Search Results (233)

The objective of this study was to evaluate the physical-hydric properties of a Planosol under an Integrated Crop–Livestock–Forest (ICLF) system in the Agreste region of Paraíba, Brazil, after eight years of implementation, and to compare them with areas under a conventional cropping system and secondary native vegetation. The experiment was conducted at the experimental station located in Alagoinha, in the Agreste mesoregion of the State of Paraíba, Brazil. The experimental design adopted was a randomized block design (RBD) with five treatments and four replications (5 × 4 + 2). The treatments consisted of: (1) Gliricidia (Gliricidia sepium (Jacq.) Steud) + Signal grass (Urochloa decumbens) (GL+SG); (2) Sabiá (Mimosa caesalpiniaefolia Benth) + Signal grass (SB+SG); (3) Purple Ipê (Handroanthus avellanedae (Lorentz ex Griseb.) Mattos) + SG (I+SG); (4) annual crop + SG (C+SG); and (5) Signal grass (SG). Two additional treatments were included for statistical comparison: a conventional cropping system (CC) and a secondary native vegetation area (NV), both located near the experimental site. The CC treatment showed the lowest bulk density (1.23 g cm⁻³) and the lowest degree of compaction (66.3%) among the evaluated treatments, as well as a total porosity (TP) higher than 75% (0.75 m³ m⁻³). In the soil under the integration system, the lowest bulk density (1.38 g cm⁻³) and the highest total porosity (0.48 m³ m⁻³) were observed in the SG treatment at the 0.0–0.10 m depth. High S-index values (>0.035) and a low relative field capacity (RFc < 0.50) and K_θ indicate high structural quality and low soil water storage capacity. It was concluded that the SG, I+SG, SB+SG, and CC treatments presented the highest values of soil bulk and degree of compaction in the layers below 0.10 m. The I+SG and C+SG treatments showed the lowest hydraulic conductivities and macroaggregation. The SG and C+SG treatments had the lowest available water content and available water capacity across the three analyzed soil layers. Full article

This paper examines how demographic characteristics, institutional structures, and livelihood strategies shape household resilience to climate variability and drought in West Pokot County, one of Kenya’s most climate-vulnerable arid and semi-arid lands (ASALs). Using a mixed-methods approach, it combines household survey data with three statistical techniques: Multinomial Logistic Regression (MLR) assesses the influence of gender, age, and education on livestock ownership and livelihood choices; Multiple Correspondence Analysis (MCA) reveals patterns in institutional access and adaptive practices; and Stepwise Linear Regression (SLR) quantifies the relationship between resilience strategies and agricultural productivity. Findings show that demographic factors, particularly gender and education, along with access to veterinary services, drought-tolerant inputs, and community-based organizations, significantly shape resilience. However, trade-offs exist: strategies improving livestock productivity may reduce crop yields due to resource and labor competition. This study recommends targeted interventions, including gender-responsive extension services, integration of indigenous and scientific knowledge, improved infrastructure, and participatory governance. These measures are vital for strengthening resilience not only in West Pokot but also in other drought-prone ASAL regions across sub-Saharan Africa. Full article

Driven by climate change and stringent ecological conservation policies, arid and semi-arid pastoral areas face acute grassland degradation and forage–livestock imbalances. In Sunan County (Gansu Province, China), herders have increasingly turned to off-site grazing—leasing crop fields in adjacent oases during autumn and winter—to alleviate local grassland pressure and adapt their livelihoods. However, the interplay between the evolving land use system (L) and this emergent borrowed pasture system (B) remains under-explored. This study introduces a coupled analytical framework linking L and B. We employ multi-temporal remote sensing imagery (2018–2023) and official statistical data to derive land use dynamic degree (LUDD) metrics and 14 indicators for the borrowed pasture system. Through entropy weighting and a coupling coordination degree model (CCDM), we quantify subsystem performance, interaction intensity, and coordination over time. The results show that 2017 was a turning point in grassland–bare land dynamics: grassland trends shifted from positive to negative, whereas bare land trends turned from negative to positive; strong coupling but low early coordination (C > 0.95; D < 0.54) were present due to institutional lags, infrastructural gaps, and rising rental costs; resilient grassroots networks bolstered coordination during COVID-19 (D ≈ 0.78 in 2023); and institutional voids limited scalability, highlighting the need for integrated subsidy, insurance, and management frameworks. In addition, among those interviewed, 75% (15/20) observed significant grassland degradation before adopting off-site grazing, and 40% (8/20) perceived improvements afterward, indicating its potential role in ecological regulation under climate stress. By fusing remote sensing quantification with local stakeholder insights, this study advances social–ecological coupling theory and offers actionable guidance for optimizing cross-regional forage allocation and adaptive governance in arid pastoral zones. Full article

