The effect of bacterial cellulose nanocrystal–fish gelatin/cinnamon essential oil (BCNCs–FGelA/CEO) nanocoatings containing different concentrations of essential oil (1.2, 1.8, and 2.4 mL/L) on reducing the ripening and aging processes of ‘Red Gold’ nectarine fruit during cold storage (60 days, 4 °C) was studied. As a general trend, the application of the coating delayed the ripening process, and increasing the concentration of essential oil was effective in improving the coating efficacy. After 60 days, the lowest values of weight loss (6.93%), peroxidase and polyphenol oxidase activity (11.49 and 0.48 abs min⁻¹ g⁻¹, respectively), soluble solid content (14.56%), and pH (4.17) were detected for samples covered with the BCNCs–FGelA coatings containing the highest tested CEO concentration, whereas the maximum values of the same parameters (20.68%, 18.74 and 0.76 abs min⁻¹ g⁻¹, 17.93%, and 4.39, respectively) were found in the uncoated samples. In addition, increasing the concentration of the essential oil resulted in a better preservation of the firmness, ascorbic acid, and total acidity of the samples. Finally, the respiration rate and ethylene production of coated samples were lower than those detected in uncoated samples, though some differences arose depending on the amount of CEO loaded in the coatings. This study showed the capability of BCNCs–FGelA/CEO coatings to increase the cold storage period and preserve the quality of ‘Red Gold’ nectarine fruit, thereby reducing losses and increasing economic efficiency in the fruit industry.

Spectroscopic analysis was employed to evaluate the quality of three bell pepper varieties within the 350–1150 nm wavelength range. Quality parameters such as firmness, pH, soluble solids content, titratable acids, vitamin C, total phenols, and anthocyanins were measured. To enhance data reliability, principal component analysis (PCA) was used to identify and remove outliers. Raw spectral data were initially modeled using partial least squares regression (PLSR). To optimize wavelength selection, support vector machines (SVMs) were combined with genetic algorithms (GAs), particle swarm optimization (PSO), ant colony optimization (ACO), and imperial competitive algorithm (ICA). The most effective wavelength selection method was subsequently used for further analysis. Three modeling techniques—PLSR, multiple linear regression (MLR), and artificial neural networks (ANNs)—were applied to the selected wavelengths. PLSR analysis of raw data yielded a maximum R² value of 0.98 for red pepper pH, while the lowest R² (0.58) was observed for total phenols in yellow peppers. SVM-PSO was determined to be the optimal wavelength selection algorithm based on ratio of performance to deviation (RPD), root mean square error (RMSE), and correlation values. An average of 15 effective wavelengths were identified using this combined approach. Model performance was evaluated using root mean square error of cross-validation and coefficient of determination (R²). ANN consistently outperformed MLR and PLSR in predicting firmness, pH, soluble solids content, titratable acids, vitamin C, total phenols, and anthocyanins for all three varieties. R² values for the ANN model ranged from 0.94 to 1.00, demonstrating its superior predictive capability. Based on these results, ANN is recommended as the most suitable method for evaluating the quality parameters of bell peppers using spectroscopic data.

This work investigated the effect of bacterial cellulose nanocrystals (BCNCs)-gelatin (GelA)/cinnamon essential oil (CEO) emulsion coatings (BCNCs-GelA/CEO) on the shelf-life extension of button mushrooms (Agaricus bisporus). CEO loadings between 1200 and 2400 μL/L were used in the coatings applied on the mushrooms' surface. The overall quality of coated mushrooms was monitored over 15 days of cold storage (4 ± 0.5 °C). Regardless of the storage time, using the highest amount of CEO within the coating formulation minimised the impact on tested parameters (weight loss, firmness, percentage of opened caps, total soluble solids, content of ascorbic acid and soluble protein, PPO/POD enzymatic activity) as compared to control samples. Interestingly, a linear relationship (R2 = 0.96 on average) between CEO concentration and the respiration rate of coated mushrooms was disclosed. Overall, this study pinpointed the capability of BCNCs-GelA/CEO coatings to delay the aging process of button mushrooms under cold storage. Our findings could be applied to address the issue of food losses, highlighting the positive role of coating technology in enhancing the efficiency of the early stages of the food supply chain, especially in the case of button mushrooms. However, an assessment of the impact of the concentration of other coating components (BCNC and fish gelatin) on the shelf-life extension of button mushrooms, as well as an evaluation of the coating's effectiveness in prolonging the shelf-life of other food items, particularly non-respiring products, is necessary to widespread the applicability of the proposed technology.

