Food Demand Research Articles

Cross-Sectional Analysis of Household Food Demand in Estuaire Gabon: A Near-Ideal Quadratic Demand System Approach

Gabon depends heavily on food imports to safeguard its food security; yet household food consumption patterns remain underexplored. This study investigates the structure of food demand in the Estuaire region, incorporating demographic determinants such as the age of the household head, household size, youth proportion, and residential distance from shopping centers. Using primary data collected from a randomized survey of 410 households, the analysis employs the Quadratic Almost Ideal Demand System (QUAIDS) model to estimate expenditure and price elasticities. The results indicate that expenditure elasticities are universally positive, with luxury items, including meat, eggs, and fish, exhibiting greater sensitivity compared to staple foods such as poultry, oil, rice, cassava, and bananas, which display inelastic demand. Price elasticities for meat, poultry, fish, eggs, and rice are negative, adhering to the law of demand. Demographic factors, including education, age, and residential location, significantly influence the consumption of meat, cassava, bananas, and oil. Household size, employment type, and youth composition also emerge as critical determinants of increased demand for poultry, fish, and rice. These findings offer policy-relevant insights to strengthen food security and address socioeconomic disparities.

Revolutionizing Citrus Health: AI-Based Detection of Greening Disease and Nutrient Deficiencies in Sweet Orange

This paper explores the application of Artificial Intelligence (AI) techniques for detecting plant diseases, focusing on citrus greening disease and various foliar nutrient deficiencies in sweet orange. Agriculture faces numerous challenges from cultivation to harvesting, including significant yield losses due to disease infections and environmental hazards from excessive use of insecticides and fungicides. As the global population grows, the demand for food is surging, and traditional farming methods fall short in meeting this demand, often degrading soil health through intensive pesticide use. AI offers significant advantages over conventional techniques in disease detection. This study employs AI for visual detection of citrus greening disease and foliar nutrient deficiencies, achieving 87% accuracy on a test dataset of infected, nutrient-deficient, and healthy sweet orange leaves. Performance is evaluated using metrics such as Accuracy, Recall, Precision, and F1-Score. Specifically, Convolutional Neural Network (CNN) architectures, including Visual Geometry Group (VGG-16), are utilized for image-based detection and classification, demonstrating the potential of AI in enhancing plant health monitoring.

Nutritional and Functional Characterization of Chia Expeller and Gluten-Free Flours as Ingredients for Premixes.

The growing consumer demand for healthier foods that help reduce the risk of chronic diseases has driven the food industry to innovate with nutritionally and technologically viable products. This trend and the nutritional gaps in gluten-free diets have spurred the exploration of unconventional, high-quality ingredients like flour from pseudocereals, legumes, and oilseeds. This study evaluated the nutritional and functional profiles of chia expeller and flours from buckwheat, green/yellow peas, and rice to study their potential as techno-functional ingredients for new gluten-free premixes. Chia expeller, rich in protein, lipids, and fiber, with a notable fatty acid profile -particularly α-linolenic and linoleic acids- and significant levels of Ca, Mg, Fe, Zn, Cu, P, and Na, emerged as a standout ingredient. It also demonstrated remarkable water-binding functionality. Pea flours were notable for their high protein, Ca, Cl, Fe, and linoleic acid content. Meanwhile, rice and buckwheat flours were distinguished by their carbohydrate and oleic acid content. Buckwheat also provides substantial Mg and Zn, while rice flour stood out for its higher brightness. These findings underscore the potential of these flours to contribute to the development of functional foods tailored to meet specific nutritional needs and consumer preferences for healthier options. The distinct functional properties of each flour type can contribute to making targeted formulations, improving the technological properties of gluten-free products.

Literature Review on Malaysia National Food Security: Challenge And Strategy in Meeting Population Rise

This research examines Malaysia's national food security, focusing on the challenges posed by rising population, global disruptions, and the need for sustainable strategies. The primary objective is to analyze the effectiveness of Malaysia's current food security measures in light of the growing population and increasing demand for food. Through qualitative methodologies, including document analysis and case studies, the study investigates the role of government policies, agricultural productivity, and technological adoption in ensuring food sustainability. The findings highlight Malaysia's dependency on food imports, aging farmer demographics, and the lack of investment in agricultural research and development as key factors threatening food security. Additionally, disruptions such as the COVID-19 pandemic and geopolitical conflicts, such as the Russia-Ukraine war, exacerbate vulnerabilities. The research emphasizes the need for comprehensive policies, enhanced private investment, and technological advancements to build resilience in the nation's food systems.

