Agricultural Systems Research Articles

Designing and application of a Comprehensive Farm Assessment Index: towards efficient and relevant policy analysis

Purpose Sustainability indicators that allow integrated farm assessments have received increasing attention. However, limited evidence is available for the use of the same when assessing the agricultural sustainability of farming systems, especially in regions practising incessant monoculture. Therefore, this study aims to develop a holistic index to assess alternative farming systems based on a stock-and-flow framework. Design/methodology/approach A composite metric was developed by aggregating the economic, social and environmental indicators. The methodology involved estimation, normalisation, hierarchical weighting and progressive aggregation of indicators to form the Comprehensive Farm Assessment Index (CFAI). The CFAI was applied to assess the farming practices of 88 organic and 90 conventional farming plots across three agro-climatic zones over two cropping seasons in selected districts of Punjab, India. Findings Results showed statistical mean differences between the organic and conventional farming systems in terms of key production costs and income for wheat, rice and cotton crops. The normalised values of the selected social indicators were higher for the organic farming system. Similarly, in the environmental dimension, more biodiversity and less water contamination were found in organic farms. Except for paddy cultivation in the North–East region, the CFAI for organic farming is higher than that for conventional farming, even under the mono-cropping system with a single-crop rotation. Originality/value The CFAI has ubiquitous applications and can be used to assess alternate sustainable approaches and practices across crops and regions. It provides a perspective on the social viability and ecological sustainability of agriculture, which would enable contextual and effective policy analysis and implementation.

An Integrated Paradigm for Advanced Irrigation Systems Leveraging Internet of Things (IoT)

As the demand for precision in agriculture and effective sustainable resource management increases, there has been a lot of pressure to have more accurate and efficient soil moisture data-transmission systems. This paper includes the discussion on how machine learning (ML) and deep learning (DL) techniques can be improvise to further accuracy and performance in IoT-based smart irrigation systems. The system is based on the perception of soil moisture using IoT sensors collecting real-time environmental data in fields, such as soil moisture, temperature, humidity, and sunlight, to be transmitted to farmers or end-users using ThingSpeak and Thinger.io platforms for analysis, storage, and visualization. It enables real-time decisions and remote agricultural systems control using web page or mobile applications. The WSNs(Wireless sensor network) helps to automate irrigation and water management in agricultural sites. The developed SIS(Smart Irrigation Systems) is based on the sensor network that carries real-time information relating to moisture content in the soil, temperature, and humidity levels as very critical determinants of the proper irrigation schedule. These are analyzed every 15 minutes at the edge server. The system uses deep learning models to predict when the soil moisture falls below a threshold and automatically activates water pumps or sprinklers, which reduces human intervention and optimizes water usage in agriculture. An important part of research forms machine learning algorithms to improvise the performance. The recent advancements relies on several models, among them KNN (K-Nearest neighbors) and TimeGPT models [TimeGPT is a time-series forecasting model that utilizes the power of GPT (Generative Pre-trained Transformer) architecture to predict future values in a sequence.], in the prediction of soil moisture while achieving optimal irrigation schedules from previous available data and weather forecasting. The comparative analyses included an accuracy rate of 97 Parsant to 98 Parsant in KNN thus describing the high level of accuracy that the system can attain regarding the soil conditions and water requirements. This research provides the possibility of embedding IoT into machine learning that may form a new age smart agriculture system that, apart from irrigation automation, enhances decision-making in farmer practices. Adoption of such systems could contribute immensely to the sustainability of such agricultural practices mainly due to reduced water wastage, decrease operation costs, and improved crop yield. Integrating real-time environmental data and predictive analytics farmlands can be optimized and maintained even the land has water scarcity or difficult to receive rainfall or other climatic conditions.

AI in agriculture: Smart greenhouses and indoor farming systems

This comprehensive article examines the transformative impact of artificial intelligence on modern indoor agriculture, focusing on key technological advancements in smart greenhouse management and controlled environment agriculture. The article explores critical areas, including precision environmental control, nutrient management in hydroponic systems, plant health monitoring and disease management, harvest optimization, quality control, and energy management with sustainability practices. AI-driven solutions have revolutionized traditional farming approaches by integrating deep learning algorithms, computer vision systems, and IoT sensor networks, enabling unprecedented levels of automation, resource efficiency, and crop yield optimization. Implementing these technologies has significantly improved agricultural metrics, from disease detection and prevention to harvest timing and quality assessment, while substantially reducing operational costs and environmental impact.

