Rice
With the increase in world population, agricultural planning is significant to ensure food security. Timely recommendations for crops could be valuable for planning food production and maintaining food sustainability. This proposed work suggests a crop recommendation model considering physical soil characteristics, chemical soil characteristics, climate, and crop characteristics, using Improved Deep Belief Networks (IDBN). For this study, four important Indian crops—rice, maize, finger millet and sugarcane were taken into account.
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The datasets in discussion present detailed records for two of the world's most cultivated crops: wheat and rice. These datasets aim to provide comprehensive insights into various environmental and soil-related factors that are traditionally considered influential in determining the yield of these crops. By analyzing these datasets, researchers, agronomists, and farmers can gain a better understanding of the interplay between different attributes and how they might impact the overall crop yield.
Wheat Dataset:
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