Search Results (696)

This study investigates the production and economic feasibility of biochar for smallholder and family farms in Central Amazonia, with potential implications for other tropical regions. The costs of construction of a prototype mobile kiln and biochar production were evaluated, using small-sized biomass from acai (Euterpe oleracea Mart.) agro-industrial residues as feedstock. The biochar produced was characterised in terms of its liming capacity (calcium carbonate equivalence, CaCO_3eq), nutrient content via organic fertilisation methods, and ash analysis by ICP-OES. Field trials with cowpea assessed economic outcomes, as well scenarios of fractional biochar application and cost comparison between biochar production in the prototype kiln and a traditional earth-brick kiln. The prototype kiln showed production costs of USD 0.87–2.06 kg⁻¹, whereas traditional kiln significantly reduced costs (USD 0.03–0.08 kg⁻¹). Biochar application alone increased cowpea revenue by 34%, while combining biochar and lime raised cowpea revenues by up to 84.6%. Owing to high input costs and the low value of the crop, the control treatment generated greater net revenue compared to treatments using lime alone. Moreover, biochar produced in traditional kilns provided a 94% increase in net revenue compared to liming. The estimated externalities indicated that carbon credits represented the most significant potential source of income (USD 2217 ha⁻¹). Finally, fractional biochar application in ten years can retain over 97% of soil carbon content, demonstrating potential for sustainable agriculture and carbon sequestration and a potential further motivation for farmers if integrated into carbon markets. Public policies and technological adaptations are essential for facilitating biochar adoption by small-scale tropical farmers. Full article

As an important ecological barrier and animal husbandry resource base in arid and semi-arid areas, grassland degradation directly affects regional ecological security and sustainable development. Ili Prefecture is located in the western part of Xinjiang, China, and is a typical grassland resource-rich area. However, in recent years, driven by climate change and human activities, grassland degradation has become increasingly serious. In view of the lack of comprehensive evaluation indicators and the inconsistency of grassland evaluation grade standards in remote sensing monitoring of grassland resource degradation, this study takes the current situation of grassland degradation in Ili Prefecture in the past 20 years as the research object and constructs a comprehensive evaluation index system covering three criteria layers of vegetation characteristics, environmental characteristics, and utilization characteristics. Net primary productivity (NPP), vegetation coverage, temperature, precipitation, soil erosion modulus, and grazing intensity were selected as multi-source indicators. Combined with data sources such as remote sensing inversion, sample survey, meteorological data, and farmer survey, the factor weight coefficient was determined by analytic hierarchy process. The Grassland Degeneration Comprehensive Index (GDCI) model was constructed to carry out remote sensing monitoring and evaluation of grassland degradation in Yili Prefecture. With reference to the classification threshold of the national standard for grassland degradation, the GDCI grassland degradation evaluation grade threshold (GDCI reduction rate) was determined by the method of weighted average of coefficients: non-degradation (0–10%), mild degradation (10–20%), moderate degradation (20–37.66%) and severe degradation (more than 37.66%). According to the results, between 2000 and 2022, non-degraded grasslands in Ili Prefecture covered an area of 27,200 km², representing 90.19% of the total grassland area. Slight, moderate, and severe degradation accounted for 4.34%, 3.33%, and 2.15%, respectively. Moderately and severely degraded areas are primarily distributed in agro-pastoral transition zones and economically developed urban regions, respectively. The results revealed the spatial and temporal distribution characteristics of grassland degradation in Yili Prefecture and provided data basis and technical support for regional grassland resource management, degradation prevention and control and ecological restoration. Full article

