Search Results (1,151)

Background/Objectives: Quality of life (QOL) is a multifaceted concept involving a variety of factors which define the overall well-being of individuals. Food security, which implies a resilient food system, is one factor that is central to the calculus of the QOL status of a community considering that food is a staple of life. Advancing food security as a strategy for attaining sustained improvement in community QOL hinges on recognizing that food security is embedded in a matrix of other factors that work with it to generate the QOL the community experiences. The lived experience of the community defines the community’s QOL value matrix and the relative position of food security in that value matrix. Our thesis is that the role of food security in the lived experience of low-income communities depends on the position food security is accorded relative to other factors in the QOL value matrix of the community. Methods: This study employed a multimethod approach to define the QOL value matrix of low-income Guilford County residents, identifying the relative position of the value components and demographic segments based on priority ranking. First, an in-depth interview was conducted and then a telephone survey (280 sample) was used for collecting data. The ISAC Analysis Procedure and Best–Worst Scaling methods were used to identify and rank components of the QOL value matrix in terms of their relative impact on QOL. Results: The analysis revealed that spiritual well-being is the most important contributor to QOL, with a weight of 0.23, followed by access to health services (0.21) and economic opportunities (0.16), while food security has a moderate impact with 0.07. Conclusions: These findings emphasize the need for targeted policy interventions that consider the specific needs of different demographic segments to effectively improve QOL and inform the design of resilient food systems that reflect the lived experiences of low-income communities. Food security policies must be integrated with broader quality of life interventions, particularly for unemployed, low-educated, and single individuals, to ensure that a resilient food system effectively reduces inequities and address community-specific vulnerabilities. Full article

Grains and their derivatives play a crucial role as staple foods for the global population. Identifying grains in the food chain that are free from mycotoxin contamination is essential. Researchers have explored various traditional detection methods to address this concern. However, as grain consumption becomes increasingly time-sensitive and dynamic, traditional approaches face growing limitations. In recent years, emerging techniques—particularly molecular-based vibrational spectroscopy methods such as visible–near-infrared (Vis–NIR), near-infrared (NIR), Raman, mid-infrared (MIR) spectroscopy, and hyperspectral imaging (HSI)—have been applied to assess fungal contamination in grains and their products. This review summarizes research advances and applications of vibrational spectroscopy in detecting mycotoxins in grains from 2019 to 2025. The fundamentals of their work, information acquisition characteristics and their applicability in food matrices were outlined. The findings indicate that vibrational spectroscopy techniques can serve as valuable tools for identifying fungal contamination risks during the production, transportation, and storage of grains and related products, with each technique suited to specific applications. Given the close link between grain-based foods and humans, future efforts should further enhance the practicality of vibrational spectroscopy by simultaneously optimizing spectral analysis strategies across multiple aspects, including chemometrics, model transfer, and data-driven artificial intelligence. Full article

Mycotoxins are secondary metabolites produced primarily by certain species of the genera Aspergillus, Fusarium, Penicillium, Alternaria, and Claviceps. Toxigenic fungi and mycotoxins are prevalent in staple foods, resulting in significant economic losses and detrimental impacts on public health and food safety. These fungi demonstrate remarkable adaptation to water and heat stress conditions associated with climate change, and the use of synthetic antifungals can lead to the selection of resistant strains. In this context, the development of novel strategies for their prevention and control of food is a priority objective. This review synthesizes the extant knowledge concerning the antifungal and anti-mycotoxin potential of the primary metal nanoparticles (silver, copper) and metal oxide nanoparticles (copper oxide and zinc oxide) studied in the literature. It also considers synthesis methods and the lack of consensus on technical definitions and regulations. Despite methodological gaps and the scarcity of publications analyzing the effect of these NPs on fungal growth and mycotoxin production simultaneously, it can be concluded that these NPs present high reactivity, stability, and the ability to combat these food risks. However, aspects related to their biosafety and consumer acceptance remain major challenges that must be addressed for their implementation in the food industry. Full article

MicroRNA528 (miR528) is a microRNA found only in monocotyledonous (monocot) plants. It has been widely reported that miR528 is involved in the regulation of plant growth and development, such as flowering, architecture, and seed and embryogenic development, in addition to playing a crucial role in response to various biotic and abiotic stresses, such as plant pathogens, salt stress, heat/cold stress, water stress, arsenic stress, oxidative stress, heavy-metal stress, and nutrient stress. Given that it is specific to monocot plants, to which the major staple food crops such as rice and wheat belong, a review of studies investigating its diverse functional roles and underlying mechanisms is presented. This review focuses on the processes in which miR528 and its targets are involved and examines their regulatory relationships with significant participation in plant development and stress responses. It is anticipated that more biological functions and evolutionary effects of miRNA targets will be elucidated with the increase in knowledge of miRNA evolution and examination of target mRNAs. Full article