Implications Due to Challenges to Food Security in Malaysia

The issue of food security encompasses challenges related to production, distribution, and accessibility of nutritious food. In Malaysia, food security is increasingly threatened due to reliance on imports, declining agricultural productivity, and income inequality. In 2023, food imports reached RM78.7 billion, indicating heavy dependence on global markets. Population growth, expected to reach 42 million by 2050, exacerbates the demand for food, creating further stress on the nation's food systems. This study employed a qualitative methodology to analyze factors impacting Malaysia's food security, focusing on secondary data from academic and institutional sources. Document analysis was used to examine existing policies and data on food security and its implications. Key findings highlight that food insecurity in Malaysia leads to hunger, malnutrition, and related health issues, such as childhood stunting and obesity. The COVID-19 pandemic significantly worsened these conditions, with 30% of the population estimated to experience food insecurity. Environmental factors, including climate change, deforestation, and resource overuse, further challenge food production. Additionally, global disruptions, such as the Russia-Ukraine conflict, have escalated costs and strained supply chains. The study concludes that addressing Malaysia's food security requires a holistic approach, integrating sustainable agricultural practices, reducing dependency on imports, and strengthening local food systems. Collaborative efforts between governments, private sectors, and international organizations are essential to ensure an equitable and sustainable food future. This research underscores the urgent need for policy reforms and strategic planning to safeguard Malaysia's food security amidst growing global and local challenges.

An analysis of the current and potential market opportunities for hempseed and fibre: the case of Scotland?

BackgroundThe growing demand for eco-friendly food and industrial products have renewed interest in industrial hemp which is a low-cost, biodegradable, sustainable, and multi-purpose plant. Many countries in Europe and Asia have changed their laws to take advantage of the tremendous benefits that industrial hemp present. However, the development of the sector in Scotland is very slow due to stringent laws. The goal of the present study is to present policymakers with economic data on the current and potential market opportunities for industrial hemp, trends in new product development, and the state of the hemp supply chain. This study entails desk-based research primary and secondary data analysis. Primary data were collected from farmers in Aberdeenshire and Scottish borders, and secondary data were collected from the FAOSTATS Office of National Statistics and the Global New Product Database.ResultsThe results of this study show that the opportunities from hemp seed and fibre are vast: hemp can sequester more carbon dioxide than traditional crops can, improve soil biodiversity, extract toxins from soil through phytoremediation, be used as an eco-friendly insecticide and pesticide, and provide an excellent source of protein, fibre and micronutrient vitamins and minerals, as well as a range of bioactive phytochemicals. The GNPD reveals that over 4000 hemp-based products have been launched worldwide. However, the supply chain for Scottish-grown hemp faces significant bottlenecks. The sector lacks a well-established market route, faces a high licensing costs, lacks hemp seed-pressing centres, etc.ConclusionThis study is relevant because it is the first study to provide a comprehensive analysis of the industrial hemp sector in Scotland. This study makes time-bound recommendations to grow the hemp sector in Scotland, which include regular extension services, easy access to licences for production, the establishment of a hempseed and fibre processing plants, and seed production centre.

Leveraging Underutilized Sri Lankan Fruits in the Fight against Autoimmune Disorders.

The potential of underutilized plant species to improve food security, health, eco-nomic output, and the environment has not been fully realized. Sri Lanka an island on the Indian Ocean is home to numerous plant species with significant medicinal potential, in-cluding many underutilized plants that could help meet the growing demand for food, en-ergy, medicines, and industrial resources. Globally, there are over a thousand known and unknown phytochemicals derived from plants. Although these compounds are primarily produced by plants for self-defence, in vitro and in vivo studies have demonstrated their anti-inflammatory properties. Recent research indicates that several phytochemicals can also protect humans from disease by regulating key inflammatory pathways, such as NF-κB, MAPK, JAK/STAT and Nrf-2, which are involved in autoimmune diseases. Thus, these bioactive compounds are vital for managing autoimmune disorders. This review will ex-plore underutilized fruit crops from Sri Lanka that could be used against inflammation, in-cluding autoimmune diseases.