The integration of computer vision (CV) and generative artificial intelligence (GenAI) into smart agriculture has revolutionised traditional farming practices by enabling real-time monitoring, automation, and data-driven decision-making. This review systematically examines the applications of CV in key agricultural domains, such as crop health monitoring, precision farming, harvesting automation, and livestock management, while highlighting the transformative role of GenAI in addressing data scarcity and enhancing model robustness. Advanced techniques, including convolutional neural networks (CNNs), YOLO variants, and transformer-based architectures, are analysed for their effectiveness in tasks like pest detection, fruit maturity classification, and field management. The survey reveals that generative models, such as generative adversarial networks (GANs) and diffusion models, significantly improve dataset diversity and model generalisation, particularly in low-resource scenarios. However, challenges persist, including environmental variability, edge deployment limitations, and the need for interpretable systems. Emerging trends, such as vision–language models and federated learning, offer promising avenues for future research. The study concludes that the synergy of CV and GenAI holds immense potential for advancing smart agriculture, though scalable, adaptive, and trustworthy solutions remain critical for widespread adoption. This comprehensive analysis provides valuable insights for researchers and practitioners aiming to harness AI-driven innovations in agricultural ecosystems. Full article

Increasing global population and threat from climate change are imposing economic, social, and ecological challenges to global food production. The demand for food is increasing, necessitating enhanced agricultural production with minimal environmental impacts. To meet this demand, sustainable intensification of both crops and livestock is necessary. This is more urgent in sub-Saharan Africa (SSA), a region characterized by low productivity and environmentally degrading agriculture. Integrated Agriculture-livestock-forestry (ALF) systems could be a key form of intensification needed for achieving food security and economic and environmental sustainability. The synergetic interactions between ALF nexus provide a mechanism to foster interconnectedness and resource circulation where practices of one system influence the outcomes in another. These systems enhance long-term farm sustainability while serving the farmers’ environmental and economic goals. It provides opportunities for improving food security, farmer incomes, soil health, climate resilience and the achievement of several UN Sustainable Development Goals. It is therefore crucial to strengthen the evidence supporting the contribution of these systems. On this basis, this paper reviews the potential pathways through which ALF nexus can enhance incomes, food security and climate change mitigation in SSA. The paper discusses the pathways through which the integration of crops, livestock and trees enhance (i) food security, (ii) incomes, (iii) soil health and (iv) mitigation of climate change in SSA. We argue that implementing ALF systems will be accompanied by an advancement of enhanced food security, farmer livelihoods and ecological conservation. It will foster a more balanced and sustainable sub-Saharan African agricultural systems. Full article

Historical application of wastewater treatment sludge (biosolids) has introduced per- and polyfluoroalkyl substances (PFAS) into agricultural systems and led to contamination of crops and livestock. Previous work validated a dynamic exposure and population toxicokinetic (DE_PopTK) modeling approach for estimating perfluorooctane sulfonic acid (PFOS) and perfluorohexane sulfonic acid (PFHxS) concentrations in cattle tissues at sites primarily dominated by water contamination. This work expands the efforts to validate the DE_PopTK model at a self-contained beef farm in Maine with PFAS exposures from feed grown on site where soil is contaminated from historical biosolids applications. The model is also extended to estimate perfluorodecanoic acid (PFDA) exposure and tissue levels. Farm-specific data were obtained to consider farm management practices, spatial variation of PFAS in soil, animal growth, and seasonal and annual variability in estimating daily exposures based on water, feed, and soil intake. A dynamic exposure pattern was observed as cattle accumulated PFAS while consuming feed grown on contaminated land and eliminated it while grazing on non-contaminated pastures. Model-estimated PFOS and PFDA levels in serum and muscle were in good agreement with biomonitoring data collected at the farm over a four-year period to reflect periods of accumulation and depuration, with the percentage error ranging from 16% to 73% when comparing modeled and measured data. Our findings demonstrated that understanding farm exposures and collecting site-specific data were integral to model performance. The model was applied to simulate management strategies and complement economic analyses to demonstrate that, with modifications to management practices, it is feasible for the farm to achieve lower PFOS and PFDA levels in beef and maintain economic viability despite elevated PFAS soil levels. Full article