Sourdough fermentation, driven by the biochemical activity of lactic acid bacteria (LAB), presents a scientifically promising approach to addressing nutritional limitations in cereal-based staples. This review critically examines both the underlying mechanisms by which LAB enhance the nutritional profile of sourdough and the translational challenges in realizing these benefits. Key improvements explored include enhanced mineral bioavailability (e.g., up to 90% phytate reduction), improved protein digestibility, an attenuated glycemic response (GI ≈ 54 vs. ≈75 for conventional bread), and the generation of bioactive compounds. While in vitro and animal studies extensively demonstrate LAB’s potential to reshape nutrient profiles (e.g., phytate hydrolysis improving iron absorption, proteolysis releasing bioactive peptides), translating these effects into consistent human health outcomes proves complex. Significant challenges hinder this transition from laboratory to diet, including the limited bioavailability of LAB-derived metabolites, high strain variability, and sensitivity to fermentation conditions. Furthermore, interactions with the food matrix and host-specific factors, such as gut microbiota composition, contribute to inconsistent findings. This review highlights methodological gaps, particularly reliance on in vitro or animal models, and the lack of long-term, effective human trials. Although LAB hold significant promise for nutritional improvements in sourdough, translating these findings to validated human benefits necessitates continued efforts in mechanism-driven strain optimization, the standardization of fermentation processes, and rigorous human studies. Full article

Durum wheat, the world’s second most cultivated wheat species, is a staple crop, critical for global food security, including in Ethiopia where it serves as a center of diversity. However, climate change and genetic erosion threaten its genetic resources, necessitating genomic studies to support conservation and breeding efforts. This study characterized genome-wide diversity, population structure (STRUCTURE, principal coordinate analysis (PCoA), neighbor-joining trees, analysis of molecular variance (AMOVA)), and selection signatures (F_ST, Hardy–Weinberg deviations) in Ethiopian durum wheat by analyzing 376 genotypes (148 accessions) using an Illumina Infinium 25K single nucleotide polymorphism (SNP) array. A set of 7842 high-quality SNPs enabled the assessments, comparing landraces with cultivars and breeding populations. Results revealed moderate genetic diversity (mean polymorphism information content (PIC) = 0.17; gene diversity = 0.20) and identified 26 loci under selection, associated with key traits like grain yield, stress tolerance, and disease resistance. AMOVA revealed 80.1% variation among accessions, with no significant differentiation by altitude, region, or spike density. Landraces formed distinct clusters, harboring unique alleles, while admixture suggested gene flow via informal seed exchange. The findings highlight Ethiopia’s rich durum wheat diversity, emphasizing landraces as reservoirs of adaptive alleles for breeding. This study provides genomic insights to guide conservation and the development of climate-resilient cultivars, supporting sustainable wheat production globally. Full article

Climate change presents urgent and complex challenges to agricultural sustainability and food security, particularly in regions reliant on resource-intensive staple crops. Smart agriculture—through the integration of crop modeling, satellite remote sensing, and artificial intelligence (AI)—offers data-driven strategies to enhance productivity, optimize input use, and mitigate greenhouse gas (GHG) emissions. This study introduces Farmdee-Mesook, a mobile-first smart agriculture platform designed specifically for Thai rice farmers. The platform leverages AquaCrop simulation, open-access satellite data, and localized agronomic models to deliver real-time, field-specific recommendations. Usability-focused design and no-cost access facilitate its widespread adoption, particularly among smallholders. Empirical results show that platform users achieved yield increases of up to 37%, reduced agrochemical costs by 59%, and improved water productivity by 44% under alternate wetting and drying (AWD) irrigation schemes. These outcomes underscore the platform’s role as a scalable, cost-effective solution for operationalizing climate-smart agriculture. Farmdee-Mesook demonstrates that digital technologies, when contextually tailored and institutionally supported, can serve as critical enablers of climate adaptation and sustainable agricultural transformation. Full article

