profits, but the system must be managed carefully to achieve positive outcomes.

Soil fertility is often considered solely a function of soil chemical properties but should also encompass aspects of soil physical and biological properties and processes. Statistical distributions of soil properties are not readily available within the southeastern United States but could help target management interventions within common land uses. We determined soil fertility characteristics at 0- to 10-cm, 10- to 30-cm, and 30- to 60-cm depths across a combination of 56 research stations and private farms (n = 614 soil profiles) in coastal, piedmont, and mountain physiographic regions of North Carolina and Virginia. The inherent soil characteristic of sand concentration varied greatly within and among physiographic regions and was a key determinant of soil chemical characteristics, such as cation exchange capacity, soil pH, and base saturation. However, the management factor of land use was also highly influential for many soil properties. On average, soil under no-till compared with conventional-till cropland had 15% greater cation exchange capacity, 27% greater Mehlich-3-extractable Ca, 68% greater soil stability index, and 63% greater soil-test biological activity at 0- to 10-cm depth. There were fewer differences deeper in the profile. Soil under grassland compared with no-till cropland had 39 ± 6% greater extractable potassium (K) throughout the soil profile and 22% greater soil stability index, 68% greater soil-test biological activity, and 8% lower bulk density at 0- to 10-cm depth. Statistical distributions of chemical, physical, and biological properties across a diversity of soil textural conditions and land uses offered a first step toward regional assessments that could be associated with nutrient sufficiency levels and targeted management interventions.

The Smith–Kerns Dollar Spot Model has been used to time preventative fungicide applications to optimize control, but additional uses of the model may expand its impact and further reduce unnecessary fungicide. This project investigates two additional uses of the model, (1) to assess whether early-season fungicide applications allow for increased model thresholds to be used the rest of the season and (2) to determine whether the model can be used to schedule when reductions in fungicide reapplication intervals are most effective. Both studies were conducted in Madison, WI, in 2022 and 2023. In the early-season study, inclusion of an early-season fungicide did not provide significant evidence for increased model thresholds to be used the remainder of the season. In the reapplication interval study, a model threshold of 60% indicated that dollar spot pressure was high, suggesting that reapplication intervals should be shortened. Collectively, these results provide additional uses of the Smith–Kerns Dollar Spot Model and increase the ability for golf course superintendents to implement data-driven strategies in their dollar spot management programs.

Soybean producers in North Carolina have shifted from later to early-maturing varieties (MG II-IV) to increase yield. This shift has coincided with more frequent seed damage and purple seed stain, sometimes resulting in dockage at the elevator. Weather is a major driving factor in seed quality issues, but management strategies may play a role to minimize these seed quality issues; these have not been investigated in North Carolina. To better understand the impact of pest management on seed quality, field trials were conducted over two growing seasons (2021–2022) in three environments across North Carolina. Soybean yield, seed damage, purple seed stain, protein, and oil were collected. Moreover, non-treated controls were scouted at R3 and R5 for each planting date and maturity group combination to determine pest dynamics at each location. While fungicide applications improved yield, pesticide applications did not significantly protect seed quality compared to the untreated control. Continuous scouting and as needed pesticide application can help producers improve soybean yield and protect seed quality.

Automated disease recognition plays a pivotal role in advancing smart artificial intelligence (AI)-based agriculture and is crucial for achieving higher crop yields. Although substantial research has been conducted on deep learning-based automated plant disease recognition systems, these efforts have predominantly focused on leaf diseases while neglecting diseases affecting fruits. We propose an efficient architecture for effective fruit disease recognition with state-of-the-art performance to address this gap. Our method integrates advanced techniques, such as multi-head attention mechanisms and lightweight convolutions, to enhance both efficiency and performance. Its ultralightweight design emphasizes minimizing computational costs, ensuring compatibility with memory-constrained edge devices, and enhancing both accessibility and practical usability. Experimental evaluations were conducted on three diverse datasets containing multi-class images of disease-affected and healthy samples for sugar apple (Annona squamosa), pomegranate (Punica granatum), and guava (Psidium guajava). Our proposed model attained exceptional results with test set accuracies and weighted precision, recall, and f1-scores exceeding 99%, which have also outperformed state-of-the-art pretrain large-scale models. Combining high accuracy with a lightweight architecture represents a significant step forward in developing accessible AI solutions for smart agriculture, contributing to the advancement of sustainable and smart agriculture.

