Search Results (517)

In recent decades, the rapid expansion of the food processing industry has led to significant losses and waste, with the fruit and vegetable sector among the most affected. According to the Food and Agriculture Organization of the United Nations (FAO), losses in this category can reach up to 60%. Vegetable waste includes edible parts discarded during processing, packaging, distribution, and consumption, often comprising by-products rich in bioactive compounds such as polyphenols, carotenoids, dietary fibers, vitamins, and enzymes. The underutilization of these resources constitutes both an economic drawback and an environmental and ethical concern. Current recovery practices, including their use in animal feed or bioenergy production, contribute to a circular economy but are often limited by high operational costs. In this context, fermentation has emerged as a promising, sustainable approach for converting vegetable by-products into value-added food ingredients. This process improves digestibility, reduces undesirable compounds, and introduces probiotics beneficial to human health. The present review examines how fermentation can improve the nutritional, sensory, and functional properties of plant-based foods. By presenting several case studies, it illustrates how fermentation can effectively valorize vegetable processing by-products, supporting the development of novel, health-promoting food products with improved technological qualities. Full article

Using LULC change detection analysis, it is possible to identify changes due to urbanization, deforestation, or a natural disaster in an area. As population growth and urbanization increase, real-time solutions for the effects of urbanization on land use are required to assess its implications for food security and livelihood. This study seeks to identify and quantify recent LULC changes in Limbe, Cameroon, and to measure rates of conversion between agricultural, forest, and urban lands between 1986 and 2020 using remote sensing and GIS. Also, there is a deficiency of research employing these data to evaluate the efficiency of LULC satellite data and a lack of awareness by local stakeholders regarding the impact on LULC change. The changes were identified in four classes utilizing maximum supervised classification in ENVI and ArcGIS environments. The classification result reveals that the 2020 image has the highest overall accuracy of 94.6 while the 2002 image has an overall accuracy of 89.2%. The overall gain for agriculture was approximately 4.6 km², urban had an overall gain of nearly 12.7 km², while the overall loss for forest was −16.9 km² during this period. Much of the land area previously occupied by forest is declining as pressures for urban areas and new settlements increase. This study’s findings have significant policy implications for sustainable land use and food security. It also provides a spatial method for monitoring LULC variations that can be used as a framework by stakeholders who are interested in environmentally conscious development and sustainable land use practices. Full article

The aim of the current study was to determine the scale and underlying causes for the waste of raw and processed fruits and vegetables in Polish households. A survey was conducted on a representative sample of 1100 respondents. The collected empirical data were analyzed using statistical tools such as non-parametric tests, multiple regression methods, and logistic regression. This study assessed the level and determinants of waste of raw and processed fruits and vegetables, identified the reasons for this waste and their impact on its extent, and analyzed the effect of waste prevention methods (including processing) on the scale of product losses. This study showed that the scale of waste of processed fruits and vegetables in Polish consumer households is significantly lower than that of raw products. The level of waste for both raw and processed products vary depending on place of residence, education, income, household size, and, in the case of processed fruits and vegetables, also the age of respondents. The main reason for fruit and vegetable losses in households is missing the product’s expiration date. Logistic regression analysis showed that the most effective strategies for reducing the waste of raw fruits and vegetables include purchasing the right quantities and freezing them. In contrast, practices such as donating food to others or composting were linked to a statistically significant decrease in the likelihood of reducing waste. Full article

Quality and mechanical resilience are crucial for reducing losses in fruit production and for supporting food chains. Indeed, integrating empirical data with rheological models bridges gaps in fruit processing equipment design. Therefore, the objective of this research is to analyze the relationship between the mechanical and physical properties of seven economically important fruits—nectarine, kiwi, cherry, apple, peach, pear, and apricot—to assess their mechanical behavior and post-harvest quality. Standardized compression, creep, and puncture tests were conducted to establish mechanical parameters, such as rupture force, elasticity, and deformation energy. Physical characteristics including size, weight, density, and moisture content were also measured. The results indicated significant differences among the various categories of fruits; apples and pears were most suitable for mechanical harvesting and long storage periods, whereas cherries and apricots were least resistant and susceptible to injury. Correlations were high among the physical measurements, tissue firmness, and viscoelastic properties, thereby confirming structural properties’ contribution in influencing fruit quality and handling efficiency. The originality of this research is in its holistic examination of physical and mechanical properties under standardized testing conditions, thus offering an integrated framework for enhancing post-harvest operations. These findings offer practical insights for optimizing harvesting, packaging, transportation, and quality monitoring strategies based on fruit-specific mechanical profiles. Full article

