Adaboost.RT Based Soil N-P-K Prediction Model for Soil and Crop Specific Data: A Predictive Modelling Approach
In relation to the evaluation of the soil breeding status of a region or realm, the soil characteristics are an important aspect in terms of agricultural production. Nitrogen, phosphorus, potassium, and sulfur are important elements of soil that regulate its fertility and yield of crops. Due to the low efficiency of other inputs or due to the use of unbalanced and inadequate fertilizer, the reaction of chemical fertilizer nutrients (production) efficiency in recent years has reduced considerably under intensive agriculture. Stability in crop productivity cannot be extended without the judicial use of macro and micro nutrients to overcome existing deficiencies. The information on the availability of macro nutrients in the study area is low. Therefore, the current study has been done to know the condition of soil nutrients. Use of advanced agricultural technology can help in predicting soil nutrient content and can help farmers to decide the amount of fertilizers to use on a particular land. The proposed study focuses on the accurate prediction of N-P-K content in the given land by utilizing the predication method using Adaboost.RT method. A comparison is also made in between the nutrient utilized using traditional methods and the proposed method. Experimental results show that the proposed stream outperforms with other existing methodologies.
KeywordsPrediction Soil nutrients content Adaboost.RT algorithm
This work was supported by the Science and Research Board (SERB), Govt. of India with the grant number ECR/2017/001273. The authors also wish to express their gratitude and heartiest thanks to the Department of Computer Science & Engineering, Indian Institute of Technology (ISM), Dhanbad, India for providing their research support.
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