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This article in AJ

  1. Vol. 88 No. 3, p. 416-422
    Received: Dec 28, 1994

    * Corresponding author(s): jwhite@cimmyt.mx
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Simulating Effects of Genes for Physiological Traits in a Process-Oriented Crop Model

  1. Jeffrey W. White  and
  2. Gerrit Hoogenboom
  1. I nt. Maize and Wheat Improvement Ctr.(CIMMYT), Lisboa 27, Apdo. Postal 6-641, 06600 Mexico, D.F., Mexico
    D ep. of Biological and Agricultural Engineering, Univ. of Georgia, Georgia Stn., Griffin, GA 30223



Recent improvements in crop simulation techniques and in understanding of crop genetics suggest the possibility of integrating genetic information on physiological traits into crop simulation models. By using known genotypes, rather than empirically fitted cultivar-specific coefficients, a simulation model should permit more explicit testing of hypotheses concerning the genetic basis of adaptation of cultivars to different environments or production systems. This paper describes and evaluates GeneGro, a version of the dry bean (Phaseolus vulgaris L.) crop simulation model BEANGRO version 1.01 modified to incorporate effects of seven genes affecting phenology, growth habit, and seed size: Ppd, Hr, Fin, Fd, and Ssz-l, and two more genes for seed size inferred from indirect evidence. Thirty cultivars were calibrated for BEANGRO using data from 14 trials conducted in Colombia, Guatemala, Mexico, and Florida. The resulting cultivar-specific coefficients of BEANGRO were replaced with information on specific genotypes of cultivars to create the gene-based model. With cultivar differences specified only by the seven genes, GeneGroe xplained 31%o f observedv ariation for seed yield, 58% for seed weight, 84% for days to flowering, 85% for days to maturity, 52%f or maximum leaf area index, and 36%f or canopy dry weight at maturity, but 0% for harvest index. In testing the effectiveness of GeneGra of ter overall trial and cultivar effects were accounted for through regression analysis, all simulated data except for seed weight showed significant relations with observed data (P ≤ 0.01). Our results indicate that for certain traits surprisingly few genes must be characterized to simulate cultivar differences as accurately as with the BEANGRO model. Furthermore, they suggest a potential for developing models similar to GeneGro for studying the effects of genes on adaptation in other crops.

Contribution of CIAT, Cali, Colombia.

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