Crop Yield Prediction and Classification using the Agriculture Resources and Data Mining Techniques
Year: 2024
Type: article
Abstract: This study investigates the application of data mining techniques in meteorological forecasting to enhance crop yield prediction accuracy Moreover, the integration of meteorological forecasting with agronomic models and geographical information systems (GIS) facilitates site-specific crop management and precision agriculture practices. By combining meteorological data with soil properties, crop phenology, and socio-economic factors, data mining techniques enable the development of predictive models that enhance crop yield potential and optimize resource allocation. By leveraging advanced data analytics and machine learning algorithms, agricultural stakeholders can make informed decisions, mitigate risks, and enhance productivity in the face of changing climatic conditions and environmental uncertainties.
DOI: 10.29070/krwa0448
Authors: Pramod Kumar Dwivedi, Dr. Prabhat Pandey
Institution: Awadhesh Pratap Singh University
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDGs: Zero hunger, Climate action
Open Access status: diamond
OpenAlex ID: W4402138591