An Investigation and Forecast of Suitable Crop Yield using Machine Learning Techniques Dependent in the Characteristics of Soil

One of the most important industries in the world, agriculture forms the foundation of the Republic of India. Conditions for agriculture have been dire. Most crops are overripe for manufacture because of the influence of temperature changes and their unpredictability. Accurate crop growth forecasting is a key component of crop forecast management. These projections will impede the federation industries’ ability to fulfill their occupational obligations. This paper presents a comprehensive performance analysis of machine learning algorithms for agricultural guidance, with a specific focus on the Random Forest(RF) algorithm. The aim of this research is to predict the most suitable crop for a given plot of land by considering a range of environmental and geographical factors. By leveraging the capabilities of the Random Forest algorithm, this research aims to provide accurate recommendations to farmers, enabling them to make informed decisions regarding crop selection and maximize agricultural yield.