Search Results (5,663)

Chemical weed control is a significant agricultural concern, and reliance on a limited range of herbicide action modes has increased resistant weed species, many of which use C4 metabolism. As a result, the identification of novel herbicidal agents with low toxicity targeting C4 plants becomes imperative. An assessment was conducted on the impact of 3-cyanobenzoic acid on the growth and photosynthetic processes of maize (Zea mays), a representative C4 plant, cultivated hydroponically over 14 days. The results showed a significant reduction in plant growth and notable disruptions in gas exchange and chlorophyll a fluorescence due to the application of 3-cyanobenzoic acid, indicating compromised photosynthetic activity. Parameters such as the chlorophyll index, net assimilation (A), stomatal conductance (g_s), intercellular CO₂ concentration (C_i), maximum effective photochemical efficiency (F_v′/F_m′), photochemical quenching coefficient (q_P), quantum yield of photosystem II photochemistry (ϕ_PSII), and electron transport rate through PSII (ETR) all decreased. The A/PAR curve revealed reductions in the maximum net assimilation rate (A_max) and apparent quantum yield (ϕ), alongside an increased light compensation point (LCP). Moreover, 3-cyanobenzoic acid significantly decreased the carboxylation rates of RuBisCo (V_cmax) and PEPCase (V_pmax), electron transport rate (J), and mesophilic conductance (g_m). Overall, 3-cyanobenzoic acid induced substantial changes in plant growth, carboxylative processes, and photochemical activities. The treated plants also exhibited heightened susceptibility to intense light conditions, indicating a significant and potentially adverse impact on their physiological functions. These findings suggest that 3-cyanobenzoic acid or its analogs could be promising for future research targeting photosynthesis. Full article

Small-sized dairy farms (SSDFs) are integral to the agricultural landscape, providing economic, social, and environmental benefits to rural communities. However, they face growing challenges, including market volatility, rising production costs, labor shortages, and complex regulatory demands. This review synthesizes the current literature on the economic and environmental obstacles confronting SSDFs and explores strategies to enhance their sustainability and competitiveness. Key barriers include limited access to capital, high feed and energy expenses, and difficulties in adopting new technologies due to financial constraints. SSDFs also struggle to compete with larger farms benefiting from economies of scale and increased market power. Potential solutions include strengthening cooperative models, implementing diversification strategies, and leveraging policy support for targeted financial assistance and technology adoption. Case studies of successful SSDFs show that transitioning to organic production, adopting climate-smart techniques, and focusing on niche markets can significantly improve profitability and resilience. This review emphasizes the need for tailored policy frameworks, innovative financial models, and collaboration among stakeholders to support SSDFs. Future research should prioritize understanding SSDF-specific financial dynamics, assessing the cost-effectiveness of technology adoption, and developing strategies to enhance market access and long-term sustainability in the U.S. dairy sector. Full article

In the face of modern global challenges and the growing impacts of anthropogenic activity, the issue of agricultural pollution of natural resources has become a critical issue, especially in countries experiencing ecological and social crises. Ukraine, as one of Europe’s largest agricultural producers, faces unique challenges stemming from the legacy of radiation contamination following the Chornobyl nuclear disaster, intensive land use, and the environmental consequences of military conflict. Our study focuses on analyzing the sources of agricultural pollution, including chemical runoff, pesticides, herbicides, heavy metals, and nutrient leaching, as well as their impacts on the sustainability of agroecosystems, food security, and human well-being. The methodology is based on a systematic analysis of scientific research, agrochemical surveys, monitoring reports, and documents from governmental and non-governmental organizations. The assessment of natural resources was conducted using an integrated approach combining quantitative and qualitative pollution indicators. The results reveal an increasing threat to natural resources in Ukraine due to outdated technologies, radiation contamination, and military activities. Special attention is given to the need for a transition to agroecological farming methods and bioremediation for restoring contaminated lands and water resources. The study contributes to the development of sustainable approaches to managing natural resources and strategic measures to minimize agricultural pollution. The Ukrainian context underscores the relevance of research in countries with transitional economies and unique environmental challenges, making the findings significant for international scientific agendas and environmental policy. Future research perspectives include developing innovative technologies to prevent pollution and enhance the sustainability of agroecosystems to ecological challenges, as well as creating international resource management models based on Ukraine’s experience. Full article

