基于多模型耦合的低温胁迫对冬小麦影响的研究

IF 4 2区 农林科学 Q2 FOOD SCIENCE & TECHNOLOGY
Jiameng Chen, Peiyan Zhang, Junming Liu, Jingyuan Deng, Wei Su, Pengxin Wang, Ying Li
{"title":"基于多模型耦合的低温胁迫对冬小麦影响的研究","authors":"Jiameng Chen,&nbsp;Peiyan Zhang,&nbsp;Junming Liu,&nbsp;Jingyuan Deng,&nbsp;Wei Su,&nbsp;Pengxin Wang,&nbsp;Ying Li","doi":"10.1002/fes3.543","DOIUrl":null,"url":null,"abstract":"<p>Crop growth models, such as the WOrld FOod STudies (WOFOST) model, mimic the mechanistic processes involved in crop development, growth, and yield production. The accuracy of simulation is decreased in unfavorable low-temperature settings because these models do not accurately represent crop response processes in low-temperature stress. Enhancing the WOFOST crop growth model's accuracy in simulating crops' responses to cold temperatures is the aim of this work. Given its vulnerability to low temperatures, the inquiry uses winter wheat in Henan Province as a focal point. It integrates the WHEATGROW wheat phenology model with the Frost model of Lethal Temperature 50 (FROSTOL) inside the framework of the crop growth model. This link aims to improve simulation accuracy and supplement the model's mechanisms, particularly when it comes to the impact of low temperatures on crop development. The study uses Long Short-Term Memory networks to build a yield model that integrates remote sensing data with information from simulated crop models. Under low temperatures, the leaf area index, total above ground biomass, and total weight of storage organs of the model WWF—which combines FROSTOL and WHEATGROW with WOFOST—show a considerable decline. It was discovered that there is a greater improvement in simulation accuracy of the linked model WWF relative to the WOFOST model in frost years than in normal years, based on a comparison analysis between typical frost years and normal years. To be more precise, the improvement is 8.03% in frost years and 1.98% in regular years. When all is said and done, the coupled model advances our knowledge of how winter wheat is impacted by low temperatures.</p>","PeriodicalId":54283,"journal":{"name":"Food and Energy Security","volume":"13 2","pages":""},"PeriodicalIF":4.0000,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/fes3.543","citationCount":"0","resultStr":"{\"title\":\"Study on the impact of low-temperature stress on winter wheat based on multi-model coupling\",\"authors\":\"Jiameng Chen,&nbsp;Peiyan Zhang,&nbsp;Junming Liu,&nbsp;Jingyuan Deng,&nbsp;Wei Su,&nbsp;Pengxin Wang,&nbsp;Ying Li\",\"doi\":\"10.1002/fes3.543\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Crop growth models, such as the WOrld FOod STudies (WOFOST) model, mimic the mechanistic processes involved in crop development, growth, and yield production. The accuracy of simulation is decreased in unfavorable low-temperature settings because these models do not accurately represent crop response processes in low-temperature stress. Enhancing the WOFOST crop growth model's accuracy in simulating crops' responses to cold temperatures is the aim of this work. Given its vulnerability to low temperatures, the inquiry uses winter wheat in Henan Province as a focal point. It integrates the WHEATGROW wheat phenology model with the Frost model of Lethal Temperature 50 (FROSTOL) inside the framework of the crop growth model. This link aims to improve simulation accuracy and supplement the model's mechanisms, particularly when it comes to the impact of low temperatures on crop development. The study uses Long Short-Term Memory networks to build a yield model that integrates remote sensing data with information from simulated crop models. Under low temperatures, the leaf area index, total above ground biomass, and total weight of storage organs of the model WWF—which combines FROSTOL and WHEATGROW with WOFOST—show a considerable decline. It was discovered that there is a greater improvement in simulation accuracy of the linked model WWF relative to the WOFOST model in frost years than in normal years, based on a comparison analysis between typical frost years and normal years. To be more precise, the improvement is 8.03% in frost years and 1.98% in regular years. When all is said and done, the coupled model advances our knowledge of how winter wheat is impacted by low temperatures.</p>\",\"PeriodicalId\":54283,\"journal\":{\"name\":\"Food and Energy Security\",\"volume\":\"13 2\",\"pages\":\"\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2024-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/fes3.543\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Food and Energy Security\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/fes3.543\",\"RegionNum\":2,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"FOOD SCIENCE & TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Food and Energy Security","FirstCategoryId":"97","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/fes3.543","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