Cassava is the sixth most important food crop and is cultivated in more than 100 countries. The crop tolerates low soil fertility and drought, enabling it to play a role in climate adaptation strategies. Cassava generally requires careful preparation to remove toxic hydrogen cyanide (HCN) before its consumption, but HCN concentrations can vary considerably between varieties. Climate change and low inputs, particularly carbon and nutrients, affect agriculture in Pacific Island countries where cassava is commonly grown alongside traditional crops (e.g., taro). Despite increasing popularity in this region, there is limited experimental data about cassava crop management for different local varieties, their relative toxicity and nutritional value for human consumption, and their interaction with changing climate conditions. To help address this knowledge gap, three field experiments were conducted at the Koronivia Research Station of the Fiji Ministry of Agriculture. Two varieties of cassava with contrasting HCN content were planted at three different times coinciding with the start of the wet (September-October) or dry (April) seasons. A time series of measurements was conducted during the full 18-month or differing 6-month durations of each crop, based on destructive harvests and phenological observations. The former included determination of total biomass, HCN potential, carbon isotopes (δ¹³C), and elemental composition. Yield and nutritional value were significantly affected by variety and time of planting, and there were interactions between the two factors. Findings from this work will improve cassava management locally and will provide a valuable dataset for agronomic and biophysical model testing. Full article

The high glycemic index (GI) of polished white rice (WR) presents challenges for blood glucose control in diabetes. This study investigated the in vitro digestibility of a whole grain blend (WGB, composed of black, red, and brown rice) and its effects on the gut microbiota in elderly diabetic individuals. WGB exhibited lower starch digestibility (69.76 ± 5.71% vs. 73.02 ± 6.16%) and a reduced estimated glycemic index (eGI, 73.43 ± 4.49 vs. 77.55 ± 2.64) than WR, likely due to its higher amylose content. WGB fermentation increased Bifidobacterium and Lactobacillaceae, reduced pro-inflammatory Bacteroides fragilis and Enterocloster bolteae, and released more arabinose and xylose. Additionally, WGB yielded higher isobutyrate, while WR contained more glucose and fructose in its structure, leading to increased acetate production and a more acidic environment. Functional analysis revealed that WGB upregulated pathways related to fatty acid elongation and fiber fermentation. These findings suggest WGB as a viable staple food alternative for diabetic patients, offering dual benefits in glycemic control and gut microbiota. Full article

In the artificial cultivation of Morchella sextelata (Black Morel), exogenous nutrient bags (ENBs) commonly employ wheat grains as the primary substrate raw material. However, this approach is costly and runs counter to the “non-grain” development direction advocated by the edible mushroom industry. Under controlled field conditions, twelve self-made formulations were set up and compared with a conventional market formulation to comprehensively analyze their impacts on the agronomic traits, yield, soil physicochemical properties, and economic benefits of M. sextelata fruiting bodies. The research findings indicate that the nutrient bag formulations have a significant effect on soil available nutrients. Specifically, the contents of alkali-hydrolysable nitrogen (AN) and available potassium (AK) exhibit a significantly negative correlation with M. sextelata yield (r = −0.60, p < 0.05; r = −0.72, p < 0.01, respectively). Among all the treatment groups, the KY1 formulation (comprising 30% wheat grains, 5% rice bran, 60% corncobs, 2% rice husks, 1% lime, and 1% gypsum) achieved the highest yield of 915.13 kg per 667 m², which was 16.1% higher than that of the control group. The net economic benefit per unit area (667 m²) reached CNY 75,282.15, representing a 20.7% increase compared to the traditional wheat grains-based formulation. In conclusion, partially substituting wheat grains with rice bran in ENBs can not only reduce reliance on staple food resources but also enhance yield and economic efficiency. Due to the differences in cultivated strains and environmental conditions, the impact on morel yield is substantial; therefore, the results of this study need further validation through pilot trials. Full article

Dioscorea species, known as “Yams”, belong to the Dioscoreaceae family. Members of the Dioscoreaceae family are widely distributed across subtropical and tropical regions. They are notable for their high content of starch, dietary fiber, and various bioactive compounds. In addition to serving as a staple food source, these tubers possess significant medicinal value in traditional medicine, particularly for treating diabetes, diarrhea, and various inflammatory diseases. This study aimed to comprehensively summarize the active components and food development potential of Dioscorea species from research over the past decade by searching commonly used databases such as PubMed, Web of Science, Scopus, and Google Scholar. This review highlights the classification of bioactive compounds in Dioscorea spp. using the NPClassifier tool. We discuss 60 representative bioactive metabolites, including terpenoids, phenylpropanoids, carbohydrates, fatty acids, alkaloids, and amino acids. Additionally, we discuss the functional food applications and regulations of Dioscorea spp., which possess antioxidant, anti-inflammatory, anti-diabetic, and anticancer properties. This review is expected to provide scientific ideas for future research related to prioritizing the optimization of extraction technologies, the execution of rigorous clinical trials to confirm therapeutic effects, and the exploration of novel applications of Dioscorea spp. bioactives to fully harness their potential in improving human health. Full article

