Clonostachys rosea, an ascomycetous, omnipresent, cellulose-decaying soil fungus, has been reported to be a well-known mycoparasitic biological control agent. In this study, we isolated C. rosea, a mycoparasitic fungus for the first time in India from sclerotia of the notorious plant pathogen Sclerotinia sclerotiorum, causing head rot disease in cabbage. A total of five mycoparasitic fungi were isolated from the sclerotial bodies of S. sclerotiorum (TNAU-CR 01, 02, 03, 04 and 05). All the isolates were tested under morpho-molecular characterization. Among them, TNAU-CR 02 showed the greatest mycelial inhibition of 79.63% over the control. Similarly, the SEM imaging of effective C. rosea isolates indicated the presence of numerous conidia destroying the outer cortex layers of sclerotia. Metabolite fingerprinting of C. rosea TNAU-CR 02 identified 18 chemical compounds using GC-MS analysis. The crude antibiotics of C. rosea TNAU-CR 02 were verified for their antifungal activity against S. sclerotiorum and the results revealed 97.17% mycelial inhibition compared with the control. Similarly, foliar application of TNAU-CR 02 at 5 mL/litre on 30, 45 and 60 days after transplanting showed the lowest disease incidence of 15.1 PDI compared to the control. This discovery expands our understanding of the biology and the dissemination of C. rosea, providing a way for the exploitation of C. rosea against cabbage head rot pathogens.

Plants are integral to human sustenance, serving as fundamental sources of sustenance, materials, and energy, crucial for economic prosperity. However, their productivity and yield are increasingly threatened by pests and diseases, exacerbated by shifting climatic conditions. Pearl millet, a vital crop in Africa and Asia, is particularly susceptible to a range of diseases including downy mildew, rust, ergot, smut, and blast, posing significant risks to crop yield and quality. Timely and accurate disease identification is paramount for effective management strategies. Traditional methods of disease detection relying on visual identification are laborious, costly, and often require specialized expertise, presenting formidable challenges for farmers. In this study, we propose a novel mobile application integrating a robust Deep Learning (DL) model for the automated identification of pearl millet leaf diseases, employing advanced computer vision techniques. A Convolutional Neural Network (CNN) architecture, named Deep Millet, was trained on a comprehensive dataset comprising 3441 field images depicting pearl millet leaves in both healthy and diseased states. It consists of fewer but more effective layers, which are optimized to extract the most pertinent features from the RGB images Comparative analysis against pre-trained models, including AlexNet, ResNet50, InceptionV3, Xception, NasNet mobile, VGG16, and VGG19, was conducted to evaluate the performance of the proposed model. Results demonstrate that Deep Millet achieved superior accuracy, completing training in a mere 240 s and yielding an impressive accuracy rating of 98.86%, surpassing current state-of-the-art models.

Plant introductions, including the movement of seeds across international borders, significantly contribute to the emergence of viral pathogens, which account for approximately half of all emerging plant diseases. Among plant virus families, the Potyviridae stand out as the largest and most economically impactful. The potyvirus genus with 201 species widespread across various crops, causes substantial crop losses globally. These viruses are primarily transmitted by aphids in a nonpersistent manner, with some also capable of transmission through seeds. Global food security is significantly impacted by the crucial part that seed transmission plays in the epidemiology and spread of different plant viruses. With transmission rates varying greatly between viruses and host plants, over 231 viruses were discovered to be capable of spreading through seeds, including 20 seed-transmitted potyviruses. The seed transmission efficiency of potyviruses such as maize dwarf mosaic virus (MDMV), cowpea aphid-borne mosaic virus (CABMV), and bean common mosaic virus (BCMV) ranges from 3% to 95%. Other notable viruses include soybean mosaic virus (SMV) (58% transmission) and pea seed-borne mosaic virus (PSbMV) (100% transmission). The diversity in seed transmission efficiency among viruses demonstrates the important role that seeds play in the propagation and dissemination of viral pathogens. In addition, seed transmission permits viruses to survive in unfavorable environments, promotes long-distance spread via international seed exchange, and acts as the main point of infection for viruses that have vertical transmission. The complex dynamics of seed transmission and the complex relationship between viruses and their host plants highlight the significance of strict phytosanitary measures in protecting global agriculture from the destructive effects of viruses transmitted through seeds. This review focuses on potyvirus seed transmission, with an emphasis on determining the significance of this mode and understanding the potential role of seed transmission in potyviruses.

Papaya is widely grown in tropical and subtropical climates due to its high yield potential and high returns. The vital hormone melatonin, regulating various biological processes in plants, is eco-friendly and less harmful to humans than other chemicals. This study aims to enhance the quality and antioxidant enzyme activities and lessen postharvest senescence in papaya cv. CO 8 fruits during both ambient (32 ± 2 °C and 55 ± 5% RH) and cold storage (10 ± 2 °C and 90–95% RH) as exogenous melatonin (EMT) is applied in varying concentrations. An optimum melatonin dose of 1.5 mM was applied as a pre-harvest spray 15 days before harvest and a postharvest dip proved effective in prolonging shelf life (under ambient it prolonged to day 9 and under cold storage up to 28 days) and delaying ripening and softening. Exogenous melatonin application enhanced antioxidant activity, reduced weight loss, maintained firmness, delayed ripening enzymes, and lowered ethylene and CO₂ levels. For instance, control fruits had weight losses between 7.42% and 10.09%, while fruits treated with 1.5 mM melatonin showed 5.74% and 9.06% weight loss under ambient and cold storage, respectively. In conclusion, applying EMT (1.5 mM) could be an economically viable and environmentally benign way to lessen senescence after harvest and preserve the qualities of the papaya fruit during ambient and cold storage.