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Mycotoxins represent an assorted range of secondary fungal metabolites that extensively occur in numerous food and feed ingredients at any stage during pre- and post-harvest conditions. Zearalenone (ZEN), a mycotoxin categorized as a xenoestrogen poses structural similarity with natural estrogens that enables its binding to the estrogen receptors leading to hormonal misbalance and numerous reproductive diseases. ZEN is mainly found in crops belonging to temperate regions, primarily in maize and other cereal crops that form an important part of various food and feed. Because of the significant adverse effects of ZEN on both human and animal, there is an alarming need for effective detection, mitigation, and management strategies to assure food and feed safety and security. The present review tends to provide an updated overview of the different sources, occurrence and biosynthetic mechanisms of ZEN in various food and feed. It also provides insight to its harmful effects on human health and agriculture along with its effective detection, management, and control strategies.

Citrinin (CIT) is a mycotoxin produced by different species of Aspergillus, Penicillium, and Monascus. CIT can contaminate a wide range of foods and feeds at any time during the pre-harvest, harvest, and post-harvest stages. CIT can be usually found in beans, fruits, fruit and vegetable juices, herbs and spices, and dairy products, as well as red mold rice. CIT exerts nephrotoxic and genotoxic effects in both humans and animals, thereby raising concerns regarding the consumption of CIT-contaminated food and feed. Hence, to minimize the risk of CIT contamination in food and feed, understanding the incidence of CIT occurrence, its sources, and biosynthetic pathways could assist in the effective implementation of detection and mitigation measures. Therefore, this review aims to shed light on sources of CIT, its prevalence in food and feed, biosynthetic pathways, and genes involved, with a major focus on detection and management strategies to ensure the safety and security of food and feed.

Soil contamination with heavy metals presents a substantial environmental peril, necessitating the exploration of innovative remediation approaches. This research aimed to investigate the efficiency of nano-silica in stabilizing heavy metals in a calcareous heavy metal-contaminated soil. The soil was treated with five nano-silica levels of 0, 100, 200, 500, and 1000 mg/kg and incubated for two months. The results showed that nano-silica had a specific surface area of 179.68  m 2 / g . At 1000 mg/kg, the DTPA-extractable concentrations of Pb, Zn, Cu, Ni, and Cr decreased by 12%, 11%, 11.6%, 10%, and 9.5% compared to the controls, respectively. Additionally, as the nano-silica application rate increased, both soil pH and specific surface area increased. The augmentation of nano-silica adsorbent in the soil led to a decline in the exchangeable (EX) and carbonate-bound fractions of Pb, Cu, Zn, Ni, and Cr, while the distribution of heavy metals in fractions bonded with Fe–Mn oxides, organic matter, and residue increased. The use of 1000 mg/kg nano-silica resulted in an 8.0% reduction in EX Pb, 4.5% in EX Cu, 7.3% in EX Zn, 7.1% in EX Ni, and 7.9% in EX Cr compared to the control treatment. Overall, our study highlights the potential of nano silica as a promising remediation strategy for addressing heavy metal pollution in contaminated soils, offering sustainable solutions for environmental restoration and ecosystem protection.

Background Soil contamination with heavy metals poses a significant threat to plant health and human well-being. This study explores the potential of nano silica as a solution for mitigating heavy metal uptake in Calendula officinalis . Results Greenhouse experiments demonstrated, 1000 mg•kg − 1 nano silica caused a 6% increase in soil pH compared to the control treatment. Also in 1000 mg. kg − 1 nano silica, the concentrations of available Pb (lead), Zn (zinc), Cu (copper), Ni (nickel), and Cr (chromium) in soil decreased by 12%, 11%, 11.6%, 10%, and 9.5%, respectively, compared to the control. Nano silica application significantly reduces heavy metal accumulation in C. officinalis exposed to contaminated soil except Zn. In 1000 mg.kg − 1 nano silica shoots Zn 13.28% increased and roots Zn increased 13% compared to the control treatment. Applying nano silica leads to increase the amount of phosphorus (P) 25%, potassium (K) 26% uptake by plant, In 1000 mg.kg − 1 treatment the highest amount of urease enzyme activity was 2.5%, dehydrogenase enzyme activity, 23.6% and the highest level of alkaline phosphatase enzyme activity was 13.5% higher than the control treatment. Conclusion Nano silica, particularly at a concentration of 1000 mg.kg − 1 , enhanced roots and shoots length, dry weight, and soil enzyme activity Moreover, it increased P and K concentrations in plant tissues while decreasing heavy metals uptake by plant.