Guaranteeing food safety in the European Union (EU) is a continuing issue affected by diverse national traditions, regulatory power, and consumer culture. Despite the presence of a harmonized regulatory context, there continues to be variability in performance among the 27 member states. This study gives an extensive comparative evaluation of EU food safety based on three indicators: Rapid Alert System for Food and Feed (RASFF) alerts, pesticide maximum-residue-limit (MRL) violation, and per capita food loss. Fuzzy TOPSIS, K-means clustering, and scenario-based sensitivity tests are used to give an extensive appraisal of the performance of member states. Alarming differences are quoted as findings of significance. The highest number of RASFF notifications (212) and percentage of pesticide MRL non-compliance (1.5%) were reported in 2022 by Bulgaria, whereas the lowest values were reported by Estonia and Lithuania—15–20 RASFF notifications and less than 0.6% MRL violation rates. A statistically significant correlation (r = 0.72, p < 0.001) between pesticide MRL violation and food safety warnings was confirmed in favor of pesticide regulation as the optimal predictor of food safety warnings. On the other hand, food loss did not significantly affect safety measures but indicated very high variation (from 76 kg/capita per year in Croatia to 142 kg/capita per year in Greece). These findings suggest that while food loss remains an environmental problem, pesticide control is more central to the protection of food safety. Targeted policy is what the research necessitates: intervention and stricter enforcement in low-income countries, and diffusion of best practice from successful states. The composite approach adds to EU food safety policy discourse through the combination of performance indicators and targeted regulatory emphasis. Full article

Lifestyle blocks (LBs) are small rural holdings primarily used for residential and recreational purposes rather than commercial farming. Despite the rapid expansion of LBs over the last 25 years, which has been driven by lifestyle amenity preference and land subdivision incentives, their environmental performance remains understudied. This is the case even though their proliferation is leading to an irreversible loss of highly productive soils and accelerating land fragmentation in peri-urban areas. Through undertaking a systematic literature review of relevant studies on LBs in New Zealand and comparable international contexts, this paper aims to quantify existing knowledge and suggest future research needs and management strategies. It focuses on the environmental implications of LB activities in relation to water consumption, food production, energy use, and biodiversity protection. The results indicate that variation in land use practices and environmental awareness among LB owners leads to differing environmental outcomes. LBs offer opportunities for biodiversity conservation and small-scale food production through sustainable practices, while also presenting environmental challenges related to resource consumption, greenhouse gas (GHG) emissions, and loss of productive land for commercial agriculture. Targeted landscape design could help mitigate the environmental pressures associated with these properties while enhancing their potential to deliver ecological and sustainability benefits. The review highlights the need for further evaluation of the environmental sustainability of LBs and emphasises the importance of property design and adaptable planning policies and strategies that balance environmental sustainability, land productivity, and lifestyle owners’ aspirations. It underscores the potential for LBs to contribute positively to environmental management while addressing associated challenges, providing valuable insights for ecological conservation and sustainable land use planning. Full article

Grain drying technology is a core process for ensuring food quality, extending storage life, and improving processing adaptability. With the continuous growth of global food demand and the increasing requirements for food quality and energy efficiency, traditional drying technologies face multiple challenges. This paper reviews six major grain drying technologies, comprising hot air drying, microwave drying, infrared drying, freeze drying, vacuum drying, and solar drying. It provides an in-depth discussion of the working principles, advantages, and limitations of each technology, and analyzes their performance in practical applications. In response to challenges such as high energy consumption, uneven drying, and quality loss during the drying process, the paper also explores the research progress of several hybrid drying systems, such as microwave–hot air drying combined systems and solar–infrared drying systems. Although these emerging technologies show significant potential in improving drying efficiency, energy saving, and maintaining food quality, their high costs, scalability, and process stability still limit large-scale applications. Therefore, future research should focus on reducing energy consumption, improving drying precision, and optimizing drying system integration, particularly by introducing intelligent control systems. This would maximize the preservation of food quality while improving the system’s economic efficiency and sustainability, promoting innovation in food production and processing technologies, and further advancing global food security and sustainable agricultural development. Full article

The quality of materials extracted from plant sources, such as oilseeds, is significantly affected by the extraction techniques employed. Thermo-photosensitive bioactive compounds are especially susceptible, often resulting in a loss of functional properties during conventional processing. In this context, studies involving unconventional or “innovative” extraction methods have emerged as a strategic approach to preserve the quality of the extracted material (whether by-product or biomass) by aligning with the core principles of green chemistry and the expansion of sustainable production chains. This approach promotes both raw material integrity and the protection of human and environmental health. These efforts contribute to a virtuous cycle of technological innovation and environmentally sound practices. This review focuses on how ultrasound-assisted extraction affects the quality of plant-derived materials, particularly Brazil nut oil. The article compiles data published over the last five years (2020–2025), following the PRISMA methodology. Recent studies highlight the synergistic potential of ultrasound as a green technology for isolating Brazil nut oil, offering enhanced nutritional and functional properties. This aligns with the growing demand for healthier food products obtained through sustainable industrial processes and presents opportunities for diverse applications across several industry sectors. Full article

