The migration of chemical compounds from packaging polymers to food presents a multifaceted challenge with implications for food safety and public health. This review explores the interaction between packaging materials and food products, focusing on permeation, migration, and sorption processes. The different migration mechanisms of contact migration, gas phase migration, penetration migration, set-off migration, and condensation/distillation migration have been discussed comprehensively. The major migrating compounds are plasticizers, nanoparticles, antioxidants, light stabilizers, thermal stabilizers, monomers, oligomers, printing inks, and adhesives, posing potential health risks due to their association with endocrine disruption and carcinogenic effects. Advanced analytical methods help in the monitoring of migrated compounds, facilitating compliance with regulatory standards. Regulatory agencies enforce guidelines to limit migration, prompting the development of barrier coatings and safer packaging alternatives. Furthermore, there is a need to decipher the migration mechanism for mitigating it along with advancements in analytical techniques for monitoring the migration of compounds.

This review describes the various innovative approaches implemented for naringin extraction as well as the recent developments in the field. Naringin was assessed in terms of its structure, chemical composition, and potential food sources. How naringin works pharmacologically was discussed, including its potential as an anti-diabetic, anti-inflammatory, and hepatoprotective substance. Citrus flavonoids are crucial herbal additives that have a huge spectrum of organic activities. Naringin is a nutritional flavanone glycoside that has been shown to be effective in the treatment of a few chronic disorders associated with ageing. Citrus fruits contain a common flavone glycoside that has specific pharmacological and biological properties. Naringin, a flavone glycoside with a range of intriguing characteristics, is abundant in citrus fruits. Naringin has been shown to have a variety of biological, medicinal, and pharmacological effects. Naringin is hydrolyzed into rhamnose and prunin by the naringinase, which also possesses l-rhamnosidase activity. D-glucosidase subsequently catalyzes the hydrolysis of prunin into glucose and naringenin. Naringin is known for having anti-inflammatory, antioxidant, and tumor-fighting effects. Numerous test animals and cell lines have been used to correlate naringin exposure to asthma, hyperlipidemia, diabetes, cancer, hyperthyroidism, and osteoporosis. This study focused on the many documented actions of naringin in in-vitro and in-vivo experimental and preclinical investigations, as well as its prospective therapeutic advantages, utilizing the information that is presently accessible in the literature. In addition to its pharmacokinetic characteristics, naringin’s structure, distribution, different extraction methods, and potential use in the cosmetic, food, pharmaceutical, and animal feed sectors were discussed.

Shikonin and its derivatives, isolated from traditional medicinal plant species of the genus Lithospermum, Alkanna, Arnebia, Anchusa, Onosma, and Echium belonging to the Boraginaceae family, have numerous applications in foods, cosmetics, and textiles. Shikonin, a potent bioactive red pigment, has been used in traditional medicinal systems to cure various ailments and is well known for its diverse pharmacological potential such as anticancer, antithrombotic, neuroprotective, antidiabetic, antiviral, anti-inflammatory, anti-gonadotropic, antioxidants, antimicrobial and insecticidal. Herein, updated research on the natural sources, pharmacology, toxicity studies, and various patents filed worldwide related to shikonin and approaches to shikonin’s biogenic and chemical synthesis are reviewed. Furthermore, recent studies to establish reliable production systems to meet market demand, functional identification, and future clinical development of shikonin and its derivatives against various diseases are presented.

Sappan wood (Caesalpinia sappan) is a tropical hardwood tree found in Southeast Asia. Sappan wood contains a water-soluble compound, which imparts a red color named brazilin. Sappan wood is utilized to produce dye for fabric and coloring agents for food and beverages, such as wine and meat. As a valuable medicinal plant, the tree is also known for its antioxidant, anti-inflammatory, and anticancer properties. It has been observed that sappan wood contains various bioactive compounds, including brazilin, brazilein, sappan chalcone, and protosappanin A. It has also been discovered that these substances have various health advantages; they lower inflammation, enhance blood circulation, and are anti-oxidative in nature. Sappan wood has been used as a medicine to address a range of illnesses, such as gastrointestinal problems, respiratory infections, and skin conditions. Studies have also suggested that sappan wood may have anticarcinogenic potential as it possesses cytotoxic activity against cancer cells. Based on this, the present review emphasized the different medicinal properties, the role of phytochemicals, their health benefits, and several food and nonfood applications of sappan wood. Overall, sappan wood has demonstrated promising medicinal properties and is an important resource in traditional medicine. The present review has explored the potential role of sappan wood as an essential source of bioactive compounds for drug development.

Machine learning assists with food process optimization techniques by developing a model to predict the optimal solution for given input data. Machine learning includes unsupervised and supervised learning, data pre-processing, feature engineering, model selection, assessment, and optimization methods. Various problems with food processing optimization could be resolved using these techniques. Machine learning is increasingly being used in the food industry to improve production efficiency, reduce waste, and create personalized customer experiences. Machine learning may be used to improve ingredient utilization and save costs, automate operations such as packing and labeling, and even forecast consumer preferences to develop personalized products. Machine learning is also being used to identify food safety hazards before they reach the consumer, such as contaminants or spoiled food. The usage of machine learning in the food sector is predicted to rise in the near future as more businesses understand the potential of this technology to enhance customer experience and boost productivity. Machine learning may be utilized to enhance nano-technological operations and fruit and vegetable preservation. Machine learning algorithms may find trends regarding various factors that impact the quality of the product being preserved by examining data from prior tests. Furthermore, machine learning may be utilized to determine optimal parameter combinations that result in maximal produce preservation. The review discusses the relevance of machine learning in ready-to-eat foods and its use as a safety tool for preservation were highlighted. The application of machine learning in agriculture, food packaging, food processing, and food safety is reviewed. The working principle and methodology, as well as the principles of machine learning, were discussed.