A systematic study of intercropping agricultural system using fuzzy and inverse fuzzy hypersoft hypergraph

A systematic study of intercropping agricultural system using fuzzy and inverse fuzzy hypersoft hypergraph

Historical Roots of Heritage Horticulture in the Southern Coastal Plain of Israel

This study reconstructs the agricultural landscape of the southern coastal plain of late Ottoman and British Mandatory Palestine (today southwestern Israel) utilizing late 19th and early 20th century cartographic materials and aerial photographs. Immense human effort and ingenuity were required to maintain sustainable agricultural on the fringes of the desert. Given today’s increasingly severe climate crisis, the lessons drawn from these historical agricultural practices have particular resonance. The agricultural land use described in this work extended into the coastal dunes of the region where the shallow water table was exploited to create complex agricultural systems that enabled the growth of citrus trees, grapes, and other crops for export and trade. Aerial photos and maps reveal the critical aspects of this region’s neglected agricultural history. The stability and resilience of these systems, some of which are still in existence 76 years or more after they were abandoned, as seen in the survey conducted for this study, point to the importance of understanding and preserving this chapter of the region’s agricultural heritage. The unique varieties of fruit trees adapted to the local climate of the western Negev still have significant economic value and are threatened with extinction from rapid urban encroachment. The remnants of this tradition serve as historical testimony of a bygone agricultural era which was replaced by mechanized monoculture. The discussion centers on the ways n which the study of heritage agriculture in rapidly changing areas can contribute to the broader field of historical geography by reconstructing landscapes that preserve the knowledge and societal patterns of behavior of past communities for future generations.

Advancing sustainable agriculture through multi-omics profiling of biosolids for safe application: A review.

Biosolids, derived from wastewater treatment processes, are valuable resources for soil amendment in agriculture due to their nutrient-rich composition. However, various contaminants of concern (CEC) such as pharmaceuticals, per-and poly-fluoroalkyl substances, endocrine disruptive chemicals, surfactants, pathogens, nanoplastics, and microplastics, are also reported in biosolids. The use of biosolids for agriculture may introduce these CEC into the soil, which raises concerns about their environmental and human health impacts. Moreover, the presence of pathogens (Escherichia coli, Salmonella sp., Shigella, Giardia, Rotavirus, etc.) even after treatment calls for microbial profiling of biosolids, especially in developing countries. Multi-omics approaches can be used as powerful tools for characterizing microbial communities and highlighting metabolic pathways. Moreover, these approaches also help in predicting the ecological and agronomic effects of biosolids application in agricultural soils. This review discusses the advantages and challenges of using biosolids in agriculture, considering the range of different CEC reported in biosolids. Moreover, the current legislation for the use of biosolids in agriculture is also presented, highlighting the limitations with respect to guidelines for emerging contaminants in biosolids. Furthermore, the role of the multi-omics approach in biosolids management, focusing on genomics, transcriptomics, proteomics, and metabolomics is also assessed. Multi-omics also allows for real-time monitoring, ensuring continuous optimization of biosolids towards changing environmental conditions. This dynamic approach not only enhances the safe use, but also enhances the sustainability of waste management practices, minimizing the negative effects. Finally, the future research directions for integrating the multi-omics approach into biosolid management practices are also suggested. The need for updating the legislative framework, continued innovation to promote sustainable and robust agricultural systems, bringing the process closer to the principles of a circular bioeconomy is also empahasized.

Detection and quantification of true proteins, casein fractions, and their genetic variants, and whey proteins in goat milk by Reverse-Phase High-Performance Liquid Chromatography.

