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.

Precision agriculture (PA) is a farm management strategy that relies on various technologies to improve the productivity and sustainability of farming operations. The adoption of PA entails on-farm and off-farm benefits; however, the adoption rates remain low in Iran. Using the socio-psychological framework of the technology acceptance model (TAM), this study examined agricultural extension experts‘ intentions to use precision agricultural technologies (PATs) in Ardabil province, Iran. Structural equation modelling (SEM-PLS) was used to map the components of the TAM (perceived usefulness, perceived ease of use, and attitudes toward PATs). All the components of the TAM showed a significant effect on experts‘ intentions, confirming the importance of socio-psychological variables in predicting agricultural experts‘ decision to apply PATs. Experts perceived PATs as helpful and relatively easy to use. In addition, they had positive attitudes toward PATs and intended to use most PA technologies. The TAM posits that two attitudinal components of perceived usefulness (PU) and perceived ease of use (PEU) determine acceptance and use. PU is the degree to which one believes using technology would enhance job performance, while PEU is the degree to which using technology is free of effort. The results showed that PEU and PU had a positive impact on attitudes. The three constructs positively affected behavioural intention toward the application of PATs and explained 68.8% of the variance of this construct. Due to the novelty of PA in the country, PEU was the most critical determinant of intention.

The evaluation of energy input and output processes in agricultural systems is a crucial method for assessing sustainability levels within these systems. In this research, the investigation focused on the input and output energies and related indices in sunflower farms in Khoy County during the agricultural year 2017–2018. Data were collected from 140 sunflower producers through specialized questionnaires and face-to-face interviews. Additionally, artificial neural networks (ANNs), specifically the multilayer perceptron, were employed to predict the output energy. The results revealed that a substantial portion of the total input energy was attributed to chemical nitrogen fertilizer (43.98%), consumable fuel (25.74%), and machinery (8.42%). The energy efficiency (energy ratio) in these agroecosystems was relatively low, measured at 1.57 for seed and 7.96 for seed and straw. These values should be improved. The energy efficiency in seed production was computed at 0.06 MJ·ha⁻¹, while, for the combined seeds and straw, it was 0.57 MJ·ha⁻¹. In particular, seed energy efficiency represents approximately 11% of the overall biological energy efficiency, highlighting that a substantial 89% of the produced energy is associated with straw. The proper use of this straw is crucial, as its improper handling could lead to a drastic decrease in overall efficiency. Furthermore, the explanatory coefficient (R²) and the mean absolute percentage error (MAPE) to predict the output energy with the best neural network were 0.94, and 1.77 for the training data, 0.97 and 1.55 for the test data, and 0.9 and 2.08 for the validation data, respectively; additionally, 0.97 and 0.42 were obtained by an ANFIS.

This research investigated the performance of a model traction combine harvester (TCH) for harvesting several varieties of peanuts. The effect of independent factors including tested varieties at three levels (local Moghan, Goli Astana, and Turkish), tractor forward speed (FS) at three levels (4, 5, and 6 km·h ⁻¹ ), and rotational speed (RS) of the thresher at three levels (500, 600, 700 rpm) on losses and wastes were studied and investigated. To analyse the obtained data, a factorial experimental design was used in the form of randomised complete blocks, and Duncan‘s multi-range test was used to compare the mean values. According to the findings, the effects of tractor FS and rotary speed of the thresher on the percentage of threshing losses were significant at the probability level of 1%. Also, the interaction effects of variety type and tractor FS, tractor FS, and rotary speed of the thresher on the percentage of threshing losses were significant at the 1% probability level. Also, the effects of variety type, tractor FS, rotary speed of the thresher, and all mutual effects on the percentage of threshing waste were significant at the 1% probability level. The results of comparing the average effects of the main factors showed that the FS of 6 km·h ⁻¹ had the highest average threshing loss (82.89%). Threshing losses were obtained in the Turkish variety with the lowest average value (2.51%) and in the local variety with the highest average value (3.53%).