Routine application of topdressing sand is widely practiced to manage putting green surfaces. Topdressing with finer sand and/or at minimal rates can enhance incorporation, greatly reducing the concerns of interference. A 7-year field study investigated the effects of topdressing and cultivation practices on turf quality and surface characteristics of creeping bentgrass (Agrostis stolonifera L.) grown on a sand-based rootzone. A 3 × 2 × 2 factorial design evaluated sand size (medium-coarse, medium-fine, and fine-medium), rate of topdressing during mid-season (0.24 or 0.49 kg m⁻² every 10–14 days), and cultivation (hollow tine cultivation [HTC] plus backfilled with medium-coarse sand or noncultivated). Sand size and topdressing rate significantly affected turf quality, surface volumetric water content (VWC), and surface hardness, with their effects dependent on cultivation. Without HTC, VWC increased as the topdressing sand size became finer. However, when HTC was applied, VWC was not increased by topdressing with medium-fine sand during any year. The practice of HTC also offset the effect of fine-medium sand increasing VWC during the first 4 years, but not Years 5 through 7. Therefore, caution is needed when considering fine-medium sand for topdressing putting greens. Additionally, after 5 years of treatment, the lower topdressing rate led to a wetter surface compared to the higher rate in the absence of cultivation, but not when HTC was applied. The major drawback of HTC was disruption of the turf surface, which resulted in better turf quality on noncultivated plots throughout the trial.

Brinton, W., Basso, B., Millar, N., Covey, K., Bettigole, C., Jagadamma, S., Loeffler, F., Kolodney, S. (2025). Agronomy Journal, 117, e70018.

In the author list, the spelling “Bettigo” was incorrect. The name was corrected to read: “Bettigole, C.” Additionally, at the end, an author was omitted. The full author list was corrected to read: “Brinton, W., Basso, B., Millar, N., Covey, K., Bettigole, C., Jagadamma, S., Loeffler, F., Kolodney, S.”

In the affiliations list, the following affiliation was missing for S. Kolodney:

Department of Plant Science and Landscape Architecture, University of Maryland.

In the Author Contributions list, the following contribution was missing for S. Kolodney:

“Resources”

Finally, in the Acknowledgments section, the author name, Shalyland Kolodey, was mistakenly left in the second sentence. The sentence should read, “We also acknowledge soil sampling by Zoe Pagliaro and lab soil handling by Nicholas Hannon, Jeremiah Vallotton, and Audrey Lafley.”

We apologize for these errors.

This study investigated the impact of climate variability on pigweed (Amaranthus spp.) management in processing tomato (Solanum lycopersicum) fields across northern Israel, which span a climate gradient from semiarid to Mediterranean conditions. Conducted over two consecutive growing seasons (2020–2021), the research aimed to optimize weed management recommendations on a regional scale. The main objectives were to assess treatment timing and intensity and evaluate the efficacy of integrated weed management (IWM) in reducing reliance on herbicides. In 2020, standard chemical treatments—a tank-mix application of metribuzin (175 g a.i. ha⁻¹) and rimsulfuron (25 g a.i. ha⁻¹)—were applied in six field experiments based on cumulative growing degree days (GDD) to account for climate variability among sites. An infestation index was developed to represent the initial state of the fields and the magnitude of the change in infestation. In 2021, IWM was introduced, combining finger weeder cultivation with herbicide treatments at three sites. Results from the first season showed that in early-plantings, a single herbicide application at 150 GDD was as effective as dual applications at 150 and 300 GDD. However, in late plantings, a single application at 300 GDD was ineffective. In the second season, all treatments effectively reduced Amaranthus infestation, with IWM performing comparably to herbicide alone. Importantly, IWM demonstrated the potential to control herbicide-resistant biotypes while minimizing chemical use, making it an environmentally sustainable option. This study underscores the importance of optimized application timing for minimizing unnecessary chemical treatments, offering valuable insights for growers facing future climate challenges.

Controlling weed populations and improving soil health while producing high yields are top priorities of organic crop farmers yet are difficult to achieve simultaneously due to the importance of cultivation for weed control. This study examined whether less frequent cultivation for weed control and the application of carbon-rich soil fertility amendments would enable progress toward those goals during the 3-year transition period to organic production. Standard weed control with cultivation was compared to high-frequency cultivation combined with delayed planting. The standard approach produced 7% higher crop yield over the course of a corn (Zea mays L.)–soybean [Glycine max (L.) Merr.]–small grain rotation, likely due in part to earlier corn and soybean planting. In-field weed counts and weed seedbank germination showed weed populations tended to be lower in the high-frequency cultivation treatment, although patterns were crop specific. Weed populations increased over the 3 years in all treatments, suggesting that additional weed control tactics may have been beneficial. Carbon-rich poultry manure had no significant effects on weed populations, soil health, or crop yield compared to an N-rich organic fertilizer. However, crop yields were positively related to soil health indicators, specifically greater soil total carbon and nitrogen and permanganate oxidizable carbon. The standard weed control approach was advantageous during the organic transition period, but the observed increase in weed populations might become problematic in future years of organic production.