Enhance Food Security Research Articles

Contributions of urban productive safety net program to enhancing food security and livelihood diversification: an in-depth analysis of household-Level perceptions among urban populations in Ethiopia

AbstractThe Urban Productive Safety Net Program is one of Africa’s most ambitious social protection initiatives, and it has achieved measurable successes. However, existing literature focusing on the role of programs in improving people’s lives, especially in ensuring food security and income diversification, gives more focus to rural areas and depends on data from individuals beyond those directly targeted by the program. Hence, this study examines beneficiaries’ perceptions of the program’s contribution to food security and livelihood diversification in the South Ethiopia Regional State. The study used a mixed research approach that included a questionnaire, interviews, observation, and focus group discussions. To select 310 survey household heads, a multistage sampling procedure was employed. We analyzed the quantitative data using SPSS version 27, while the qualitative data was analyzed through narration and summarization. The findings indicate that the selection process for beneficiaries, activities performed by public work groups, and beneficiaries graduating with reliable sources of income are generally positive, whereas negative assumptions exist regarding the adequacy and timeliness of cash transfers and the overall living status of residents. Therefore, the program managers and zonal-level team leaders should collaborate closely to directly engage with beneficiaries, monitor the support system, and raise awareness.

Recombinant Breeding in Barnyard Millet (Echinochloa frumentacea. L): Pioneering High-yield Varieties for Sustainable Agriculture

The development of new crop varieties, including barnyard millet, typically spans 6 to 9 years, a process that began with breeding efforts initiated in 2008. The breeding work involved initial crossings, followed by selection starting from the F2 generation, which achieved stabilization in the F5 generation with the identification of the best plants. The resulting high-yielding, medium-maturing barnyard millet variety, DHBM-93-3, was developed at the Agricultural Research Station in Hanumanamatti, under the University of Agricultural Sciences, Dharwad. This variety matures in 85 to 90 days, features an erect growth habit with a height ranging from 132 to 147.5 cm, and produces bold, oval-shaped grains of gray color. DHBM-93-3 has demonstrated an impressive grain yield of 23.20 q/ha and a fodder yield of 6.33 t/ha, along with remarkable tolerance to shoot fly infestation (0.0%). Notably, this variety outperformed national checks VL-172 and VL-207, with yield increases of 27.17% and 12.59%, respectively. In preliminary and station trials conducted between 2010 and 2013, DHBM-93-3 achieved an average seed yield of 39.24 q/ha, significantly exceeding RAU-11 and VL-207 by 42.17% and 16.82%. Over a three-year evaluation period, it consistently yielded 23.20 q/ha, surpassing VL-172 and VL-207 by 27.15% and 12.59%, respectively. The varieties exceptional adaptability was highlighted by significant yield increases across various states, particularly in Andhra Pradesh, where it exceeded VL-172 by 108.5%. DHBM-93-3 also exhibited superior disease resistance, with a mean grain smut incidence of 2.46%, compared to 10.06% for VL-172 and 15.93% for VL-207, as well as complete resistance to head smut. Furthermore, it showed outstanding resilience against shoot fly infestation, maintaining a consistent infestation rate of 0.0%. Nutritionally, DHBM-93-3 excelled in zinc (36.8 mg/kg), iron (12.5 mg/kg), and calcium (14 mg/kg) content, although its protein content was slightly lower than that of VL-172. DHBM-93-3 represents a highly productive and resilient variety, capable of enhancing food security and addressing micronutrient deficiencies, thus positioning it as an excellent choice for cultivation across diverse agro-climatic regions of India.

