In the past few decades, fruits have been increasingly consumed, leading to an increase in global fruit production. However, fresh produce is susceptible to large losses during production and preservation. In the postharvest preservation stage, fruits undergo various technical treatments for maintaining their quality. A widely adopted technology is the application of edible coatings, which can be applied to a diverse range of fruits to regulate the exchange of moisture and gases between the fruit and its environment. In addition, edible coatings provide a significant benefit by allowing the integration of different active ingredients into the coating’s matrix, meaning that these substances will associate with and possibly be eaten together with the fruit. This would help improve the organoleptic and nutritional qualities of the fruit as well as the shelf life. This paper provides an overview of the available data on the typical components used in coating matrix, focusing on the effect of the material combinations and application techniques to fruit properties. The processors can use this knowledge in choosing a suitable coating material and concentration for various fresh and fresh-cut fruits. Additionally, this paper reviews recent developments and limitations in utilizing edible coatings for prolonging the shelf-life of fruits.

The rheology of yogurt, a critical factor influencing its texture, stability, and sensory appeal from production to consumption is explored in this review. Yogurt undergoes a transformation from a Newtonian liquid to a non‐Newtonian thixotropic gel during fermentation, a process shaped by factors such as milk source, starter culture, and fat content. Recent advances in non‐thermal treatments, such as ultrasound, microfiltration, high‐pressure processing (HPP), and ultraviolet C (UV‐C) light treatment, promise to enhance nutritional and sensory qualities of yogurt. Additionally, incorporating herbs and fruits into yogurt not only diversifies consumer options but also affects its texture, viscosity, and overall mouthfeel. The review examines how different yogurt styles—set, stirred, Greek, and drinkable—develop unique textures through varied production processes. Advances in rheological techniques and microstructural analysis have deepened our understanding of the interactions between proteins and fat globules, providing insights into the complex gel network of yogurt. Despite significant progress, further research is needed in areas such as non‐destructive rheological testing during production, the impact of extended storage, and the development of plant‐based yogurt alternatives. The insights are valuable for the dairy industry to support innovation and meet growing consumer demands.

Fruit juice and wine are important beverages that are consumed all over the world. Due to their constantly increasing demand and high value, fruit juice and wine are one of the most frequent targets of adulteration. Since adulterated foods are proven to have harmful effects on health, several approaches have been utilized for the detection of fruit juice and wine adulteration. Based on the requirement for sample destruction, analytical techniques to assess food authenticity can be classified into 2 main categories, i.e., destructive and non-destructive techniques. This paper provides an overview on the principle of adulteration detection, its application and performance, and the advantages and limitations of various analytical techniques. Destructive approaches, such as physicochemical methods, isotope analysis, elemental analysis, chromatographic techniques, and DNA-based techniques, are reviewed. Furthermore, non-destructive approaches, including spectroscopic-based techniques, nuclear magnetic resonance spectroscopic technique, electronic techniques, and imaging-based techniques, are discussed.

Presented work investigated the application of a new color analysis technique in post-harvest life of sweet cherry (Prunus avium L. ‘Hudson’). The hue spectra fingerprinting creates a histogram of image colors by summarizing the saturation. The advantage of this calculation method is that vivid colors make peaks while neutral background color is eliminated without object segmentation. Partial Least Squares (PLS) regression was used to estimate reference parameters during 9 d cold storage at 10 ± 0.5 °C (RH = 90 ± 1%) and following 2 d shelf-life at 20 ± 0.5 °C. The reference parameters of respiration, weight loss, fruit firmness and total soluble solid (TSS) content were measured. Samples were split into seven groups according to the number of perforations of polypropylene film and fructose concentration of moisture absorber. It was observed that parameters TSS and fruit firmness were the most sensitive to the length of storage. Weight loss was affected significantly by packaging. All reference parameters were estimated by PLS model with R² > 0.917, but weight loss and respiration obtained high estimation error of RMSE% = 48.02% and 11.76%, respectively. TSS and fruit firmness prediction were successful with RMSE% = 0.84% and 1.85%, respectively. Desiccation and color change of peduncle became visible in the green range of hue spectra. Color change of red fruit was observed with decreasing saturation in the red range of hue spectra. Our findings suggest that hue spectra fingerprinting can be a useful nondestructive method for monitoring quality change of sweet cherry during post-harvest handling and shelf-life.

Food adulteration is in the focus of research due to its negative effect on safety and nutritional value and because of the demand for the protection of brands and regional origins. Portugieser and Sauvignon Blanc wines were selected for experiments. Samples were made by water dilution, the addition of sugar and then a combination of both. Near infrared (NIR) spectra were acquired in the range of 900–1700 nm. Partial least squares regression was performed to predict the adulteration level. The model including all wines and adulterations achieved a prediction error of 0.59% added sugar and 6.85% water dilution. Low-power laser modules were used to collect diffuse reflectance signals at wavelengths of 532, 635, 780, 808, 850, 1064 nm. The general linear model resulted in a higher prediction error of 3.06% added sugar and 20.39% water dilution. Instead of classification, the present study investigated the feasibility of non-destructive methods in the prediction of adulteration level. Laser scattering successfully detected the added sugar with linear discriminant analysis (LDA), but its prediction accuracy was low. NIR spectroscopy might be suitable for rapid non-destructive estimation of wine adulteration.