Open AccessA COMPREHENSIVE SURVEY OF GRAPE LEAF DISEASE DETECTION AND CLASSIFICATION USING MACHINE LEARNING BASED MODELS
Author(s) -
Dr.Sarumathi S,
C Saraswathy,
P Ranjetha
Publication year - 2021
Publication title -
international research journal of computer science
Language(s) - English
Resource type - Journals
ISSN - 2393-9842
DOI - 10.26562/irjcs.2021.v0808.005
Subject(s) - vitaceae , food security , vineyard , agriculture , plant disease , identification (biology) , machine learning , population , vitis vinifera , artificial intelligence , computer science , geography , microbiology and biotechnology , biology , horticulture , medicine , botany , environmental health , archaeology
Plant diseases are becoming a major danger to agricultural productivity as the world's population expands, causing farmers to incur serious consequences. Plant disease can be detected early, which can assist ensure food security and save financial losses. Grape (Vitis Vinifera), a member of the Vitaceae family, is one of India's most important commercial fruit crops. It's a wide-ranging temperate crop that's adapted to the subtropical environment of India's peninsula. Grapefruits and their leaves are more likely to contract illnesses in a grape vineyard. For experts and agronomists, manual observation is impracticable and time-consuming. We conduct a literature study on alternate disease identification and classification methodologies in order to predict disease progression at an early stage. A review of automated classifying and sorting grape leaf disease, including machine learning and deep learning approaches, is also discussed.