Author : Manish Kumar 1
Date of Publication :8th August 2022
Abstract: Agriculture is India's rural population's livelihood. It's also essential for human existence, and it's developed over time to suit the demands of an ever-growing human population. Agriculture is their main source of income in rural area of India. Agriculture is the primary employment of the majority of Indians, as we all know. The majority of Indians rely on agriculture for their living, either openly or implicitly. The great majority of Indian farmers trust on their intuition to determine which crop to plant in a given season. Farmers are accustomed to sowing the same crop, using more fertilizer, and following public opinion. They find comfort in just following historical agricultural traditions and standards, oblivious to the reality that crop yield is highly dependent on current weather, soil, and other variables. The most frequent problem faced by Indian farmers is that they do not select the appropriate crop based on their soil requirements and other factors such as fertilizer s and irrigation patterns. As a result, productivity is impacted. However, a single farmer cannot be expected to take into consideration all of the numerous elements that influence crop development before deciding which one to plant. This problem can be efficiently addressed with machine learning. There have been major advancements in how machine learning may be employed in many businesses and studies during the last several years. As a result, we intend to develop a model/system that will allow machine learning to be utilised in agriculture to benefit farmers.
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