The potential of the method of fluorescence spectroscopy for the detection of damage and diseases of fruits and vegetables was studied. For this purpose, the spectra of fluorescence of healthy and rotten apples and potatoes have been investigated. Excitation of samples was carried out using a continuous semiconductor laser with a wavelength of 405 nm and a pulsed solid-state laser with a wavelength of 527 nm. Peaks in the region of 600–700 nm in rotten samples were shifted towards shorter wavelengths for most samples in both modes of spectroscopy. The differences in the fluorescence spectra of a healthy and rotten apple surface have been revealed to be in the spectral range of 550–650 nm for 405 nm continuous excitation. When exposed to a laser in a pulsed mode (527 nm), the contribution of the 630 nm peak in the spectrum increases in rotten samples. The observed differences make it possible to use this method for separating samples of healthy and rotten fruits and vegetables. The article paid attention to the influence of many factors such as sample thickness, time after excitation, contamination by soil and dust, cultivar, and location of the probing on fluorescence spectra.

In this paper, iron oxide nanoparticles coated with trisodium citrate were obtained. Nanoparticles self-assembling stable clusters were ~10 and 50–80 nm in size, consisting of NPs 3 nm in size. The stability was controlled by using multi-angle dynamic light scattering and the zeta potential, which was −32 ± 2 mV. Clusters from TSC-IONPs can be destroyed when interacting with a hen egg-white lysozyme. After the destruction of the nanoparticles and proteins, aggregates are formed quickly, within 5–10 min. Their sizes depend on the concentration of the lysozyme and nanoparticles and can reach micron sizes. It is shown that individual protein molecules can be isolated from the formed aggregates under shaking. Such aggregation was observed by several methods: multi-angle dynamic light scattering, optical absorption, fluorescence spectroscopy, TEM, and optical microscopy. It is important to note that the concentrations of NPs at which the protein aggregation took place were also toxic to cells. There was a sharp decrease in the survival of mouse fibroblasts (Fe concentration ~75–100 μM), while the ratio of apoptotic to all dead cells increased. Additionally, at low concentrations of NPs, an increase in cell size was observed.

Plant diseases of an infectious nature are the reason for major economic losses in agriculture throughout the world. The early, rapid and non-invasive detection of diseases and pathogens is critical for effective control. Optical diagnostic methods have a high speed of analysis and non-invasiveness. The review provides a general description of such methods and also discusses in more detail methods based on the scattering and absorption of light in the UV, Vis, IR and terahertz ranges, Raman scattering and LiDAR technologies. The application of optical methods to all parts of plants, to a large number of groups of pathogens, under various data collection conditions is considered. The review reveals the diversity and achievements of modern optical methods in detecting infectious plant diseases, their development trends and their future potential.

Using a number of optical techniques (interferometry, dynamic light scattering, and spectroscopy), denaturation of hen egg white lysozyme (HEWL) by treatment with a combination of dithiothreitol (DTT) and guanidine hydrochloride (GdnHCl) has been investigated. The denaturing solutions were selected so that protein denaturation occurred with aggregation (Tris-HCl pH = 8.0, 50 mM, DTT 30 mM) or without aggregation (Tris-HCl pH = 8.0, 50 mM, DTT 30 mM, GdnHCl 6 M) and can be evaluated after 60 min of treatment. It has been found that denatured by solution with 6 M GdnHCl lysozyme completely loses its enzymatic activity after 30 min and the size of the protein molecule increases by 1.5 times, from 3.8 nm to 5.7 nm. Denaturation without of GdnHCl led to aggregation with preserving about 50% of its enzymatic activity. Denaturation of HEWL was examined using interferometry. Previously, it has been shown that protein denaturation that occurs without subsequent aggregation leads to an increase in the refractive index (Δn ~ 4.5 × 10⁻⁵). This is most likely due to variations in the HEWL–solvent interface area. By applying modern optical techniques conjointly, it has been possible to obtain information on the nature of time-dependent changes that occur inside a protein and its hydration shell as it undergoes denaturation.

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, selenium nanoparticles (SeNPs) are considered potential immunomodulatory agents and as targets for activity modulation are granulocytes, which have the most abundant population of immune blood cells. The present study aims to evaluate the cytotoxic effect and its effect on the functional responses of granulocytes. In addition to the intrinsic activity of SeNPs, we studied the activity of the combination of SeNPs and IgG antibodies. Using laser ablation and fragmentation, we obtained nanoparticles with an average size of 100 nm and a rather narrow size evolution. The resulting nanoparticles do not show acute toxicity to primary cultures of fibroblasts and hepatocytes, epithelial-like cell line L-929 and granulocyte-like culture of HL-60 at a concentration of 10⁹ NPs/mL. SeNPs at a concentration of 10¹⁰ NPs/mL reduced the viability of HL-60 cells by no more than 10% and did not affect the viability of the primary culture of mouse granulocytes, and did not have a genotoxic effect on progenitor cells. The addition of SeNPs can affect the production of reactive oxygen species (ROS) by mouse bone marrow granulocytes, modulate the proportion of granulocytes with calcium spikes and enhance fMLF-induced granulocytes degranulation. SeNPs can modulate the effect of IgG on the physiological responses of granulocytes. We studied the expression level of genes associated with inflammation and cell stress. SeNPs increase the expression of catalase, NF-κB, Xrcc5 and some others; antibodies enhance the effect of SeNPs, but IgG without SeNPs decreases the expression level of these genes. This fact can be explained by the interaction between SeNPs and IgG. It has been established that antibodies interact with SeNPs. We showed that antibodies bind to the surface of selenium nanoparticles and are present in aqueous solutions in a bound form from DLS methods, ultraviolet–visible spectroscopy, vibrational–rotational spectrometry, fluorescence spectrometry, and refractometry. At the same time, in a significant part of the antibodies, a partial change in the tertiary and secondary structure is observed. The data obtained will allow a better understanding of the principles of the interaction of immune cells with antibodies and SeNPs and, in the future, may serve to create a new generation of immunomodulators.