Article(id=1305136340719394844, tenantId=1146029695717560320, journalId=1303687221787852879, issueId=1305136340186718236, articleNumber=null, orderNo=null, doi=10.7606/j.issn.1009-1041.2026.04.10, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1752768000000, receivedDateStr=2025-07-18, revisedDate=1755446400000, revisedDateStr=2025-08-18, acceptedDate=null, acceptedDateStr=null, onlineDate=1789098351887, onlineDateStr=2026-09-11, pubDate=1776182400000, pubDateStr=2026-04-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1789098351887, onlineIssueDateStr=2026-09-11, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1789098351887, creator=13701087609, updateTime=1789098351887, updator=13701087609, issue=Issue{id=1305136340186718236, tenantId=1146029695717560320, journalId=1303687221787852879, year='2026', volume='46', issue='4', pageStart='F2', pageEnd='566', issueExtLink='null', onlineDate='null', pubDate='1776182400000', pubDateStr='2026-04-15', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1789098351761, creator='13701087609', updateTime=1789103128365, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1305156374778900923, tenantId=1146029695717560320, journalId=1303687221787852879, issueId=1305136340186718236, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1305156374778900924, tenantId=1146029695717560320, journalId=1303687221787852879, issueId=1305136340186718236, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=511, endPage=519, ext={EN=ArticleExt(id=1305136341054939165, articleId=1305136340719394844, tenantId=1146029695717560320, journalId=1303687221787852879, language=EN, title=Simulation Analysis of Rainfed Spring Wheat Yield and Leaf Area Index Responses to Future Climate Conditions in Longzhong Dryland, columnId=1305133133406433355, journalTitle=Journal of Triticeae Crops, columnName=Physiology, Ecology and Cultivation, runingTitle=null, highlight=null, articleAbstract=

To adapt to the future climate change and increased carbon emissions in the Longzhong region, this study proposes optimization strategies for the production management of rain-fed spring wheat. Based on field experimental data from Dingxi, Gansu, collected from 2014 to 2017, the Root Zone Water Quality Model 2 (RZWQM2) was calibrated and validated for this region. Using this model, climate projections under the RCP4.5 and RCP8.5 scenarios for the period 2025-2060 in Northwest China were analyzed. Different sowing dates and CO₂ concentration gradients (370, 400, 500 and 600 μmol·mol^-1) were applied to evaluate the impact of future climate change on spring wheat yield and LAI. The results show that, The model accurately simulated the leaf area index (LAI) and yield of spring wheat, with R₂ values reaching 0.913 and 0.992, respectively. Under the RCP4.5 scenario with moderate warming, when CO₂ concentration exceeds 500 μmol·mol^-1, significant yield increases were observed. The average yield increases for early sowing (March 7), conventional sowing (March 19), and late sowing (March 31) were 29.3%, 28.9%, and 24.7%, respectively. Under the RCP8.5 scenario, high temperatures, reduced radiation, and precipitation fluctuations weakened the CO₂ fertilization effect, resulting in a yield increase of only 20.9%-27.5%, with significant interannual variability. The sowing date effect was also prominent, with early sowing maintaining the highest and most stable yield and LAI in both climate scenarios, while late sowing, impacted by combined heat and drought stress, showed the highest yield fluctuation. In conclusion, under the future higher CO₂ concentrations, through coordinating reasonable early sowing and water and fertilizer management the risks of high temperature and water stress can be alleviated to increase the LAI and yield of spring wheat in Longzhong dryland.

, authors=Rui MA, Qiang LIU, Guang LI, authorsList=Rui MA, Qiang LIU, Guang LI, authorCompany=null, correspAuthors=Qiang LIU, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1305136341470175262, articleId=1305136340719394844, tenantId=1146029695717560320, journalId=1303687221787852879, language=CN, title=未来气候条件下陇中旱地春小麦产量与叶面积指数响应的模拟分析, columnId=1305133133590982733, journalTitle=麦类作物学报, columnName=生理、生态与栽培, runingTitle=null, highlight=null, articleAbstract=

为适应未来气候变化及碳排放升高，优化陇中地区旱地春小麦的生产管理策略，基于甘肃定西2014—2017年田间试验数据，对根区水质模型RZWQM2（root zone water quality model 2）进行率定并验证了其在该地区应用的有效性，并基于未来RCP4.5和RCP8.5气候情景下的2025—2060年的逐日气候数据，通过设置3种播期和不同CO₂浓度梯度（370、400、500和600 μmol·mol^-1），评估了未来气候变化对春小麦产量及叶面积指数（LAI）的影响。结果表明，该模型对该地区春小麦的产量及LAI实现高精准模拟，R₂值分别达到0.913、0.992。在RCP4.5适度升温的情景下，≥500 μmol·mol^-1的CO₂浓度能显著提高春小麦产量，早播（3月7日）、常规播（3月19日）和晚播（3月31日）的平均产量增幅分别为29.3%、28.9%和24.7%；RCP8.5情景下，高温、辐射下降与降水波动削弱了CO₂肥效，春小麦增产幅度降至20.9%~27.5%，且年际波动显著增大；播期效应显著，早播在两种情景下均能维持最高且稳定的产量与LAI，而晚播小麦的产量受高温与干旱叠加影响，波动最大。因此，在未来较高CO₂浓度下，通过适期早播与水肥协同可降低高温与水分胁迫风险，提高陇中旱地春小麦产量和LAI。

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