Solid biomass (agro-residue) is the most important source of renewable energy. The accelerating impacts of climate change and global population growth contribute to air pollution through the use of fossil fuels. These processes increase the demand for energy. The European Union has adopted a climate action plan to address the above challenges. The main aim of this study was to assess the economic performance of the producers of biomass for energy generation in Poland. The detailed objectives were to determine land resources in the studied agricultural farms and to determine the value of fixed and current assets in the analyzed farms. We used questionnaires as the main method to collect data. Purposive sampling was used to choose the farms. We conducted various tests to analyze the revenues from biomass sales and their normality, such as the Dornik–Hansen test, the Shapiro–Wilk test, the Liliefors test, and the Jargue–Berra statistical test. Moreover, we conducted regression analysis to find factors that are the basis for the economic performance (incomes) of farms that sell biomass. Results: This study demonstrated that biomass sales had a minor impact on the performance of agricultural farms, but they enabled farmers to maintain their position on the market. The economic analysis was carried out on a representative group of Polish agricultural farms, taking into account fixed and current assets, land use, production structure, and employment. The findings indicate that a higher income from biomass sales was generally associated with better economic results per farm and per employee, although not always per hectare of land. This suggests that capital intensity and strategic resource management play a crucial role in the profitability of bioenergy-oriented agricultural production. Conclusions: We concluded that biomass sales had a negligible influence on farm income. But a small income from biomass sales could affect a farm’s economic viability. Full article

Lactic acid (LA) is a high-value chemical with growing demand for the production of polymers and plastics and in the food and pharmaceutical industries. However, production costs remain a significant constraint when using conventional food-grade substrates. This study investigates Ivorian sugarcane molasses, an abundant agro-industrial by-product, as a low-cost carbon source for LA production via batch fermentation with Limosilactobacillus fermentum ATCC 9338. Molasses was pretreated by acid hydrolysis to improve fermentability, increasing glucose and fructose concentrations. Comparative fermentations using raw and pretreated molasses showed a 75% increase in LA production (32.4 ± 0.03 g/L) after pretreatment. Optimisation using Box–Behnken design revealed that the initial sugar concentration, inoculation rate, and stirring speed significantly influenced lactic acid production. Under optimal conditions, a maximum LA concentration of 52.4 ± 0.49 g/L was achieved with a yield of 0.95 g/g and productivity of 0.73 g/L·h. Kinetic analysis confirmed efficient sugar utilisation under the optimised conditions, and polarimetry revealed a near-racemic lactic acid. A simplified cost analysis showed that molasses could reduce carbon source costs by over 70% compared to refined sugars, supporting its economic viability. This work demonstrates the potential of pretreated molasses under robust fermentation conditions as a sustainable and cost-effective substrate for LA production in resource-limited contexts. The approach aligns with circular bioeconomy principles and presents a replicable model for decentralised bioproduction in a developing country like Côte d’Ivoire. Full article

Integrated rice–crayfish (Oryza sativa–Procambarus clarkii) co-culture (RC) systems have gained prominence due to their economic benefits and ecological sustainability; however, the interactions between soil properties and microbial communities in such systems remain poorly understood. This study evaluated the effects of the RC systems on soil physicochemical characteristics and microbial dynamics in paddy fields of southern Henan Province, China, over the 2023 growing season and subsequent fallow period. Using a randomized complete design, rice monoculture (RM, as the control) and RC treatments were compared across replicated plots. Soil and water samples were collected post-harvest and pre-transplanting to assess soil properties, extracellular enzyme activity, and microbial community structure. Results showed that RC significantly enhanced soil moisture by up to 30.2%, increased soil porosity by 9.6%, and nearly tripled soil organic carbon compared to RM. The RC system consistently elevated nitrogen (N), phosphorus (P), and potassium (K) throughout both the rice growth and fallow stages, indicating improved nutrient availability and retention. Elevated extracellular enzyme activities linked to carbon, N, and P cycling were observed under RC, with enzymatic stoichiometry revealing increased microbial nutrient limitation intensity and a shift toward P limitation. Microbial community composition was significantly altered under RC, showing increased biomass, a higher fungi-to-bacteria ratio, and greater relative abundance of Gram-positive bacteria, reflecting enhanced soil biodiversity and ecosystem resilience. Further analyses using the Mantel test and Random Forest identified extracellular enzyme activities, PLFAs, soil moisture, and bulk density as major factors shaping microbial communities. Redundancy analysis (RDA) confirmed that total potassium (TK), vector length (VL), soil pH, and total nitrogen (TN) were the strongest environmental predictors of microbial variation, jointly explaining 74.57% of the total variation. Our findings indicated that RC improves soil physicochemical conditions and microbial function, thereby supporting sustainable nutrient cycling and offering a promising, environmentally sound strategy for enhancing productivity and soil health in rice-based agro-ecosystems. Full article