Analysis on Salinity Tolerance of Lettuce Cultivars Under Saline Irrigation and Application of Organic Acids.

Freshwater depletion becomes a significant challenge as the population grows and food demand rises. We evaluated the responses of lettuce cultivars (Lactuca Sativa) under saline stress in photosynthetic responses, production, and ion homeostasis. We used a randomized block design in a 3 × 5 factorial scheme with five replications-the first factor: three cultivars of curly lettuce: SVR 2005, Simpson, and Grand Rapids. The second factor consisted of five treatments: T1-control (water of 0.53 dS m-1); T2-saline stress (water of 4.0 dS m-1); T3-saline stress + ascorbic acid; T4-saline stress + gibberellic acid; and T5-saline stress + salicylic acid. The Grand Rapids lettuce cultivar tolerated water salinity, obtaining the highest production. The Simpson lettuce cultivar was sensitive to salinity, reducing biomass production under saline stress by 11.47% compared to Grand Rapids. Salicylic acid was more effective at mitigating saline stress in the Simpson lettuce cultivar than ascorbic and gibberellic acids, with a 24.85% increase in production compared to saline stress. The findings suggest that the Grand Rapids lettuce cultivar is more resilient to saline conditions, while salicylic acid can significantly enhance production in the sensitive Simpson cultivar under saline stress.

The Analysis of the Impact of Soil Health and Land Fertility through Green Manuring in Organic Farming

Green manures can play a significant role. Utilising green manure is one of the trends in environmental protection that aids in the agricultural sector's transition to sustainability by conserving help conservere sources and meeting consumer demand for food. There is a positive relationship between the benefits of green manuring and factors that improve soil health and land fertility in organic farming. Additionally, there is no positive effects on the quality of soil health, land fertility, and environmental sustainability from chemical fertilizers.” This discussion concludes that agriculture farmers are aware of environmental protection and soil heath and land fertility affordable but some economic affordable benefits encourage to usages of chemical fertiliser that is hindering the green manuring based organic farming

The competitive advantages of traceability: Constructing a theoretical framework for enhancing the competitiveness of tea enterprises

With the rising global consumer demand for green and healthy food, the tea industry is facing unprecedented competitive pressure. Therefore, how to build tea enterprises with sustainable competitiveness has become a key issue facing the industry. This paper firstly reviews the concept of traceability systems and their evolution and, based on the theory of enterprise competitive advantage, explores the influence mechanism of traceability as a strategic resource on the long-term competitiveness of tea enterprises; secondly, it analyzes the multi-dimensional role of traceability on enterprise competitiveness from five aspects, namely, quality and safety control and guarantee, brand image shaping and trust construction, market dynamics response and consumer feedback, risk response and product recall, as well as technological innovation and efficiency enhancement; finally, combined with the above analysis, this paper constructs a theoretical framework for the competitiveness of tea enterprises, integrates the impact of traceability in different dimensions, and proposes a multi-level competitiveness enhancement model. Through this framework, tea enterprises can more comprehensively understand and grasp the close relationship between traceability and the long-term competitive advantage of enterprises and then make strategic adjustments according to their own actual situation so as to realize sustainable competitiveness enhancement in the future market competition.

Soil quality indicator-based land productivity modelling for agricultural sustainability.

Rapid population expansion has made food security a global concern for humanity, necessitating a sustainable assessment of natural resources. Well evaluated and managed soil is one of the most significant resources that can assist close the gap between supply and demand for food to attain food security. A precise assessment of land productivity (LP) is essential for sustainable land use management. The primary aim of this research is to predict the land productivity index (LPI) for certain locations on Egypt's northwest coast under current conditions using soil quality indicators (SQIs). Additionally, the study proposed relevant management actions to boost land productivity in the future. To achieve this aim, a spatial model was created to assess LPI for some areas in the north western coast of Egypt. LP equation was used to estimate current land productivity index (CLPI) and potential land productivity index (PLPI). Results found that the study area mainly located under two classes of CLPI, e.g., average (class ⅡⅠ) represents an area of 13322.63 ha (67.55%) and good grade (class Ⅱ) covers an area of 4339.78 ha (22%). PLPI grades were good (II) and average (III) with an area of 16192.54 ha (82.10%) and 1903.23 ha (9.65%), respectively. The finding showed that more than 60% of the studied area was converted from poor and average class to good class after applying the proposed solutions of soil improvement. The methodology presented here can easily be replicated under similar circumstances in arid zones, allowing local governments and decision-makers to utilize the quantitative results obtained to ensure sustainable development.

