Prediction and Analysis of Plant Growth Promoting Bacteria using Machine Learning for Millet Crops

Abstract

Objectives: Microorganisms present within the rhizosphere play important roles in ecological fitness of their plant host. Important microbial processes that are expected to occur within the rhizosphere include pathogenesis and its counterpart, along with plant protection and growth promotion. This paper deal’s with predicting the Plant Growth Promoting Rhizobacteria from the microbes using Machine learning techniques to enhance the plant growth. Methods: This paper presents some Machine Learning approaches such as LDA, KNN and SVM for analyzing the genomes and predicts the Rhizosphere molecular mechanisms to find the Growth promoting bacteria and recommending the secondary metabolic model for further growth. NCBI Dataset was used for the experimental purpose. Findings: Among the Machine learning techniques used in this paper such as LDA, KNN and SVM, the best accuracy was obtained by SVM in predicting the Plant Promoting Rhizobacteria. Novelty: Exploring these microorganisms by unraveling their possible relationships with plants has launched a new and fascinating area of investigations in the rhizosphere research. As a beginning, we tried using Machine Learning to predict the Rhizobacteria, which paves the way for further studies.