Use of regression techniques for rice yield estimation in the North-Western province of Sri Lanka
One of the aspects in the agriculture sector beneficial to farmers and all other stakeholders is the prior knowledge on the yield of crops expected from an agricultural season. In this paper, several regression techniques have been used to model the relationship between climatic factors and paddy pr...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Faculty of Science, University of Peradeniya, Sri Lanka
2021-12-01
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| Series: | Ceylon Journal of Science |
| Subjects: | |
| Online Access: | https://cjs.sljol.info/articles/7942 |
| _version_ | 1811323883658149888 |
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| author | E. M. P. Ekanayake L. C. D. Wickramasinghe R. T. Weliwatta |
| author_facet | E. M. P. Ekanayake L. C. D. Wickramasinghe R. T. Weliwatta |
| author_sort | E. M. P. Ekanayake |
| collection | DOAJ |
| description | One of the aspects in the agriculture sector beneficial to farmers and all other stakeholders is the prior knowledge on the yield of crops expected from an agricultural season. In this paper, several regression techniques have been used to model the relationship between climatic factors and paddy production in the North-Western province of Sri Lanka that makes a significant contribution to the total harvest of the country. Nearly two decades of rice yield data from 2000 to 2018 and several climatic factors in the two agricultural seasons of Yala (May-August) and Maha (September-March) were considered in the analysis. Monthly mean climatic data of temperature, evaporation, sunshine, and wind speed were applied along with the overall rainfall in four regression techniques <em>viz.</em> Support Vector Machine Regression, Multiple Linear regression, Power Regression, and the Robust Regression on MATLAB and R software. The performance of the models developed on those techniques was evaluated in terms of the Mean Absolute Error and the Coefficient of Determination. It was found that the Support Vector Machine Regression produces the best correlation between actual and predicted yields in both administrative districts of the Province, which can be used for yield estimation under normal climatic conditions. |
| first_indexed | 2024-04-13T14:03:56Z |
| format | Article |
| id | doaj.art-9251f930eaf840fda8b68dd0464313bf |
| institution | Directory Open Access Journal |
| issn | 2513-2814 2513-230X |
| language | English |
| last_indexed | 2024-04-13T14:03:56Z |
| publishDate | 2021-12-01 |
| publisher | Faculty of Science, University of Peradeniya, Sri Lanka |
| record_format | Article |
| series | Ceylon Journal of Science |
| spelling | doaj.art-9251f930eaf840fda8b68dd0464313bf2022-12-22T02:43:58ZengFaculty of Science, University of Peradeniya, Sri LankaCeylon Journal of Science2513-28142513-230X2021-12-0150443944710.4038/cjs.v50i4.79425898Use of regression techniques for rice yield estimation in the North-Western province of Sri LankaE. M. P. Ekanayake0L. C. D. Wickramasinghe1R. T. Weliwatta2Wayamba University of Sri Lanka, KuliyapitiyaWayamba University of Sri Lanka, KuliyapitiyaWayamba University of Sri Lanka, KuliyapitiyaOne of the aspects in the agriculture sector beneficial to farmers and all other stakeholders is the prior knowledge on the yield of crops expected from an agricultural season. In this paper, several regression techniques have been used to model the relationship between climatic factors and paddy production in the North-Western province of Sri Lanka that makes a significant contribution to the total harvest of the country. Nearly two decades of rice yield data from 2000 to 2018 and several climatic factors in the two agricultural seasons of Yala (May-August) and Maha (September-March) were considered in the analysis. Monthly mean climatic data of temperature, evaporation, sunshine, and wind speed were applied along with the overall rainfall in four regression techniques <em>viz.</em> Support Vector Machine Regression, Multiple Linear regression, Power Regression, and the Robust Regression on MATLAB and R software. The performance of the models developed on those techniques was evaluated in terms of the Mean Absolute Error and the Coefficient of Determination. It was found that the Support Vector Machine Regression produces the best correlation between actual and predicted yields in both administrative districts of the Province, which can be used for yield estimation under normal climatic conditions.https://cjs.sljol.info/articles/7942regression, coefficient of determination, mean absolute error, yield estimation, north-western province |
| spellingShingle | E. M. P. Ekanayake L. C. D. Wickramasinghe R. T. Weliwatta Use of regression techniques for rice yield estimation in the North-Western province of Sri Lanka Ceylon Journal of Science regression, coefficient of determination, mean absolute error, yield estimation, north-western province |
| title | Use of regression techniques for rice yield estimation in the North-Western province of Sri Lanka |
| title_full | Use of regression techniques for rice yield estimation in the North-Western province of Sri Lanka |
| title_fullStr | Use of regression techniques for rice yield estimation in the North-Western province of Sri Lanka |
| title_full_unstemmed | Use of regression techniques for rice yield estimation in the North-Western province of Sri Lanka |
| title_short | Use of regression techniques for rice yield estimation in the North-Western province of Sri Lanka |
| title_sort | use of regression techniques for rice yield estimation in the north western province of sri lanka |
| topic | regression, coefficient of determination, mean absolute error, yield estimation, north-western province |
| url | https://cjs.sljol.info/articles/7942 |
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