Chilli leaf curl disease (ChiLCD), which is a significant problem in chilli cultivation, is caused by begomoviruses that are transmitted by the whitefly Bemisia tabaci. This disease leads to severe impacts on crop yields. To determine the incidence of begomovirus in the chilli crop, infected chilli leaf samples exhibiting symptoms such as curling, yellowing, reduced leaf size, and overall stunted growth were collected from various districts of Tamil Nadu, namely, Coimbatore, Dharmapuri, Kancheepuram, Karur, Salem, Krishnagiri, Thoothukudi, Thiruvallur, Tiruchirappalli, Virudhunagar, Tiruvannamalai, Tenkasi, and Vellore, during the years 2018-2022. To determine the complete genome sequence of the begomoviruses, the rolling circle amplification (RCA) method was used to clone and sequence the begomovirus genomes from the chilli samples collected from various districts of Tamil Nadu. Here we characterized 17 DNA A genome sequences and 12 betasatellite sequences. BLAST results of the DNA A genome sequences revealed nucleotide identities ranging from 94.2 to 99.7% with five distinct begomovirus species of chilli, namely, chilli leaf curl Salem virus (HM007119), chilli leaf curl virus Bhavanisagar (NC_055130), chilli leaf curl Ahmedabad virus (MW795666), chilli leaf curl virus (NC_055131), and chilli leaf curl Sri Lanka virus (JN555600). BLAST results of the betasatellite sequences showed nucleotide identities of 96 to 98.8% with the tomato leaf curl Bangladesh betasatellite (MZ151286). In the present study, five distinct begomovirus species and one associated betasatellite were found to infect chilli crops in Tamil Nadu. This finding indicates a changing pattern of begomovirus occurrence in the different districts of Tamil Nadu. This study highlights the prevalence of chilli-infecting begomoviruses in the major chilli growing districts of Tamil Nadu, the identification of begomovirus species, and the significance of understanding and managing these viruses to safeguard chilli cultivation in the region.
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http://dx.doi.org/10.1007/s10123-024-00580-0 | DOI Listing |
Front Plant Sci
December 2024
School of Future Technology, Fujian Agriculture and Forestry University, Fuzhou, China.
In the cultivation of green chili peppers, the similarity between the fruit and background color, along with severe occlusion between fruits and leaves, significantly reduces the efficiency of harvesting robots. While increasing model depth can enhance detection accuracy, complex models are often difficult to deploy on low-cost agricultural devices. This paper presents an improved lightweight Pepper-YOLO model based on YOLOv8n-Pose, designed for simultaneous detection of green chili peppers and picking points.
View Article and Find Full Text PDFEnviron Entomol
December 2024
Environment and Plant Protection Institute, Chinese Academy of Tropical Agriculture/Key Laboratory of Integrated Pest Management on Tropical Crops, Ministry of Agriculture and Rural Affairs/Hainan Key Laboratory for Monitoring and Control of Tropical Agricultural Pests, Haikou, China.
In recent years, the damage caused by thrips has become a key factor impacting the winter and spring production of fruits and vegetables in Hainan Province, China. This study aimed to elucidate the effects of different pupation environments on pupal development and eclosion of chilli thrips (Scirtothrips dorsalis Hood) by analyzing pupal development and eclosion of chilli thrips in an indoor environment with simulated natural soils and water content. Soil type, soil water content, and temperature substantially affected the eclosion of chilli thrips during the pupal stage.
View Article and Find Full Text PDFPeerJ Comput Sci
November 2024
Department of Mechatronics Engineering, Faculty of Engineering and Technology, SRM Institute of Science and Technology, Chennai, India.
This article aims to develop a novel Artificial Intelligence-powered Internet of Things (AI-powered IoT) system that can automatically monitor the conditions of the plant (crop) and apply the necessary action without human interaction. The system can remotely send a report on the plant conditions to the farmers through IoT, enabling them for tracking the healthiness of plants. Chili plant has been selected to test the proposed AI-powered IoT monitoring and actuating system as it is so sensitive to the soil moisture, weather changes and can be attacked by several types of diseases.
View Article and Find Full Text PDFFoods
November 2024
College of Food Science and Technology, Hebei Agricultural University, No. 2596 Lekai South Road, Baoding 071000, China.
This research is intended to ascertain the impact of low-voltage electrostatic field (LVEF) together with chili pepper leaf essential oil (CLEO) on the storage quality of chili pepper. Four groups of samples were investigated, namely, control (CK), CLEO, LVEF, and CLEO + LVEF. Chili pepper from the CLEO + LVEF group reduced the weight loss and malondialdehyde content but improved the ascorbic acid contents, antioxidant potential, firmness, and color attributes.
View Article and Find Full Text PDFJ Hazard Mater
November 2024
College of Resource and Environmental Engineering, Guizhou University, Guiyang 550025, China.
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