Search Results (268)

Tillage is a major factor influencing soil biological communities, particularly earthworms, which play a key role in soil structure and nutrient cycling. To address soil degradation, less-intensive tillage practices are increasingly being adopted globally and have shown positive effects on earthworm populations when applied consistently over extended periods. However, understanding of the earthworm population dynamics in the period following the implementation of changes in tillage practices remains limited. This three-year field study (2021–2023) investigates earthworm populations during the early transition phase (4–6 years) following the conversion from conventional ploughing to conservation (<8 cm depth, with residue retention) and no-tillage systems in a temperate arable system in central Slovenia. Earthworms were sampled annually in early October from three adjacent fields, each following the same three-year crop rotation (maize—winter cereal + cover crop—soybeans), using a combination of hand-sorting and allyl isothiocyanate (AITC) extraction. Results showed that reduced tillage practices significantly increased both earthworm biomass and abundance compared to conventional ploughing. However, a significant interaction between tillage and year was observed, with a sharp decline in earthworm abundance and mass in 2022, likely driven by a combination of 2022 summer tillage prior to cover crop sowing and extreme drought conditions. Juvenile earthworms were especially affected, with their proportion decreasing from 62% to 34% in ploughed plots and from 63% to 26% in conservation tillage plots. Despite interannual fluctuations, no-till showed the lowest variability in earthworm population. Long-term monitoring is essential to disentangle management and environmental effects and to inform resilient soil management strategies. Full article

The primary aim of this study was to explore the influence of abiotic factors on weed development in maize fields, with the goal of informing more effective weed management practices. We focused on identifying key environmental, edaphic, and agricultural variables that contribute to weed infestations, particularly before the application of spring herbicide treatments. Field investigations were conducted from 2018 to 2021 across selected maize-growing regions in Hungary. Over the four-year period, a total of 51 weed species were recorded, with Echinochloa crus-galli, Chenopodium album, Portulaca oleracea, and Hibiscus trionum emerging as the most prevalent taxa. Collectively, these four species accounted for more than half (52%) of the total weed cover. Altogether, the 20 most dominant species contributed 95% of the overall weed coverage. The analysis revealed that weed cover, species richness, and weed diversity were significantly affected by soil properties, nutrient levels, geographic location, and tillage systems. The results confirm that the composition of weed species was influenced by several environmental and management-related factors, including soil parameters, geographical location, annual precipitation, tillage method, and fertilizer application. Environmental factors collectively explained a slightly higher proportion of the variance (13.37%) than farming factors (12.66%) at a 90% significance level. Seasonal dynamics and crop rotation history also played a notable role in species distribution. Nutrient inputs, particularly nitrogen, phosphorus, and potassium, influenced both species diversity and floristic composition. Deep tillage practices favored the proliferation of perennial species, whereas shallow cultivation tended to promote annual weeds. Overall, the composition of weed vegetation proved to be a valuable indicator of site-specific soil conditions and agricultural practices. These findings underscore the need to tailor weed management strategies to local environmental and soil contexts for sustainable crop production. Full article

Drylands cover approximately 41% of Earth’s land surface, supporting about 500 million people and 45% of global agriculture. Groundwater is essential in drylands and is crucial for maintaining ecosystem services and offering numerous benefits. This article, for the first time, analyses and valuates the hydrological ecosystem services (HESs) provided by groundwater in a region of the Colorado River Delta in Mexico, an area with uncertain economic impact due to water scarcity. The main water sources are the Colorado River and groundwater from the Mexicali and San Luis Rio Colorado valley aquifers, both of which are overexploited. Valuation techniques include surrogate and simulated market methods for agricultural, industrial, urban, and domestic uses, the shadow project approach for water conservation and purification cost avoidance, and the contingent valuation method for recreation. Data from 2013 to 2015 and 2020 were used as they are the most reliable sources available. The annual value of HESs provided by groundwater was USD 883,520 million, with water conservation being a key factor. The analyzed groundwater uses reflect differences in efficiency and economic value, providing key information for decisions on governance, allocation, conservation, and revaluation of water resources. These results suggest reorienting crops, establishing differentiated rates, and promoting payment for environmental services programs. Full article