Adaptive Month Matching: A Phenological Alignment Method for Transfer Learning in Cropland Segmentation

The increasing demand for food and rapid population growth have made advanced crop monitoring essential for sustainable agriculture. Deep learning models leveraging multispectral satellite imagery, like Sentinel-2, provide valuable solutions. However, transferring these models to diverse regions is challenging due to phenological differences in crop growth stages between training and target areas. This study proposes the Adaptive Month Matching (AMM) method to align the phenological stages of crops between training and target areas for enhanced transfer learning in cropland segmentation. In the AMM method, an optimal Sentinel-2 monthly time series is identified in the training area based on deep learning model performance for major crops common to both areas. A month-matching process then selects the optimal Sentinel-2 time series for the target area by aligning the phenological stages between the training and target areas. In this study, the training area covered part of the Mississippi River Delta, while the target areas included diverse regions across the US and Canada. The evaluation focused on major crops, including corn, soybeans, rice, and double-cropped winter wheat/soybeans. The trained deep learning model was transferred to the target areas, and accuracy metrics were compared across different time series chosen by various phenological alignment methods. The AMM method consistently demonstrated strong performance, particularly in transferring to rice-growing regions, achieving an overall accuracy of 98%. It often matched or exceeded other phenological matching techniques in corn segmentation, with an average overall accuracy across all target areas exceeding 79% for cropland segmentation.

Monitoring Yield and Quality of Forages and Grassland in the View of Precision Agriculture Applications—A Review

The potential of precision agriculture (PA) in forage and grassland management should be more extensively exploited to meet the increasing global food demand on a sustainable basis. Monitoring biomass yield and quality traits directly impacts the fertilization and irrigation practises and frequency of utilization (cuts) in grasslands. Therefore, the main goal of the review is to examine the techniques for using PA applications to monitor productivity and quality in forage and grasslands. To achieve this, the authors discuss several monitoring technologies for biomass and plant stand characteristics (including quality) that make it possible to adopt digital farming in forages and grassland management. The review provides an overview about mass flow and impact sensors, moisture sensors, remote sensing-based approaches, near-infrared (NIR) spectroscopy, and mapping field heterogeneity and promotes decision support systems (DSSs) in this field. At a small scale, advanced sensors such as optical, thermal, and radar sensors mountable on drones; LiDAR (Light Detection and Ranging); and hyperspectral imaging techniques can be used for assessing plant and soil characteristics. At a larger scale, we discuss coupling of remote sensing with weather data (synergistic grassland yield modelling), Sentinel-2 data with radiative transfer modelling (RTM), Sentinel-1 backscatter, and Catboost–machine learning methods for digital mapping in terms of precision harvesting and site-specific farming decisions. It is known that the delineation of sward heterogeneity is more difficult in mixed grasslands due to spectral similarity among species. Thanks to Diversity-Interactions models, jointly assessing various species interactions under mixed grasslands is allowed. Further, understanding such complex sward heterogeneity might be feasible by integrating spectral un-mixing techniques such as the super-pixel segmentation technique, multi-level fusion procedure, and combined NIR spectroscopy with neural network models. This review offers a digital option for enhancing yield monitoring systems and implementing PA applications in forages and grassland management. The authors recommend a future research direction for the inclusion of costs and economic returns of digital technologies for precision grasslands and fodder production.

Addressing Regional Agro-ecological Boundaries: An Integrated Environmental Footprint Framework for Revealing Sustainability Gaps in Agroecosystems.

