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Nickel salts of Keggin-type heteropolyacid on Zr(IV)-based metal-organic frameworks (UiO-66) has been synthesized via ion-exchange followed by a facile one-pot hydrothermal method. The synthesized catalysts underwent FT-IR, N2 adsorption-desorption, powder XRD, SEM and TEM analysis. The NiHSiW/UiO-66 catalyst was used as a new and effective solid acid in the catalytic transfer free fatty acid to biodiesel with an optimum conversion of 86.7%. The excellent activity of the NiHSiW/UiO-66 nanocatalyst was closely related to its high specific surface area, nano-sized catalyst, and the synergistic effects of NiHSiW salts and UiO-66 matrix. Importantly, a relatively stable catalytic performance was achieved for 8 repeated cycles. Finally, kinetics of the esterification reaction have been assumed to be of pseudo first order.

Maintaining food safety and quality is critical for public health and food security. Conventional food preservation methods, such as pasteurization and dehydration, often change the overall organoleptic quality of the food products. Herein, we demonstrate a method that affects only a thin surface layer of the food, using beef as a model. In this method, Joule heating is generated by applying high electric power to a carbon substrate in ~2000 K. The beef surface in direct contact with the heating substrate is subjected to ultra-high temperature flash heating, leading to the formation of a microbe-inactivated, dehydrated layer of ~100 µm in thickness. Aerobic mesophilic bacteria, Enterobacteriaceae, yeast and mold on the treated samples are inactivated to a level below the detection limit and remained low during room temperature storage of 5 days. Meanwhile, the product quality, including visual appearance, texture, and nutrient level of the beef, remains mostly unchanged. In contrast, microorganisms grow rapidly on the untreated control samples, along with a rapid deterioration of the meat quality. This method might serve as a promising preservation technology for securing food safety and quality.

Addressing the critical need for swift and precise nutritional profiling in healthcare and in food industry, this study pioneers the integration of vision‐language models (VLMs) with chemical analysis techniques. A cutting‐edge VLM is unveiled, utilizing the expansive UMDFood‐90k database, to significantly improve the speed and accuracy of nutrient estimation processes. Demonstrating a macro‐AUCROC of 0.921 for lipid quantification, the model exhibits less than 10% variance compared to traditional chemical analyses for over 82% of the analyzed food items. This innovative approach not only accelerates nutritional screening by 36.9% when tested amongst students but also sets a new benchmark in the precision of nutritional data compilation. This research marks a substantial leap forward in food science, employing a blend of advanced computational models and chemical validation to offer a rapid, high‐throughput solution for nutritional analysis. [ABSTRACT FROM AUTHOR]

Tea contains a variety of bioactive components, including catechins, amino acids, tea pigments, caffeine and tea polysaccharides, which exhibit multiple biological activities. These functional components in tea provide a variety of unique flavors, such as bitterness, astringency, sourness, sweetness and umami, which meet the demand of people for natural plant drinks with health benefits and pleasant flavor. Meanwhile, the traditional process of tea plantation, manufacturing and circulation are often accompanied by the safety problems of pesticide residue, heavy metal, organic solvents and other exogenous risks. High-quality tea extract refers to the special tea extract obtained by enriching the specific components of tea. Through green and efficient extraction technologies, diversed high-quality tea extracts such as high-fragrance and high-amino acid tea extracts, low-caffeine and high-catechin tea extracts, high-bioavailability and high-theaflavin tea extracts, high-antioxidant and high-tea polysaccharide tea extracts, high-umami-taste and low-bitter and astringent taste tea extracts are produced. Furthermore, rapid detection, green control and intelligent processing are applied to monitor the quality of tea in real-time, which guarantee the stability and safety of high-quality tea extracts with enhanced efficiency. These emerging technologies will realize the functionalization and specialization of high-quality tea extracts, and promote the sustainable development of tea industry. HIGHLIGHTS: Main high-quality tea extracts and their preparation methods were introduced. Potential pollutants in the processing of tea extracts and their detection methods were proposed. Emerging intelligent processing technologies of tea extract were summarized. The applications of high-quality tea extracts in food industry were explored. Future trends of tea extracts and relevant suggestions were presented. [ABSTRACT FROM AUTHOR]

Broccoli sprouts have been considered as functional foods which have received increasing attention because they have been highly prized for glucosinolates, phenolics, and vitamins in particular glucosinolates. One of hydrolysates-sulforaphane from glucoraphanin is positively associated with the attenuation of inflammatory, which could reduce diabetes, cardiovascular and cancer risk. In recent decades, the great interest in natural bioactive components especially for sulforaphane promotes numerous researchers to investigate the methods to enhance glucoraphanin levels in broccoli sprouts and evaluate the immunomodulatory activities of sulforaphane. Therefore, glucosinolates profiles are different in broccoli sprouts varied with genotypes and inducers. Physicochemical, biological elicitors, and storage conditions were widely studied to promote the accumulation of glucosinolates and sulforaphane in broccoli sprouts. These inducers would stimulate the biosynthesis pathway gene expression and enzyme activities of glucosinolates and sulforaphane to increase the concentration in broccoli sprouts. The immunomodulatory activity of sulforaphane was summarized to be a new therapy for diseases with immune dysregulation. The perspective of this review served as a potential reference for customers and industries by application of broccoli sprouts as a functional food and clinical medicine. [ABSTRACT FROM AUTHOR]

Neural network (i.e. deep learning, NN)-based data analysis techniques have been listed as a pivotal opportunity to protect the integrity and safety of the global food supply chain and forecast $11.2 billion in agriculture markets. As a general-purpose data analytic tool, NN has been applied in several areas of food science, such as food recognition, food supply chain security and omics analysis, and so on. Therefore, given the rapid emergence of NN applications in food safety, this review aims to provide a comprehensive overview of the NN application in food analysis for the first time, focusing on domain-specific applications in food analysis by introducing fundamental methodology, reviewing recent and notable progress, and discussing challenges and potential pitfalls. NN demonstrated that it has a bright future through effective collaboration between food specialist and the broader community in the food field, for example, superiority in food recognition, sensory evaluation, pattern recognition of spectroscopy and chromatography. However, major challenges impeded NN extension including void in the food scientist-friendly interface software package, incomprehensible model behavior, multi-source heterogeneous data, and so on. The breakthrough from other fields proved NN has the potential to offer a revolution in the immediate future. [ABSTRACT FROM AUTHOR]