作物生长模型,如世界作物研究(WOFOST)模型,模拟了作物发育、生长和产量产生的机理过程。在不利的低温环境下,模拟的准确性会降低,因为这些模型不能准确地反映作物在低温胁迫下的反应过程。提高 WOFOST 作物生长模型模拟作物对低温反应的准确性是这项工作的目的。鉴于冬小麦易受低温影响,研究以河南省的冬小麦为重点。它将 WHEATGROW 小麦物候模型与致命温度 50 的霜冻模型(FROSTOL)整合在作物生长模型的框架内。这种联系旨在提高模拟精度,补充模型机制,特别是在低温对作物生长的影响方面。该研究利用长短期记忆网络建立了一个产量模型,将遥感数据与模拟作物模型的信息整合在一起。在低温条件下,WWF 模型(将 FROSTOL 和 WHEATGROW 与 WOFOST 结合在一起)的叶面积指数、地上生物量总量和储藏器官总重量都出现了显著下降。通过对典型霜冻年和正常年的对比分析发现,与 WOFOST 模型相比,WWF 模型在霜冻年的模拟精度比正常年有更大的提高。更准确地说,霜冻年的提高幅度为 8.03%,正常年份为 1.98%。总而言之,耦合模型增进了我们对冬小麦如何受低温影响的了解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Study on the impact of low-temperature stress on winter wheat based on multi-model coupling

Study on the impact of low-temperature stress on winter wheat based on multi-model coupling

Crop growth models, such as the WOrld FOod STudies (WOFOST) model, mimic the mechanistic processes involved in crop development, growth, and yield production. The accuracy of simulation is decreased in unfavorable low-temperature settings because these models do not accurately represent crop response processes in low-temperature stress. Enhancing the WOFOST crop growth model's accuracy in simulating crops' responses to cold temperatures is the aim of this work. Given its vulnerability to low temperatures, the inquiry uses winter wheat in Henan Province as a focal point. It integrates the WHEATGROW wheat phenology model with the Frost model of Lethal Temperature 50 (FROSTOL) inside the framework of the crop growth model. This link aims to improve simulation accuracy and supplement the model's mechanisms, particularly when it comes to the impact of low temperatures on crop development. The study uses Long Short-Term Memory networks to build a yield model that integrates remote sensing data with information from simulated crop models. Under low temperatures, the leaf area index, total above ground biomass, and total weight of storage organs of the model WWF—which combines FROSTOL and WHEATGROW with WOFOST—show a considerable decline. It was discovered that there is a greater improvement in simulation accuracy of the linked model WWF relative to the WOFOST model in frost years than in normal years, based on a comparison analysis between typical frost years and normal years. To be more precise, the improvement is 8.03% in frost years and 1.98% in regular years. When all is said and done, the coupled model advances our knowledge of how winter wheat is impacted by low temperatures.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Food and Energy Security
Food and Energy Security Energy-Renewable Energy, Sustainability and the Environment
CiteScore
9.30
自引率
4.00%
发文量
76
审稿时长
19 weeks
期刊介绍: Food and Energy Security seeks to publish high quality and high impact original research on agricultural crop and forest productivity to improve food and energy security. It actively seeks submissions from emerging countries with expanding agricultural research communities. Papers from China, other parts of Asia, India and South America are particularly welcome. The Editorial Board, headed by Editor-in-Chief Professor Martin Parry, is determined to make FES the leading publication in its sector and will be aiming for a top-ranking impact factor. Primary research articles should report hypothesis driven investigations that provide new insights into mechanisms and processes that determine productivity and properties for exploitation. Review articles are welcome but they must be critical in approach and provide particularly novel and far reaching insights. Food and Energy Security offers authors a forum for the discussion of the most important advances in this field and promotes an integrative approach of scientific disciplines. Papers must contribute substantially to the advancement of knowledge. Examples of areas covered in Food and Energy Security include: • Agronomy • Biotechnological Approaches • Breeding & Genetics • Climate Change • Quality and Composition • Food Crops and Bioenergy Feedstocks • Developmental, Physiology and Biochemistry • Functional Genomics • Molecular Biology • Pest and Disease Management • Post Harvest Biology • Soil Science • Systems Biology
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信