An integrated tea leaf diseases identification and retrieval model using machine learning and deep learning approach

Abstract

newline The tea plant, or Camellia sinensis, is a tiny plant cultivated for its newlineleaves, which are used to prepare beverages. India is home to one of the most newlineextensive tea plantations in the world. After 1920, tea became one of the most newlinepopular drinks in India. Tea is cultivated in various parts of India, such as newlineDarjeeling, Nilgiris, Munnar, and Karnataka tea estates. India s economy newlinedepends heavily on the tea plantation business. Tea production is directly newlineimpacted by foliar diseases, which many bacteria, fungi, and other pests can newlinebring on. The tea plant is affected by various diseases, such as root disease newline(capital loss), Stem disease (yield stagnation), and leaf disease (Crop loss). newlineThis initiative focuses on leaf diseases, which aims to increase output. Tea newlineleaves are susceptible to various fungal infections, including blister blight, newlinefrog eye spot, grey blight, scab, and brown blight. newlineThe raw ingredient for the tea industry is tea leaves. In any newlinebusiness, the raw material quality is crucial to the quality of the final product. newlineThe quality of tea leaves in this country has risen to the forefront of the newlinegovernment s concerns. Consequently, early detection of tea leaf disease will newlineincrease production. This research focuses on three significant leaf diseases newlineblister blight, scab, and spot. Blister blight is the most severe disease affecting newlinetea leaves. Developing a disease identification model using a computer newlinetechnique is critical for plant research.