{"title":"公开的统计方法不能准确地估计作物的生产潜力","authors":"","doi":"10.1038/s43016-025-01166-3","DOIUrl":null,"url":null,"abstract":"Estimating yield potential and yield gaps is crucial for global food security. However, many studies rely on statistical methods that lack theoretical and empirical justification for their use. We show that well-validated crop models, combined with local weather and soil data, provide a more accurate assessment of production potential.","PeriodicalId":19090,"journal":{"name":"Nature Food","volume":"29 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Published statistical methods fail to accurately estimate crop production potential\",\"authors\":\"\",\"doi\":\"10.1038/s43016-025-01166-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Estimating yield potential and yield gaps is crucial for global food security. However, many studies rely on statistical methods that lack theoretical and empirical justification for their use. We show that well-validated crop models, combined with local weather and soil data, provide a more accurate assessment of production potential.\",\"PeriodicalId\":19090,\"journal\":{\"name\":\"Nature Food\",\"volume\":\"29 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-04-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature Food\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1038/s43016-025-01166-3\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Food","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1038/s43016-025-01166-3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Published statistical methods fail to accurately estimate crop production potential
Estimating yield potential and yield gaps is crucial for global food security. However, many studies rely on statistical methods that lack theoretical and empirical justification for their use. We show that well-validated crop models, combined with local weather and soil data, provide a more accurate assessment of production potential.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
