Predictive modelling for rice weeds in climate change: a review
Rice (Oryza sativa L.) is an important staple food not only for Asians but also for people worldwide. However, weeds in rice fields can cause yield reduction due to their tendency to compete for resources. These significant biological obstacles can potentially cause complete yield loss if inappropri...
| Main Authors: | , , , , , , |
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| Format: | Article |
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HH Publisher
2022
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| Online Access: | http://psasir.upm.edu.my/id/eprint/108786/ |
| _version_ | 1848865208863293440 |
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| author | Abd Manaf, Muhamd Noor Hazwan Juraimi, Abdul Shukor Che'Ya, Nik Norasma Mat Su, Ahmad Suhaizi Mohd Roslim, Muhammad Huzaifah Ahmad, Anuar Mohd Noor, Nisfariza |
| author_facet | Abd Manaf, Muhamd Noor Hazwan Juraimi, Abdul Shukor Che'Ya, Nik Norasma Mat Su, Ahmad Suhaizi Mohd Roslim, Muhammad Huzaifah Ahmad, Anuar Mohd Noor, Nisfariza |
| author_sort | Abd Manaf, Muhamd Noor Hazwan |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Rice (Oryza sativa L.) is an important staple food not only for Asians but also for people worldwide. However, weeds in rice fields can cause yield reduction due to their tendency to compete for resources. These significant biological obstacles can potentially cause complete yield loss if inappropriately managed. In addition, future climate change can cause rice weeds to become more competitive against cultivated rice plants by providing new favourable conditions for the unwanted species to expand aggressively. As the effect of climate change on rice weeds has been studied, the abiotic parameters, including carbon dioxide concentration, atmospheric temperature, drought, and soil salinity, can be used to construct predictive modelling to forecast rice weed infestation. If the weed invasion in rice fields can be predicted accurately based on the weather information, the farmers can prepare the countermeasure early to avoid high yield loss. However, some challenges need to be faced by the researchers as the weed invasion depends not only on the climate condition alone. This review summarizes the effect of climatic variation on weed infestation in rice fields. It also discusses how predictive modelling can be developed based on the information of the environmental conditions and their challenges. |
| first_indexed | 2025-11-15T14:01:04Z |
| format | Article |
| id | upm-108786 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-15T14:01:04Z |
| publishDate | 2022 |
| publisher | HH Publisher |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1087862024-09-26T08:28:20Z http://psasir.upm.edu.my/id/eprint/108786/ Predictive modelling for rice weeds in climate change: a review Abd Manaf, Muhamd Noor Hazwan Juraimi, Abdul Shukor Che'Ya, Nik Norasma Mat Su, Ahmad Suhaizi Mohd Roslim, Muhammad Huzaifah Ahmad, Anuar Mohd Noor, Nisfariza Rice (Oryza sativa L.) is an important staple food not only for Asians but also for people worldwide. However, weeds in rice fields can cause yield reduction due to their tendency to compete for resources. These significant biological obstacles can potentially cause complete yield loss if inappropriately managed. In addition, future climate change can cause rice weeds to become more competitive against cultivated rice plants by providing new favourable conditions for the unwanted species to expand aggressively. As the effect of climate change on rice weeds has been studied, the abiotic parameters, including carbon dioxide concentration, atmospheric temperature, drought, and soil salinity, can be used to construct predictive modelling to forecast rice weed infestation. If the weed invasion in rice fields can be predicted accurately based on the weather information, the farmers can prepare the countermeasure early to avoid high yield loss. However, some challenges need to be faced by the researchers as the weed invasion depends not only on the climate condition alone. This review summarizes the effect of climatic variation on weed infestation in rice fields. It also discusses how predictive modelling can be developed based on the information of the environmental conditions and their challenges. HH Publisher 2022-09-25 Article PeerReviewed Abd Manaf, Muhamd Noor Hazwan and Juraimi, Abdul Shukor and Che'Ya, Nik Norasma and Mat Su, Ahmad Suhaizi and Mohd Roslim, Muhammad Huzaifah and Ahmad, Anuar and Mohd Noor, Nisfariza (2022) Predictive modelling for rice weeds in climate change: a review. Advances in Agricultural and Food Research Journal, 4 (1). art. no. 317. pp. 1-20. ISSN 2735-1084 https://journals.hh-publisher.com/index.php/AAFRJ/article/view/556 10.36877/aafrj.a0000317 |
| spellingShingle | Abd Manaf, Muhamd Noor Hazwan Juraimi, Abdul Shukor Che'Ya, Nik Norasma Mat Su, Ahmad Suhaizi Mohd Roslim, Muhammad Huzaifah Ahmad, Anuar Mohd Noor, Nisfariza Predictive modelling for rice weeds in climate change: a review |
| title | Predictive modelling for rice weeds in climate change: a review |
| title_full | Predictive modelling for rice weeds in climate change: a review |
| title_fullStr | Predictive modelling for rice weeds in climate change: a review |
| title_full_unstemmed | Predictive modelling for rice weeds in climate change: a review |
| title_short | Predictive modelling for rice weeds in climate change: a review |
| title_sort | predictive modelling for rice weeds in climate change: a review |
| url | http://psasir.upm.edu.my/id/eprint/108786/ http://psasir.upm.edu.my/id/eprint/108786/ http://psasir.upm.edu.my/id/eprint/108786/ |