Advancements in Hydroponic Systems: A Comprehensive Review

Hydroponics, the practice of growing plants without soil using mineral nutrient solutions in water, represents a significant shift in agricultural methodologies. Modern hydroponic systems have evolved substantially since the early 20th century, with advancements in system design, automation, nutrient management, and environmental control enhancing efficiency, scalability, and applicability. This review examines recent innovations that have addressed traditional challenges and created new opportunities for hydroponic cultivation. Hydroponics offers advantages over traditional soil-based agriculture, including precise nutrient control, reduced water usage, and the elimination of soil-borne diseases and pests. These benefits are critical in addressing modern agricultural challenges such as soil degradation, water scarcity, and the need for increased food production for a growing global population. Hydroponic systems can be implemented in diverse environments, making them adaptable solutions for enhancing food security and sustainability. Key developments in various hydroponic systems are highlighted, including the Nutrient Film Technique (NFT), Deep Water Culture (DWC), Ebb and Flow, Aeroponics, Wick Systems, and Drip Systems. Innovations in these systems focus on optimizing nutrient delivery, oxygenation, and integrating sensors for precise control, improving overall performance and yield. Technological advancements, such as automation and control systems, sensors, and monitoring technologies, have revolutionized hydroponic farming by enabling real-time data collection and environmental management. The integration of the Internet of Things (IoT) and smart farming practices, combined with data analytics and machine learning, has further optimized system performance and decision-making. LED lighting and vertical farming techniques have maximized space utilization and improved crop yields, particularly in urban environments. Advances in nutrient solutions, disease management, and water quality have optimized plant health and resource efficiency. Economic and environmental considerations, including cost-benefit analyses and comparisons with traditional agriculture, highlight the potential for hydroponics to offer better returns on investment and reduce environmental impact. Despite the significant progress, challenges such as high initial setup costs and technical complexities remain. Future research opportunities and interdisciplinary collaborations are essential to address these challenges and drive further innovation in hydroponic farming.

Part-Time Farming, Agricultural Socialized Services, and Organic Fertilizer Use: Implications for Climate Change Mitigation

The adoption of organic fertilizers is essential for advancing China’s green agricultural transformation, ensuring food security, and supporting agricultural adaptations. However, several challenges hinder its widespread use in rural areas. This study examines how part-time farming and agricultural service provision influences organic fertilizer use, employing fixed and random effects models on data from 523 households in Shaanxi Province, one of China’s main apple-producing regions. The results reveal: (1) Part-time farming reduces organic fertilizer use by 7.6%, primarily due to labor shortages; (2) Higher non-farm income exacerbates this decline, particularly for Type II part-time farmers; and (3) Mechanized fertilization services help mitigate this reduction. These findings offer valuable policy insights for promoting organic fertilizer adoption in the context of shifting rural labor dynamics and highlight the complex interactions between farming practices and labor migration in the broader trajectory of organic fertilizer use. Moreover, this study highlights the role of organic fertilizer use in enhancing food security while also helping to reduce the carbon footprint of the crop sector in China.

Breeding for Pest and Disease Tolerance High Yielding Variety (DHLM-36-3-1) in Little Millet (Panicum sumetrense. L)

Developed from 2008 to 2013 and evaluated between 2010 and 2014, the high-yielding medium-maturing little millet variety DHLM-36-3-1 was officially released and notified in 2018, showing its potential as an excellent variety. This cultivar, developed at the Agricultural Research Station in Hanumanamatti, University of Agricultural Sciences, Dharwad, is well-suited to the state of Karnataka. It matures in 85 to 90 days and features an erect growth habit, reaching heights of 112 to 130 cm, with bold, oval-shaped grains of light black color. DHLM-36-3-1 demonstrated a grain yield of 14.29 q/ha and a fodder yield of 5.6 t/ha, showing good tolerance to shoot fly infestation (15.50%) compared with the national check JK-8, which recorded a 20.34% infestation rate. Furthermore, DHLM-36-3-1 outperformed both national checks OLM-203 and JK-8 by 9.59% and 11.21%, respectively, in terms of grain yield. Similarly, the newly developed variety DHLM-14-1 has yielded promising results across various trials conducted throughout India, demonstrating its potential as a high-yielding and nutritionally rich option for farmers. Over three growing seasons, DHLM-14-1 achieved an impressive average seed yield of 35.12 q/ha, exceeding the local check TNAU-63 by 18.56% and the national check OLM-203 by 12.06%. It has consistently performed well in All India Coordinated Trials, showing adaptability across diverse agro-climatic conditions, with notable yield improvements in states such as Andhra Pradesh, Jharkhand, and Tamil Nadu. Nutritional assessments highlight DHLM-14-1's superior mineral profile, boasting higher levels of zinc (4.06 mg/100 g) and calcium (3.45 mg/100 g) compared to national checks, while its iron content (16.2 mg/100 g) significantly surpasses that of OLM-203. Additionally, disease resistance evaluations revealed that DHLM-14-1 maintained lower incidence rates for grain smut and brown spots, with competitive resistance to shoot fly. Collectively, these findings emphasize DHLM-14-1's vital role in promoting sustainable millet production, enhancing food security and farmer livelihoods, supporting integrated pest management strategies, and improving the nutritional quality of staple diets in areas with micronutrient deficiencies.