In the Sahelian context characterized by the increasing scarcity of forage resources, this study investigated how climate change perceptions influence the adoption of cottonseed cake in pastoral and agro-pastoral systems in the Hauts-Bassins region of Burkina Faso. Drawing on the Subjective Expected Utility (SEU) theory and using a logit model estimated from survey data collected from 366 livestock farms, the analysis reveals that the perceived degradation of rangelands due to climate change is a key determinant of adoption. Over 40% of surveyed herders believed that climate change is negatively affecting the availability of natural forage. This heightened awareness is significantly associated with a greater likelihood of adopting cottonseed cake as a feed supplementation strategy. This study highlights the crucial role of cognitive factors in shaping adaptation decisions, beyond traditional economic and structural determinants. It underscores the importance of incorporating environmental perceptions into public policies supporting livestock systems and technological innovations in pastoral. Full article

Chemically demethoxylated and Ca-cross-linked orange-peel waste was engineered as a biosorbent for Mn(II) removal from water. A three-factor Box–Behnken design (biosorbent dose 3–10 g L⁻¹, initial Mn²⁺ 100–300 mg L⁻¹, contact time 3–8 h; pH 5.5 ± 0.1, 25 °C) required only 16 runs to locate the optimum (10 g L⁻¹, 100 mg L⁻¹, 8 h), at which the material removed 94.8% ± 0.3% manganese removal under the optimized conditions (10 g L⁻¹, 100 mg L⁻¹, 8 h, pH 5.5) of dissolved manganese and reached a Langmuir capacity of 29.7 mg g⁻¹. Equilibrium data fitted the Freundlich (R² = 0.968) and Sips (R² = 0.969) models best, indicating a heterogeneous surface, whereas kinetic screening confirmed equilibrium within 6 h. FTIR and SEM–EDX verified abundant surface –COO⁻/–OH groups and showed Mn deposits that partially replaced residual Ca, supporting an ion-exchange component in the uptake mechanism. A preliminary cost analysis (<USD 10 kg⁻¹) and > 90% regeneration efficiency over three cycles highlight the economic and environmental promise of this modified agro-waste for polishing Mn-laden effluents. Full article

Variable-rate nitrogen (VR-N) application allows farmers to optimize nitrogen (N) input site-specifically within field boundaries, enhancing both economic efficiency and environmental sustainability. In this study, VR-N technology was applied to durum wheat in two small-scale commercial fields (3–4 ha each) located in distinct agro-climatic zones of Thessaly, central Greece. A real-time VR-N application algorithm was used to calculate N rates based on easily obtainable near-real-time data from unmanned aerial vehicle (UAV) imagery, tailored to the crop’s actual needs. VR-N implementation was carried out using conventional fertilizer spreaders equipped to read prescription maps. Results showed that VR-N reduced N input by up to 49.6% compared to the conventional uniform-rate N (UR-N) application, with no significant impact on wheat yield or grain quality. In one of the fields, the improved gain of VR-N when compared to UR-N was 7.2%, corresponding to an economic gain of EUR 163.8 ha⁻¹, while in the second field—where growing conditions were less favorable—no considerable VR-N economic gain was observed. Environmental benefits were also notable. The carbon footprint (CF) of the wheat crop was reduced by 6.4% to 22.0%, and residual soil nitrate (NO₃⁻) levels at harvest were 13.6% to 36.1% lower in VR-N zones compared to UR-N zones. These findings suggest a decreased risk of NO₃⁻ leaching and ground water contamination. Overall, the study supports the viability of VR-N as a practical and scalable approach to improve N use efficiency (NUE) and reduce the environmental impact of wheat cultivation which could be readily adopted by farmers. Full article

