Agrosystems, Geosciences & Environment最新文献

Estifanos, F., Getu, E., Beyene, D., Habtegebriel, M. H., & Fenta, B. A.(2025). Grain yield stability by different statistical models in small seeded common bean (Phaseolus vulgaris L.) genotypes at diverse agroecologies of Ethiopia. Agrosystems, Geosciences & Environment, 8, e70253. https://doi.org/10.1002/agg2.70253

There was a grammatical error in the title of the article—“acroecologies” was mistakenly used instead of “agroecologies.” This has now been corrected in both the title and in the How to Cite section. The correct title is “Grain yield stability by different statistical models in small seeded common bean (Phaseolus vulgaris L.) genotypes at diverse agroecologies of Ethiopia.”

We apologize for this error.

Knowing the most yield-limiting soil nutrient is crucial for closing the yield gap in all crop production systems. The proper supply of balanced nutrients is essential for maximizing the production of onions and tomatoes. The study was conducted to determine the response of onion and tomato to the omission of different nutrients in their growth and yield under open-field conditions at Raya Kobo District during the 2020/21 growing season, under irrigation. The experiment was laid out in the Randomized Complete Block Design (RCBD) with three replications. A soil sample was taken using an auger before planting for the analysis of the physicochemical properties of the soil. Analysis of variance was computed using R software. The analysis result showed that statistically, the lowest marketable yield of onion was recorded from the omission of nitrogen and the control treatment. In contrast, the highest total unmarketable yield of onion was recorded from the control treatments. Similarly, the combined analysis result for tomato showed that the highest marketable yield was recorded from boron-omitted plots, which significantly differs from N omitted and control treatments but not significantly from others. In contrast, the lowest total marketable yield was recorded from the control and N-omitted treatments. There was also a substantial and positive correlation between marketable yield and the number of clusters per plant and the number of fruit per cluster (p < 0.01). The analysis of variance indicates that N was the most yield-limiting nutrient for both onion and tomato production, more than any other nutrient. This study was conducted to determine which nutrient was yield-limiting and did not address what amount was needed. Therefore, optimum fertilizer rate determination on the yield-limiting nutrient should be conducted.

The use of carbon-based biostimulants (e.g., humic acid [HA] and molasses/yeast extract [MYE]) to enhance grain yield and/or quality of maize (Zea mays L.) and soybean [Glycine max (L.) Merr.] is increasing. The objectives of this study were to (1) determine if MYE or HA use can consistently influence grain yield and quality of maize and soybean across site-years and (2) ascertain if these applications are profitable. Treatments consisted of an untreated control and two commercially available products, one MYE and one HA, applied as either a broadcast soil application or to the seed furrow at planting of maize and soybean in 2020, 2021, and 2022. Maize yield was higher with in-furrow applications compared to preplant broadcast applications, culminating in a 3-year average yield increase of 310 (HA) or 370 (MYE) kg ha⁻¹ and respective return on investment of $29 or $63 ha⁻¹. Maize grain protein concentration increased with both the broadcast HA (+1.7 g kg⁻¹) and in-furrow MYE (+1.8 g kg⁻¹) applications, netting an increase in protein production of 40 and 50 kg ha⁻¹, respectively. Conversely, there were no consistent effects of HA or MYE applications on soybean grain yield or quality, netting an average loss of $51 ha⁻¹. These data suggest that soil-applied MYE or HA can increase grain yield, protein production, and profitability of maize but did not have a measurable agronomic or economic value when applied to soybean grown under the non-stressed field conditions observed here.

Albrecht, K. A.,Contreras-Govea, F. E., Munaiz, E. D., Bures, E. J., & Arriaga, F. J. (2025). Performance of drought-tolerant maize for silage or grain in conventional and Kura clover perennial groundcover cropping systems. Agrosystems, Geosciences & Environment, 8, e70255.https://doi.org/10.1002/agg2.70255

The affiliation for co-author Eduardo D. Munaiz was incomplete. The original affiliation is listed as “UniLaSalle, College of Agrosciences, Beauvais, France.” It has now been updated to “UniLaSalle, College of Agrosciences, AGHYLE UP 2018.C101, Beauvais, France.”

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With the increasing availability of soil water sensing technologies for irrigation management, it is essential to compare sensor options in production field settings. In this study, four soil water sensors—CropX, FieldNet with Watermark sensors, Valley Aqua Trac Lite using Sentek probe, and Aqua Trac Pro with Watermark sensors—were compared with Acclima TDR-310H (where TDR is time domain reflectometry) at four depths during the 2021–2023 growing seasons in three production fields in southeastern North Dakota. The Acclima sensor was calibrated in the same fields where the sensors were installed and was considered the reference standard for comparison with the other sensors. Soil water characteristic curves were developed to convert soil water potential from Watermark sensors from FieldNet and Valley Aqua Trac Pro systems to volumetric water content for comparison to other sensors. Overall, Aqua Trac Lite and CropX had mixed results at all depths (root mean square error [RMSE] typically above 0.05 cm³ cm⁻³). Lindsay and Aqua Trac Pro had better (smaller) RMSE across depths at sites 1 and 3 compared to CropX and Aqua Trac Lite. As expected, measured soil water contents varied over time for all sensors (i.e., significant main effect for timestamp [p < 0.05]). However, the sensor type's effect on θ_v was consistent across all 3 years (i.e., main effect for sensor type [p < 0.05] but there was no interaction with timestamp [p > 0.05]). These results will help farmers and crop consultants understand sensor performance when selecting soil water sensors for irrigation management.