In wet subtropical environments, perennial groundcovers are common in horticultural plantations to protect the soil from erosion. However, there has been little investigation into whether seeding annual cover crops into the perennial groundcovers provides additional soil services including carbon and nutrient cycling in these systems. To investigate this, farmer participatory field trials were conducted in commercial avocado, macadamia, and coffee plantations in the wet Australian subtropics. Cover crops were direct-seeded into existing inter-row groundcovers in winter (cool season cover crops), and into the same plots the following summer (warm season cover crops). Inter-row biomass was quantified at the end of winter and summer in the control (no cover crop) and cover crops treatments. Soil carbon and nutrient cycling parameters including hot water extractable carbon, water soluble carbon, autoclavable citrate-extractable protein and soil enzyme activities were quantified every two months from early spring (September) 2021 to late autumn (May) 2022. Seeded cover crops produced 500 to 800 kg ha⁻¹ more total inter-row biomass over winter at the avocado coffee sites, and 3000 kg ha⁻¹ biomass in summer at the coffee site. However, they had no effect on biomass production in either season at the macadamia site. Soil functional parameters changed with season (i.e., time of sampling), with few significant effects of cover crop treatments on soil function parameters across the three sits. Growing a highly productive annual summer cover crop at the coffee site led to suppression and death of perennial groundcovers, exposing bare soil in the inter-row by 3 weeks after termination of the summer cover crop. Annual cover crops seeded into existing perennial groundcovers in tree crop systems had few significant impacts on soil biological function over the 12-month period, and their integration needs careful management to avoid investment losses and exacerbating the risk of soil erosion on sloping lands in the wet subtropics. Full article

The DNDC-Rice model effectively simulates yield and greenhouse gas emissions within a paddy system, while its performance under upland conditions remains unclear. Using data from a long-term cover crop experiment (fallow [FA] vs. rye [RY]) in a soybean field, this study validated the DNDC-Rice model’s performance in simulating soil dynamics, crop growth, and C-N cycling processes in upland systems through various indicators, including soil temperature, water-filled pore space (WFPS), soybean biomass and yield, CO₂ and N₂O fluxes, and soil organic carbon (SOC). Based on simulated results, the underestimation of cumulative N₂O flux (25.6% in FA and 5.1% in RY) was attributed to both underestimated WFPS and the algorithm’s limitations in simulating N₂O emission pulses. Overestimated soybean growth increased respiration, leading to the overestimation of CO₂ flux. Although the model captured trends in SOC stock, the simulated annual values differed from observations (−9.9% to +10.1%), potentially due to sampling errors. These findings indicate that the DNDC-Rice model requires improvements in its N cycling algorithm and crop growth sub-models to improve predictions for upland systems. This study provides validation evidence for applying DNDC-Rice to upland systems and offers direction for improving model simulation in paddy-upland rotation systems, thereby enhancing its applicability in such contexts. Full article

Current rice cultivation relies on mechanical transplanting, which is costly and complex, and direct seeding, which suffers from poor quality and low efficiency. To address these issues, a double-press precision depth-control seeding method was developed in this study. Discrete element modeling (DEM) was employed to optimize key operational parameters—compaction force, soil covering cutter rotational speed, and penetration depth—using qualified seeding depth and missed seeding rates as performance metrics. Optimal results were achieved at a 60 kPa compaction force, a 300 rpm rotational speed, and a 7 cm penetration depth. A prototype seeder was manufactured and evaluated in three-year field trials against conventional dry direct seeders and mechanical transplanters. The double-press seeder demonstrated significantly superior performance compared to conventional direct seeding. It optimized the crop population structure by maintaining a high tiller number while increasing the productive tiller rate, resulting in stable annual yields exceeding 10.11 t·hm⁻². Although its yield was slightly lower than that of mechanical transplanting, the double-press seeder offers a compelling practical alternative due to its operational convenience and economic benefits. Full article