Traditional farming practices are becoming increasingly inadequate to meet global food demand due to water scarcity, prolonged production cycles, climate variability, and declining arable land. In contrast, aeroponic, smart, soil-free farming technologies offer a more sustainable alternative by reducing land use and providing efficient water use, given that aeroponics intermittently delivers water in mist form rather than maintaining continuous root zone moisture. However, aeroponics faces critical challenges in irrigation management due to non-standardized structures and limited real-time control. A key limitation is the inability to dynamically respond to temperature (T), relative humidity (RH), light intensity (L_i), electrical conductivity (EC), pH, and photosynthesis rate (P_n), resulting in suboptimal crop yields and resource wastage. Despite growing interest, there remains a research gap in integrating internet of things (IoT) and machine learning technologies into aeroponic systems for adaptive control. IoT-enabled sensors provide real-time data on ambient conditions and plant health, while ML models can adaptively optimize misting intervals based on the fluctuations in P_n and environmental inputs. These technologies are particularly well suited to address the dynamic, data-intensive nature of aeroponic environments. This review purposes a novel, standardized IoT–ML framework to control irrigation by emphasizing IoT sensing and ML-based decision making in aeroponics. This integrated approach is essential for minimizing water loss, enhancing resource efficiency, and advancing the sustainability of controlled-environment agriculture. Full article

Improper stakeholder practices are considered a primary driver of food loss. This study aims to investigate the consequences of pre- and post-harvest practices on extending the shelf life of agro-food products, identifying which practices yield the highest marginal returns for quality. Using Fractional Regression Models (FRM) and Ordinary Least Squares (OLS), the research analyzed data from 343 Egyptian grape farmers and intermediaries. Key findings at the farmer level include significant food loss reductions through drip irrigation (13.9%), avoiding maturity-accelerating chemicals (24%), increased farmer-cultivated area (6.1%), early morning harvesting (8.7%), and improved packing (13.7%), but delayed harvesting increased losses (21.6%). For intermediaries, longer distances to market increased losses by 0.15%, while using proper storage, marketing in the formal markets, and using an appropriate transportation mode reduced losses by 65.9%, 13.8%, and 7.9%, respectively. Furthermore, the interaction between these practices significantly reduced the share of losses. The study emphasizes the need for increased public–private partnerships in agro-food logistics and improved knowledge dissemination through agricultural extension services and agri-cooperatives to achieve sustainable food production and consumption. This framework ensures robust, policy-actionable insights into how stakeholders’ behaviors influence postharvest losses (PHL). The findings can inform policymakers and agribusiness managers in designing cost-efficient strategies for reducing PHL and promoting sustainable food systems. Full article

We synthesized QM-AgNPs (Dianthus superbus L.-AgNPs, Qu Mai-AgNPs) by an economical and environmentally friendly method using Dianthus superbus L. extract as a reducing and stabilizing agent. The resulting QM-AgNPs were comprehensively characterized and evaluated for their antioxidant, cytotoxic, and antibacterial activities. Herein, TEM analysis revealed that the QM-AgNPs were predominantly spherical, polydisperse, and exhibited a core particle size ranging from 11 to 18 nm. In contrast, DLS analysis showed a larger hydrodynamic diameter (primarily 60–87 nm), reflecting the hydrated shell and surface biomolecular corona. The crystalline nature of QM-AgNPs was confirmed by XRD and SAED spectra while FTIR spectroscopy indicated the presence of functional groups from the plant extract that may contribute to nanoparticle stabilization. Functional assessments demonstrated that QM-AgNPs exhibited strong antioxidant activity, with efficient DPPH radical scavenging, and selective cytotoxicity against A549 cancer cells while sparing normal cells. Moreover, QM-AgNPs showed significant antibacterial activity against both Staphylococcus aureus (Gram-positive) and Escherichia coli (Gram-negative), likely due to membrane disruption and the leakage of intracellular contents. To explore practical applications, we developed a GEL@AgNPs coating system for the postharvest preservation of grapes. As a result, the reduced weight loss and decay rate suggest a potential role for QM-AgNPs in extending fruit freshness. Comprehensive shelf-life studies are planned to further substantiate the potential of QM-AgNPs as an effective material for active food packaging applications. Full article