Background Among different adsorbents, natural and inorganic compounds such as diatomite are important and advantageous in terms of high efficiency and cost-effectiveness, and function in stabilizing heavy metals in the environment. Calendula officinalis , a plant known as a high accumulator of heavy metals, was cultivated in soil treated with varying concentrations of modified diatomite to demonstrate the efficiency of modified diatomite in stabilizating of heavy metals in soils, Results The modification of diatomite aimed to enhance Calendula officinalis adsorptive properties, particularly towards heavy metals such as lead (Pb), Zinc (Zn), Chromium (Cr), Nickle (Ni), and Copper (Cu), common contaminants in industrial soils. The experimental design included both control and treated soil samples, with assessments at regular intervals. Modified diatomite significantly decreased the bioaccumulation of heavy metals in contaminated soils except Zn, evidenced by decreased DTPA extractable heavy metals in soil and also heavy metal concentrations in plant tissues. Using 10% modified diatomite decreased 91% Pb and Cu, 78% Cr, and 79% Ni concentration of plants compared to the control treatment. The highest concentration of Zn in plant tissue was observed in 2.5% modified diatomite treatment. Remarkably, the application of modified diatomite also appeared to improve the nutrient profile of the soil, leading to enhanced uptake of key nutrients like phosphorus (P) 1.18%, and potassium (K) 79.6% in shoots and 82.3% in roots in Calendula officinalis . Consequently, treated plants exhibited improved growth characteristics, including shoots and roots height of 16.98% and 12.8% respectively, and shoots fresh and dry weight of 48.5% and 50.2% respectively., compared to those in untreated, contaminated soil. Conclusion The findings suggest promising implications for using such amendments in ecological restoration and sustainable agriculture, particularly in areas impacted by industrial pollution.

Recent advancements in signal processing and computational power have revolutionized computer vision applications in diverse industries such as agriculture, food processing, biomedical, and the military. These developments are propelling efforts to automate processes and enhance efficiency. Notably, computational techniques are replacing labor-intensive manual methods for assessing the maturity indices of fruits and vegetables during critical growth stages. This review paper focuses on recent advancements in computer vision techniques specifically applied to determine the maturity indices of fruits and vegetables within the food processing sector. It highlights successful applications of Nuclear Magnetic Resonance (NMR), Near-Infrared Spectroscopy (NIR), thermal imaging, and image scanning. By examining these techniques, their underlying principles, and practical feasibility, it offers valuable insights into their effectiveness and potential widespread adoption. Additionally, integrating biosensors and AI techniques further improves accuracy and efficiency in maturity index determination. In summary, this review underscores the significant role of computational techniques in advancing maturity index assessment and provides insights into their principles and effective utilization. Looking ahead, the future of computer vision techniques holds immense potential. Collaborative efforts among experts from various fields will be crucial to address challenges, ensure standardization, and safeguard data privacy. Embracing these advancements can lead to sustainable practices, optimized resource management, and progress across industries. Graphical Abstract Highlights 1. Recent advancements in signal processing and computation drive interest in computer vision across industries. 2. The review focuses on non-destructive methods in fruits and vegetables. 3. Computational techniques replace manual methods for maturity index determination. 4. The principles of techniques are highlighted, along with their successful applications. 5. The potential of computation techniques in destructive, non-destructive methods, biosensors, and AI summarized.