Peanuts, owing to their composition of complex carbohydrates, plant protein, unsaturated fatty acids, and essential minerals (magnesium, iron, zinc, and potassium), hold significant potential as a vital component of the human diet. Additionally, their low water requirements and nitrogen fixation capacity make them an appropriate choice for cultivation in adverse environmental conditions. The germination ability of seeds profoundly impacts the final yield of the crop; assessing seed viability is of extreme importance. Conventional methods for assessing seed viability and germination are both time-consuming and costly. To address these challenges, this study investigated Visible–Near-Infrared Spectroscopy (Vis/NIR) in the wavelength range of 500–1030 nm as a nondestructive and rapid method to determine the viability of two varieties of peanut seeds: North Carolina-2 (NC-2) and Spanish flower (Florispan). The study subjected the seeds to three levels of artificial aging through heat treatment, involving incubation in a controlled environment at a relative humidity of 85% and a temperature of 50 °C over 24 h intervals. The absorbance spectra noise was significantly mitigated and corrected to a large extent by combining the Savitzky–Golay (SG) and multiplicative scatter correction (MSC) methods. To identify the optimal wavelengths for seed viability assessment, a range of metaheuristic algorithms were employed, including world competitive contest (WCC), league championship algorithm (LCA), genetics (GA), particle swarm optimization (PSO), ant colony optimization (ACO), imperialist competitive algorithm (ICA), learning automata (LA), heat transfer optimization (HTS), forest optimization (FOA), discrete symbiotic organisms search (DSOS), and cuckoo optimization (CUK). These algorithms offer powerful optimization capabilities for effectively extracting relevant wavelength information from spectral data. Results revealed that all the algorithms demonstrated remarkable accuracy in predicting the allometric coefficient of seeds, achieving correlation coefficients exceeding 0.985 and errors below 0.0036, respectively. In terms of execution time, the ICA (2.3635 s) and LCA (44.9389 s) algorithms exhibited the most and least efficient performance, respectively. Conversely, the FOA and the LCA algorithms excelled in identifying the least number of optimal wavelengths (10 wavelengths). Subsequently, the seeds were classified based on the wavelengths selected via the FOA (10 wavelengths) and (DSOS (16 wavelengths) methods, in conjunction with logistic regression (LR), decision tree (DT), multilayer perceptron (MP), support vector machine (SVM), k-nearest neighbor (K-NN), and naive Bayes (NB) classifiers. The DSOS–DT and FOA–MP methods demonstrated the highest accuracy, yielding values of 0.993 and 0.983, respectively. Conversely, the DSOS–LR and DSOS–KNN methods obtained the lowest accuracy, with values of 0.958 and 0.961, respectively. Overall, our findings demonstrated that Vis/NIR spectroscopy, coupled with variable selection algorithms and learning methods, presents a suitable and nondestructive approach for detecting seed viability.

The aim of this study was to characterize films obtained from fish gelatin (GelA, 3% w/w), encapsulated with cinnamon essential oil (CEO, 0.03–0.48% v/w), and loaded with bacterial cellulose nanocrystals (BCNCs, 0.06% w/w) at pH = 3.5. CEO-GelA/BCNC films were prepared by casting, and thickness, light transmittance (TT) and haze (H), surface hydrophobicity, tensile properties, chemical composition, and water solubility (WS) thereof were assessed. All films displayed outstanding optical properties (TT > 89.4%), with haze slightly exceeding a 3% value only at the highest CEO loading within the nanoemulsion formulation. The CEO plasticizing effect increased the elongation at break (EAB, from 0.84% up to 3.79%) and decreased the tensile strength (TS, from 8.98 MPa down to 1.93 MPa). The FT-IR spectra of films revealed good interaction among nanoemulsion components via hydrogen bonding. The CEO hydrophobic nature negatively impacted the WS (from 52.08% down to 8.48%) of the films. The results of this work confirmed the possibility of producing packaging systems from renewable sources to be potentially used in the form of edible films/coatings for the preservation of water-sensitive food products, both vegan-based (fruits/vegetables) and animal-based (meat/seafood).

Fereydounshahr experiences growing electricity shortfalls and an overreliance on polluting diesel generators. This analysis models renewable hybrid systems to electrify a local dairy operation using HOMER Pro 3.11 software. Despite higher upfront costs, adding just 5% solar photovoltaics maintained low net present costs while increasing clean energy penetration versus diesel generators alone. Furthermore, a combined diesel-solar-wind system reduced carbon dioxide and nitrogen oxide emissions by over 1%. Although diesel generators had the shortest payback period at 48 years, the capital recovery factor for a diesel–solar combination reached 62 years. Thus, tailored hybrid renewable systems could provide an affordable, low-emissions electricity solution for the Fereydounshahr livestock facility. With suitable wind and solar resources, the right policy incentives could also unlock substantial local renewable capacity to meet rising demand and mitigate dependence on imported, climate-harming fossil fuels.