Contemporary Research Trends in Plant Leaf Disease Detection

Abstract

Agriculture is the backbone of Indian economy. Crop yield is decreased due to various disease-causing organism on plants. Plant disease identification has major impact on the agriculture production with respect to crop quality and quantity. Disease infected plants show symptoms on many parts of the plant like leaf, stem, bud, flower, fruit and root. Early identification of the disease will prevent further crop loss. In this paper, four different sections are covered. The first section focusses on different types of disease and its symptoms. Second section discuss about different traditional methods of disease identification. And the third section cover methodologies that can be used for disease identification in plants through image processing, deep learning and convolution neural network techniques. Fourth section highlights challenges and future trends in disease identification. Finally, this paper reveals that, particularly in rural areas and underdeveloped nations, relying solely on the expertise of professionals to identify and categorize diseases can be very much time-consuming and expensive.

Plant phenotyping relevance

植物病害の画像処理・深層学習による識別手法を扱うレビューであり、植物の病徴・病害状態を観測から推定する方法が中心。

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