It is a well-known fact that proper nutrition is essential for human beings to live healthy lives. For thousands of years, it has been considered that dates are one of the best nutrient providers. To have better-quality dates and to enhance the shelf life of dates, it is vital to preserve dates in optimal conditions that contribute to food security. Hence, it is crucial to know the shelf life of different types of dates. In current practice, shelf life assessment is typically based on manual visual inspection, which is subjective, error-prone, and requires considerable expertise, making it difficult to scale across large storage facilities. Traditional cold storage systems, whilst being capable of monitoring temperature and humidity, lack the intelligence to detect spoilage or predict shelf life in real-time. In this study, we present a novel IoT-based shelf life estimation system that integrates multichannel gas sensors and a lightweight machine learning model deployed on an edge device. Unlike prior approaches, our system captures the real-time emissions of spoilage-related gases (methane, nitrogen dioxide, and carbon monoxide) along with environmental data to classify the freshness of date fruits. The model achieved a classification accuracy of 91.9% and an AUC of 0.98 and was successfully deployed on an Arduino Nano 33 BLE Sense board. This solution offers a low-cost, scalable, and objective method for real-time shelf life prediction. This significantly improves reliability and reduces postharvest losses in the date supply chain. Full article

Functional foods are evolving beyond basic nutrition to address nutrition-related diseases and enhance well-being. While probiotic-fortified products dominate this sector, most remain dairy-based. This study investigated the incorporation of Lactobacillus rhamnosus GG and Bacillus coagulans GBI-30 into cereal-based pasta and noodles, evaluating bacterial survival during processing and cooking. Extrusion-based pasta production exerted greater stress on Lactobacillus rhamnosus GG, whereas Bacillus coagulans GBI-30 demonstrated higher thermal resistance. In sheeted noodles, both strains maintained ≥8 log CFU/g viability pre-cooking. After 7 min boiling, Lactobacillus rhamnosus GG retained 6.88 log CFU/g and Bacillus coagulans GBI-30 5.75 log CFU/g in noodles, meeting the recommended 10⁶–10⁷ CFU/g threshold for probiotic efficacy. Cooking performance analysis revealed lower cooking loss in noodles (2.4–4.04%) versus extruded pasta (10.6–19.05%), indicating superior structural integrity. These results confirm cereal matrices as viable non-dairy carriers for probiotics, with sheeting processes better preserving bacterial viability than extrusion. The findings highlight a practical strategy for developing functional foods that sustain probiotic viability through processing and consumption, potentially enhancing gut microbiota balance. This approach expands probiotic delivery options beyond traditional dairy formats while maintaining therapeutic bacterial concentrations critical for health benefits. Full article

Cotton is one of the most valuable non-food agricultural products in the world. However, cotton production is often hampered by the invasion of disease. In most cases, these plant diseases are a result of insect or pest infestations, which can have a significant impact on production if not addressed promptly. It is, therefore, crucial to accurately identify leaf diseases in cotton plants to prevent any negative effects on yield. This paper presents a hybrid deep learning approach based on Bidirectional Encoder Representations from Transformers with Residual network and particle swarm optimization (BERT-ResNet-PSO) for detecting cotton plant diseases. This approach starts with image pre-processing, which they pass to a BERT-like encoder after linearly embedding the image patches. It results in segregating disease regions. Then, the output of the encoded feature is passed to ResNet-based architecture for feature extraction and further optimized by PSO to increase the classification accuracy. The approach is tested on a cotton dataset from the Plant Village dataset, where the experimental results show the effectiveness of this hybrid deep learning approach, achieving an accuracy of 98.5%, precision of 98.2% and recall of 98.7% compared to the existing deep learning approaches such as ResNet50, VGG19, InceptionV3, and ResNet152V2. This study shows that the hybrid deep learning approach is capable of dealing with the cotton plant disease detection problem effectively. This study suggests that the proposed approach is beneficial to help avoid crop losses on a large scale and support effective farming management practices. Full article

Salt accumulation in arable lands causes significant abiotic stress, resulting in a 10% loss in global arable land area and jeopardizing food production and agricultural sustainability. In order to attain high and sustainable food production, it is imperative to enhance traditional agricultural practices with modern technology to enable the restoration of arable lands afflicted by salinity. This review consolidates recent rice-specific advancements aimed at enhancing salt stress resilience through integrated strategies. We explore the functions of primary and secondary metabolic pathways, organic amendments, microbial symbiosis, and plant growth regulators in reducing the negative impacts of salt. Furthermore, we highlight the significance of emerging genetic and epigenetic technologies, including gene editing and transcriptional regulation, in developing salt-tolerant rice cultivars. Physiological studies reveal salt stress responses in rice plants, biochemical analyses identify stress-related metabolites, microbial investigations uncover beneficial plant–microbe interactions, and molecular approaches enable the identification of key genes—together providing essential insights for developing salt-tolerant rice varieties. We present a comprehensive overview of the multilayered strategies—ranging from agronomic management and physiological adaptations to molecular breeding and microbial applications—that have been developed and refined over recent decades. These approaches have significantly contributed to understanding and improving salinity tolerance mechanisms in rice. This review provides a foundational framework for future research and practical implementation in stress-resilient rice farming systems. Full article