The protein profile of milk is an increasingly important research topic in relation to the technological properties of milk for cheese-making and value of it for human nutrition. Goats are a valuable source of milk worldwide, but there is no precise and rapid method for the simultaneous identification and quantification of the genetic variants of the major protein fractions. In this study we devised a method for the rapid identification and quantification of the main genetic variants of αS1-, αS2-, β- and κ- caseins, and of α-lactalbumin and β-lactoglobulin (whey proteins) in caprine milk using an HPLC-UV reverse-phase C8 column. The R2 of the calibration equations was > 0.99 for all 15 protein fractions identified. A total of 520 milk samples were taken from 260 goats (in duplicates) of 6 different breeds reared on 22 farms operating different farming systems, ranging from traditional/extensive to modern/intensive, and analyzed them to externally validate the method. Milk samples from DNA-genotyped goats were used to identify the genetic variants of the caseins. Compared with other studies, with our method we were able to separate the main genetic variant of caseins within a total run time of 24 min and with a repeatability > 92% for all fractions except for the C variant of κ-casein. Farms were found to be the major source of the variability in the contents of true proteins (56.1% of total variance), true caseins (48.6%), κ-casein C (50.6%) and whey proteins (52.9-62.9%) in goats' milk, whereas individual goat within farm was the most important source of variability in the contents of individual caseins and their genetic variants (53.9% to 94.7%).

Maize monoculture supported pre-Columbian urbanism in southwestern Amazonia.

The Casarabe culture (500-1400 CE), spreading over roughly 4,500 km2 of the monumental mounds region of the Llanos de Moxos, Bolivia, is one of the clearest examples of urbanism in pre-Columbian (pre-1492 CE) Amazonia. It exhibits a four-tier hierarchical settlement pattern, with hundreds of monumental mounds interconnected by canals and causeways1,2. Despite archaeological evidence indicating that maize was cultivated by this society3, it is unknown whether it was the staple crop and which type of agricultural farming system was used to support this urban-scale society. Here, we address this issue by integration of remote sensing, field survey and microbotanical analyses, which shows that the Casarabe culture invested heavily in landscape engineering, constructing a complex system of drainage canals (to drain excess water during the rainy season) and newly documented savannah farm ponds (to retain water in the dry season). Phytolith analyses of 178 samples from 18 soil profiles in drained fields, farm ponds and forested settings record the singular and ubiquitous presence of maize (Zea mays) in pre-Columbian fields and farm ponds, and an absence of evidence for agricultural practices in the forest. Collectively, our findings show how the Casarabe culture managed the savannah landscape for intensive year-round maize monoculture that probably sustained its relatively large population. Our results have implications for how we conceive agricultural systems in Amazonia, and show an example of a Neolithic-like, grain-based agrarian economy in the Amazon.

Utilization of Microalgae and Duckweed as Sustainable Protein Sources for Food and Feed: Nutritional Potential and Functional Applications.

Aquatic biomass, particularly microalgae and duckweed, presents a promising and sustainable alternative source of plant-based protein and bioactive compounds for food and feed applications. This review highlights the nutritional potential of these aquatic species, focusing on their high protein content, rapid growth rates, and adaptability to nonarable environments. Microalgae, such as Chlorella and Arthrospira spp., and duckweed, such as Lemna minor, are evaluated for their functional food applications, including their roles as protein supplements, bioactive components, antioxidants, and emulsifiers in food formulations. The study also examines their environmental benefits, including wastewater bioremediation, nutrient recycling, and greenhouse gas mitigation, which contribute to a more sustainable agricultural system. Technological advancements in the cultivation, harvesting, and processing of microalgae and duckweed are discussed to enhance their scalability and economic feasibility in food and feed production. The findings suggest that integrating microalgae and duckweed into agricultural and food systems can significantly improve food security, nutritional outcomes, and sustainability. Future research should focus on optimizing cultivation efficiencies, advancing protein extraction techniques, and expanding the applications of aquatic biomass in various food products.

Analysis of past and future temperature variability and change in Southern Ethiopia

