A Review on the Relevant Applications of Machine Learning in Agriculture

Abstract

Manual identification, classification and taxonomy of a definite and specific species or plant disease are generally obstructed by several difficulties such as time consumption, the limited number of expert specialists and the increase in the number of the defined characteristics of each species. The steady progress of the computational technology over the last few years concerning the automated species recognition including plant structures is be easier particularly in the presence of huge databases of information and the enhancement of classification and analyzing image technology. Several investigators are currently working in agriculture field mainly those concerned with plant identification or of plant disease recognition through image processing, extraction of identical features and classifying them into exact classes. In this review, the integration of computer science with agriculture has been discussed to detect, quantify, predict, early identify and classify plant diseases as well as forecasting agricultural crops using different machine learning techniques. Weather forecasting, smart irrigation system, plant leaf identification, etc will also discussed. The aim of this paper is to provide the investigators particularly biologists with computational recognition techniques as well as the possibility of using image informative morphological features of a species or a group of related species in recognition of many biological organisms including plants and microorganisms.