Maintaining soil fertility and enhancing food production on smallholder farms in Ethiopia remain a major challenge due to severe nutrient depletion caused by continuous cropping with minimal external nutrient inputs. In this context, a field study was conducted on Nitisols over two consecutive cropping seasons (2022–2023) across four locations to evaluate the effects of combining bio-slurry with inorganic fertilizer on selected soil chemical properties, wheat yield, and economic feasibility. The experiment consisted of 11 treatments comprising sole and integrated applications of liquid bio-slurry, dry bio-slurry, vermicompost, and nitrogen fertilizer from urea. Treatments were arranged in a randomized complete block design with three replications. The results showed that the integrated use of bio-slurry with inorganic fertilizer significantly improved soil chemical properties, wheat yield, yield attributes, and overall economic profitability. The combined treatments increased grain yield by 84%–102% compared to the untreated plot, with the highest yield (3835.2 kg ha⁻¹) achieved with 50% N from urea and 50% N from liquid bio-slurry. Specifically, 75% N from urea combined with 25% N from liquid bio-slurry produced the highest grain yields in Hula and Basoliben, while 100% N from urea supplemented with 25% N from liquid and dry bio-slurries provided the maximum yields in Welmera and Ejere districts, respectively. In conclusion, the integrated application of bio-slurry and inorganic fertilizer enhances soil chemical properties, improves wheat yield and its components, and offers a promising approach for sustainable intensification of smallholder wheat production in Nitisols of the study areas and similar agro-ecologies.

Reduced tillage (RT) is a common conservation agriculture practice, generally regarded to be a valuable greenhouse gas (GHG) mitigation approach through increasing soil carbon (C) stocks. However, direct GHG measurements from RT compared to conventional tillage (CT) treatments can vary greatly depending on site-specific soil properties and management practices. The objective of this study was to evaluate the short-term effects of RT on soil-to-atmosphere carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O) fluxes and emissions, global warming potential (GWP), yield, and emissions intensity (EI) throughout the 2024 soybean (Glycine max) growing season in a southeast Arkansas production field. Bulk density was lower (p < 0.05) in the CT (1.29 g cm⁻³) than in the RT (1.44 g cm⁻³) treatment at the beginning of the growing season, but the greater bulk density in the RT treatment did not result in a change in yield compared to CT. There was no difference in CO₂ fluxes between tillage treatments on any measurement date. Methane fluxes from CT were greater (p < 0.05) than from RT on four out of seven measurement dates. Nitrous oxide fluxes were greater (p < 0.05) from CT than RT and greater from RT than CT on four out of eight measurement dates each. Season-long CO₂, CH₄, and N₂O emissions and EI, as well as GWP, did not differ (p > 0.05) between RT and CT. Results showed that more continuous RT practices are needed to develop a residue layer capable of affecting GHG emissions.

The golf industry is undergoing a technological transformation with the integration of autonomous solutions for turf maintenance. The implementation of autonomous mowers (AMs) offers the potential for maintaining low cutting heights at high frequencies, thereby reducing soil compaction and labor requirements. In this case study conducted at Montecchia Golf Course in Italy, a comparative analysis was performed between AMs set to work with a daily mowing frequency and reel mowers set to work two times per week at 16 mm mowing height focusing on turf quality, color, normalized difference vegetation index, root growth, and soil moisture, temperature, and surface hardness. Economic and environmental evaluations, including cost analysis and local CO₂ emissions, were also taken into account to assess the two mowing managements. Results indicate that although the reel mower exhibited superior turf quality in May, July, August, and September and turf color during all the study period (May, June, July, August, and September), AMs maintained acceptable standards while providing significant cost and environmental advantages, notably reduced CO₂ emissions. This research supports informed decision-making for turf managers contemplating the adoption of autonomous mowing technology.

The composition and breakdown paths of urea ammonium nitrate (UAN) and urea are different, but there is limited information on how soil properties relate to ammonia volatilization loss from surface-applied, unincorporated UAN and urea on various soils. Controlled environment incubation experiments were conducted to evaluate ammonia volatilization potential of commonly used urea-containing fertilizers, and to correlate these losses to selected soil properties. A completely randomized design with four replicates was used to evaluate and correlate ammonia loss from urea and UAN applied onto eight soils at a rate of 134 kg N ha⁻¹. Urea was more susceptible to ammonia loss (21% of applied N) than UAN (3.3% of applied N) in soils with pH < 7. In contrast, the losses from UAN were either higher or comparable to urea for soils with pH > 7. A significant and strong relationship was evident between ammonia loss from UAN and soil pH (R² = 0.84), soil organic matter (R² = 0.65), clay content (R² = 0.69), and container capacity (R² = 0.90). In contrast, the loss relationships observed for the urea and these properties were insignificant. Stepwise regression analysis identified clay content and soil pH as the most influential factors affecting ammonia loss from both urea and UAN applications. In conclusion, high initial soil pH significantly increases ammonia loss for surface-applied UAN but not for urea, suggesting that different soil management strategies may be needed depending on the N fertilizer source used.

Precise nondestructive methods for monitoring soil water content (SWC) are essential for maintaining plant growth and metabolic activity. In this study, an inductance-based monitoring system was developed using a solenoid-coil sensor for continuous in situ SWC measurements. Three plant species, Melissa officinalis L., Ficus benghalensis L., and Podocarpus macrophyllus (Thunb.) Sweet, were selected as the experimental plants based on their distinct leaf morphologies and stomatal traits. In the control experiments, the inductance variation showed a strong linear correlation with soil moisture meter-based SWC (r² = 0.900, p < 0.001). When the system was applied to live experimental plants, plant species-specific differences in water consumption rates were monitored. The system showed a strong relationship between photosynthetic efficiency (Fv/Fm) and the inductance-based SWC. These results indicate that the inductance measurement system supports rapid, reliable, and noninvasive plant cultivation based on an accurate watering schedule and enhanced water-use efficiency.