IEICE Transactions on Information and Systems
Online ISSN : 1745-1361
Print ISSN : 0916-8532
Special Section on Data Engineering and Information Management
Predicting A Growing Stage of Rice Plants Based on The Cropping Records over 25 Years — A Trial of Feature Engineering Incorporating Hidden Regional Characteristics —
Hiroshi UEHARAYasuhiro IUCHIYusuke FUKAZAWAYoshihiro KANETA
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2022 Volume E105.D Issue 5 Pages 955-963

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Abstract

This study tries to predict date of ear emergence of rice plants, based on cropping records over 25 years. Predicting ear emergence of rice plants is known to be crucial for practicing good harvesting quality, and has long been dependent upon old farmers who acquire skills of intuitive prediction based on their long term experiences. Facing with aging farmers, data driven approach for the prediction have been pursued. Nevertheless, they are not necessarily sufficient in terms of practical use. One of the issue is to adopt weather forecast as the feature so that the predictive performance is varied by the accuracy of the forecast. The other issue is that the performance is varied by region and the regional characteristics have not been used as the features for the prediction. With this background, we propose a feature engineering to quantify hidden regional characteristics as the feature for the prediction. Further the feature is engineered based only on observational data without any forecast. Applying our proposal to the data on the cropping records resulted in sufficient predictive performance, ±2.69days of RMSE.

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© 2022 The Institute of Electronics, Information and Communication Engineers
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