28 extractive question-and-answer pairs built from Applicability of medium range weather forecasts for yield prediction of wheat (Triticum aestivum) using CERES-wheat model in south-western Punjab | The Indian Journal of Agricultural Sciences, published by epubs.icar.org.in. Source-evidenced topics include medium range weather forecasts, yield prediction, wheat, triticum aestivum, ceres-wheat model, south-western punjab, sowing dates, wheat varieties. Every answer is a verbatim span of text the source prints, and each row carries the passage it sits in, its offset in that passage, the source quote, the page and the location in the document, so any row can be checked against the original. Question types in the export: 14 factual, 5 list, 3 definition, 3 relationship, 2 summary, 1 comparison. 14 of the 28 pairs (50.0%) ask explanatory questions; the remaining 14 are factual or table-based questions. 96.43% of rows pass the corpus quality gate.
This dataset includes 28 extractive question-and-answer pairs derived from a study on the use of the CERES-wheat model for yield prediction of wheat in south-western Punjab. The study evaluates wheat production predictability using medium-range weather forecasts from the India Meteorological Department. It provides details on experimental designs, sowing dates, wheat varieties, and model validation metrics such as R2 and RMSE values. The dataset also references related studies on crop modeling and climate impacts on agriculture.
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df = desidata.load("epubs-icar-org-in-71c478777dd31d7435ee61c31298abc0")
df.head()First 10 of 28 rows
| question | answer | context | answer_start | question_type | knowledge_quality_score | source_document | source_quote | source_page | source_location | confidence | validation_status |
|---|---|---|---|---|---|---|---|---|---|---|---|
| What is the purpose of the CERES-wheat model? | used to estimate crop phenology and wheat yield | The study was carried out during the winter (rabi) season of 2021–22 at Punjab Agricultural University, Regional Research Station, Bathinda, Punjab to evaluate the predictability of wheat (Triticum aestivumL.) production using forecast scenarios that were gathered from the India Meteorological Department (IMD). CERES-wheat model was used to estimate crop phenology and wheat yield. The experiment was laid out in a split-plot design (SPD) with three replications. | 335 | definition | 1.000 | https://epubs.icar.org.in/index.php/IJAgS/article/view/148258 | CERES-wheat model was used to estimate crop phenology and wheat yield. | p[0] | 0.850 | valid | |
| Under what conditions does the Indian Council of Agricultural Research allow the use of material from The Indian Journal of Agricultural Sciences? | provided the information is not being utilized for commercial purposes and wherever the information is being used, proper credit is given to ICAR | This work is licensed under aCreative Commons Attribution-NonCommercial-ShareAlike 4. International License. The copyright of the articles published inThe Indian Journal of Agricultural Sciencesis vested with the Indian Council of Agricultural Research, which reserves the right to enter into any agreement with any organization in India or abroad, for reprography, photocopying, storage and dissemination of information. The Council has no objection to using the material, provided the information is not being utilized for commercial purposes and wherever the information is being used, proper credit is given to ICAR. Print ISSN:0019-5022Online ISSN:2394-3319NAAS Rating (2026):6.7WoS Impact Factor (June 2026):0. Indexedin Elsevier Scopus, Clarivate Analytics ESCI, DOAJ.Plagiarism checkby iThenticate.The work is licensed underAttribution-NonCommercial-NoDerivatives 4. | 474 | relationship | 0.970 | https://epubs.icar.org.in/index.php/IJAgS/article/view/148258 | The Council has no objection to using the material, provided the information is not being utilized for commercial purposes and wherever the information is being used, proper credit is given to ICAR. | ||||