Vegetation is a fundamental component of terrestrial ecosystems. Understanding how vegetation changes and what drives these evolutions is crucial for developing a high-quality ecological environment and addressing global climate change. Extensive evidence has shown that China has undergone substantial vegetation changes, characterized primarily by greening. To quantify vegetation dynamics in China and assess the contributions of various drivers, we explored the spatiotemporal variations in the kernel Normalized Difference Vegetation Index (kNDVI) from 2001 to 2020, and quantitatively separated the influences of climate and human factors. The kNDVI time series were generated from the MCD19A1 v061 dataset based on the Google Earth Engine (GEE) platform. We employed the Theil-Sen trend analysis, the Mann-Kendall test, and the Hurst index to analyze the historical patterns and future trajectories of kNDVI. Residual analysis was then applied to determine the relative contributions of climate change and human activities to vegetation dynamics across China. The results show that from 2001 to 2020, vegetation in China showed a fluctuating but predominantly increasing trend, with a significant annual kNDVI growth rate of 0.002. The significant greening pattern was observed in over 48% of vegetated areas, exhibiting a clear spatial gradient with lower increases in the northwest and higher amplitudes in the southeast. Moreover, more than 60% of vegetation areas are projected to experience a sustained increase in the future. Residual analysis reveals that climate change contributed 21.89% to vegetation changes, while human activities accounted for 78.11%, being the dominant drivers of vegetation variation. This finding is further supported by partial correlation analysis between kNDVI and temperature, precipitation, and the human footprint. Vegetation dynamics were found to respond more strongly to human influences than to climate drivers, underscoring the leading role of human activities. Further analysis of tree cover fraction and cropping intensity data indicates that the greening in forests and croplands is primarily attributable to large-scale afforestation efforts and improved agricultural management. Full article

The accurate mapping of crop planting patterns is vital for sustainable agriculture and food security, particularly in regions with complex cropping systems and limited cloud-free observations. This research focuses on the Jianghan Plain in southern China, where diverse planting structures and persistent cloud cover make consistent monitoring challenging. We integrated multi-temporal Sentinel-2 and Landsat-8 imagery from 2017 to 2021 on the Google Earth Engine platform and applied a sample migration strategy to construct multi-year training data. A random forest classifier was used to identify nine major planting patterns at a 10 m resolution. The classification achieved an average overall accuracy of 88.3%, with annual Kappa coefficients ranging from 0.81 to 0.88. A spatial analysis revealed that single rice was the dominant pattern, covering more than 60% of the area. Temporal variations in cropping patterns were categorized into four frequency levels (0, 1, 2, and 3 changes), with more dynamic transitions concentrated in the central-western and northern subregions. A multiscale geographically weighted regression (MGWR) model revealed that economic and production-related factors had strong positive associations with crop planting patterns, while natural factors showed relatively weaker explanatory power. This research presents a scalable method for mapping fine-resolution crop patterns in complex agroecosystems, providing quantitative support for regional land-use optimization and the development of agricultural policies. Full article

Anthropogenic activities and climate change have significantly altered runoff generation in the upper Han River basin, posing a challenge to the water supply sustainability for the Middle Route of the South-to-North Water Diversion Project. Land use/cover changes (LUCCs) affect hydrological processes by modifying evapotranspiration, infiltration and soil moisture content. Based on hydro-meteorological data from 1961 to 2023 and LUCC data series from 1985 to 2023, this study aimed to identify the temporal trend in hydro-meteorological variables, to quantify the impacts of underlying land surface and climate factors at different time scales and to clarify the effects of LUCCs and basin greening on the runoff generation process. The results showed that (1) inflow runoff declined at a rate of −1.71 mm/year from 1961 to 2023, with a marked shift around 1985, while potential evapotranspiration increased at a rate of 2.06 mm/year within the same time frame. (2) Annual climate factors accounted for 61.01% of the runoff reduction, while underlying land surface contributed 38.99%. Effective precipitation was the dominant climatic factor during the flood season, whereas potential evapotranspiration had a greater influence during the dry season. (3) From 1985 to 2023, the LUCC changed significantly, mainly manifested by the increasing forest area and decreasing crop land area. The NDVI also showed an upward trend over the years; the actual evapotranspiration increased by 1.163 billion m³ due to the LUCC. This study addresses the climate-driven and human-induced hydrological changes in the Danjiangkou Reservoir and provides an important reference for water resource management. Full article

