Soil testing is an important step for increasing agricultural production and raising farm income. However, traditional soil testing methods are based on chemical methods that are time consuming, tedious, and require elaborate sample preparation steps. Therefore, there is a need for new technologies that can provide rapid and accurate soil testing results. Some of the new technologies that can be used for soil testing are: Machine learning methods: These methods use algorithms to classify soil types based on various parameters such as pH, organic matter, nitrogen, phosphorus, potassium, etc. These parameters are important for determining the fertility and nutrient status of the soil and the suitability of the soil for different crops. For example, a study by ¹ used weighted k-Nearest Neighbor (k-NN), Bagged Trees, and Gaussian kernel based Support Vector Machines (SVM) for soil classification and crop suggestion. The results showed that the SVM based method performed better
Agro Tech Blog is your source of information on innovation and modern agriculture. Learn from articles on agritech start-ups, soil testing, crop management, and more.