The European Union’s developing rural development plan places digital and precision agriculture at the centre of agricultural modernisation and economic development. This article examines how agricultural practices in rural EU regions are being influenced by smart technology, such as drones, IoT sensors, satellite-based research, and AI-driven platforms, through an analysis of recent data from sources across the European Union. This study applies a mixed-methods approach, combining quantitative analysis of strategic policy documents and EU databases, to evaluate the ways in which precision agriculture reduces input consumption, increases productivity, reduces labour shortages and rural area depopulation, and improves sustainability. By investing in infrastructure, developing communities for data exchange, and organising training for farmers, European policies such as the Strategic Plans of the Common Agricultural Policy (CAP), the SmartAgriHubs initiative, and the AgData program actively encourage the transition to digital agriculture. Cyprus is analysed as a case study to show how targeted investments and initiatives supported by the EU can help smaller countries, with limited natural resources, to realise the benefits of digital transformation in agriculture. A special focus is placed on how solutions adapted to agro-climatic and socioeconomic conditions can contribute to strengthening the competitiveness of the agricultural sector, attracting young people to get involved in this field and opening up new economic opportunities. The results of previous research indicate that digital agriculture not only improves productivity but also proves to be a strategic mechanism for attracting and retaining young people in rural areas. Thus, this work additionally contributes to the broader goal of the European Union—the development of smart, inclusive, and sustainable rural areas, in which digital technologies are not only seen as tools for efficiency but also as key means for integrated and long-term rural development. Full article

Establishing a sustainable production system requires a more efficient utilization of resources and the adoption of cleaner production methodologies. Specifically, industrial symbiosis promotes collaboration among interconnected industries by exchanging waste, byproducts, and utilities, thereby providing innovative ways to enhance the efficiency of production processes. However, the sustainability of agricultural products and agro-based industries is essential for human survival. This study proposed an integrated symbiotic production system that targets agro-based industries. The system includes seven plants: a sugar production plant, a corn-integrated industrial plant, an alcohol production plant, a feed production plant, a fertilizer plant, a bioethanol production plant, and a wastewater treatment plant. The study aimed to design a sustainable industrial system that shares byproducts, waste, and water reuse. Symbiotic relations between production plants are designed in a provided multi-objective optimization model that considers both the mitigation of CO₂ emissions and the maximization of system profit. The multi-objective model with the epsilon-constraint method results in Pareto-efficient solutions that address the tradeoff between the objectives. This allows decision makers to select a suitable one among the solution set that prioritizes conflicting objectives. We developed ten scenarios to assess costs, revenue, profit, and CO₂ emissions, offering significant insights into how model parameters affect managerial knowledge. This study also addresses environmental and economic concerns, thereby making the development of agro-based industries more sustainable. Full article

The extensive environmental pollution caused by petroleum-based plastics highlights the urgent need for sustainable, economically viable alternatives. The practical challenge of enhancing polyhydroxybutyrate (PHB) production with cost-effective agro-industrial residues—rice-bran and corn-flour hydrolysates—has been demonstrated. Bacillus bingmayongensis GS2 was isolated from soil samples collected at the Pirana municipal landfill in Ahmedabad, India, and identified through VITEK-2 biochemical profiling and 16S rDNA sequencing (GenBank accession OQ749793). Initial screening for PHB accumulation was performed using Sudan Black B staining. Optimization via a sequential one-variable-at-a-time (OVAT) approach identified optimal cultivation conditions (36 h inoculum age, 37 °C, pH 7.0, 100 rpm agitation), resulting in a PHB yield of 2.77 g L⁻¹ (66% DCW). Further refinement using a central composite response surface methodology (RSM)—varying rice-bran hydrolysate, corn-flour hydrolysate, peptone concentration, and initial pH—significantly improved the PHB yield to 3.18 g L⁻¹(74% DCW), representing more than a threefold enhancement over unoptimized conditions. Structural validation using Fourier Transform Infrared spectroscopy (FTIR) and Proton Nuclear Magnetic Resonance spectroscopy (¹H-NMR) confirmed the molecular integrity of the produced PHB. That Bacillus bingmayongensis GS2 effectively converts low-cost agro-industrial residues into high-value bioplastics has been demonstrated, indicating substantial industrial potential. Future work will focus on bioreactor scale-up, targeted metabolic-engineering strategies, and comprehensive sustainability evaluations, including life-cycle assessment. Full article

Agri-food waste management poses a growing challenge in the pursuit of sustainable development. This bibliographic review analyses the scientific literature from 2014 to 2025 to examine current methods of agro-waste valorisation and the application of circular-economy principles in the transformation of biological waste into valuable resources. Special attention is given to nanofibers—particularly nanocellulose—and other high-value biocomponents. The review assesses these recovery practices’ economic, ecological, and health-related impacts and the relevant barriers to implementation. Potential application domains are discussed, and estimations of waste quantities and future trends are provided. The findings highlight the importance of investment in sustainable technologies and increased stakeholder awareness in efforts to optimize agri-food waste valorisation and support the transition to a more sustainable agricultural sector. Full article