Phytophthora cinnamomi is a globally distributed plant-pathogenic oomycete that threatens economically important crops, including Lauraceae, Bromeliaceae, Fabaceae, and Solanaceae. Utilizing species occurrence records and 35 environmental variables (|R| < 0.8), we employed the MaxEnt model and ArcGIS spatial analysis to systematically predict the potential geographical distribution of P. cinnamomi under current (1970–2000) and future (2030S, 2050S, 2070S, 2090S) climate scenarios across three Shared Socioeconomic Pathways (SSPs). The results indicate that currently suitable habitats cover the majority of China’s provinces (>50% of their areas), with only sporadic low-suitability zones in Qinghai, Tibet, and Xinjiang. The most influential environmental variables were the mean diurnal temperature range, mean temperature of the warmest quarter, annual precipitation, precipitation of the driest month, and elevation. Under future climate scenarios, new suitable habitats emerged in high-latitude regions, while the highly suitable area expanded significantly, with the distribution centroid shifting northeastward. This study employs predictive modeling to elucidate the future distribution patterns of P. cinnamomi in China, providing a theoretical foundation for establishing a regional-scale disease early warning system and formulating ecological management strategies. Full article

The search for waste management opportunities is crucial for achieving environmentally friendly waste practices and ensuring the country’s energy security. This research aimed to valorize biomass and waste generated in greenhouses and to analyze the potential for electricity production from this waste. The analyses compared the situations in Turkey and Poland, where greenhouse production of vegetables is developing and constitutes an important link in agricultural activities, despite differences in climatic conditions. The cultivation of vegetables and flowers under cover is rapidly expanding in both countries and, with changing climatic conditions, is expected to shape the future of agriculture. In addition to estimating the energy that can be obtained, the study also evaluated the economic benefits of such a solution and the volume of avoided CO₂ emissions from fossil fuels. The issue of utilizing these wastes is significant because current methods of their management do not lead to energy production, so their considerable energy potential is wasted, as highlighted in this study. Moreover, there is a lack of similar studies in the literature. The plant species chosen as materials in this study were tomatoes, peppers, eggplant, watermelon, and melon in the case of Turkey. For Poland, the analysis was conducted for tomatoes and greenhouse cucumbers. These crops represent the largest cultivated areas under cover in the respective countries. Results indicated that the average yearly amount of vegetable residue is approximately 463 thousand Mg in Turkey, and 77 thousand Mg in Poland. The estimated annual electricity potential is 430 GWh in Turkey and 80 GWh in Poland. Considering the efficiency of power generation in a typical power plant, the real amount of electricity to be obtained is 0.46 MWh per Mg of waste in Turkey and 0.52 MWh in Poland. Full article

This study analyzes the potential of optical and radar satellite data to monitor faba bean (Vicia faba L.) phenology over six years (2016–2021) in southwestern France. Using Sentinel-1, Sentinel-2, and Landsat-8 data, temporal variations in NDVI and radar backscatter coefficients (γ⁰_VV, γ⁰_VH, and γ⁰_VH/VV) are examined to assess crop growth, detect anomalies, and evaluate the impact of climatic conditions and sowing strategies. The results show that NDVI and the radar ratio (γ⁰_VH/VV) were suited to monitor faba bean phenology, with distinct growth phases observed annually. NDVI provides a clear seasonal pattern but is affected by cloud cover, while radar backscatter offers continuous monitoring, making their combination highly beneficial. The signal γ⁰_VH/VV exhibits well-marked correlations with NDVI (r = 0.81) and LAI (r = 0.83), particularly in orbit 30, which provides greater sensitivity to vegetation changes. The analysis of individual fields (inter-field approach) reveals variations in sowing strategies, with both autumn and spring plantings detected. Fields sown in autumn show early NDVI (and γ⁰_VH/VV) increases, while spring-sown fields display delayed growth patterns. This study also highlights the impact of climatic factors, such as precipitation and temperature, on inter-annual variability. Moreover, faba beans used as an intercropping species exhibit a shorter and more intense growth cycle, with a rapid NDVI (and γ⁰_VH/VV) increase and an earlier end of the vegetative cycle compared to standard rotations. Double logistic modeling successfully reconstructs temporal trends, achieving high accuracy (r > 0.95 and rRMSE < 9% for γ⁰_VH/VV signals and r > 0.89 and rRMSE < 15% for NDVI). These double logistic functions are capable of reproducing the differences in phenological development observed between fields and years, providing a reference set of functions that can be used to monitor the phenological development of faba beans in real time. Future applications could extend this methodology to other crops and explore alternative radar systems for improved monitoring (such as TerraSAR-X, Cosmos-SkyMed, ALOS-2/PALSAR, NISAR, ROSE-L…). Full article