Monitoring and predicting land surface phenology (LSP) are essential for understanding ecosystem dynamics, climate change impacts, and forest and agricultural productivity. Satellite Earth observation (EO) missions have played a crucial role in the advancement of LSP research, enabling global and continuous monitoring of vegetation cycles. This review provides a brief overview of key EO satellite missions, including the advanced very-high resolution radiometer (AVHRR), moderate resolution imaging spectroradiometer (MODIS), and the Landsat program, which have played an important role in capturing LSP dynamics at various spatial and temporal scales. Recent advancements in machine learning techniques have further enhanced LSP prediction capabilities, offering promising approaches for short-term prediction of vegetation phenology and cropland suitability assessment. Data cubes, which organize multidimensional EO data, provide an innovative framework for enhancing LSP analyses by integrating diverse data sources and simplifying data access and processing. This brief review highlights the potential of satellite-based monitoring, machine learning models, and data cube infrastructure for advancing LSP research and provides insights into current trends, challenges, and future directions. Full article

Global herbicide-resistant weed populations continue rising due to selection pressures exerted by herbicides. Despite this, herbicides continue to be farmers’ preferred weed-control method due to cost and efficiency relative to physical or biological methods. However, weeds developing resistance to herbicides not only challenges crop production but also threatens ecosystem services by disrupting biodiversity, reducing soil health, and impacting water quality. Our objective was to develop a simulation model that captures the feedback between weed population dynamics, agricultural management, profitability, and farmer decision-making processes that interact in unique ways to reinforce herbicide resistance in weeds. After calibration to observed data and evaluation by subject matter experts, we tested alternative agronomic, mechanical, or intensive management strategies to evaluate their impact on weed population dynamics. Results indicated that standalone practices enhanced farm profitability in the short term but lead to substantial adverse ecological outcomes in the long term, indicated by elevated herbicide resistance (e.g., harm to non-target species, disrupting natural ecosystem functions). The most management-intensive test yielded the greatest weed control and farm profit, albeit with elevated residual resistant seed bank levels. We discuss these findings in both developed and developing-nation contexts. Future work requires greater connectivity of farm management and genetic-resistance models that currently remain disconnected mechanistically. Full article

New challenges will be experienced by the agriculture sector in the near future, especially due to the effects of climate change. For example, rising temperatures could result in increased evapotranspiration demand, causing difficulties in the management of irrigation practices. Generally, an important predictor of plant water status to be taken into account for irrigation monitoring and management is the stem water potential. However, it requires a huge amount of time-consuming fieldwork, particularly when an adequate data amount is necessary to fully investigate the spatial and temporal variability of large areas under monitoring. In this study, the integration of machine learning and satellite remote sensing (Sentinel-2) was investigated to obtain a model able to predict the stem water potential in viticulture using multispectral imagery. Vine water status data were acquired within a Montepulciano vineyard in the south of Italy (Puglia region), under semi-arid conditions; data were acquired over two years during the irrigation seasons. Different machine learning algorithms (lasso, ridge, elastic net, and random forest) were compared using vegetation indices and spectral bands as predictors in two independent analyses. The results show that it is possible to remotely estimate vine water status with random forest from vegetation indices (R² = 0.72). Integrating machine learning techniques and satellite remote sensing could help farmers and technicians manage and plan irrigation, avoiding or reducing fieldwork. Full article

