Comparing genetic coefficient estimation methods using the CERES-Maize model

Many crop simulation models use genetic coefficients to characterize variet ies or hybrids. Two methods now used with CERES-Maize to obtain genetic coe fficients are: (1) direct experimental measurement; and (2) estimation usin g the Genetic Coefficient Calculator (GENCALC), an iterative computerized p rocedure, The objective of this research was to compare all adaptation of t he Uniform Covering by Probabilistic Region (UCPR) method with these two ap proaches. UCPR delineates a joint confidence region for the parameters corr esponding to a goodness-of-fit threshold level. The study focuses on two ge netic coefficients, duration of the juvenile phase (P1) and photoperiod sen sitivity (P2), for five maize hybrids, Field experiments were conducted at Rossville, KS, during 1995 in which genetic coefficients of four of the hyb rids were determined. Silking date data for the same hybrids were obtained from the Kansas Corn Performance Tests for use in estimating coefficients w ith UCPR and GENCALC. UCPR was better than GENCALC at minimizing squared er ror but at the cost of much longer run times, Both estimation procedures un derestimated P1 relative to the field data. This may have resulted from the model's propensity to overestimate leaf number. An independent set of silk ing date data for B73 xMol7 From the Kansas Corn Performance Tests was used for comparing methods, Simulated silking dates using P1 and P2 values obta ined by UCPR and CENCALC accounted for only 26 and 47%, respectively, of th e variability in actual dates. Both underestimated longer durations to silk ing. Use of published values for P1 and P2 accounted for 45% of variability but underestimated all data (bias - 9.5 days). (C) 2000 Published by Elsev ier Science Ltd.