Overexploiting ecosystems to meet growing food demands threatens global agricultural sustainability and food security. Addressing these challenges requires solutions tailored to regional agro-ecological boundaries (AEBs) and overall agro-ecological risks. Here, we propose a globally consistent and regionally adapted approach for quantifying regional AEBs. Based on this approach, we develop a region-specific integrated Footprint-AEB framework that combines six environmental footprints (EFs) with AEBs to capture the overall environmental impacts on China's regional agro-ecosystems. Results indicate that individual EFs cannot reliably reveal the complexity of agro-ecological stressors without comprehensive assessment relative to regionally determined boundaries. For example, Northwest China faces higher water boundary stress despite lower water footprints compared to Central China, and regions such as Qinghai and Ningxia exhibit higher integrated AEB stress driven by combined water, land, and biodiversity stresses. Additionally, imbalanced integrated AEB stress transfer via trade, mainly from industrialized eastern to vulnerable western regions, is identified as a key driver of AEB exceedance in Northwest China. This fosters a nuanced understanding of environmental responsibility and equity. The integrated Footprint-AEB framework provides new insights into agro-ecosystem dynamics and supports targeted interventions to avoid shifting environmental stressors. These challenges confront agro-ecosystems worldwide.

Triple Threat: How Global Fungal Rice and Wheat Pathogens Utilize Comparable Pathogenicity Mechanisms to Drive Host Colonization.

Plant pathogens pose significant threats to global cereal crop production, particularly for essential crops like rice and wheat, which are fundamental to global food security and provide nearly 40% of the global caloric intake. As the global population continues to rise, increasing agricultural production to meet food demands becomes even more critical. However, the production of these vital crops is constantly threatened by phytopathological diseases, especially those caused by fungal pathogens such as Magnaporthe oryzae, the causative agent of rice blast disease, Fusarium graminearum, responsible for Fusarium head blight (FHB) in wheat, and Zymoseptoria tritici, the source of Septoria tritici blotch (STB). All three pathogens are hemibiotrophic, initially colonizing the host through a biotrophic, symptomless lifestyle, followed by causing cell death through the necrotrophic phase. Additionally, they deploy a diverse range of effectors, including proteinaceous and non-proteinaceous molecules, to manipulate fundamental host cellular processes, evade immune responses, and promote disease progression. This review discusses recent advances in understanding the effector biology of these three pathogens, highlighting both the shared functionalities and unique molecular mechanisms they employ to regulate conserved elements of host pathways, such as directly manipulating gene transcription in host nuclei, disrupting reactive oxygen species (ROS) signaling, interfering with protein stability, and undermining host structural integrity. By detailing these complex interactions, the review explores potential targets for innovative control measures and emphasizes the need for further research to develop effective strategies against these destructive pathogens in the face of evolving environmental and agricultural challenges.

Evaluating the nutritional, therapeutic, and economic potential of Tetragonia decumbens Mill.: A promising wild leafy vegetable for bio-saline agriculture in South Africa

Abstract Global agriculture feeds over seven billion people and alarmingly, this number is expected to increase by a further 50% by 2050. To meet the additional food demand, the world development report has estimated that crop production should increase by 70–100% by 2050. However, climate change, expanding soil salinization, and the developing shortages of freshwater have negatively affected crop production of edible plants around the world. Current attempts to adapt to these conditions include the use of salt-tolerant plant species with potential economic value to fulfil the increasing food demand escalated by the increasing human population. The wild edible halophyte Tetragonia decumbens commonly known as dune spinach has the potential to be used as a leafy vegetable, a source of dietary salt, in phytoremediation and as a source of secondary metabolites. However, it remains underutilized in South Africa as commercial farming of this species has never been explored. This review examined the potential of domesticating the wild dune spinach as a leafy vegetable, describing its morphology and ecology, its propagation and cultivation requirements as well as its potential use on human health and in phytoremediation of saline soils. Furthermore, this analysis is expected to be useful towards further research and popularization of this underexploited halophyte.

Microbial Control in the Processing of Low-Temperature Meat Products: Non-Thermal Sterilization and Natural Antimicrobials.