How to make land use policy decisions: Integrating science and economics to deliver connected climate, biodiversity, and food objectives

Land use change is crucial to addressing the existential threats of climate change and biodiversity loss while enhancing food security [M. Zurek et al., Science 376, 1416-1421 (2022)]. The interconnected and spatially varying nature of the impacts of land use change means that these challenges must be addressed simultaneously [H.-O. Pörtner et al., Science 380, eabl4881 (2023)]. However, governments commonly focus on single issues, incentivizing land use change via "Flat-Rate" subsidies offering constant per hectare payments, uptake of which is determined by the economic circumstances of landowners rather than the integrated environmental outcomes that will be delivered [G. Q. Bull et al., Forest Policy Econ. 9, 13-31 (2006)]. Here, we compare Flat-Rate subsidies to two alternatives: "Land Use Scenario" allocation of subsidies through consultation across stakeholders and interested parties; and a "Natural Capital" approach which targets subsidies according to expected ecosystem service response. This comparison is achieved by developing a comprehensive decision support system, integrating new and existing natural, physical, and economic science models to quantify environmental, agricultural, and economic outcomes. Applying this system to the United Kingdom's net zero commitment to increase carbon storage via afforestation, we show that the three approaches result in significantly different outcomes in terms of where planting occurs, their environmental consequences, and economic costs and benefits. The Flat-Rate approach actually increases net carbon emissions while Land Use Scenario allocation yields poor economic outcomes. The Natural Capital targeted approach outperforms both alternatives, providing the highest possible social values while satisfying net zero commitments.

Machine learning-based crop type detection and vegetation mon-itoring using Sentinel-1 SAR and Landsat 8

This study explores the use of machine learning for crop type detection and vegetation monitoring in arid and semi-arid regions, specifically in Biskra and Khenchela, Algeria. Traditional field-based agricultural monitoring is labor-intensive and limited in spatial coverage, prompting the need for more efficient and scalable methods. The research integrates Synthetic Aperture Radar (SAR) data from Sentinel-1 and optical imagery from Landsat 8 to enhance the classification of different crop types and track vegetation dynamics. Key metrics such as radar backscatter and Normalized Difference Vegetation Index (NDVI) are employed to distinguish between irrigated and rainfed crops. The Random Forest algorithm is utilized for classification, with training data derived from field surveys, high-resolution satellite imagery, and existing land cover maps. The Google Earth Engine (GEE) platform facilitates large-scale data processing, providing real-time agricultural analysis. Over the 12-month study period (January to December 2020), the integrated approach demonstrated high accuracy, achieving over 85% precision in classifying key crops such as date palms, cereals, and vegetables. Results indicate that SAR and NDVI data provide complementary insights into vegetation health, phenology, and agricultural practices in different climatic zones. This methodology offers a promising solution for improving agricultural monitoring and resource management in arid and semi-arid regions, enhancing food security and optimizing water usage. The study’s findings also underscore the value of satellite-based remote sensing for large-scale, real-time agricultural analysis.

Crop Diversification in India (1990–2016): Implications for the Eastern and Northeastern States

This study utilises data from the Agriculture Census for 1990–1991, 2005–2006 and 2015–2016, employing the Herfindahl-Hirschman Index (HHI) to assess crop diversification in Indian states. The overall HHI declined from 1990–1991 to 2015–2016, indicating increased crop diversification nationally. However, the proportion of states exceeding the overall average HHI significantly decreased, indicating a shift towards specialisation or monoculture in some states. The analysis notes a decrease in the gross cropped area (GCA) under total food crops (TFC) and an increase in total non-food crops (TNFC). Despite the overall decline in TFC, high-value crops like horticultural produce, sugar crops, spices, and condiments have seen improvement. Focusing on the Eastern region (ER) and the Northeastern region (NER), the study reveals diversification in NER due to higher allocation of land to high-value crops, while economically disadvantaged states in the ER, such as Bihar and Odisha, show a trend towards crop specialisation, potentially affecting overall food security in the region. The study emphasises the need for government support to address persistent vulnerabilities in poverty, unemployment, and low yields in cereals, pulses, and oilseeds in these regions, recommending inputs, infrastructure development, insurance, and market linkages for perishable items to enhance food security.

