Knowledge Discovery Model for Predicting Optimal Climatic Conditions for Maize Crop Productivity

Johnson Wito Malgwa; Dr.  Asabe Sandra Ahmadu; Ahmed Zainab Tijjani

doi:10.56201/ijcsmt.v10.no4.2024.pg53.69

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Knowledge Discovery Model for Predicting Optimal Climatic Conditions for Maize Crop Productivity

Johnson Wito Malgwa, Dr. Asabe Sandra Ahmadu, Ahmed Zainab Tijjani

Abstract

This research presents an integrated approach to forecasting the impact of climate on maize output in Nigeria, emphasizing the critical role of predictive modeling and data mining techniques. The study acknowledges the profound influence of climate conditions, particularly temperature, rainfall, soil moisture and humidity, on maize development and yield in agriculture. By examining historical climatic data and its correlation with agricultural outcomes, the research aims to develop a predictive model, the Maize Yield Predictive Model, tailored to Nigeria's agricultural landscape. Leveraging data mining techniques, such as Linear Regression, Decision Trees, Support Vector Machine and K-Nearest Neighbor, the study analyzes meteorological data collected over a Five-year period to predict future climatic conditions and their effects on Maize output. Through meticulous data preprocessing and experimentation with classification algorithms, the optimal predictive model is identified, facilitating strategic planning and decision- making for farmers. The significance of the research lies in its potential to enhance agricultural productivity, profitability, and resilience in the face of climate variability, thereby contributing to the socioeconomic development of Nigeria. From the result of the study: Based on the given metrics, KNN (K-Nearest Neighbors) is the best algorithm for this task due to its lowest RMSPE and high CC, indicating good prediction accuracy despite its longer training time withTime: 0.19 (highest), CC: 0.8604 (second highest), RMSPE: 0.0687 (lowest). Additionally, the study adds to the body of literature on the application of data mining techniques in predicting climate effects on agriculture and on maize yield, paving the way for further empirical research in this domain. Despite its scope limitations, focusing on selected cereal crop and sub-variables, the study provides valuable insights into the intersection of c

Keywords

AgricultureData miningSoiland Prediction

References

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Knowledge Discovery Model for Predicting Optimal Climatic Conditions for Maize Crop Productivity

Abstract

Keywords

References

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