Boost Yields Save Crops

<p>It is a well-known fact that economy of a nation highly depends on agricultural productivity.</p><p>Occurrence of diseases in plants is quite natural. Thus detection of diseases in plants forms a vital</p><p>aspect of enhancing agricultural productivity. Lack of proper care can cause serious effects on</p><p>plants which in turn affects quality quantity or productivity of the plant product. For example</p><p>The Great Famine (1845-1849) was a period of crop failure which led to diseases mass</p><p>starvation emigration and death. Biologists later arrived at a conclusion that the famine was</p><p>caused by a potato blight a natural event. Death was widespread and the toll rose to a 100000.</p><p>Automatic disease detection techniques can be used on crops in big farms which will help reduce</p><p>the manual monitoring of crops and detect disease or their symptoms at very early stages. This</p><p>gives time for proper remedy. This paper presents an application with machine learning algorithms</p><p>to detect and classify diseases in tomato plants by processing images of the leaves.</p>