Crop and Fertilizer Recommendation using AI

Artificial Intelligence

Instead of cultivating different types in different seasons, farmers produce the same crop every season. They also apply more fertilizer without knowing its exact composition or dosage. In order to describe the best crop to produce and the fertilizer to seed based on soil and weather circumstances, we developed a recommendation model based on machine learning. Therefore, using our technique allows farmers to grow fresh crops in various seasons while making a better profit and preventing soil contamination. Analyze the different factors that are associated, such as the location and the pH level used to calculate the soil's alkalinity. The use of third-party apps like APIs for weather and temperature, soil type, soil nutritional content, degree of rainfall in that zone, and soil composition is combined with the usage of location. Percentages of nutrients like Nitrogen (N), Phosphorous (P), and Potassium (K) are also used. All of these characteristics of the data will be examined while building a model by using several acceptable machine learning techniques on the data. The system includes a model to provide the end user with accurate suggestions about the appropriate fertilizer ratio based on atmospheric and soil data of the field, which enhance crop production and raise farmer income.

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