Forecasting pre-harvest rice (Oryza sativa) yield: A regression analysis of meteorological factors and climate change impacts on food security
In order to arrive at the findings, different statistical models have been developed as a result to examine how climate change may affect rice yield at various phases of the crop as well as it has been attempted to forecast its output for Karnal district. Time series data on rice yield for the past...
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| Language: | English |
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Indian Council of Agricultural Research
2025-05-01
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| Series: | The Indian Journal of Agricultural Sciences |
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| Online Access: | https://epubs.icar.org.in/index.php/IJAgS/article/view/158592 |
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| author | ASHUTOSH KUMAR VISHWAKARMA NAGALAXMI M RAMAN AJAY KUMAR CHETNA VINAY KUMAR ARADHNA SAGWAL SUMAN GHALAWAT KAPIL ROHILLA SUSHMA RAVI PRAKASH XALXO SHRISHTI SAXENA |
| author_facet | ASHUTOSH KUMAR VISHWAKARMA NAGALAXMI M RAMAN AJAY KUMAR CHETNA VINAY KUMAR ARADHNA SAGWAL SUMAN GHALAWAT KAPIL ROHILLA SUSHMA RAVI PRAKASH XALXO SHRISHTI SAXENA |
| author_sort | ASHUTOSH KUMAR VISHWAKARMA |
| collection | DOAJ |
| description |
In order to arrive at the findings, different statistical models have been developed as a result to examine how climate change may affect rice yield at various phases of the crop as well as it has been attempted to forecast its output for Karnal district. Time series data on rice yield for the past 37 years on crop and weather variables have been used in the Karnal district of Haryana from 1985–1986 through 2021–22. The relationship between rice (Oryza sativa L.) crop and various models was investigated. A boost in yield can be obtained by creating fresh weather indices from weekly data. The model takes various weather variables into account. It was discovered that the best models (models 1, 2, and 7, 8) for assessing the impact of specific weather variables were linear functions across weekly data, meteorological factors, and adjusted crop production for the trend impact are the independent variables. A forecast model was also built and the findings revealed that forecasting at the 15th week of the crop period or one and a half months before harvest was found reliable.
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| format | Article |
| id | doaj-art-bd3fdbefd8054d0a90f4d2fd94aee31f |
| institution | Kabale University |
| issn | 0019-5022 2394-3319 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Indian Council of Agricultural Research |
| record_format | Article |
| series | The Indian Journal of Agricultural Sciences |
| spelling | doaj-art-bd3fdbefd8054d0a90f4d2fd94aee31f2025-08-20T03:30:40ZengIndian Council of Agricultural ResearchThe Indian Journal of Agricultural Sciences0019-50222394-33192025-05-0195510.56093/ijas.v95i4.158592Forecasting pre-harvest rice (Oryza sativa) yield: A regression analysis of meteorological factors and climate change impacts on food securityASHUTOSH KUMAR VISHWAKARMA0NAGALAXMI M RAMAN1AJAY KUMAR2CHETNA3VINAY KUMAR4ARADHNA SAGWAL5SUMAN GHALAWAT6KAPIL ROHILLA7SUSHMA8RAVI PRAKASH XALXO9SHRISHTI SAXENA10ICAR-National Bureau of Plant Genetics and Resources, New Delhi 110 012, IndiaAmity University, Noida, Uttar PradeshKrishi Vigyan Kendra (Chaudhary Charan Singh Haryana Agricultural University), Jhajjar, HaryanaChaudhary Charan Singh Haryana Agricultural University, Hisar, HaryanaChaudhary Charan Singh Haryana Agricultural University, Hisar, HaryanaChaudhary Charan Singh Haryana Agricultural University, Hisar, HaryanaChaudhary Charan Singh Haryana Agricultural University, Hisar, HaryanaHaryana Space Applications Centre, Hisar, HaryanaChaudhary Charan Singh Haryana Agricultural University, Hisar, HaryanaHaryana Space Applications Centre, Hisar, HaryanaForest Survey of India, Dehradun, Uttrakhand In order to arrive at the findings, different statistical models have been developed as a result to examine how climate change may affect rice yield at various phases of the crop as well as it has been attempted to forecast its output for Karnal district. Time series data on rice yield for the past 37 years on crop and weather variables have been used in the Karnal district of Haryana from 1985–1986 through 2021–22. The relationship between rice (Oryza sativa L.) crop and various models was investigated. A boost in yield can be obtained by creating fresh weather indices from weekly data. The model takes various weather variables into account. It was discovered that the best models (models 1, 2, and 7, 8) for assessing the impact of specific weather variables were linear functions across weekly data, meteorological factors, and adjusted crop production for the trend impact are the independent variables. A forecast model was also built and the findings revealed that forecasting at the 15th week of the crop period or one and a half months before harvest was found reliable. https://epubs.icar.org.in/index.php/IJAgS/article/view/158592Crop production, Pre-harvest forecast, Statistical model, Weather indices |
| spellingShingle | ASHUTOSH KUMAR VISHWAKARMA NAGALAXMI M RAMAN AJAY KUMAR CHETNA VINAY KUMAR ARADHNA SAGWAL SUMAN GHALAWAT KAPIL ROHILLA SUSHMA RAVI PRAKASH XALXO SHRISHTI SAXENA Forecasting pre-harvest rice (Oryza sativa) yield: A regression analysis of meteorological factors and climate change impacts on food security The Indian Journal of Agricultural Sciences Crop production, Pre-harvest forecast, Statistical model, Weather indices |
| title | Forecasting pre-harvest rice (Oryza sativa) yield: A regression analysis of meteorological factors and climate change impacts on food security |
| title_full | Forecasting pre-harvest rice (Oryza sativa) yield: A regression analysis of meteorological factors and climate change impacts on food security |
| title_fullStr | Forecasting pre-harvest rice (Oryza sativa) yield: A regression analysis of meteorological factors and climate change impacts on food security |
| title_full_unstemmed | Forecasting pre-harvest rice (Oryza sativa) yield: A regression analysis of meteorological factors and climate change impacts on food security |
| title_short | Forecasting pre-harvest rice (Oryza sativa) yield: A regression analysis of meteorological factors and climate change impacts on food security |
| title_sort | forecasting pre harvest rice oryza sativa yield a regression analysis of meteorological factors and climate change impacts on food security |
| topic | Crop production, Pre-harvest forecast, Statistical model, Weather indices |
| url | https://epubs.icar.org.in/index.php/IJAgS/article/view/158592 |
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