Artificial Neural Network Modeling to Predict Electrical Conductivity and Moisture Content of Milk During Non-Thermal Pasteurization: New Application of Artificial Intelligence (AI) in Food Processing

This study proposed applying artificial intelligence (AI) to predict the actual electrical conductivity (EC) of raw and pasteurized milk using moderate electric field (MEF) based on the electric field strength (EFS) and mass flow rate (MFR) along with modeling moisture content (MC) based on the EC. To this end, an artificial neural network (ANN) was implemented for conventionally (CP) and non-thermally (NP) pasteurized milk. The findings indicated no significant difference (p > 0.05) between the experimental and predicted data for EC and MC. The MFR and EFS affected the actual EC. The raw milk samples had an EC of 0.468812–0.46913 S/m and MC of 87.3218–87.35941%, while these values in NP pasteurized milk were 0.457441–0.638224 S/m and 87.33986–87.40851%. With correlation coefficients (R) of 0.736478106–0.951840323 and mean square errors (MSE) of 0.005539–0.0064, the ANN accurately predicted the raw and pasteurized milk MC based on the EC using the sixth-order polynomial model and the EC based on the EFS and MFR using a quadratic model. The EC of pasteurized milk by NP was significantly (p < 0.05) lower than that of CP and raw dairy by 15.44% and 11.30%, respectively. The results show that the EFS and MFR might be used for the online assessment of milk’s physical attributes (e.g., EC), followed by using the assessed parameter to determine other properties (e.g., MC) by developing AI approaches based on optimized models. These observations showcase the innovative use of ANN-based AI to predict milk’s EC and MC accurately. Integrating such AI platforms into non-thermal food processing could eventually develop more sustainable food production and enhance food security and quality through process innovation and sustainable manufacturing, contributing to the industrial revolution and sustainable development goals.

Spatio-Temporal Differentiation and Driving Factors of County-Level Food Security in the Yellow River Basin: A Case Study of Ningxia, China

Food security is the primary condition for the development of human society. The Great River Basin is very important to ensure the accessibility and availability of agricultural irrigation, which is vital for food security. The Yellow River Basin plays a significant role in China’s food security, with counties serving as key administrative units for guaranteeing this security. This study uses the Yellow River Basin in China as a case study to construct an evaluation index system for county-level food security. It assesses the food security of 22 counties (districts) in Ningxia from 2013 to 2022, applying spatial correlation theories and driving factor analysis methods to explore the factors influencing county-level food security. The results reveal the following: (1) Overall, the food security index in Ningxia has been on the rise, but there is significant internal variation among counties. (2) Spatially, the food security index is relatively low in administrative centers, while the irrigation areas along the Yellow River play a crucial role in maintaining food security, and the overall food security index in the central arid areas is improving. (3) Food security is driven by multiple factors including economic, social, and climatic influences. To enhance food security in the Yellow River Basin, it is necessary to manage land resources systematically, improve grain production technology, and balance ecological protection with food security.

Empowering Rural Women through Nutrition Education: Enhancing Dietary Quality with Mushroom-enriched Foods and Participation in Local Mushroom Production Systems

Ensuring quality nutrition for rural women remains a critical public health challenge, particularly in regions where dietary diversity is limited, and micronutrient deficiencies are prevalent. One potential solution is the incorporation of mushroom-enriched food into the daily diets of these women, combined with effective nutrition education and active participation in the mushroom production system. Mushrooms are a nutrient-dense food source, rich in essential vitamins such as vitamin D, and B vitamins, and minerals like zinc, selenium, and iron, which are often deficient in rural diets. Additionally, mushrooms provide a valuable source of protein and fiber, making them an ideal complement to traditional staples. Nutrition education programs focusing on the health benefits of mushrooms can help shift dietary patterns and empower rural women to make healthier food choices for themselves and their families. The integration of mushroom cultivation into local agricultural practices not only enhances food security but also provides an additional income source for women, supporting their economic empowerment. Moreover, the cultivation process is relatively low-cost and can be sustainably managed within small-scale farming systems, making it an accessible and feasible solution for rural communities. Training women to grow, harvest, and prepare mushroom-enriched foods can address both the supply and demand side of the nutrition equation, ensuring that nutrient-rich foods are both available and consumed regularly. The dual focus on nutrition education and production system participation also fosters a sense of ownership and self-reliance among rural women, leading to more sustainable long-term improvements in dietary quality. This approach has the potential to reduce gender disparities in agricultural participation by providing women with a specific and profitable area of expertise within their communities.