To evaluate the estimation and spatiotemporal variation characteristics of nitrous oxide emissions from agricultural sources in Anhui Province, the nitrous oxide emissions generated during crop cultivation and manure management were assessed based on the recommended methods in the “Guidelines for Provincial Greenhouse Gas Inventories” and official statistical data. The results showed that the overall emission of nitrous oxide from agricultural land showed a downward trend, reaching a valley value in 2019 with an emission of 2.83 × 10⁴ tons. The annual average emissions of nitrous oxide from agricultural land and manure management account for 80.98% and 19.02% of the total annual average emissions of nitrous oxide from agricultural activities in Anhui Province, respectively. Both agricultural land emissions and livestock manure management show a trend of nitrous oxide emissions decreasing from the northern region of Anhui > central region of Anhui > southern region of Anhui. In this paper, we explored and discussed the intrinsic driving factors behind the spatiotemporal changes in nitrous oxide emissions, and analyzed the potential for future emission reductions. It is suggested that the emissions of nitrous oxide from agricultural sources can be reduced through measures such as reasonable nitrogen application, adjustment of aquaculture structures, and the improvement of manure treatment methods, providing a theoretical reference for the estimation of greenhouse gas emissions from agricultural sources. Full article

Agricultural activities generate substantial quantities of waste, which are often relegated to landfills or incineration. However, these residues can be effectively valorized through composting, which transforms them into valuable organic fertilizers (OF). Composting agricultural waste (AW) mitigates environmental impacts and offers significant benefits in enhancing soil fertility and productivity. This practice is particularly beneficial in regions with low soil fertility and degraded land, where compost can improve soil health and productivity. This review provides a comprehensive analysis of the literature on the valorization of AW through composting, focusing on its environmental, agricultural, and economic impacts on soil health, especially in Morocco’s agricultural ecosystems. It synthesizes findings from studies published over the past two decades to offer critical insights and recommendations for optimizing composting practices. By systematically evaluating, this review highlights composting as a pivotal strategy for enhancing soil health, reducing environmental impact, and promoting sustainable AW management. Future research is essential to explore opportunities for optimizing the composting process, including content enhancement and processing duration. In summary, the composting process can be seen as an effective and sustainable solution that fits within the principles of circular economy (CE) and that requires careful evaluation and ongoing monitoring. Full article

In the context of growing concerns over food security and climate change, research on sustainable agricultural development increasingly emphasizes the interconnections within agricultural systems. This study developed a regionally integrated optimization and prediction agricultural model to systematically analyze the impacts of climate change on agricultural systems and their feedback mechanisms from a water-energy-food-carbon (WEFC) nexus perspective. Applied to the Pearl River Basin, the model evaluates future trends in grain yield, water use, energy consumption, and carbon emissions under various climate scenarios throughout this century. The results indicate that rising temperatures significantly reduce crop yields, particularly in the western basin, increasing the environmental footprint per unit of grain produced. However, the CO₂ fertilization effect substantially offsets these negative impacts. Under the SSP585 scenario, CO₂ concentrations rising from 599.77 ppm to 1135.21 ppm by the century’s end led to a shift in crop yield trends from negative (Z = −7.03) to positive (Z = 11.01). This also reduces water, energy, and carbon footprints by 12.82%, 10.62%, and 10.59%, respectively. These findings highlight the critical importance of adaptive management strategies, including precision irrigation, optimized fertilizer use, and climate-resilient practices, to ensure sustainable agricultural production. Despite these insights, the model has limitations. Future research should incorporate uncertainty analysis, diverse adaptation pathways, and advanced technologies such as machine learning and remote sensing to improve predictive accuracy and applicability. This study offers valuable guidance for mitigating the adverse impacts of climate change on the WEFC nexus, supporting sustainable agricultural practices and science-based policy development. Full article

