A Wide Survey on Data Mining Approach for Crop Diseases Detection and Prevention

V. N. Nirgude, S. Malik
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引用次数: 0

Abstract

India is agriculture land and major revenue manufacturing sector. However, because of amendment in temporal parameters and uncertainty in climate directly have an effect on quality and amount of the assembly and maintenance of crops. Also, quality even a lot of degrade once the crops area unit infected by any malady. The main focus of this analysis in agriculture is to increment the crop quality and potency at lower price and gain profit as result of in India the majority of the population depends on agriculture. Big selection of fruits is growing up in India such as apple, banana, guava, grape, mango, pomegranate, orange is the main one. Fruit production gives around 20% of the country’s development. However, because of absence of maintenance, inappropriate development of fruits and manual investigation there has been scale back in generate the standard of fruits.So, Data Mining Approach used in the agriculture domain to resolve several agricultural issues of classification or prediction. During this paper complete survey of several data mining approach for crop disease management has been done. Detection of disease in early state will improve in quality of crop still as decrease the production cost. Also, we can improve the production of the particular crop. Several major parameters are used for the crop disease classification or prediction.
作物病害检测与预防的数据挖掘方法综述
印度是农业用地和制造业的主要收入部门。然而,由于时间参数的变化和气候的不确定性直接影响作物的种植和维持质量和数量。另外,作物一旦受到任何病害的感染,其质量甚至会大大降低。这一分析在农业方面的主要重点是在较低的价格下提高作物的质量和效力,并获得利润,因为在印度,大多数人口依赖农业。大量的水果选择正在印度成长,如苹果,香蕉,番石榴,葡萄,芒果,石榴,橙子是主要的。水果生产约占该国经济发展的20%。然而,由于缺乏维护,水果开发不当和人工调查,导致水果生产标准下降。因此,数据挖掘方法应用于农业领域,解决了农业分类或预测的若干问题。本文对作物病害管理的几种数据挖掘方法进行了较为全面的综述。早期发现病害不仅能提高作物品质,还能降低生产成本。此外,我们还可以提高特定作物的产量。几种主要参数用于作物病害分类或预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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