| What aspect of wheat growth was analyzed using the CERES-wheat model in the Western Himalayas in 2013? | Temperature effect on growth parameters | Mohan D and Krishnappa G. 2020. Wheat improvement for growth and sustainability in yield under varying. (In) Improving Cereal Productivity through Climate Smart Practices, pp. 269. Sareen S, Sharma P, Singh C, Jasrotia P, Singh G P and Sarial A K (Eds). Woodhead Publishing, Elsevier Inc. United Kingdom. Mohanty U C, Sinha P, Nageswara Rao M M, Swain D K. and Singh K K. 2024. Crop modelling and simulation concept. (In) Climate Risk Management in Agriculture: Monthly and Seasonal Forecast Application, pp. 183–224. Pal R K, Tripathi P and Rao M M N. 2012. Validation of CERES-wheat model for growth parameters of wheat in eastern Uttar Pradesh. Environment and Ecology 4A: 1434–38. Pal R K and Murty N S. 2013. Temperature effect on growth parameters of wheat (CV. PBW-343) using CERES-wheat model for different sowing dates in foot hills of Western Himalayas. | 714 | relationship | 0.970 | https://epubs.icar.org.in/index.php/IJAgS/article/view/148258 | 2013. Temperature effect on growth parameters of wheat (CV. | p[19] | 0.700 | ||
| What experimental design was implemented in the wheat production study? | split-plot design (SPD) | The study was carried out during the winter (rabi) season of 2021–22 at Punjab Agricultural University, Regional Research Station, Bathinda, Punjab to evaluate the predictability of wheat (Triticum aestivumL.) production using forecast scenarios that were gathered from the India Meteorological Department (IMD). CERES-wheat model was used to estimate crop phenology and wheat yield. The experiment was laid out in a split-plot design (SPD) with three replications. The main plot treatments included five sowing dates, viz. October 25, November 4, November 14, November 24 and December 4 with four sub-plot treatments of variety which were HD 3086, PBW 725, HD 2967 and PBW 658. The model’s output with R2/RMSE for emergence, anthesis and maturity by using actual and forecasted data having 0.38/3.37 and 0.48/2.63, 0.56/4.28 and 0.70/8.48 and 0.71/8.30 and 0.49/2.63, respectively. | 417 | definition | 0.940 | https://epubs.icar.org.in/index.php/IJAgS/article/view/148258 | The experiment was laid out in a split-plot design (SPD) with three replications. | p[0] | 0.700 | ||
| What is highlighted as an important tool for crop management in the 2023 study? | Crop simulation modeling | Kumar M, Pannu R K, Singh R, Singh B, Dhaka A K and Rajeev. 2017. Prediction of growth and yield of late sown wheat using DSSAT model under western zone of Haryana. International Journal of Current Microbiology and Applied Sciences 6: 1687–96. Kundathil C, Viswan H and Kumar P. 2023. Crop simulation modeling: A strategic tool in crop management. Journal of Food Chemistry and Nanotechnology 9: S342–58. | 285 | definition | 0.940 | https://epubs.icar.org.in/index.php/IJAgS/article/view/148258 | 2023. Crop simulation modeling: A strategic tool in crop management. | p[7] | 0.700 | valid | |
| What factor affecting wheat productivity in central Punjab was analyzed in 2016? | Climate variability impacts | International Journal of Chemical Studies 8(5): 404–09. Grover K S and Pal R K. 2018. Simulating the effect of sowing dates and different irrigation levels on wheat cultivars using DSSAT-CSM-CERES wheat model. Journal of Pharmacognosy and Phytochemistry 7(5): 1934–38. Hoogenboom G, Jones J W, Wilkens P W, Porter C H, Boote K J, Hunt L A, Singh U, Lizaso J L, White J W, Gijsman A J and Tsuji G Y. 2010. Decision Support System for Agrotechnology Transfer (DSSAT) Version 4. University of Hawaii, Honolulu, Hawaii (CD ROM). Kaur P, Sandhu S S, Kothiyal S and Kaur J. 2022. Determination of sowing window for wheat in Punjab, India using sensitized, calibrated and validated CERES-wheat model. Journal of Agricultural Physics 22(2): 215–27. Kingra P K. 2016. Climate variability impacts on wheat productivity in central Punjab. Journal of Agrometeorology 18(1): 97–99. | 759 | relationship | 0.890 | https://epubs.icar.org.in/index.php/IJAgS/article/view/148258 | 2016. Climate variability impacts on wheat productivity in central Punjab. | p[7] | 0.700 | ||
| What was identified using the CERES-wheat model in Punjab, India in 2022? | sowing window for wheat | International Journal of Chemical Studies 8(5): 404–09. Grover K S and Pal R K. 2018. Simulating the effect of sowing dates and different irrigation levels on wheat cultivars using DSSAT-CSM-CERES wheat model. Journal of Pharmacognosy and Phytochemistry 7(5): 1934–38. Hoogenboom G, Jones J W, Wilkens P W, Porter C H, Boote K J, Hunt L A, Singh U, Lizaso J L, White J W, Gijsman A J and Tsuji G Y. 2010. Decision Support System for Agrotechnology Transfer (DSSAT) Version 4. University of Hawaii, Honolulu, Hawaii (CD ROM). Kaur P, Sandhu S S, Kothiyal S and Kaur J. 2022. Determination of sowing window for wheat in Punjab, India using sensitized, calibrated and validated CERES-wheat model. Journal of Agricultural Physics 22(2): 215–27. Kingra P K. 2016. Climate variability impacts on wheat productivity in central Punjab. Journal of Agrometeorology 18(1): 97–99. | 591 | summary | 0.890 | https://epubs.icar.org.in/index.php/IJAgS/article/view/148258 | Determination of sowing window for wheat in Punjab, India using sensitized, calibrated and validated CERES-wheat model. | p[7] | 0.700 | ||