In arid areas, droughts caused by climate change seriously impact wheat production. Therefore, research on spatial and temporal variability of dry and hot wind events and drought risk under different development patterns of future climate can provide a reference for wheat cultivation planning in the study area. Based on meteorological data under three scenarios of the CMIP6 (Sixth International Coupled Model Comparison Program) shared socio-economic path (SSP), we introduced wheat dry hot wind discrimination criteria and calculated the Standardized Precipitation–Evapotranspiration Index (SPEI). Future temperature changes within the Ningxia Province were consistent, increasing at a rate of 0.037, 0.15 and 0.45 °C·(10 a⁻¹) under SSP126, 245 and 585 scenarios, respectively. Simultaneously, average annual precipitation would increase by 17.77, 38.73 and 32.12 mm, respectively. Dry hot wind frequency differed spatially, being higher in northern Ningxia and western Ningxia, and lower in southern Ningxia and eastern Ningxia. During the wheat growing period, there is an obvious increasing drought risk trend under the SSP585 model in May, and the possibility of drought risk in the middle period was highest under the SSP126 model. In June, SPEI was generally higher than in May, and the risk of alternating drought and flood was greater under the SSP585 model, while near-medium drought risk was lower under the SSP126 and SSP245 models. The influence of DHW (dry and hot wind) on wheat yield will increase with the increase of warming level. However, when DHW occurs, effective irrigation can mitigate the harm. Irrigation water can be sourced from various channels, including rainfall, diversion, and groundwater. These results provide scientific reference for sustainable agricultural production, drought risk and wheat meteorological disaster forecast in inland arid areas affected by climate change. Full article

This article delves into the role of microalgae in advancing a green economy, thereby contributing to the attainment of Sustainable Development Goals (SDGs). Microalgae, as sustainable resources, offer multifaceted benefits across various sectors, including aquaculture, agriculture, food and feed, pharmaceuticals, cosmetics, wastewater treatment, and carbon sequestration. This review highlights the versatility of microalgae in producing biofuels, high-value bioactive compounds, and bioremediation processes. It examines the technical viability and environmental sustainability of microalgae cultivation, emphasizing its low carbon footprint and resource efficiency. This article also explores the integration of microalgae into existing industrial processes, illustrating their potential to mitigate climate change, promote biodiversity, and enhance resource circularity. Challenges such as scalability, cost-effectiveness, and regulatory frameworks are discussed alongside the prospects for technological innovations and policy support to bolster the microalgae industry. By harnessing the potential of microalgae, this article underscores a pathway towards a more sustainable and greener future, aligning with the global agenda for sustainable development. Full article

High consumption of ultra-processed foods, rich in sugar and unhealthy fats, has been linked to the onset of numerous chronic diseases. Consequently, there has been a growing shift towards a fiber-rich diet, abundant in fruits, vegetables, seeds, and nuts, to enhance longevity and quality of life. The primary bioactive components in these plant-based foods are polyphenols, which exert significant effects on modulating the gastrointestinal microbiota through their antioxidant and anti-inflammatory activities. This modulation has preventive effects on neurodegenerative, metabolic, and cardiovascular diseases, and even cancer. The antimicrobial properties of polyphenols against pathogenic bacteria have significantly reduced the need for antibiotics, thereby lowering the risk of antibiotic resistance. This paper advances the field by offering novel insights into the beneficial effects of polyphenols, both directly through the metabolites produced during digestion and indirectly through changes in the host’s gastrointestinal microbiota, uniquely emphasizing swine as a model highly relevant to human health, a topic that, to our knowledge, has not been thoroughly explored in previous reviews. This review also addresses aspects related to both other animal models (mice, rabbits, and rats), and humans, providing guidelines for future research into the benefits of polyphenol consumption. By linking agricultural and biomedical perspectives, it proposes strategies for utilizing these bioactive compounds as therapeutic agents in both veterinary and human health sciences. Full article