Purpose This study aims to analyze the temperature variability and change for the past 30 years (1990–2019) and the future 60 years (2030s, 2050s and 2070s) in Wolaita Zone and the surroundings, in Southern Ethiopia. Design/methodology/approach The temperature (maximum and minimum) data of the past 30 years (1990–2019) of ten meteorological stations and the future (2021–2080) data of regional climate models (RCMs) under two representative concentration pathways (RCP4.5 and RCP8.5) were used in this study. The accuracy of RCMs in representing observed temperature data was evaluated against mean absolute error, root-mean-square error, percent bias, Nash–Sutcliffe measure of efficiency, index of agreement (d) and coefficient of determination (R2). The temperature variability was analyzed using the coefficient of variation, and the trend was determined using the Mann–Kendall trend and Sen’s slope tests. Findings The results indicate that the past maximum (Tmax) and minimum (Tmin) temperatures showed low variability (CV = 4.3%) with consistently increasing trends. Similarly, Tmax and Tmin are projected to have low variability in the future years, with upward trends. The Tmax and Tmin are projected to deviate by 0.7°C–1.2°C, 1.3°C–2.2°C and 1.5°C–3.2°C by 2030s, 2050s and 2070s, respectively, under RCP4.5 and RCP8.5, from the baseline. Thus, it can be concluded that temperature has low variability in all periods, with consistently increasing trends. The increasing temperature could have been affecting agricultural production systems in Southern Ethiopia. Research limitations/implications This research did not remove the uncertainties of models (inherited errors of models) in future temperature projections. However, this study did not have any limitation. Therefore, individuals or organizations working on agricultural productivity, food security and sustainable development can use the results and recommendations. Practical implications The globe has been warming due to the increasing temperature; as a result, many adaptation and mitigation measures have been suggested globally and nationally (IPCC, 2021). FAO (2017) indicates that the level of vulnerability to the impacts of climate change varies with geographic location, economy and demography; the adaptation measures need to be local. The detailed information on temperature variability and change in the past and future helps to understand the associated negative impacts on agriculture, hydrology, biodiversity, environment and human well-being, among others. Social implications The projected future climate pattern helps the country devise proactive adaptation and mitigation measures for the associated damages at different levels (from local to national). This could improve the resilience of farmers and the country to climate change impacts. This contributes to achieving sustainable development goals (e.g. no poverty, zero hunger and climate action). This is because the agriculture sector in Ethiopia accounts for 80% of employment, 33% of the gross domestic product and 76% of exports (EPRSS, 2023). Originality/value Temperature is one of the major climate elements affecting agricultural production in rain-fed production systems. Despite this, past studies in Southern Ethiopia considered only the past temperature but not the future climate. Thus, generating detailed information about past and future temperatures is very important to take proactive adaptation measures for reducing climate-associated damages in the agriculture sector in Ethiopia.

Management Practices at Poultry Demonstration Centres for Boosting Backyard Poultry Farming System in Ramban District of Jammu & Kashmir, India: A Review

The Backyard poultry farming is an age-old practice in India and plays an important role to reduce poverty among the most under-privileged sections of the Jammu & Kashmir, particularly in far flung areas of rural J&K, India. There is not any specific arrangement required for backyard poultry farming and is mostly popular in backward and resource-deprived areas of J&K and provides rural families with good source of income, healthy food sources in terms of meat and eggs. Backyard poultry farming improves the status of women in rural communities, creates jobs for rural residents, and closes the gap between supply and demand for chicken products, such as meat and eggs. The high mortality rate among chicks due to frequent disease outbreaks, lack of a framework, lower potential of Desi chickens, lack of scientific information, predation, hunger, climate change, and year-round fluctuations in feed supply and price are some of the major drawbacks of backyard poultry farming in J&K. This farming needs to be improved because it is the best way for J&K's marginal and small farmers to supplement their income with relatively little investment. Nonetheless, the J&K government has started 29 projects under the Holistic Agriculture growth Programme (HADP), of which P25 is only focused on the growth of poultry in J&K. Backyard poultry farming results in socio-economic development, nutritional and livelihood security, empowerment of women etc. among rural people. Birds are kept mostly on scavenging system, where they acquire their feeds through natural foraging, kitchen wastes etc. Rural poultry farming has been responsible to produce 40 per cent meat and 44 per cent egg requirement in J&K. Chicken eggs and meat are the only cheapest and best sources of protein, vitamin and minerals with high biological value for rural poor and marginal sections of people. The additional income earned from indigenous chicken farming has improved their socio- economic stability.

The Role of Gut Microbiota in Shaping Immune Responses in Tephritidae Fruit Fly and Prospective Implications for Management.