| What was the focus of the 2020 study involving the DSSAT model (CERES rice)? | rice production | Boote K J, Jones J W and Hoogenboom G. 2018. Simulation of crop growth: CROPGRO model. (In) Agricultural Systems Modelling and Simulation, pp. 651–92. Dhir A, Pal R K, Kingra P K and Kaur R. 2024. Climate-smart cotton (Gossypium herbaceum) crop production in Punjab: A comprehensive review of sustainable management practices. The Indian Journal of Agricultural Sciences 94(2): 119–28. Dhir A, Pal R K, Kingra P K, Mishra S K and Sandhu S S. 2021. Cotton phenology and production response to sowing time, row orientation and plant spacing using CROPGRO-cotton model. Mausam 72(3): 627–34. Endalew A A. 2019. Calibration and validation of CERES-wheat in DSSAT model for yield simulation under future climate in Adet, north-western Ethiopia. African Journal of Agricultural Research 14(8): 509–18. Goswami P and Dutta G. 2020. Evaluation of DSSAT model (CERES rice) on rice production: A review. | 867 | summary | 0.890 | https://epubs.icar.org.in/index.php/IJAgS/article/view/148258 | Evaluation of DSSAT model (CERES rice) on rice production: A review. | p[7] | 0.700 | ||
| What were the R2/RMSE values for anthesis based on actual and forecasted data? | 0.56/4.28 and 0.70/8.48 | The study was carried out during the winter (rabi) season of 2021–22 at Punjab Agricultural University, Regional Research Station, Bathinda, Punjab to evaluate the predictability of wheat (Triticum aestivumL.) production using forecast scenarios that were gathered from the India Meteorological Department (IMD). CERES-wheat model was used to estimate crop phenology and wheat yield. The experiment was laid out in a split-plot design (SPD) with three replications. The main plot treatments included five sowing dates, viz. October 25, November 4, November 14, November 24 and December 4 with four sub-plot treatments of variety which were HD 3086, PBW 725, HD 2967 and PBW 658. The model’s output with R2/RMSE for emergence, anthesis and maturity by using actual and forecasted data having 0.38/3.37 and 0.48/2.63, 0.56/4.28 and 0.70/8.48 and 0.71/8.30 and 0.49/2.63, respectively. | 816 | comparison | 0.840 | https://epubs.icar.org.in/index.php/IJAgS/article/view/148258 | The model’s output with R2/RMSE for emergence, anthesis and maturity by using actual and forecasted data having 0.38/3.37 and 0.48/2.63, 0.56/4.28 and 0.70/8.48 and 0.71/8.30 and 0.49/2.63, respectively. | ||||
| What were the sowing dates used as main plot treatments in the wheat production predictability experiment? | October 25, November 4, November 14, November 24 and December 4 | The study was carried out during the winter (rabi) season of 2021–22 at Punjab Agricultural University, Regional Research Station, Bathinda, Punjab to evaluate the predictability of wheat (Triticum aestivumL.) production using forecast scenarios that were gathered from the India Meteorological Department (IMD). CERES-wheat model was used to estimate crop phenology and wheat yield. The experiment was laid out in a split-plot design (SPD) with three replications. The main plot treatments included five sowing dates, viz. October 25, November 4, November 14, November 24 and December 4 with four sub-plot treatments of variety which were HD 3086, PBW 725, HD 2967 and PBW 658. The model’s output with R2/RMSE for emergence, anthesis and maturity by using actual and forecasted data having 0.38/3.37 and 0.48/2.63, 0.56/4.28 and 0.70/8.48 and 0.71/8.30 and 0.49/2.63, respectively. | 524 | list | 0.820 | https://epubs.icar.org.in/index.php/IJAgS/article/view/148258 | The main plot treatments included five sowing dates, viz. October 25, November 4, November 14, November 24 and December 4 with four sub-plot treatments of variety which were HD 3086, PBW 725, HD 2967 and PBW 658. |
Read straight from the file — download or use the API URL for the full dataset.
| p[31] |
| 0.700 |
| valid |
| valid |
| valid |
| valid |
| valid |
| valid |
| p[0] |
| 0.700 |
| valid |
| p[0] |
| 0.700 |
| valid |