Stabilizing food supply chains with Blockchain technology during periods of economic inflation

This study explores the potential of blockchain technology to stabilize food supply chains during periods of economic inflation. Economic inflation poses significant challenges to food security, as rising prices can disrupt supply chain transparency, efficiency, and trust among stakeholders. This research develops a conceptual model demonstrating how blockchain can enhance transparency and stability in food supply chains, ultimately improving resilience against inflationary pressures. By providing a decentralized, immutable ledger, blockchain technology allows for real-time tracking of food products from farm to table, enabling better inventory management and demand forecasting. The proposed model integrates key components, including smart contracts, which automate transactions and ensure compliance with quality and safety standards. This feature not only reduces delays but also fosters trust among supply chain participants, such as farmers, distributors, retailers, and consumers. Additionally, the model emphasizes the role of data analytics in harnessing blockchain data to provide insights into pricing trends and inventory levels, facilitating proactive decision-making in response to inflation. Future research directions are identified, focusing on innovations within blockchain technology that could further mitigate the effects of inflation on food supply chains. Potential areas of exploration include integrating artificial intelligence (AI) for predictive analytics, utilizing Internet of Things (IoT) devices for real-time data collection, and developing decentralized finance (DeFi) solutions to enhance liquidity and investment in the agricultural sector. This study contributes to the growing body of literature on blockchain applications in supply chain management by highlighting its potential as a tool for enhancing food security in inflationary environments. By ensuring transparency, improving stakeholder collaboration, and providing actionable insights, blockchain technology can play a pivotal role in stabilizing food supply chains amidst economic fluctuations. Ultimately, this research advocates for the adoption of blockchain solutions as part of comprehensive strategies to safeguard food systems from the adverse impacts of inflation. Keywords: Blockchain Technology, Food Supply Chains, Economic Inflation, Transparency, Stability, Smart Contracts, Predictive Analytics, Data Analytics, Food Security, Decentralized Finance.

The potential role of abandoned cropland for food security in China

The widespread abandonment of croplands poses a severe threat to China's food security. However, the existing knowledge regarding the potential for recultivating abandoned croplands is limited. Previous studies have generally overestimated this potential due to inadequate assessments of their suitability for recultivation. In the present study, an optimized machine learning approach was introduced to assess, for the first time, the suitability of abandoned croplands for recultivation in China. In 2022, the total abandoned croplands in China covered 31.2 million hectares, of which 82.54 % was deemed suitable for recultivation. Recultivating abandoned croplands in China could substantially enhance food security, potentially yielding around 162 million tons annually. Moreover, crop switching can further increase the yield rate by up to 24.95 % or energy supply by up to 43.14 %. The present study offers valuable insights to policymakers in determining cropping strategies, establishing strategic grain reserves, and managing international food trade.

Enhancing Food Security in an Era of Rising Fertilizer Prices: Evaluation of an Intervention Promoting Mungbean Adoption in Nepal

The improved food security in Asia that has facilitated the region’s development progress depends on nitrogenous fertilizers. Rising prices and shortages of imported fertilizer have prompted countries to explore alternative sources of crop nitrogen, including diversification with legumes. We evaluate an intervention in Nepal that promoted mungbean adoption. Our doubly robust impact evaluation approach accounts for nonrandom patterns of adoption related to livestock rearing, participation in agricultural cooperatives and training, and greater irrigated land use. Adopters growing mungbean for the 2-year study period showed an average increase of 20 kilograms (kg) in their annual consumption of mungbean-based foods, applied almost 40[Formula: see text]kg per hectare (ha) less fertilizers to their rice crops, and obtained an additional 280[Formula: see text]kg in rice yield per ha. Hence, agricultural innovations that use legumes such as mungbean can help promote sustainable intensification of cereal-based production systems, while enhancing food security and reducing balance-of-payments issues for the countries dependent on fertilizer imports.