The safety and health of food have been persistent concerns, particularly about meat products. Low-temperature meat products refer to those that are processed at lower temperatures. Meat, rich in proteins and other nutrients, is highly susceptible to microbial contamination, leading to spoilage, particularly when processed at lower temperatures that increase storage and transportation requirements. In response to the limitations of conventional preservation methods, such as heat treatment and chemical bacteriostats, emerging preservation technologies are increasingly being adopted. These technologies aim to mitigate the negative effects of microorganisms on meat products. Non-thermal technologies and biotechnological approaches, which are low in energy consumption and energy efficiency, are becoming more prevalent. Non-thermal sterilization technology is widely applied in various food products. It maintains the original quality of food, enhances food safety, reduces energy consumption, and improves production efficiency. Biocides are extensively used in the antibacterial field owing to their high efficiency, low toxicity, and long-lasting properties. Both non-thermal sterilization technology and biocides can ensure food safety, extend the shelf life of food products, improve food quality, meet consumers' demand for natural and healthy food, enhance market competitiveness, and play a positive role in promoting the sustainable development of the food industry. This paper provides a comprehensive review of the specific applications of biocides and non-thermal sterilization methods in food, highlighting the control parameters and their effects on microbes during low-temperature meat processing, to supply pertinent researchers with theoretical references.

Exploring the Linkages Between Land Degradation and Food Insecurity

Currently, two major challenges significantly threaten human civilisation: the degradation of land quality and the insufficient access to sustainable food supplies. They are becoming common in numerous places globally, especially in developing nations with elevated population growth rates. Prior studies have examined the impact of several types of land degradation, including soil erosion, waterlogging, stalinisation and desertification, on crop yield, water quality and agricultural productivity. This article comprehensively examines the interrelationship and reciprocal influence between land degradation and food insecurity, emphasising the intricate dynamics of elements contributing to both global challenges. The article analyses several types of land degradation, their direct and indirect effects on the foundations of food security, and how rising food demands exacerbate land degradation. The research advocates for collaborative initiatives at local, national, and global tiers to disrupt the detrimental cycle and establish a resilient, food-secure future.

Performance, adaptability, and multi‐trait stability of rice varieties (Oryza sativa L.) in rainfed conditions

AbstractRainfed rice (Oryza sativa L.) cultivation is crucial for meeting food demand in regions like Bangladesh, where irrigation resources are scarce. A study was conducted in five rainfed districts during the 2022 Aman season. The objective was to assess grain yield performance, adaptation patterns, and identify a stable rice variety using multiple trait evaluations. The results showed that Binadhan‐17 produced the highest grain yield, reaching 5.58 t/ha, with its maximum yield recorded in Gopalganj at 6.12 t/ha. Heritability estimates from a linear mixed model were high for plant height (0.93) and grain yield (0.65), with genotypic variance contributing 92.70% and 64.84% to these traits, respectively. A negative correlation (r = −0.43) indicated that shorter varieties tend to perform better for grain yield. Stability analysis using weighted average absolute scores and best linear unbiased prediction identified Binadhan‐17 as the most stable for grain yield, while the genotype–genotype environment biplot confirmed its adaptability across all locations. Factor analysis of the multi‐trait stability index showed stability across traits, with selection gains from 1.49% to 6.99%. Binadhan‐22 was identified as the most stable for average performance and multi‐trait stability. Given its high yield and consistent performance across environments, Binadhan‐17 is recommended for large‐scale cultivation, while Binadhan‐22 offers a reliable, stable alternative across various traits.

Microbial Inoculants in Sustainable Agriculture: Advancements, Challenges, and Future Directions.

The rapid growth of the human population has significantly increased the demand for food, leading to the intensification of agricultural practices that negatively impact the environment. Climate change poses a significant threat to global food production, as it can disrupt crop yields and modify the lifecycle stages of phytopathogens and pests. To address these challenges, the use of microbial inoculants, which are bioproducts containing beneficial microorganisms known as plant growth promotion microorganisms (PGPMs), has emerged as an innovative approach in sustainable agriculture. This review covers the isolation and identification of beneficial strains, the screening and selection process, the optimization of production techniques, and the importance of quality control and field testing. It also discusses the key points for the development and formulation of high-quality microbial inoculants, as well as highlights their advancements, current challenges, and future directions for research and application.