Understanding the complex and multidimensional nature of poverty is essential for designing effective and targeted policy interventions in rural Ethiopia. This study examined the determinants of multidimensional poverty in Bilate River Basin in South Ethiopia, employing cross-sectional household survey data collected in 2024. A total of 359 households were selected using a multistage sampling technique, ensuring representation across agro-ecological and socio-economic zones. The analysis applied the Generalized Ordered Logit (GOLOGIT) model to categorize households into four mutually exclusive poverty statuses: non-poor, vulnerable, poor, and extremely poor. The results reveal that age, dependency ratio, education level, livestock and ox ownership, access to information and credit, health status, and grazing land access significantly influence poverty status. Higher dependency ratios and poor health substantially increase the likelihood of extreme poverty, while livestock ownership and access to grazing land reduce it. Notably, credit use and access to information typically considered poverty reducing were associated with increased extreme poverty risks, likely due to poor financial literacy and exposure to misinformation. These findings underscored the multidimensional and dynamic nature of poverty, driven by both structural and behavioral factors. Policy implications point to the importance of integrated interventions that promote education, health, financial literacy, and access to productive assets to ensure sustainable poverty reduction and improved rural livelihoods in Ethiopia. Full article

Understanding the spatial association network structure and carbon balance zoning of land-use carbon emissions (LUCEs) is essential for guiding regional environmental management. This study constructs a LUCE spatial association network for Hubei Province using a modified gravity model to uncover the spatial linkages in carbon emissions. Carbon balance zones are delineated by integrating LUCE network characteristics with economic and ecological indicators. To further examine the network dynamics, link prediction algorithms are employed to anticipate potential emission connections, while quadratic assignment procedure (QAP) regression analyzes how intercity differences in socioeconomic, ecological, and land-use attributes influence LUCE connectivity. The results reveal a pronounced core–periphery structure, with potential carbon spillover pathways extending toward both eastern and western cities. Based on the carbon balance analysis, six functional zones are identified, each aligned with targeted collaborative mitigation strategies. The QAP results indicate that intercity differences in innovation capacity, industrial structure, and economic development are positively associated with the formation of LUCE spatial networks, whereas disparities in urbanization level, government expenditure, and construction land use are negatively associated with LUCE connectivity. This study provides a differentiated governance framework to address the dual challenges of carbon emissions and land-use transformation in agro-urban regions. Full article

Agricultural water resource management is increasingly challenged by climate variability, land degradation, and socio-economic pressures, particularly in the Mediterranean region. This study, conducted in 2023–2024 within the REACT4MED project (PRIMA initiative), addresses sustainable water use through a comparative analysis of organic and conventional farms in the Stornara and Tara area (Puglia, Italy). The research aimed to identify critical indicators for sustainable water management and develop ecosystem restoration strategies that can be replicated across similar Mediterranean agro-ecosystems. An interdisciplinary, participatory approach was adopted, combining technical analyses and stakeholder engagement through three workshops involving 30 participants from diverse sectors. Fieldwork and laboratory assessments included soil sampling and analysis of parameters such as pH, electrical conductivity, soil organic carbon, nutrients, and salinity. Cartographic studies of vegetation, land use, and pedological characterization supplemented the dataset. The key challenges identified were water loss in distribution systems, seawater intrusion, water pumping from unauthorized wells, and inadequate public policies. Soil quality was significantly influenced by salt stress, hence affecting crop productivity, while socio-economic factors affected farm income. Restoration strategies emphasized the need for water-efficient irrigation, less water-intensive crops, and green vegetation in infrastructure channels while incorporating also the native flora. Enhancing plant biodiversity through weed management in drainage channels proved beneficial for pathogen control. Proposed socio-economic measures include increased inclusion of women and youth in agricultural management activities. Integrated technical and participatory approaches are essential for effective water resource governance in Mediterranean agriculture. This study offers scalable, context-specific indicators and solutions for sustainable land and water management in the face of ongoing desertification and climate stress. Full article