Building Agricultural Resilience: Strategies for Climate Change Adaptation

Climate change has a significant impact on India's agriculture, influencing environmental conditions, agricultural techniques, and production. The term "climate-resilient agriculture" refers to technologies, methods, tools, and frameworks aimed at adapting to and mitigating the effects of climate change on agricultural production, food security, and livelihoods. Crop productivity and food security are greatly impacted by climate changes, which calls for creative agricultural methods to maintain food supply while reducing environmental damages. These difficulties are made worse by environmental changes and global population expansion, especially in developing countries. Technological advancements, such as geospatial analysis, and eco-friendly farming technologies, play a crucial role in optimizing land use and enhancing food security. Crop variety adaptation and management of seed, water, land, livestock, soil and nutrients, pest management, risk management, and post-harvest management are examples of effective agricultural adaptation strategies. Technological developments like geographic analysis.

Determinants of Food Security Under Different Land Use Systems: Example of Pastoralists and Agro-Pastoralists in Northeastern Ethiopia

The issue of ensuring food and nutrition security has become a prominent item on the global agenda, particularly for low-income countries with high population growth rates. Despite the implementation of numerous policies and programs with the objective of enhancing household calorie intake, food insecurity is worsening in Ethiopia. It is crucial to comprehend the principal factors influencing food security, as this knowledge is essential for implementing effective interventions to enhance food security. Therefore, this study aimed to estimate the food security status of households, measure the extent and severity of food insecurity, and identify the determinants of food security in Northeastern Ethiopia. The data for this study were collected through key informant interviews, focus group discussions, and a multi-stage sampling method, which involved the selection of 300 households. Descriptive and inferential statistics, the Foster–Greer–Thorbecke (FGT) index, and a probit model were employed to analyze the collected data. The results indicate that 41.67% of the sample households were food secure. By decomposing the results to the two land use systems, 34.62% and 50.69% of the pastoral and agro-pastoral households were food secure, respectively, indicating that agro-pastoral households were relatively more food secure than pastoral counterparts. Furthermore, the gap and severity of food insecurity among the sample households were calculated using FGT indices, resulting in a value of 15.02% and 5.31%, respectively. The probit model revealed that educational attainment, the number of milking cows, cultivated farm size, annual farm income, and participation in off-farm activities were significant predictors of improved household food security status. The findings of this study suggest that policies aimed at addressing food insecurity should consider livelihood diversification, the promotion of education and training, and the strengthening of institutional and technological environments.

FORECASTING LEAFY VEGETABLE PRODUCTION IN BANGLADESH: UNRAVELLING THE NEXUS AMONG AGRO-METEOROLOGICAL FACTORS

Leafy vegetables in the food basket provide vital nutrients required for human health, but Bangladesh faces challenges of sustainable production potential due to the vulnerability of various agrometeorological factors. This study has addressed a holistic approach to forecasting leafy vegetable production through the nexus of agricultural responses and climatic factors. The secondary yearly data of seasonal leafy vegetable production and area wise daily key climatic predictors such as rainfall, humidity, sunshine, and temperature for the period 2000-2001 to 2022-2023 have been collected from Bangladesh Bureau of Statistics (BBS) and Bangladesh Meteorological Division (BMD), respectively. Scenario analysis and stepwise dynamic regression model was applied to diagnose the pattern and also forecast winter and summer leafy vegetable production for the years 2023-2024 to 2030-2031 addressing meteorological predictors. Results show that winter production is significantly influenced by the previous year’s output (lag-1), sunshine hour, and maximum temperature. In contrast, summer leafy vegetable production is influenced solely by previous year production. Using growth projection of sunshine hours and maximum temperature of Bangladesh Meteorological Department (BMD) in the fitted dynamic regression model, winter leafy vegetable production is forecasted to rise from 167,558 tons in 2022-2023 to 211,929 tons by 2030-2031. Summer production is expected to increase from 176,234 tons in 2022-2023 to 285,085 tons by 2030-2031. These findings provide critical insights for policymakers aiming to enhance food security and stabilize leafy vegetable markets amidst climate change for achieving sustainable development goals (SDG) 12.

