In the present study, the toxicity of essential oils of Mentha piperata L. and Mentha pulegium L. and pathogenicity of Lecanicillium muscarium (Zare & Gams) were studied in the melon aphid, Aphis gossypii Glover. Analyses of the essential oils by GC–MS indicated limonene (27.28%), menthol (24.71%), menthone (14.01%), and carvol (8.46%) in the M. piperata essential oil and pulegone (73.44%), piperitenone (5.49%), decane (4.99%), and limonene (3.07%) in the essential oil of M. pulegium as the main components. Both essential oils and the pathogenic fungus had useful toxicity against A. gossypii. Probit analysis indicated LC₅₀ values (lethal concentrations to kill 50% of population; 95% confidence limits in parentheses) of M. piperata and M. pulegium essential oils as 15.25 (12.25–19.56) and 23.13 (19.27–28.42) µl/liter air, respectively. Susceptibility to the pathogenic fungus increased with exposure time. Aphid mortality also increased when the essential oils were combined with L. muscarium, although the phenomena was additive rather than synergistic. Mycelial growth inhibition of L. muscarium exposed to the essential oils was also very low. Based on our results, M. piperata and M. pulegium essential oils and the pathogenic fungus L. muscarium have some potential for management of A. gossypii.

There are many methods to detect plant pests and diseases, but they are primarily time-consuming and costly. Computer vision techniques can recognize the pest- and disease-damaged fruits and provide clues to identify and treat the diseases and pests in their early stages. This study aimed to identify common pests, including the apple capsid (Plesiocoris rugicollis)/AC, apple codling moth (Cydia pomonella)/ACM, Pear lace bug (Stephanitis pyri)/PLB, and one physiological disease-apple russeting/AR in two cultivars, Golden Delicious and Red Delicious, using the digital image processing and sparse coding method. The Sparse coding method is used to reduce the storage of the elements of images so that the matrix can be processed faster. There have been numerous studies on the identification of apple fruit diseases and pests. However, most of the previous studies focused only on diagnosing a pest or disease, not on computational volume reduction and rapid detection. This research focused on the comprehensive study on identifying pests and diseases of apple fruit using sparse coding. The sparse coding algorithm in this work was designed using Matlab software. The apple pest and disease detection were performed based on 11 characteristics: R, G, B, L, a, b, H, S, V, Sift, and Harris. The class detection accuracy using the sparse coding method was obtained for 10 classes with three views of apple for S. pyri of red apple as 81%, S. pyri of golden apple as 88%, golden apple russeting as 85%, S. pyri and russeting of red apple as 100%, S. pyri and russeting of golden apple as 80%, codling moth of red apple as 86%, codling moth of golden apple as 72%, S. pyri of red apple as 83%, S. pyri of golden apple as 90%, codling moth and S. pyri of red apple as 80%, and codling moth and S. pyri of golden apple as 67%. The total processing time for developing the dictionary was 220 s. Once the dictionary was developed, pest and disease detection took only 0.175 s. The results of this study can be useful in developing automatic devices for the early detection of common pests and diseases of apples. Although the study was focused on apple diseases, results for this work have huge potential for other crops.

This study aimed to assess the effectiveness of bacterial cellulose nanocrystals (BCNCs)-gelatin (GelA)/cinnamon essential oil (CEO) emulsion coatings containing various CEO concentrations (1200, 1800, and 2400 μL/L) in retarding ripening and senescence of ‘Red Delicious’ apples during cold storage (60 days at 4 °C). Coatings decreased the weight loss (WL) (~3.6%), as compared to uncoated fruit (~4.8%). A direct relationship between CEO concentration and respiration rate/ethylene production was also disclosed. Flesh firmness was higher for coated samples, with better results detected especially when the highest amount of CEO was applied (36.48 N for the 2400 μL/L delivered dose vs. 32.60 N for the 1200 μL/L one). These findings were corroborated by additional tests on the surface color, total acidity, soluble solids content, pH, ascorbic acid, and activities of polyphenol oxidase (PPO) and peroxidase (POD). This study demonstrated the capability of BCNCs-GelA/CEO systems to dramatically enhance the storability and quality of apples during refrigerated storage, thus avoiding undesired losses and increasing the economic performance of fresh fruit industries.

The utilization of plant essential oils (EOs) and nanomaterials due to their safety compared with synthetic chemicals has been considered in the management of plant diseases. In this study, the inhibitory effects of Zataria multiflora, Nepeta haussknechtii, Artemisia sieberi, and Citrus aurantifolia EOs in pure and Zinc Oxide (ZnO) nanocapsulated formulations were evaluated on the mycelial growth of Alternaria solani to find a suitable alternative for synthetic chemicals. The crystal structure and morphological properties of the fabricated nanomaterials were assessed via X-ray diffraction (XRD) and scanning electron microscope (SEM) analyses. The textural features of the prepared nanoparticles were investigated with Brunauer–Emmett–Teller (BET) analysis, and the presence of elements in the samples was studied with energy-dispersive X-ray (EDX) technique. The mycelial growth inhibitory (MGI) was performed in the laboratory by mixing with potato dextrose agar (PDA) medium at concentrations of 100, 300, 600, 1,000, 1,500, and 2,000 ppm. Based on the results, major differences were monitored between different concentrations. At the highest studied concentration, the inhibition of Z. multiflora EO was 100%, which was 43.20, 42.37, and 21.19% for N. haussknechtii, A. sieberi, and C. aurantifolia, respectively, and the inhibition of their nanocapsules was 100, 51.32, 55.23, and 26.58%, respectively. In the greenhouse study, Z. multiflora EO and its nanocapsule (ZnO-ZmEO) were compared with the ZnO and chlorothalonil fungicide based on the highest inhibitory of Z. multiflora in vitro. The highest antifungal effect was related to the ZnO-ZmEO by 53.33%. Therefore, the ZnO-ZmEO formulation can be recommended as a biofungicide for managing and controlling tomato early blight disease after further research.