Estimation and Improvement of Soil Nutrient Deficiencies Using Machine Learning

Organic farming has been a rising concern in today’s world in order to restore balance and increase lifetime. Many environmentalaspects along with product yield are to be considered while undertaking organic farming. Our solution primarily aims at utili zing machinelearning algorithms in recommending suitable organic fertilizers that promotes plant growth without causing major damage to soil health.The proposed system obtains soil’s nitrogen, phosphorous and potassium values followed by basic soil data like soil moisture content,temperature and soil type with the help of a Stream lit UI along with type of crop the user wants to grow and these values are used furtherto determine nutrient deficiencies and suitable organic fertilizer combinations to improve them. Primarily used machine learningalgorithm that has better accuracy score is the random forest algorithm. Support vector machine algorithm was also tested on dataset forprediction although accuracy score was less when compared to random forest algorithm.