Soybean [Glycine max (L.) Merr.] is a globally significant crop that provides essential meal protein and vegetable oil for human consumption. The protein content in soybean seeds is a critical factor that affects nutrition regarding human dietary needs as well as livestock feed. Therefore, identifying the key genes that affect the soybean seed protein content is one of the major goals in soybean research. To identify candidate genes and related pathways involved in soybean seed storage protein during seed development, an RNA-seq analysis was conducted in two soybean varieties that differ in protein content. A series of pathways related to seed protein metabolism, including “Photosynthesis”, “TCA cycle”, and “Starch and sucrose metabolism” pathways, were identified through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Seven candidate genes exhibiting two different gene regulation patterns were identified, six of which are directly related to the seed storage protein pathway, and one of which is related to the carbon binding pathway. An integrated analysis of transcriptomic and candidate gene expression trend suggested that 40 days after flowering (DAF) might be a crucial period for seed protein accumulation in soybean. Through a Weighted Gene Co-expression Network Analysis (WGCNA), two modules and two novel hub genes were found, which may be highly correlated with seed protein development. These findings might be valuable for a complete understanding of the genetic basis of seed protein content and lay a theoretical foundation for future gene functional identification and breeding efforts in soybean. Full article

This study investigates the effect of monochromatic light on the body weight (BW), melatonin concentration and its receptors expression levels, intestinal health, and gut microorganisms of Yangzhou geese. Green light (GL) significantly increased BW, melatonin and its receptor expression levels, villus height (VH) and villus height/crypt depth (VH/CD) ratio, superoxide dismutase (SOD), catalase (CAT), and total antioxidant capacity (T-AOC) activities, as well as the abundance of Synergistota and Prevotellaceae_UCG-001, compared with white light (WL). Blue light (BL) significantly increased the mRNA expression of melatonin membrane receptor 1a (Mel1a) and nuclear receptor 1α (RORα), VH and VH/CD ratio, CAT activity, cecal microbes diversity, and decreased malondialdehyde (MDA) levels. Red light (RL) significantly decreased average daily feed intake, reduced the abundances of Synergistota and Prevotellaceae_UCG-001, and increased Mel1a and RORα mRNA expression levels, MDA content, and cecum microbial diversity. Moreover, melatonin levels were significantly higher in the GL and BL groups compared to RL. Furthermore, the mRNA expression levels of Claudin-10, Occludin, and occludens-1 (ZO-1) were significantly upregulated under GL or BL exposures compared to the WL group, whereas RL only enhanced the expression levels of ZO-1. Spearman’s correlation analysis revealed that the relative abundance of Prevotellaceae_UCG-001 exhibited positive correlations with BW, melatonin and its receptors expression, gut health, and antioxidant capacity. Overall, these findings suggested that GL exposure enhanced melatonin synthesis and its receptors expression, modulated intestinal homeostasis and microbial ecology, and ultimately increased goose BW. Full article

Tropical pasture degradation represents a major challenge for global food security and environmental conservation, particularly in Brazil, where up to 60% of pastures are degraded. This study evaluates the economic viability of recovery of degraded pastures using an integrated crop–livestock–forest (ICLF) system. A representative 2-hectare system in the Brazilian Cerrado was analyzed, featuring native Dipteryx alata trees interplanted with pasture for cattle grazing. A deterministic financial model was developed to simulate annual cash flows over a 20-year period under various financing scenarios, including self-financing and multiple subsidized rural credit lines (e.g., Pronaf and Pronamp programs, and ABC Ambiental). The analysis shows that subsidized credit lines with low interest rates and extended grace periods significantly improve project profitability, yielding positive NPVs and robust internal rates of return, while self-financing and high-cost credit options (such as Pronaf Mulher) result in negative NPVs. The dual cash flow strategy—where borrowed funds are immediately invested in secure fixed-income instruments—further enhances economic performance. The findings demonstrate that ICLF-based pasture recovery is economically viable when supported by appropriate financing, offering a scalable model for sustainable agriculture that delivers both economic and environmental benefits. Full article

