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This article in AJ

  1. Vol. 104 No. 3, p. 600-611
     
    Received: Aug 25, 2011


    * Corresponding author(s): cgspedreira@usp.br
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doi:10.2134/agronj2011.0272

Predicting Growth of Panicum maximum: An Adaptation of the CROPGRO–Perennial Forage Model

  1. Márcio A.S. Laraa,
  2. Carlos G.S. Pedreira *b,
  3. Kenneth J. Bootec,
  4. Bruno C. Pedreirad,
  5. Leonardo S.B. Morenoe and
  6. Phillip D. Aldermanc
  1. a Dep. de Zootecnia, Federal Univ. of Lavras, Lavras, MG 37200-000, Brazil
    b Dep. de Zootecnia-ESALQ, Univ. of São Paulo, Piracicaba, SP 13418-900, Brazil
    c Dep. of Agronomy, Univ. of Florida, Gainesville, FL 32611
    d EMBRAPA Agrossilvipastoril, Sinop, MT 78550-003, Brazil
    e EMBRAPA Pesca e Aquicultura, Palmas, TO 77015-012, Brazil

Abstract

Warm-season grasses are economically important for cattle production in tropical regions and tools to aid in management and research on these forages would be highly beneficial both in research and the industry. This research was conducted to adapt the CROPGRO–Perennial Forage model to simulate growth of the tropical species guineagrass (Panicum maximum Jacq. cv. ‘Tanzânia’) and to describe model adaptation for this species. To develop the CROPGRO parameters for this species, we began with values and relationships reported in the literature. Some parameters and relationships were calibrated by comparison with observed growth, development, dry matter accumulation, and partitioning during a 17-mo experiment with Tanzânia guineagrass in Piracicaba, SP, Brazil. Compared with starting parameters for palisadegrass [Brachiaria brizantha (A. Rich.) Stapf. cv. ‘Xaraes’], dormancy effects of the perennial forage model had to be minimized, partitioning to storage tissue or root decreased, and partitioning to leaf and stem increased to provide for more leaf and stem growth and less root. Parameters affecting specific leaf area and senescence of plant tissues were improved. After these changes were made to the model, biomass accumulation was better simulated, mean predicted herbage yield was 6576 kg ha−1, averaged across 11 regrowth cycles of 35 (summer) or 63 d (winter), with a RMSE of 494 kg ha−1 (Willmott's index of agreement d = 0.985, simulated/observed ratio = 1.014). The model also gave good predictions against an independent data set, with similar RMSE, ratio, and d. The results of the adaptation suggest that the CROPGRO model is an efficient tool to integrate physiological aspects of guineagrass and can be used to simulate growth.

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