Ultrasound technology has emerged as a transformative tool in modern food science, offering non-destructive, real-time assessment and enhancement of food quality attributes. This review systematically explores the fundamental mechanisms by which ultrasound interacts with food matrices, including mechanical effects such as acoustic cavitation, localized shear forces, and microstreaming, as well as thermal and acoustic attenuation phenomena. Applications of ultrasound in food texture evaluation are discussed across multiple sectors, with particular emphasis on its role in assessing moisture distribution, fat content, structural integrity, and microstructural alterations in meat, dairy, fruits, and vegetables. The versatility of ultrasound—spanning low-intensity quality assessments to high-intensity processing interventions—makes it an invaluable technology for both quality control and product innovation. Moreover, emerging innovations such as ultrasound-assisted extraction, non-thermal pasteurization, and real-time quality monitoring are highlighted, demonstrating the synergy between ultrasound and advanced technologies like AI-driven data interpretation and portable, handheld sensing devices. Despite these advances, challenges related to technical limitations in heterogeneous food systems, high initial investment costs, scalability, and the absence of standardized protocols remain critical barriers to widespread adoption. The future directions emphasize the integration of ultrasound with multi-modal approaches, the development of miniaturized and cost-effective equipment, and the establishment of global regulatory standards to facilitate its broader application. Overall, ultrasound is positioned as a key enabler for sustainable, efficient, and non-invasive quality assurance across the global food industry.

Carbon quantum dots (CQDs), with their excellent photoluminescence, tunable surface chemistry, and low toxicity, have emerged as versatile nanomaterials in sensing technologies. Meanwhile, metal–organic frameworks (MOFs) possess exceptionally porous architectures and extensive surface areas, and tunable functionalities ideal for molecular recognition and analyte enrichment. The synergistic integration of CQDs and MOFs has significantly expanded the potential of hybrid materials with enhanced selectivity, sensitivity, and multifunctionality. While several reviews have addressed QD/MOF systems broadly, this review offers a focused and updated perspective on CQDs@MOFs composites specifically tailored for food safety and environmental sensing applications. This review provides a comprehensive analysis of recent advances in the design, synthesis, and surface functionalization of these hybrids, emphasizing the mechanisms of interaction, photophysical behavior, and performance advantages over conventional sensors. Special attention is given to their use in detecting food contaminants such as heavy metals, pesticides, antibiotics, mycotoxins, pathogens, and aromatic compounds. Key strategies to enhance stability, selectivity, and detection limits are highlighted, and current challenges and future directions for practical deployment are critically discussed.

The increasing demand for toxin-free food, driven by the rise in fast food consumption and changing dietary habits, necessitates advanced and efficient detection methods to address the potential risks associated with contaminated food. Nanomaterial-based detection methods have shown significant promise, particularly using metal-organic frameworks (MOFs) combined with biomolecules. This review article provides an overview of recent advancements in using functionalized metal-organic frameworks (FMOFs) with biomolecules to detect various food contaminants, including heavy metals, antibiotics, pesticides, bacteria, mycotoxins and other chemical contaminants. We discuss the fundamental principles of detecting food contaminants, evaluate existing analytical techniques, and explore the development of biomacromolecule-functionalized MOF-based sensors encompassing colorimetric, optical, electrochemical, and portable variants. The review also examines sensing mechanisms, uses FMOFs as signal probes and carriers for capture probes, and assesses sensitivity. Additionally, we explore the opportunities and challenges in producing FMOFs with biomacromolecules for food contaminant assessment. Future directions include improving sensor sensitivity and specificity, developing more cost-effective production methods, and integrating these technologies into real-world food safety monitoring systems. This work aims to pave the way for innovative and reliable solutions to ensure the safety of our food supply.

Meat is a vital source of high-quality proteins, amino acids, vitamins, and minerals essential for human health. Growing demand for healthier lifestyles and technological advancements has heightened the focus on meat products, whose quality depends on meat protein properties, such as texture, water holding capacity (WHC), and structural integrity. Non-thermal processing technologies are gaining attention for enhancing the gelation properties of meat protein gels (MPGs) by optimizing solubilization, denaturation, and aggregation while preserving nutritional and sensory qualities and avoiding the drawbacks of thermal treatments. This review focuses on advanced non-thermal processing techniques, including high-pressure processing (HPP), pulsed electric fields (PEFs), ultrasound, and cold plasma, and their impact on MPGs. It also examines vibrational spectroscopy methods, such as Fourier Transform Infrared (FTIR) and Raman spectroscopy, for non-invasive analysis of MPGs. The integration of these approaches with hyperspectral imaging and machine learning is also explored as a tool to improve quality control and assessment.

The demand for safe, high-quality, and minimally processed food has intensified interest in non-destructive analytical techniques capable of assessing freshness and safety in real time. Among these, near-infrared (NIR) spectroscopy and biosensors have emerged as leading technologies due to their rapid, reagent-free, and sample-preserving nature. NIR spectroscopy offers a holistic assessment of internal compositional changes, while biosensors provide specific and sensitive detection of biological and chemical contaminants. Recent advances in miniaturization, chemometrics, and deep learning have further enhanced their potential for inline and point-of-need applications across diverse food matrices, including meat, seafood, eggs, fruits, and vegetables. This review critically evaluates the operational principles, instrumentation, and current applications of NIR spectroscopy and biosensors in food freshness and safety monitoring. It also explores their integration, highlights practical challenges such as calibration transfer and regulatory hurdles, and outlines emerging innovations including hybrid sensing, Artificial Intelligence (AI) integration, and smart packaging. The scope of this review is to provide a comprehensive understanding of these technologies, and its objective is to inform future research and industrial deployment strategies that support sustainable, real-time food quality control. These techniques enable near real-time monitoring under laboratory and pilot-scale conditions, showing strong potential for industrial adaptation. The nature of these targets often determines the choice of transduction method.