The interaction of microbial communities with host immunity has become one of the most explored research areas with significant implications for pest control strategies. It has been found that the gut microbiota plays substantial roles in immune response regulation and host-gut microbiome symbiosis, as well as in pathogen resistance and overall fitness in Tephritidae fruit flies that are major pests of agricultural importance. In this review, we discuss the modulation of immune responses of Tephritidae fruit flies by the gut microbiota with particular emphasis on the general interactions between microbiota and the immune system. These interactions help to unravel new horizons of pest management. Regulating gut microbiota modifies the performance of biological control agents and SIT and allows the creation of microbial therapies that affect the vital physiological functions of fruit flies. Besides, deploying microbes that can modulate the immune response and using microbial-derived signals provide an eco-friendly and more sustainable way of eradicating chemical pesticides and making farming systems less susceptible to climatic variability. This paper reviews various aspects of the possibility of using gut microbiota for changing the approach to Integrated Pest Management (IPM) programs that would improve methods of controlling Tephritidae fruit fly populations more ecologically.

Unveiling the rhizosphere microbiome of Dendrobium: mechanisms, microbial interactions, and implications for sustainable agriculture

The rhizosphere microbiome plays a critical role in plant health and productivity by fostering beneficial microbial interactions that support nutrient cycling, stress tolerance, and disease suppression. In the context of Dendrobium, understanding its interactions is essential for optimizing cultivation and promoting sustainable agricultural practices. This review explores the rhizosphere microbiome of Dendrobium, focusing on the mechanisms and microbial interactions that contribute to plant health, stress tolerance, and growth and their implications for sustainable agriculture. This study highlights the diverse composition of microbial communities in the Dendrobium rhizosphere, including key bacteria (e.g., Pseudomonas fluorescens and Bacillus subtilis), fungi (e.g., Glomus spp.), and biocontrol agents (Trichoderma spp.), and discusses their roles in nutrient cycling, disease suppression, and plant growth promotion. This review emphasizes the significance of plant-microbe signaling, such as the production of flavonoids, phytohormones, and strigolactones, in shaping the microbial environment and enhancing plant resilience. Additionally, it addresses modern techniques for analyzing microbial communities, including metagenomics and next-generation sequencing, and their applications in advancing precision agriculture. Future research should focus on bridging knowledge gaps related to genotype-microbiome interactions, exploring emerging microbial consortia and enhancing the integration of microbiome management in precision agriculture systems to improve plant health and productivity.

The shifting of buffer crop repertoires in pre-industrial north-eastern Europe

This study explores how major climatic shifts, together with socioeconomic factors over the past two millennia, influenced buffer crop selection, focusing on five crops: rye, millet, buckwheat, oat, and hemp. For this study, we analyzed archaeobotanical data from 135 archaeological contexts and historical data from 242 manor inventories across the northeastern Baltic region, spanning the period from 100 to 1800 AD. Our findings revealed that rye remained a main staple crop throughout the studied periods reflecting environmental adaptation to northern latitudes. The drought-tolerant and thermophilic millet crop exhibited resilience during the adverse dry climatic conditions of the Medieval Climatic Anomaly while showing a significant decline during the Little Ice Age. During the period of post-1500 AD, a significant shift towards cold-resilient summer crops such as buckwheat and hemp is recorded. This study enhances our understanding of how historical agricultural systems responded to both socioeconomic factors and climatic change in northern latitudes, offering notable potential solutions for modern agricultural practices in the face of future climate variability trends.

Decomposition and nutrient release from shoot of legumes cover crops

The cover crops can reduce soil exposure and erosion while enhancing nutrient cycling for crops. Effective implementation requires understanding how cover crops decompose and release nutrients to align with crop demand. This research assessed the decomposition rates and nutrient release of various legume residues commonly used as green manure or cover crops in agricultural systems. The study took place in a nutrient-deficient Red-Yellow Ultisol, using a split-plot design with different legume cover crop species: Crotalaria juncea, Crotalaria spectabilis, Cajanus cajan, Cajanus cajan (L.) Millsp), Dolichos lablab, Canavalia ensiformis and Mucuna aterrima as the main plots and six evaluation periods: 0, 30, 60, 90, 120, and 150 days after incorporation (DAI) as the subplots. Initial mass losses were observed in the first 60 days, followed by a slower decline over the study period. The order of nutrient accumulation in biomass was found to be: K > N > P > Ca > Mg. The Dolichos lablab species had the slowest decomposition rate, with a half-life of 43 days, while Cajanus cajan had the fastest, with a half-life of 65 days. Potassium reached its maximum by 30 DAI, indicating a rapid transfer to the soil. Nitrogen, P, and K contents decreased during different vegetative phases, highlighting the importance of proper timing for legume management. Hemp, Crotalaria spectabilis, Dolichos lablab, and Canavalia ensiformis were suitable for short-cycle vegetables due to rapid nutrient availability. Conversely, Cajanus spp., and Mucuna aterrima were better for extended soil coverage and slow nutrient release.

