文章基本信息

标题：Cotton Crop Yield Prediction using Data Mining Technique
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作者：Amiksha Ashok Patel ; Dhaval Kathiriya
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2022
卷号：13
期号：1
DOI：10.14569/IJACSA.2022.0130184
语种：English
出版社：Science and Information Society (SAI)
摘要：Cotton is a very important crop, as India leads it in terms of production in the world; and also that a vast number of manpower is engaged in farming as well as post-harvest processing and management of different derivatives of it. Weather is crucial for the productivity of the crop. The challenges of climate change; availability of limited land and water for farming; lake of knowledge for good cultivation practices and judicious use of agricultural inputs with farmers are critical hindrances for improving productivity. This requires thorough research on land preparation and use, how to improve fertility of soil, good agronomic practices in lieu of variable climatic conditions, etc. All the talukas of the three districts of North Gujarat where cotton is cultivated have been selected purposively for this study. The effect of soil type, soil pH, soil organic carbon, phosphorous, potassium, precipitation and temperature were selected as independent factors. The yield of cotton crop has positive correlation with the selected parameters. The data sets were applied for analytical process to WEKA. The difference between average of predicted and actual yields of all talukas for high rainfall year 2013 was only 1.55 per cent. The difference between actual and predicted yield for the low temperature year (2015) in different talukas of all talukas was only 0.44 per cent.
关键词：Data mining; cotton crop yield prediction; agriculture; data processing; data visualization