Fish–Seascape Associations Within an Offshore Protected Area in the Arabian Gulf

ABSTRACTCoral reef ecosystems support high fish biodiversity through ecological interactions with structural complexity across multiple spatial scales including coral colony architecture and the surrounding seascape structure. In an era where the complexity of coral reef ecosystems is being diminished, understanding the importance of structural characteristics beyond single focal patches has the potential to better inform actions for protecting, restoring or creating habitat for reef‐associated species. A seascape ecology approach was applied to explore the associations between multiple scales of seascape structure and fish assemblage response variables within a small (49.6 km2) offshore no‐take MPA, Sir Bu Nair Island Protected Area, in Sharjah, United Arab Emirates. Fish–seascape associations were modelled with single regression trees. Both in situ and remote sensing–derived variables produced the best models with highest contributions from coral cover, amount of hard‐bottom habitat type and structural complexity of the seafloor terrain. Fish species richness was significantly higher where coral cover exceeded 35%. The hard‐bottom areas with coral supported diverse assemblages dominated by carnivorous and omnivorous fishes. The Sir Bu Nair Island Protected Area provides a critical refuge for threatened and regionally overexploited species including those with low resilience to fishing. The ecological success of this protected area is key to safeguarding regional marine biodiversity and recovering fish populations to enhance food security.

COVID and consumers’ food strategies in Madrid, Spain: Towards a resilient city-region food system approach

Lockdowns, restrictions on people's movements and gatherings, and other COVID-19 containment measures have had economic, social, and environmental effects. The pandemic resulted in major disruption to food systems, highlighting serious weaknesses in the way such systems are currently configured. However, the pandemic also created important opportunities to develop transformative actions enabling the creation of more resilient and sustainable food systems. In this paper, we delve more deeply into the strategies developed by consumers, as key stakeholders in the food system, through an in-depth survey and statistical analysis of changes in consumers' habits during the pandemic lockdowns. We adopt a city-region food system (CRFS) approach to explore ways to enhance food system resilience to future crises.Data were collected through a telephone survey of a representative sample (600 consumers), conducted in the region of Madrid in May 2021. First, descriptive analyses allowed different consumer strategies to be identified. Differences in food preferences and behaviour changes between individuals in the sample were analysed by age, gender, income, and level of education using exponential family Principal Component Analysis (EPCA), logistic regression, and Multiple Correspondence Analysis (MCA). Lastly, Principal Component Analysis (PCA) was applied to classify the consumer strategies into four discrete profiles.The findings show significant differences in consumers' responses according to age, income, and level of education. Additionally, the results highlight increased consumption of local and organic products, and online shopping, as typical strategies employed by consumers to respond to the COVID-19 pandemic. In this context, alternative food networks were shown to play a key role in enhancing food security. Interestingly, no significant differences were found between urban and rural areas. Our discussion addresses this apparent homogeneity in consumers’ habits from a resilient CRFS approach.

Preface

The International Conference on Agriculture, Environment and Food Security (AEFS) is a prominent global conference organised by the Faculty of Agriculture at Universitas Sumatera Utara, Indonesia. It provides a platform for sharing innovative and practical insights in agriculture, environment, and food security. Furthermore, it facilitates global communication among scientists, researchers, academics, resource managers, practitioners, students, policymakers, and everyone interested in agriculture, environmental sciences, and food security. The AEFS Conference has been conducted every year since 2017. The AEFS Conference has focused on the following themes over the past four years: Agriculture, Plantation, and Livestock for World Food Security (AEFS 2017); Prospects and Challenges of Sustainable Agriculture to Improve Food Security and Environment (AEFS 2018); Challenges on Food Security and Sovereignty in the Industrial Era 4.0 (AEFS 2019); Innovation and Technologies on Agricultural and Environmental Sustainability Systems (AEFS 2020); Precision Agriculture Technologies and Farming Systems Towards Food Security and Sustainability (AEFS 2021); Strengthening Sustainable Agriculture for A Better Future (AEFS 2022); Green Economy for Enhancing Food Security, Environmental and Agricultural Sustainability (AEFS 2023). In addition, the 8th AEFS 2024 Conference with the theme Eco-Friendly Agricultural to Increase Food System Resilience. List of Honorary Board, Steering Committee, Organizing Committee, Scientific Committee and Editorial and Reviewing Committee are available in this pdf.