Oleogel-based frying: quality attributes, food properties and future perspectives - A mini review.

The United Nations Sustainable Development Goals (UN SDGs) were defined to improve the quality of life of the global population particularly regarding social and economic aspects, with a major focus on environmental sustainability. The incorporation of digital technologies into the agri-food sector has become a key enabler in increasing the efficiency, productivity, and sustainability of food production and processing systems. Digital technologies and innovations including artificial intelligence (AI), robotics, in-ground and remote sensors, connectivity, and internet of things (IoT) have been recognized as also being critical for the successful implementation of the UN SDGs. In particular, the utilization of sensing technologies (e.g., in-ground and remote sensors) has been shown to be of great importance to achieve these goals. The use of vibrational spectroscopy and data analytics have shown potential to contribute with the development and implementation of UN SDGs. An overview of the contribution of sensing technologies based on the utilization of vibrational spectroscopy (e.g., near- and mid-infrared spectroscopy, hyperspectral imaging) and data analytics to achieve the UN SDGs is provided. Advantages and limitations of these techniques are also discussed. The incorporation of technology will provide tools that can be used to monitor and predict the safety and quality of foods. Furthermore, digital technologies are enabling the development of novel decision-management systems along the food supply and value chain. Ultimately, the goal will be to assure the consumers the use of these technologies plays a key role in the applicability of the UN SDG. © 2025 The Author(s). Journal of the Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

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Research progress on enantiomers detection in fermented foods.

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Electrolyzed water technologies in agri-food fields: From pesticide reduction to shelf-life extension and bioactive preservation.

Deep learning regression model based on data pairing and pseudo-label fusion for NIR predictive modeling in food and pharmaceutical quality analysis.

Intelligent storage year identification of Anhua dark tea via carbon quantum dots-based colorimetric sensor array and computer vision.

Structural elucidation and quantitative analysis of cinnamic acid derivatives using TIMS-MS, cyclodextrin adducts, and computational chemistry.

A rapid identification study of Atractylodis Macrocephalae Rhizoma and its hot processed products based on composite feature reconstruction combined with OOA-BP algorithm.

The improvement of freeze-thaw stability of surimi 3D printing products by fructooligosaccharides/trehalose-based natural deep eutectic solvent.

In-syringe dispersive solid-phase microextraction of oxalate using starch/dextrin- calcium/Silver nanoparticles sorbent followed by UV-visible spectrometry.

Modulation of highland barley noodles quality by water-soluble polyphenols epigallocatechin gallate and ferulic acid.

Elemental fingerprinting and regional verification of Pakistani basmati and non-basmati rice varieties using ICP-MS and multivariate analysis.

Adaptive foraging under stoichiometric constraints can reshape competitive outcomes.

Multi-omics reveals efficient thiamethoxam biodegradation but altered flavor profile by native microbiota during Pixian broad bean paste fermentation.

Purpose The objective of this study was to check the respective effects of perceived food value (PFV), perceived food quality (PFQ), and convenience (CON) on perceived behavioural control (PBC), subjective norms (SUN), and attitude (ATT). The study also assesses the effect of PBC, SUN, ATT, consumer lifestyle (COL), and health consciousness (HEC) on street food purchase intention (SFP). Design/methodology/approach To evaluate the framework, primary data were gathered through a questionnaire, from 386 street food consumers from Anand and Gandhinagar cities located in the State of Gujarat, India. An online and paper-pen survey was used to collect the data. The partial least squares-structural equation modelling technique was applied to the analysis of the data. Findings Results indicated that attitude (ATT) and SUN were the most significant predictors of street food purchase intention (SFP), whereas PBC showed limited influence. PFQ significantly influenced all three core constructs of the Theory of Planned Behaviour-ATT, SUN and PBC, followed by convenience (CON). PFV did not significantly influence PBC. HEC had a negative impact on SFP, reflecting the hesitation of health-conscious consumers, while COL had no significant impact. Originality/value In the study, peer judgement and personal attributes were preferred over the concern for accessibility and health risks for street food consumption. These practical insights can be used by vendors, marketers and policymakers aiming to sustain and regulate the informal food segment.

Fresh vegetables, especially green onions and chives, are raw ingredients widely consumed by Koreans, and have been linked to Listeria monocytogenes-induced food poisoning. This study aimed to assess microbial contamination levels in commercially available fresh-cut vegetables and produce, compare the effects of different types and concentrations of disinfectants on green onions and chives, and determine the growth rate of L. monocytogenes on chives under different storage conditions. Among the five fresh-cut vegetable mix salad products, the average total mesophilic count (TMC) was 2.00 log CFU/g, whereas the crown daisies exhibited the highest levels of raw produce contamination (TMC of 4.14 log CFU/g). The disinfection experiments indicated the elevated disinfectant capacities of electrolyzed water as well as washing under running water against Escherichia coli and L. monocytogenes. Enhanced anti-TMC ability of electrolyzed water were observed in acidic 30 ppm (pH 3.2) and 60 ppm (pH 5.6) of HOCl, and alkaline 100 ppm (pH 8.1) and 200 ppm (pH 8.8) of NaClO. Moreover, in the L. monocytogenes inoculation experiment in chive, the growth rates at 5 °C, 12 °C, and 30 °C were -0.002, 0.023, and 0.030 log CFU/g/h, respectively. This observation suggests that L. monocytogenes cannot grow on chives if stored at 5 °C but can at 12 °C. This study provides scientific evidence to guide the management of microbial quality of fresh produce and fresh-cut vegetables for safer meal provision in home and eating-out settings.