Enabling technologies (KETs) offer transformative potential for agriculture by addressing major challenges such as climate change, resource efficiency, and sustainable development across economic, social, and environmental dimensions. However, KET adoption is often limited by high R&D requirements, rapid innovation cycles, investment costs, and cultural or training barriers, especially among small agricultural businesses. Sicily’s agricultural sector, already strained by pandemic-related economic setbacks and inflationary pressures, faces additional barriers in adopting these technologies. To investigate these adoption challenges and develop viable solutions, the ARIA Living Lab (Agritech Research Innovation Environment) was established within the PNRR framework. A qualitative approach was used, involving documentary analysis and data from stakeholders across Sicilian agriculture. This approach enabled an in-depth exploration of sector-specific needs, infrastructure, and socio-economic factors influencing KET adoption. The analysis highlighted that adoption barriers differ significantly across sectors (citrus, olive, and wine), with public incentives and digital infrastructure playing key roles. However, a persistent lack of technical skills among farmers reduces the effectiveness of these innovations. The findings suggest that an integrated approach—combining targeted incentives, training, and enhanced infrastructure—is essential for a sustainable transition to KETs. Future research should examine collaborative efforts between farms and tech providers and evaluate the impact of public policies in promoting the widespread, informed adoption of enabling technologies. Full article

A field study was conducted to investigate the effects of selected climate-smart agriculture practices on soil bulk density (ρ), porosity (β), hydraulic conductivity (K_sat), and nutrient dynamics in southeast Texas. Treatment combinations of two types of organic manure (chicken and dairy) with three rates (0, 224, and 448 kg N ha⁻¹) and two levels of biochar (2500 and 5000 kg ha⁻¹) were used in a factorial randomized block design. Bulk density and porosity measurements were conducted on undisturbed soil core samples collected from the topsoil (0–10 cm) of a field cultivated with sweet corn. K_sat was calculated from the steady-state infiltration measured using the Tension Infiltrometer (TI). The ANOVA results indicated that the manure application rates, and biochar levels significantly affected the soil properties. Compared to the control, β increased by 15% and 29% for the recommended and double recommended manure rates. Similarly, hydraulic conductivity increased by 25% in the double-recommended rate plots compared to the control. Also, we applied the concept of non-parametric elasticity to understand the sensitivity of soil physical and chemical properties to K_sat. ρ and β are critical physical properties that are highly sensitive to K_sat. Among soil nutrients, Boron showed the highest sensitivity to K_sat. Hydraulic conductivity can be enhanced by employing selected climate-smart practices and improving water management. Future directions for this study focus on scaling these findings to diverse cropping systems and soil types while integrating long-term assessments to evaluate the cumulative effects of climate-smart practices on soil health, crop productivity, and ecosystem sustainability. Full article

The research has been undertaken to determine whether it is worthwhile to do a post-tillage on stubble before applying strip-till or whether tillage operations such as tillage and stubble ploughing should be performed. Therefore, ploughed tillage + strip tillage (PT), stubble discing + strip tillage (SD) and strip tillage (ST) operations were evaluated on three genetically distant winter wheat cultivars, including Formacja, Metronom and Desamo. A three-year field experiment was conducted from 2018 to 2021 at the Agricultural Experimental Station Kepa-Osiny in Pulawy, Poland. The experiment design was a split-block design with four repetitions of every treatment. The results showed that the cultivars differed in dry matter growth. However, no differences were found between the cultivar and post-harvest tillage method in terms of dry matter, plant height, and flag leaf area. Grain yield per ear was the main factor of yield variation across the cultivar and tillage systems. The extent of tillage only in the case of previously performed ploughing had an effect on the thousand grain weight. On the other hand, the omission of post-harvest tillage (ST) had a positive effect on the sedimentation index value. In terms of wheat grain yield, plough tillage (PT) proved to be the most advantageous, while reducing the intensity of tillage caused a systematic decrease in yield by 6% in the SD treatment and 9% in the ST treatment, respectively. Other quality parameters (gluten quantity, gluten index, falling number) did not depend on the applied tillage range. The response of cultivars to the applied cultivation methods was generally similar. Due to the beneficial effect of reducing the scope of cultivation on the environment, a small reduction in yield and no negative impact on the quality characteristics of grain, it is recommended to use strip-till cultivation without prior post-harvest cultivation. The results provide new insights into the growth of different winter wheat cultivars and the postharvest tillage applied, and they can be used in the future to validate existing wheat growth models. Full article