Soil Data Analytics using Machine Learning Techniques - A Survey

Food security is the most basic need with any individual all over the globe. With food security we can reduce malnutrition in children, who are the backbone of nation's development. To achieve this using machine learning techniques in agriculture domain is the new beginning. Machine learning te...

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Bibliographic Details
Published in2023 3rd International Conference on Intelligent Technologies (CONIT) pp. 1 - 7
Main Authors Raghavendra Rao, R V, Srinivasulu Reddy, U, Mohan Reddy, Ch Ram
Format Conference Proceeding
LanguageEnglish
Published IEEE 23.06.2023
Subjects
Agriculture
Crops
Data analysis
Food security
Machine learning algorithms
Machine Learning techniques
Soil
Soil data analysis
Soil micro-nutrients
Soil nutrients
Surveys
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Summary:Food security is the most basic need with any individual all over the globe. With food security we can reduce malnutrition in children, who are the backbone of nation's development. To achieve this using machine learning techniques in agriculture domain is the new beginning. Machine learning techniques successfully implemented in innumerable domains, now entered in agriculture. Machine learning techniques establishes a novel way in data processing and data analytics, producing good results with larger data. In this work we carried out survey on machine learning technique's role in agriculture domain and challenges involved in it. We examined the models developed based on agricultural soil. In addition, we analyzed the associations between soil nutrients, which help in crop yield. These results specify that the accuracy of the model is more with ensemble methods.
DOI:10.1109/CONIT59222.2023.10205531