The potential of arbuscular mycorrhizal fungi to improve soil organic carbon agricultural ecosystems: A meta‐analytical approach

Abstract Increasing soil organic carbon (SOC) in agroecosystems is a key objective for enhancing agricultural sustainability and mitigating climate change. Arbuscular mycorrhizal fungi (AMF) can increase yield and provide several other ecosystem services. Still, studies conducted in agricultural soils have shown that their effects on SOC can be either positive, neutral or negative. In this study, we conducted a quantitative review of the literature to evaluate the role of AMF in influencing SOC across various crop species and conditions. Through a systematic search of publications, we compiled a dataset comprising 62 trials from 19 studies including field and pot experiments that directly manipulated the mycorrhizal status of plants. We conducted a meta‐analysis to quantitatively evaluate the role of AMF on SOC across several crop species and conditions. We found an overall positive effect of AMF on SOC, with an average increase of 21.5%. However, this positive effect was statistically significant only in pot experiments whereas in field experiments, the effect was mainly modulated by texture and organic matter content. The effect of AMF on SOC did not vary with crop species' functional type, AMF inoculation sources (single or mixed AMF species) or other soil variables considered. Our results highlight the significant potential for AMF‐mediated mechanisms to promote SOC accumulation in agricultural soils, although this effect is context‐dependent. However, future research with different approaches and scales is needed to evaluate the impact of AMF on SOC dynamics in agricultural systems and elucidate the mechanisms behind their contribution to SOC accrual. Read the free Plain Language Summary for this article on the Journal blog.

Gender and antimicrobial resistance: a conceptual framework for researchers working in livestock systems

BackgroundTo promote gender mainstreaming in future AMR research projects and policy implementation within livestock and other systems, researchers need to embrace gender-responsive research methodologies. Ignoring gender considerations can lead to unsustainable interventions and exacerbate existing equity gaps. Incorporating gender analysis is crucial for identifying data collection needs and opportunities to develop gender-responsive research programs and policies.ObjectivesWe have developed a conceptual framework and a set of research questions designed to enhance the gender-responsiveness of AMR research in livestock systems.MethodsA narrative review previously identified three key entry points for gender dynamic impacting AMR in agricultural systems: gendered antimicrobial resistance exposure, gendered antimicrobial use and gendered outcomes of antimicrobial resistance infections. This information was then analyzed using a health system gender framework. Combining these insights, we developed a comprehensive list of research questions.ResultsWe developed comprehensive list of gender-related questions. Given the limited understanding of how gender dynamics and norms influence AMR, we have primarily proposed qualitative, exploratory questions. These questions are categorized into two types: integrated and strategic. Integrated questions offer a deeper understanding of gender dynamics and norms in livestock systems with the aim of improving them, while strategic questions focus on gender-related issues in livestock as entry points, highlighting some of the mechanisms behind these gender issues to progress towards gender equality.ConclusionAs gender-analysis in livestock research gains prominence, there is an increasing expectation for AMR researchers to integrate gender considerations into their work. This framework provides a starting point for researchers aiming to enhance gender inclusivity and considerations in AMR research within livestock systems. The next phase of our project will involve applying this framework in the field, where a real-life application will enable its validation and further refinement.