This study aims to evaluate soil erosion mitigation strategies in Poland’s agricultural landscapes by applying the Revised Soil Loss Equation (RUSLE) model to identify high-risk areas where excessive soil loss adversely affects agricultural sustainability and productivity. Scenario assessments were conducted to evaluate the effectiveness of specific conservation practices—contour farming, reduced tillage, and cover crops—by simulating changes in the C-factor (cover-management factor) and P-factor (support practices factor) within the RUSLE framework. The research revealed heightened soil erosion rates during the summer months, particularly in regions with steep slopes and loess formations. Analysis indicated that annual soil loss from arable lands in Poland totals approximately 4.65 Mt yr⁻¹ and that contour farming, reduced tillage, and cover crops could collectively reduce this amount by up to 47%, with the highest reduction observed during the summer period. These findings highlighted the urgent need for stakeholders to adopt sustainable land management strategies. By quantifying the impact of these management practices on soil erosion rates, the study provided insights into the effectiveness of soil conservation measures in reducing erosion risks within Poland’s agricultural landscapes. This study emphasizes the importance of adopting sustainable land management strategies to preserve soil integrity and maintain agricultural productivity in Poland. Full article

Comprehensive studies are needed to investigate the diversity, abundance, and seed bank of weeds in winter wheat, spring barley, and spring oilseed rape crops due to a lack of experimental studies. Tillage has a long-term impact on agroecosystems. Since 1999, a long-term field experiment has been conducted at the Experimental Station of Vytautas Magnus University. The soil of the experimental site is classified as Epieutric Endocalcaric Planosol (Endoclayic, Episiltic, Aric, Drainic, Endoraptic, Uterquic), according to the World Reference Base. Treatments were arranged using a split-plot design. According to the factorial field experiment, the straw was removed from one part of the experimental field, and on the other part of the field, the straw was chopped and spread at harvesting (factor A). Six tillage systems, conventional (deep) and shallow plowing, shallow loosening, shallow rotovation, catch cropping and rotovation, and no tillage, were used as a subplot (factor B). The current study results show that the number of annual, perennial, and total weeds and the dry matter biomass decreased in shallow-plowed plots compared to deep-plowed plots. Different applied tillage treatments had different effects on perennial weeds. In the upper (0–10 cm) soil layer studied, the number of annual, perennial, and total weed seeds decreased in the fields where the straw was chopped and spread compared to the fields where the straw was removed. In the deeper soil layer (10–25 cm), no tillage with cover crops and direct seeding without cover crops reduced the number of annual and perennial weed seeds compared to deep tillage. The aim of this experiment was to investigate the effects of long-term tillage of different intensities and straw retention systems on weeds in crop fields. The results were obtained in 2019 and 2021 (winter wheat, spring barley, spring oilseed rape). Full article

The strategic incorporation of low-cost management practices, such as cover crops (CCs), to citrus production in southern Texas could add valuable ecosystem services that increase trees’ resilience to changing climatic conditions. To provide insight into how producers can manage CCs to optimize ecosystem services, we conducted a study in controlled conditions to examine the potential of adding three annual summer CCs species: common buckwheat (Fagopyrum esculentum), sunflower (Helianthus annuus L.), and sunn hemp (Crotalaria juncea L.) as monocultures growing in two representative soil types of the citrus region in Texas, and receiving one of these irrigation volumes based on calculated daily water losses [i.e., evapotranspiration (ET)] corresponding to 100, 75, 50, and 25% field capacity replenishment. Sunflower and sunn hemp produced the highest aboveground dry matter, which was on average 338 and 342% greater than buckwheat. Sunn hemp emerged faster than the other CCs, and mortality was relatively uniform across CCs, but buckwheat exhibited the highest sensitivity to drought and heat distress. Sunn hemp exhibited superior aboveground biomass accumulation, height, and chlorophyll content. All CCs performed similarly in both experimental soils, under native fertility conditions, and without the addition of mineral fertilizers. Irrigation at 75 and 100% ET levels were conducive to enhanced plant growth, which indicates that a minimum of 86.4 mm (75% ET) is required during CCs lifespan, but sunn hemp and sunflower were also capable of tolerating medium (50% ET) drought stress. Overall, our findings suggest that sunflower and sunn hemp exhibited traits desirable for incorporation as CCs to a perennial citrus production system. The primary benefit was the addition of organic matter with minimum management; however, both CCs’ performance was dependent on planting timing, successful early establishment, and favorable environmental conditions. Full article