A Survey on Precision agriculture using Machine Learning
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Abstract
Purpose: The objective of this paper is to yield suggestion contraption that encourages ranchers to choose the correct harvest to plant in their fields.
Methodology: Machine picking up information on systems gives an effective structure to decision-making through records at varies time
Findings: Precision Agriculture (PA) allows for the exact usage of data sources like water toxicant, seed, and composts at the absolute time to the harvest for expanding productiveness, decent, and yields. By fetching sensors and mapping fields, ranchers can comprehend their range in a higher way safeguard the assets being utilized and decrease unfavorable effects on the earth. The vast majority of the Indian ranchers practice customary cultivating styles to decide yield to be developed in order. In any case, the ranchers don't comprehend crop yield is related to soil qualities and climatic conditions. In this way, this paper proposes a yield suggestion contraption that encourages ranchers to choose the correct harvest to plant in their fields. Machine picking up information on systems gives an effective structure to decision-making through records at varies time. This paper bears a survey onset of machine picking up information on methods to help the ranchers in settling on choice roughly appropriate yield to develop depending regarding their matter's conspicuous traits.
Originality/value: In this study, the results show precision agriculture relate to certain crop parameters positively. To promote future research and practical applications, a framework has been developed for identified crop prediction and increase in yield to implemented crop rotation, soil characteristics, rainfall, land instruction and incontrollable elements along with weather.
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Article Details
Precision Agriculture (PA), Crop and Yield prediction, Machine learning (ML)
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