{"id":28,"date":"2025-10-21T13:11:53","date_gmt":"2025-10-21T13:11:53","guid":{"rendered":"https:\/\/research.unl.edu\/annualreport\/2025\/?p=28"},"modified":"2025-11-13T23:28:52","modified_gmt":"2025-11-13T23:28:52","slug":"agriculture","status":"publish","type":"post","link":"https:\/\/research.unl.edu\/annualreport\/2025\/agriculture\/","title":{"rendered":"Challenging current approaches to estimating crop yield potential"},"content":{"rendered":"
Research Impact<\/a><\/div>\n\n\n

Accurate estimates of crop yield potential and gaps are key in planning how to meet growing food demand globally. Nebraska agronomists significantly contributed to an international study that demonstrates long-standing statistical methods are insufficient.<\/p>\n\n\n\n

\u201cWe are in a race to feed the world and to try to feed the population with the available agricultural land that we have,\u201d said Patricio Grassini, Sunkist Distinguished Professor of Agronomy and an author of the Nature Food<\/em> paper outlining the team\u2019s findings.<\/p>\n\n\n\n

Predicting both yield potential, as determined by weather and soil properties, and yield gaps, the difference between yield potential and current farm yields, helps guide investments in agricultural research and development, both from public and private sources.<\/p>\n\n\n\n

The most widely used methods to compile those estimates tend to rely too heavily on best-case scenarios \u2013 the most productive counties with the most fertile soils in a year with the most favorable weather, Grassini said. They also extrapolate a single yield potential across large regions with a wide diversity of climates and soils that likely would produce a similarly wide range in yield potential. <\/p>\n\n\n\n

In some instances, those methods can overestimate yield potential; in others, they might underestimate it.<\/p>\n\n\n\n

The team\u2019s study compared estimates of yield potential and yield gaps of major U.S. rainfed crops \u2013 corn, soybeans and wheat \u2013 derived from four statistical models against those derived from a \u201cbottom-up\u201d spatial scaling approach based on robust crop modeling and local weather and soil data, such as the Global Yield Gap and Water Productivity Atlas developed at Nebraska.<\/p>\n\n\n\n

The team discovered that a bottom-up approach that incorporates local weather and soil data and accounts for regional variations, is superior. This approach could better quantify yield gaps, which may help scientists, agronomists and policy makers identify regions with the greatest potential to increase crop production.<\/p>\n\n\n\n

\n

This is a call to set the record straight because if we are going to use this information to inform policy and our investments, we better make sure that the information is sound and has been validated.<\/p>\nPatricio Grassini<\/cite><\/blockquote>\n\n\n\n

Grassini said he expects the study to challenge prevailing attitudes.<\/p>\n\n\n\n

\u201cThis is a call to set the record straight because if we are going to use this information to inform policy and our investments, we better make sure that the information is sound and has been validated,\u201d said Grassini.<\/p>\n\n\n\n

The international team includes scientists from Kansas State University, Iowa State University and the French Agricultural Research Centre for International Development.<\/p>\n\n\n\n

\n\n\n\n

Additional Content<\/h2>\n\n\n\n
\n
News release<\/a><\/div>\n\n\n\n
Journal article<\/a><\/div>\n\n\n\n
Iowa State news release<\/a><\/div>\n<\/div>\n\n\n
Agriculture<\/a>, <\/span>Breakthroughs<\/a>, <\/span>Climate<\/a>, <\/span>Food Security<\/a>, <\/span>Leadership<\/a>, <\/span>Nebraska Impact<\/a>, <\/span>Patricio Grassini<\/a>, <\/span>Statistics<\/a><\/div>","protected":false},"excerpt":{"rendered":"

Accurate estimates of crop yield potential and gaps are key in planning how to meet growing food demand globally. Nebraska agronomists significantly contributed to an international study that demonstrates longstanding statistical methods are insufficient. <\/p>\n","protected":false},"author":1,"featured_media":219,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7],"tags":[16,182,50,22,181,177,149,66],"class_list":["post-28","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-research-impact","tag-agriculture","tag-breakthroughs","tag-climate","tag-food-security","tag-leadership","tag-nebraska-impact","tag-patricio-grassini","tag-statistics"],"_links":{"self":[{"href":"https:\/\/research.unl.edu\/annualreport\/2025\/wp-json\/wp\/v2\/posts\/28","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/research.unl.edu\/annualreport\/2025\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/research.unl.edu\/annualreport\/2025\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/research.unl.edu\/annualreport\/2025\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/research.unl.edu\/annualreport\/2025\/wp-json\/wp\/v2\/comments?post=28"}],"version-history":[{"count":8,"href":"https:\/\/research.unl.edu\/annualreport\/2025\/wp-json\/wp\/v2\/posts\/28\/revisions"}],"predecessor-version":[{"id":484,"href":"https:\/\/research.unl.edu\/annualreport\/2025\/wp-json\/wp\/v2\/posts\/28\/revisions\/484"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/research.unl.edu\/annualreport\/2025\/wp-json\/wp\/v2\/media\/219"}],"wp:attachment":[{"href":"https:\/\/research.unl.edu\/annualreport\/2025\/wp-json\/wp\/v2\/media?parent=28"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/research.unl.edu\/annualreport\/2025\/wp-json\/wp\/v2\/categories?post=28"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/research.unl.edu\/annualreport\/2025\/wp-json\/wp\/v2\/tags?post=28"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}