Cereals and cereal-based products are primary sources of nutrition across the world. However, contamination of these foods with aflatoxins (AFs), secondary metabolites produced by several fungal species, has raised serious concerns. AF generation in innate substrates is influenced by several parameters, including the substrate type, fungus species, moisture content, minerals, humidity, temperature, and physical injury to the kernels. Consumption of AF-contaminated cereals and cereal-based products can lead to both acute and chronic health issues related to physical and mental maturity, reproduction, and the nervous system. Therefore, the precise detection methods, detoxification, and management strategies of AFs in cereal and cereal-based products are crucial for food safety as well as consumer health. Hence, this review provides a brief overview of the occurrence, chemical characteristics, biosynthetic processes, health hazards, and detection techniques of AFs, along with a focus on detoxification and management strategies that could be implemented for food safety and security.

This study investigates the kinetics and optimization of fluidized bed drying of onion slices using CCRD design by Response Surface Methodology, aiming to enhance drying efficiency and preserve product quality. The effects of drying process parameters viz., drying temperature (43.18, 50,60,70, & 76.82 °C), NaCl concentration (6.59, 10, 15, 20, & 23.41%) and bed thickness (1.636, 3,5, 7, & 8.362 mm) on dehydration ratio, rehydration ratio, color change, ascorbic acid content and overall acceptability were evaluated using multiple response optimization techniques. Optimization analysis revealed that a drying temperature of 70 °C, NaCl concentration of 20%, and bed thickness of 3 mm yielded the highest desirability value of 0.637. Under these optimized conditions, the dehydration ratio, rehydration ratio, color change, ascorbic acid content, and overall acceptability of onion slices were measured at 6.76, 5.87, 4.85, 8.06 and 4.02, respectively. Higher drying temperatures, NaCl concentrations and lower bed thickness were associated with faster drying rates. Various mathematical models, including Page, Logarithmic, Henderson and Pabis, Midilli and Newton models, were employed to characterize the drying kinetics, with the Page Model demonstrating superior fit to experimental data. Furthermore, quality parameters such as moisture content, water activity, ascorbic acid content, color change and crispiness of onion slices stored for three months under optimized conditions and packaged in different materials (LDPE and HDPE) were evaluated. Results indicate that the optimized fluidized bed drying process parameters effectively maintained the quality of onion slices during storage.

Mycotoxins are fungi-produced secondary metabolites that can contaminate many foods eaten by humans and animals. Deoxynivalenol (DON), which is formed by Fusarium, is one of the most common occurring predominantly in cereal grains and thus poses a significant health risk. When DON is ingested, it can cause both acute and chronic toxicity. Acute signs include abdominal pain, anorexia, diarrhea, increased salivation, vomiting, and malaise. The most common effects of chronic DON exposure include changes in dietary efficacy, weight loss, and anorexia. This review provides a succinct overview of various sources, biosynthetic mechanisms, and genes governing DON production, along with its consequences on human and animal health. It also covers the effect of environmental factors on its production with potential detection, management, and control strategies.

Pullulanases are the most important industrial group of enzymes in family 13 glycosyl hydrolases. They hydrolyze either α-1,6 and α-1,4 or both glycosidic bonds in pullulan as well as other carbohydrates to produce glucose, maltose, and maltotriose syrups, which have important uses in food and other related sectors. However, very less reports are available on pullulanase production from native strains because of low yield issues. In line with the increasing demands for pullulanase, it has become important to search for novel pullulanase-producing microorganisms with high yields. Moreover, high production costs and low yield are major limitations in the industrial production of pullulanase enzymes. The production cost of pullulanase by using the solid-state fermentation (SSF) process can be minimized by selecting agro-industrial waste. This review summarizes the types, sources, production strategies, and potential applications of pullulanase in different food and other related industries. Researchers should focus on fungal strains producing pullulanase for better yield and low production costs by using agro-waste. It will prove a better enzyme in different food processing industries and will surely reduce the cost of products.