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This article in CS

  1. Vol. 36 No. 6, p. 1606-1614
     
    Received: May 26, 1995


    * Corresponding author(s): e_piper@ops1.agric.za
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doi:10.2135/cropsci1996.0011183X003600060033x

Comparison of Two Phenology Models for Predicting Flowering and Maturity Date of Soybean

  1. Ernest L. Piper ,
  2. Kenneth J. Boote,
  3. James W. Jones and
  4. Sadi S. Grimm
  1. G rain Crops Inst., Private Bag X1251, Potchefstroom, 2520 Republic of South Africa
    D ep. of Agronomy, 304 Newell Hall, Univ. of Florida, Gainesville, FL 32611
    D ep. of Agricultural Engineering, 110 Roger Hall, Univ. of Florida, Gaineville, FL 32611
    E PAGRI/SC - Empresa de Pesquisa Agropecuaria e Difusao de Tecnologia de Santa Catarine S.A., Caixa Postal 502, 88001 Florianopolis, SC, Brazil

Abstract

Abstract

Unbiased prediction of plant growth stages is essential for accurate simulation of stage-specific responses to environmental factors. The phenology model in SOYGRO V5.42 was compared with the phenology model in CROPGRO V3.0 for prediction of flowering and maturity date. Data came from 17 sources in North America and covered a wide range of maturity groups. An additional large-scale data set from the U.S. Soybean Uniform Tests was used to evaluate predictions of maturity date. Parameters of the phenology models were estimated with an optimization procedure in which the downhill simplex method determined the direction of the search. While the optimization procedure was valuable to estimate the parameters, additional criteria were required to obtain realistic values. Based on the root mean square error (RMSE) criterion between predicted and observed dates, SOYGRO and CROPGRO predicted flowering equally well. Development rate after flowering was underpredicted by SOYGRO in cool environments so that in some years, maturity was predicted very late. CROPGRO has a separate temperature function after beginning seedfill, which decreased the RMSE for prediction of maturity date compared with SOYGRO, especially for early maturity cultivars. Allowing the critical short day length to increase after flowering date in the CROPGRO model consistently decreased the RMSE for prediction of beginning seedfill and maturity. CROPGRO was superior to SOYGRO for prediction of maturity date.

Florida Exp. Stn. no. R-04523.

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