In integrated crop–livestock systems (ICLSs), grazing intensity and crop rotation influence residue dynamics, making it essential to assess shoot and root contributions to soil carbon (C) and nitrogen (N) inputs. This study aimed to assess the shoot and root biomass of Italian ryegrass, soybean, and maize; the distribution of roots within the soil profile; and the contributions of shoot and root biomass to soil C and N under varying winter grazing intensities and summer crop rotations. The experiment was conducted within a long-term (12-year) field protocol, arranged in a randomized complete block design with split plots and four replicates. Grazing intensity was defined as the following: (i) moderate grazing—forage allowance equivalent to 2.5 times the potential dry matter intake of sheep, and (ii) low grazing—forage allowance equivalent to 5.0 times the intake potential. Grazing intensities (moderate and low) were allocated to the main plots, while cropping systems—monoculture (soybean/soybean) and crop rotation (soybean/maize)—were assigned to the subplots. Soil depth layers (0–10, 10–20, 20–30, and 30–40 cm) were treated as sub-subplots. Root samples of Italian ryegrass, soybean, and maize were collected using the soil monolith method. Low grazing intensity (8.6 Mg ha⁻¹) promoted greater aboveground biomass production of Italian ryegrass compared to moderate intensity (6.6 Mg ha⁻¹). Maize exhibited a higher capacity for both root and shoot biomass accumulation, with average increases of 85% and 120%, respectively, compared to soybean. Root biomass was primarily concentrated in the surface soil layer, with over 70% located within the top 10 cm. Italian ryegrass showed a more uniform root distribution throughout the soil profile compared to soybean and maize. Carbon inputs were higher under crop rotation (17.2 Mg ha⁻¹) than under monoculture (15.0 Mg ha⁻¹), whereas nitrogen inputs were greater in soybean monoculture (0.23 Mg ha⁻¹) than in crop rotation (0.16 Mg ha⁻¹). Low grazing intensity in winter and summer crop rotation with high-residue and quality species enhance the balance between productivity and soil C and N inputs, promoting the sustainability of ICLSs. Full article

Agricultural waste poses significant environmental, economic, and social challenges globally, with estimates indicating that 10–50% of agricultural products are discarded annually as waste. This review explores strategies for managing agricultural waste to mitigate its adverse impacts and promote sustainable development. Agricultural residues, such as those from sugarcane, rice, and wheat, contribute to pollution when improperly disposed of through burning or burying, contaminating soil, water, and air. However, these residues also represent untapped resources for bioenergy production, composting, mulching, and the creation of value-added products like biochar, bioplastics, single-cell protein and biobased building blocks. The paper highlights various solutions, including integrating agricultural waste into livestock feed formulations to reduce competition for human food crops, producing biofuels like ethanol and biodiesel from lignocellulosic materials, and adopting circular economy practices to upcycle waste into high-value products. Technologies such as anaerobic digestion for biogas production and gasification for synthesis gas offer renewable energy alternatives and ample feedstocks for gas fermentation while addressing waste management issues. Composting and vermicomposting enhance soil fertility, while mulching improves moisture retention and reduces erosion. Moreover, the review emphasizes the importance of policy frameworks, public-private partnerships, and farmer education in promoting effective waste management practices. By implementing these strategies, agricultural waste can be transformed into a resource, contributing to food security, environmental conservation, and economic growth. Full article

Climate change poses a significant threat to Ethiopian agriculture, impacting both cereal and livestock production through rising temperatures, erratic rainfall, prolonged droughts, and increased pest and disease outbreaks. These challenges intensify food insecurity, particularly for smallholder farmers and pastoralists who rely on climate-sensitive agricultural systems. This systematic review aims to synthesize the impacts of climate change on Ethiopian agriculture, with a specific focus on cereal production and livestock feed quality, while exploring effective adaptation strategies that can support resilience in the sector. The review synthesizes 50 peer-reviewed publications (2020–2024) from the Climate Change Effects on Food Security project, which supports young African academics and Higher Education Institutions (HEIs) in addressing Sustainable Development Goals (SDGs). Using PRISMA guidelines, the review assesses climate change impacts on major cereal crops and livestock feed in Ethiopia and explores adaptation strategies. Over the past 30 years, Ethiopia has experienced rising temperatures (0.3–0.66 °C), with future projections indicating increases of 0.6–0.8 °C per decade resulting in more frequent and severe droughts, floods, and landslides. These shifts have led to declining yields of wheat, maize, and barley, shrinking arable land, and deteriorating feed quality and water availability, severely affecting livestock health and productivity. The study identifies key on-the-ground adaptation strategies, including adjusted planting dates, crop diversification, drought-tolerant varieties, soil and water conservation, agroforestry, supplemental irrigation, and integrated fertilizer use. Livestock adaptations include improved breeding practices, fodder enhancement using legumes and local browse species, and seasonal climate forecasting. These results have significant practical implications: they offer a robust evidence base for policymakers, extension agents, and development practitioners to design and implement targeted, context-specific adaptation strategies. Moreover, the findings support the integration of climate resilience into national agricultural policies and food security planning. The Climate Change Effects on Food Security project’s role in generating scientific knowledge and fostering interdisciplinary collaboration is vital for building institutional and human capacity to confront climate challenges. Ultimately, this review contributes actionable insights for promoting sustainable, climate-resilient agriculture across Ethiopia. Full article

