Cerón-Rojas, J. JesusGowda, ManjeToledo, FernandoBeyene, YosephBentley, Alison R.Crespo-Herrera, LeoGardner, KeithCrossa, Jose2025-06-112025-06-110011-183XORCID:/0000-0001-5519-4357/work/171153623http://www.scopus.com/inward/record.url?scp=85146313748&partnerID=8YFLogxKhttps://hdl.handle.net/1885/733759335The profit function (net returns minus costs) allows breeders to derive trait economic weights to predict the net genetic merit (H) using the linear phenotypic selection index (LPSI). Economic weight is the increase in profit achieved by improving a particular trait by one unit and should reflect the market situation and not only preferences or arbitrary values. In maize (Zea mays L.) and wheat (Triticum aestivum) breeding programs, only grain yield has a specific market price, which makes application of a profit function difficult. Assuming the traits’ phenotypic values have multivariate normal distribution, we used the market price of grain yield and its conditional expectation given all the traits of interest to construct a profit function and derive trait economic weights in maize and wheat breeding. Using simulated and real maize and wheat datasets, we validated the profit function by comparing its results with the results obtained from a set of economic weights from the literature. The criteria to validate the function were the estimated values of the LPSI selection response and the correlation between LPSI and H. For our approach, the maize and wheat selection responses were 1,567.13 and 1,291.5, whereas the correlations were.87 and.85, respectively. For the other economic weights, the selection responses were 0.79 and 2.67, whereas the correlations were.58 and.82, respectively. The simulated dataset results were similar. Thus, the profit function is a good option to assign economic weights in plant breeding.Open Access fees were received from the Bill & Melinda Gates Foundation. We acknowledge the financial support provided by the Bill & Melinda Gates Foundation (INV‐003439 BMGF/FCDO Accelerating Genetic Gains in Maize and Wheat for Improved Livelihoods, AGG) as well as USAID projects (Amend. No. 9 MTO 069033, USAID‐CIMMYT Wheat/AGGMW, AGG‐Maize Supplementary Project, AGG, Stress Tolerant Maize for Africa) generated the CIMMYT data analyzed in this study. We are also thankful for the financial support provided by the Foundation for Research Levy on Agricultural Products (FFL) and the Agricultural Agreement Research Fund (JA) through the Research Council of Norway for Grants 301835 (Sustainable Management of Rust Diseases in Wheat) and 320090 (Phenotyping for Healthier and more Productive Wheat Crops) We thank all CIMMYT scientists, field workers, and lab assistants who collected the real data used in this study. We very much appreciate the fruitful exchange of ideas with Prof. Dr. Agustin Blasco, a source of scientific inspiration. We appreciate the efficient assistance from the associate and technical editors, and the valuable opinions of two anonymous reviewers that enrich the discussion on the value and limitations of selection indices based solely on profitability. Open Access fees were received from the Bill & Melinda Gates Foundation. We acknowledge the financial support provided by the Bill & Melinda Gates Foundation (INV-003439 BMGF/FCDO Accelerating Genetic Gains in Maize and Wheat for Improved Livelihoods, AGG) as well as USAID projects (Amend. No. 9 MTO 069033, USAID-CIMMYT Wheat/AGGMW, AGG-Maize Supplementary Project, AGG, Stress Tolerant Maize for Africa) generated the CIMMYT data analyzed in this study. We are also thankful for the financial support provided by the Foundation for Research Levy on Agricultural Products (FFL) and the Agricultural Agreement Research Fund (JA) through the Research Council of Norway for Grants 301835 (Sustainable Management of Rust Diseases in Wheat) and 320090 (Phenotyping for Healthier and more Productive Wheat Crops)13enPublisher Copyright: © 2022 International Maize and Wheat Improvement Center (CIMMYT). Crop Science published by Wiley Periodicals LLC on behalf of Crop Science Society of America.2023-03-0110.1002/csc2.2088285146313748