From Climate to Crop: Unveiling the Impact of Agro-Climate Dataset on Rice Yield in Cotabato Province
The data was collected from the Office of the Provincial Agriculturist and NASA Power dataset agro-climate dataset from 2007 to 2021. The data was processed using ETL, and multivariate linear regression analysis was conducted to identify the agro-climates that significantly influence the production of irrigated and rainfed rice. The dataset provides information on various agro-climatic factors such as temperature, rainfall, solar radiation, and humidity, along with the production of irrigated and rainfed rice. The dataset also includes explanatory factors that significantly influence the production of rice, which are presented in an Analytical Dashboard.The dataset can be used for predictive analytics research at the municipal level to provide more detailed insights into the agro-climates of different municipalities in Cotabato Province. It can also be used to distribute different varieties of rice that can withstand the effects of climate change to the municipalities of Cotabato. Overall, the dataset provides valuable insights into the relationship between agro-climate and rice production in Cotabato Province, and can inform future decision-making and resource allocation in the region.
Steps to reproduce
To reproduce the results presented in the data article, researchers should first obtain access to the same datasets used in the study. These datasets include the agro-climate dataset from NASA Power and the rice yield dataset from the Office of the Provincial Agriculturist of Cotabato Province. After obtaining the datasets, researchers should process them using ETL techniques to ensure they are in a suitable format for analysis. Multivariate linear regression analysis should then be conducted to identify the agro-climates that significantly influence the production of irrigated and rainfed rice. The explanatory factors that significantly influence the production of rice should also be determined, and an Analytical Dashboard can be created to present these findings. Moreover, the researchers should then analyze the dataset and identify trends in the climatic factors and rice yield over the study period. Data visualization tools such as charts and graphs can be used for this purpose. Further analysis can also be conducted to identify potential patterns and relationships between different variables in the dataset. To validate the results obtained from the analysis, researchers should compare them with other studies or datasets, and check for consistency and accuracy. Finally, researchers should document the methods used and the results obtained in a clear and detailed manner, to ensure that the research can be replicated and verified by others. By following these steps, researchers can reproduce the results presented in the data article and conduct further analyses to gain new insights into the relationship between agro-climate and rice production in Cotabato Province.