Biogas production from agricultural waste reduces methane emissions and addresses climate change challenges by converting livestock and organic waste into energy. This study analyzed biogas production in agricultural enterprises under the European Green Deal, the advantages of biogas as an energy source, and the use of digestate in agriculture. The raw material for biogas production from agro-industrial wastes in Ukraine has been investigated, showing that the country’s biogas production potential amounts to 34.59 billion m³, including 0.65 billion m³ from processing plant wastes. The main types of biomass that can be used for biogas production in Ukraine are crop residues (71.4%), manure (26.6%), and food industry waste (2.0%). The implementation of biogas production projects will reduce greenhouse gas emissions by 3.98 billion tons of CO₂ and increase profits through electricity sales. This study examines the barriers and prospects for the development of electricity generation from biogas in Ukraine in the context of the integration of Ukraine’s energy system into the EU energy space. Directions for developing the biogas industry, focusing on electricity production within the framework of European decarbonization initiatives, will enhance the energy security of Ukraine and the EU. Estimating the energy production from agricultural waste allows for determining biogas output from organic waste. A regional biogas cluster model was developed based on the agro-industrial complex, which combines the production of biogas, electricity, water, and biofertilizers with increased efficiency and regional sustainable development. Full article

The application of organic amendments in agriculture has gained increasing attention as a sustainable approach to improving soil fertility and crop productivity. This study assessed the effects of vermicompost derived from water buffalo (Bubalus bubalis) manure on the yield and biochemical quality of cauliflower cultivated in soil types typical of the Campania region: loam and clay. Three fertilization treatments were tested, an unfertilized control, vermicompost (140 kg N ha⁻¹), and mineral fertilizer (MIN), at the same nitrogen rate. The results showed that vermicompost more significantly improved plant growth compared to the unfertilized control, particularly in loam soil, where the biomass and the leaf number increased by 160% and 335%, respectively. In clay soil, vermicompost enhanced nutrient availability, leading to a 159% biomass increase relative to the control. While mineral fertilization resulted in the highest yields, vermicompost improved the antioxidant capacity and influenced the amino acid composition, particularly in clay soil, where it enhanced the total amino acid content by 35% over that of the control. Additionally, vermicompost increased the quantity of soil organic matter and moderated the oxidative stress responses, suggesting long-term benefits for soil health. These findings highlight the potential of vermicompost as an effective and sustainable soil amendment, particularly in regions with intensive livestock farming and nitrate-sensitive environments. Further research is needed to optimize its integration with conventional fertilization strategies to maximize the agronomic and environmental benefits. Full article

Silage maize is vital to livestock development in northern China, but intensive chemical fertilization has led to soil degradation and reduced productivity. Bio-organic fertilizers offer a sustainable alternative, though their effects on soil multifunctionality remain underexplored. This study evaluated the impact of combining decomposed cow manure, Bacillus amyloliquefaciens, and mineral potassium fulvic acid with chemical fertilizers (NPK) on silage maize yield, soil microbial diversity, and ecosystem multifunctionality (EMF). Field experiments showed that bio-organic fertilization increased silage maize yield by 10.23% compared to chemical fertilizers alone, primarily by boosting labile organic carbon and soil enzyme activity. It also enhanced bacterial richness and diversity, with little effect on fungal communities. Microbial network analysis revealed more complex and stable bacterial networks under bio-organic treatments, indicating strengthened microbial interactions. Random forest and structural equation modeling (SEM) identified soil carbon storage and bacterial diversity as key drivers of EMF, which integrates soil functions such as nutrient cycling, decomposition, enzyme activity, and microbial diversity. These findings suggest that soil bacterial diversity and its interactions with soil properties are critical to both crop productivity and soil health. The optimal fertilization strategy for silage maize in this region involves the combined use of cattle manure, Bacillus amyloliquefaciens, mineral potassium fulvic acid, and NPK fertilizers. This approach improves yield, microbial diversity, and soil multifunctionality. Future studies should consider environmental variables and crop varieties across diverse regions to support broader application. Full article