Recognizing and classifying localized lesions on apple fruit surfaces during automated sorting is critical for improving product quality and increasing the sustainability of fruit production. This study is aimed at developing sustainable methods for fruit sorting by applying hyperspectral analysis and machine learning to improve product quality and reduce losses. The employed hyperspectral technologies and machine learning algorithms enable the rapid and accurate detection of defects on the surface of fruits, enhancing product quality and reducing the number of rejects, thereby contributing to the sustainability of agriculture. This study seeks to advance commercial fruit quality control by comparing hyperspectral image classification algorithms to detect apple lesions caused by pathogens, including sunburn, scab, and rot, on three apple varieties: Honeycrisp, Gala, and Jonagold. The lesions were confirmed independently using expert judgment, real-time PCR, and 3D fluorimetry, providing a high accuracy of ground truth data and allowing conclusions to be drawn on ways to improve the sustainability and safety of the agrocenosis in which the fruits are grown. Hyperspectral imaging combined with mathematical analysis revealed that Venturia inaequalis is the main pathogen responsible for scab, while Botrytis cinerea and Penicillium expansum are the main causes of rot. This comparative study is important because it provides a detailed analysis of the performance of both supervised and unsupervised classification methods for hyperspectral imagery, which is essential for the development of reliable automated grading systems. Support Vector Machines (SVM) proved to be the most accurate, with the highest average adjusted Rand Index (ARI) scores for sunscald (0.789), scab (0.818), and rot (0.854), making it the preferred approach for classifying apple lesions during grading. K-Means performed well for scab (0.786) and rot (0.84) classes, but showed limitations with lower metrics for other lesion types. A design and technological scheme of an optical system for identifying micro- and macro-damage to fruit tissues is proposed, and the dependence of the percentage of apple damage on the rotation frequency of the sorting line rollers is obtained. The optimal values for the rotation frequency of the rollers, at which the damage to apples is less than 5%, are up to 6 Hz. The results of this study confirm the high potential of hyperspectral data for the non-invasive recognition and classification of apple diseases in automated sorting systems with an accuracy comparable to that of human experts. These results provide valuable insights into the optimization of machine learning algorithms for agricultural applications, contributing to the development of more efficient and accurate fruit quality control systems, improved production sustainability, and the long-term storage of fruits.

Currently, there is a growing interest in biomedical research in the use of inorganic nanoparticles for targeted drug delivery, as biosensors, and in theranostic applications. This review examines the interaction of inorganic nanoparticles with protein molecules depending on the chemical nature, size, and surface charge of the nanoparticles. The effect of protein and nanoparticle concentration, as well as their incubation time, is analyzed. The work focuses on the influence of parameters such as pH, ionic strength, and temperature on the interaction of nanoparticles with protein molecules. The following dependencies were studied in detail: the thickness of the protein corona as a function of nanoparticle size; the size of nanoparticles after interaction with protein as a function of protein and nanoparticle concentration; the distribution of zeta potentials in colloids of nanoparticles, proteins, and their mixtures. It has been shown that proteins and nanoparticles can influence each other’s physicochemical properties. This can lead to the emergence of new biological properties in the system. Therefore, the adsorption of proteins onto nanoparticle surfaces can induce conformational changes. The probability of changing the protein structure increases when a covalent bond is formed between the nanoparticle and the protein molecule. Studies demonstrate that protein structure remains more stable with spherical nanoparticles than with rod-shaped or other high-curvature nanostructures. The results presented in the review demonstrate the possibility of adapting physiological responses to nanomaterials by changing the chemical composition of the surface of nanoparticles and their size and charge.

With the help of laser ablation, a technology for obtaining nanosized crystalline selenium particles (SeNPs) has been created. The SeNPs do not exhibit significant toxic properties, in contrast to molecular selenium compounds. The administration of SeNPs can significantly increase the viabilities of SH-SY5Y and PCMF cells after radiation exposure. The introduction of such nanoparticles into the animal body protects proteins and DNA from radiation-induced damage. The number of chromosomal breaks and oxidized proteins decreases in irradiated mice treated with SeNPs. Using hematological tests, it was found that a decrease in radiation-induced leukopenia and thrombocytopenia is observed when selenium nanoparticles are injected into mice before exposure to ionizing radiation. The administration of SeNPs to animals 5 h before radiation exposure in sublethal and lethal doses significantly increases their survival rate. The modification dose factor for animal survival was 1.2. It has been shown that the introduction of selenium nanoparticles significantly normalizes gene expression in the cells of the red bone marrow of mice after exposure to ionizing radiation. Thus, it has been demonstrated that SeNPs are a new gene-protective and radioprotective agent that can significantly reduce the harmful effects of ionizing radiation.

Optical methods (spectroscopy, spectrofluorometry, dynamic light scattering, and refractometry) were used to study the change in the state of hen egg-white lysozyme (HEWL), protein molecules, and gold nanoparticles (AuNPs) in aqueous colloids with changes in pH, and the interaction of protein molecules with nanoparticles was also studied. It was shown that changing pH may be the easiest way to control the protein corona on gold nanoparticles. In a colloid of nanoparticles, both in the presence and absence of protein, aggregation–deaggregation, and in a protein colloid, monomerization–dimerization–aggregation are the main processes when pH is changed. A specific point at pH 7.5, where a transition of the colloidal system from one state to another is observed, has been found using all the optical methods mentioned. It has been shown that gold nanoparticles can stabilize HEWL protein molecules at alkaline pH while maintaining enzymatic activity, which can be used in practice. The data obtained in this manuscript allow for the state of HEWL colloids and gold nanoparticles to be monitored using one or two simple and accessible optical methods.

The influence of the solution acidity on the interaction between bovine serum albumin (BSA) molecules and gold nanoparticles in solutions has been investig

The effect of pH and temperature on the interaction of sodium citrate-coated magnetic iron oxide nanoparticles (IONPs) with the BSA protein was studied using optical methods. The optical properties of aqueous colloids of BSA, IONPs, and BSA with IONPs were studied with pH changes in the range of 2–12 and temperature in the range of 25–85 °C. It was found that at pH 2.0, no significant changes in the optical properties were observed with increasing temperature in aqueous colloids containing a mixture of BSA with IONPs. Temperature affects the optical properties of BSA colloids with IONPs in the pH range from 5.0 to 8.0. Moreover, by increasing the temperature at these pH levels, it is possible to control the particle size in the colloids. In general, both temperature and pH have a significant effect on the properties of the aqueous colloid of BSA with IONPs and allow for the control of interactions between BSA and IONPs, namely, the processes of aggregation, particle reclustering, and protein denaturation.