Climate Change and Agricultural Nitrogen Losses: A Review of Mitigating Strategies for Soil, Water, and Environmental Protection

Climate change presents considerable challenges to agricultural systems, particularly regarding nitrogen (N) dynamics within ecosystems. While nitrogen is crucial for plant growth, its overuse in agriculture results in environmental issues such as water pollution, soil degradation, and increased greenhouse gas emissions. This review summarizes current understanding of the interactions between climate change and agricultural nitrogen losses, emphasizing their implications for soil, water, and environmental quality. We explore various strategies to improve nitrogen use efficiency (NUE) while minimizing environmental losses. These strategies include adopting precision agriculture techniques, using cover crops and crop rotation, implementing controlled-release fertilizers, and integrating agro ecological practices. We also discuss the importance of policy frameworks and farmer education in promoting sustainable nitrogen management. By addressing the complex challenges posed by climate change, this review aims to provide a comprehensive overview of effective practices that can protect soil health, safeguard water resources, and contribute to a more resilient agricultural future. Through coordinated efforts among researchers, practitioners, and policymakers, we can reduce nitrogen losses and enhance the sustainability of agricultural systems in a changing climate.

Chitosan-Coated Alginate Matrices with Protein-Based Biostimulants: A Controlled-Release System for Sustainable Agriculture

Developing biodegradable complex fertilizers is crucial for sustainable agriculture to reduce the environmental impact of mineral fertilizers and enhance soil quality. This study evaluated chitosan-based hydrogel coatings for sodium alginate matrices encapsulating amino acid hydrolysates from mealworm larvae, known for their plant growth-promoting properties. The research aims to identify the potential of biopolymer matrices for producing biodegradable slow-release fertilizers and to outline future development pathways necessary for this technology to be usable in the fertilizer industry. Chitosan coatings prepared with citric acid and crosslinked with ascorbic acid optimized plant growth, while those using acetic acid negatively affected it. Water absorption and nutrient release tests showed that chitosan coatings reduced water uptake and slowed initial nutrient release compared to uncoated samples. Leaching assays confirmed controlled-release behavior, with an initial burst followed by stability, driven by alginate–chitosan interactions and ion exchange. The X-ray diffraction (XRD) analysis revealed that adding hydrolysate and chitosan increased amorphousness and reduced porosity, improving structural properties. Thermogravimetric analysis (TGA) and Fourier-transform infrared (FTIR) spectroscopy demonstrated enhanced homogeneity and the presence of chemical interactions, which led to improvements in the material’s thermal stability and chemical characteristics. Biodegradation tests indicated greater durability of chitosan-coated composites, although hydrolysate incorporation accelerated decomposition due to its acidic pH. Germination tests confirmed no phytotoxicity and highlighted the potential of biopolymeric matrices for slow nutrient release. These findings indicate the possibilities of chitosan-coated alginate matrices as sustainable fertilizers, emphasizing the importance of adjusting coating composition and hydrolysate pH for enhanced efficacy and environmental benefits. The main recommendation for future research focuses on optimizing the chitosan coating process by exploring whether adding hydrolysate to the chitosan solution can reduce diffusional losses. Additionally, investigating the use of glycerol in the alginate matrix to minimize pore size and subsequent losses during coating is suggested. Future studies should prioritize analyzing percentage losses during the crosslinking of the alginate matrix, chitosan coating, and final shell crosslinking. This pioneering research highlights the potential for encapsulating liquid fertilizers in biopolymer matrices, offering promising applications in modern sustainable agriculture, which has not been studied in other publications.

Can Digitalization Improve China's Food Security?

ABSTRACTAs global food security continues to be extremely challenging, countries are seeking optimal solutions for the sustainable development of their agriculture and food systems under environmental and resource pressures. This study explores whether and how digitalization facilitates or hinders China's food security. Based on data from the Food and Agriculture Organization (FAO), World Bank, and United Nations E‐Government survey, we assess digital transformation in terms of digital infrastructure, competition, innovation, and digital governance using the entropy method. Specifically, we use ordinary least‐squares and robust and ridge regressions to estimate the impact of digitalization on food security in China during 2000–2021. The results indicate that digitalization improves food security through production and transaction enablement. Namely, digital infrastructure and competition significantly contribute to food availability, accessibility, and utilization. In addition, digital innovation experiences synergies with other digital indicators to improve food security. However, digital governance decreases food sustainability because of premature digital governance, as well as a lack of digital talent, investment, and technical support. Thus, to increase food security, it is essential to upgrade the digital infrastructure, accelerate digital innovation, cultivate digital talents, improve digital governance, and make full use of digital enabling in production as well as the market.