This research presents a comprehensive methodology for calibrating Discrete Element Method (DEM) parameters governing rice grain interactions with biodegradable Polylactic Acid (PLA) components in agricultural bucket elevator systems. Rice grains, a critical global food staple requiring efficient post-harvest handling, were modeled as three-sphere clusters to accurately represent their physical dimensions (6.5 mm length), while the Hertz–Mindlin contact model provided the theoretical framework for particle interactions. The calibration process employed a multi-phase experimental design integrating Plackett–Burmann screening, steepest ascent method, and Face Central Composite Design to systematically identify and optimize critical micro-mechanical parameters for agricultural material handling. Statistical analysis revealed the coefficient of static friction between rice and PLA as the dominant factor, contributing 96.49% to system performance—significantly higher than previously recognized in conventional agricultural processing designs. Response Surface Methodology generated predictive models achieving over 90% correlation with experimental results from 3D-printed PLA shear box tests. Validation through comparative velocity profile analysis during bucket elevator discharge operations confirmed excellent agreement between simulated and experimental behavior despite a 20% discharge velocity variance that warrants further investigation into agricultural material-specific phenomena. The established parameter set enables accurate virtual prototyping of sustainable agricultural handling equipment, offering post-harvest processing engineers a powerful tool for optimizing bulk material handling systems with reduced environmental impact. This integrated approach bridges fundamental agricultural material properties with sustainable engineering design principles, providing a scalable framework applicable across multiple agricultural processing operations using biodegradable components. Full article

Food quality and safety are paramount in preserving the culinary authenticity and cultural integrity of Chinese cuisine, characterized by intricate ingredient combinations, diverse cooking techniques (e.g., stir-frying, steaming, and braising), and region-specific flavor profiles. Traditional non-destructive detection methods often struggle with the unique challenges posed by Chinese dishes, including complex textural variations in staple foods (e.g., noodles, dumplings), layered seasoning compositions (e.g., soy sauce, Sichuan peppercorns), and oil-rich cooking media. This study pioneers a hyperspectral imaging framework enhanced with domain-specific deep learning algorithms (spatial–spectral convolutional networks with attention mechanisms) to address these challenges. Our approach effectively deciphers the subtle spectral fingerprints of Chinese-specific ingredients (e.g., fermented black beans, lotus root) and quantifies critical quality indicators, achieving an average classification accuracy of 97.8% across 15 major Chinese dish categories. Specifically, the model demonstrates high precision in quantifying chili oil content in Mapo Tofu with a Mean Absolute Error (MAE) of 0.43% w/w and assessing freshness gradients in Cantonese dim sum (Shrimp Har Gow) with a classification accuracy of 95.2% for three distinct freshness levels. This approach leverages the detailed spectral information provided by hyperspectral imaging to automate the classification and detection of Chinese dishes, significantly improving both the accuracy of image-based food classification by >15 percentage points compared to traditional RGB methods and enhancing food quality safety assessment. Full article

Maize is an essential staple food, and its genetic diversity plays a central role in breeding programs aimed at developing climate-adapted cultivars. Constructing a representative core germplasm set is necessary for the efficient conservation and utilization of maize genetic resources. In this study, we analyzed 588 cultivated maize accessions using agronomic traits such as plant morphology and yield traits such as ear characteristics and single-nucleotide polymorphisms (SNPs) to assess molecular diversity and population structure and to construct a core collection. Nineteen phenotypic traits were evaluated, revealing high genetic diversity and significant correlations among most quantitative traits. The optimal sampling strategy was identified as “Mahalanobis distance + 20% + deviation sampling + flexible method.” Whole-genome genotyping was conducted using the Maize6H-60K liquid phase chip. Population structure analysis, principal component analysis, and cluster analysis divided the 588 accessions into six subgroups. A core collection of 172 accessions was selected based on both phenotypic and genotypic data. These were further evaluated for salt–alkali tolerance during germination, and cluster analysis classified them into five groups. Sixty-five accessions demonstrated salt–alkali tolerance, including 18 with high resistance. This core collection serves as a valuable foundation for germplasm conservation and utilization strategies. Full article