Author : Rajendra Prasad Bellapu 1
Date of Publication :15th March 2017
Abstract: As India is an agricultural country, almost 80% of India's total population depends directly or indirectly on agriculture. Agriculture is one of the most significant contributors to the Gross Domestic Product (GDP) for India. According to experts, India has to play a bigger role in the global markets in agriculture products in the future. The country is expected to reinforce its position among the world's leading exporters of rice. Presently it is the second-largest rice producer after China; India produces 155.682 Million Metric Tons of rice. Now India, as well as the whole world, is facing nutritional starvation. The naked eye observation of experts is the primary approach adopted to detect and identify plant diseases. But this requires continuous monitoring of experts, which might be prohibitively expensive in large farms. Farmers usually apply chemical pesticides to cure plant diseases as suggested by agricultural-trained raters. Pesticides use has increased since 1960, WHO estimated in 2009 that 4.2 million pesticide poisonings occur annually, causing 225,000 deaths. Therefore the Pressure has been increased during recent years to develop non-chemical approaches to control plant diseases. The idea is instead of identifying the plant diseases through the naked eye or through agricultural experts, identifying these crop diseases at its early stages through software using computer vision toolbox is efficient. Multi-Band Thresholding algorithm (MBT) and OTSU algorithm gives the best results in detecting the paddy plant disease at its early stage. Next, region growing and fuzzy logic algorithms are used to quantify disease colour analysis and compare the results.
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