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Agronomy Journal Abstract - Potato

Approaches to Modeling Potato Leaf Appearance Rate


This article in AJ

  1. Vol. 98 No. 3, p. 522-528
    Received: May 9, 2005

    * Corresponding author(s): dfleishe@asrr.arsusda.gov
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  1. David H. Fleisher *a,
  2. Rose M. Shillitob,
  3. Dennis J. Timlina,
  4. Soo-Hyung Kima and
  5. Vangimalla R. Reddya
  1. a USDA-ARS Crop Systems and Global Change Lab., 10300 Baltimore Ave., Beltsville, MD 20705
    b Dep. of Natural Resources and Landscape Architecture, Univ. of Maryland, College Park, MD 20742


Two approaches quantifying potato (Solanum tuberosum L. cv. Kennebec) leaf appearance rates were evaluated: a thermal time approach using the phyllochron, and a nonlinear temperature response approach using a modified β distribution function. Leaf appearance measurements at six temperature treatments (14/10, 17/12, 20/15, 23/18, 28/23, and 34/29°C thermoperiods with a 16/8 h cycle) were obtained from three SPAR (soil–plant–atmosphere–research) chamber experiments at 450 (D0), 370 (D1), or 740 (D2) μmol mol−1 atmospheric CO2 concentration. Independent data from a field study and the literature were obtained. The [CO2] effects on leaf appearance rate were not significant (P ≤ 0.05). Leaf appearance rate increased from 12 to 27.2°C and declined with increasing temperature for all SPAR data except D2. Data from D0 and D1 were pooled to estimate model parameters. Phyllochrons of 28.2 and 24.3°C-d leaf−1 (4°C base temperature) were obtained with all temperature treatments and without the 34/29°C treatment, respectively. Parameters for the modified β distribution function were 39.5°C for the ceiling temperature, 27.2°C for the optimum temperature at which the leaf appearance rate is maximum, and 0.96 leaves plant−1 d−1 for the maximum leaf appearance rate. Both approaches were comparable with values reported in the literature and were suitable for simulating leaf appearance in the field study (root mean square deviations of 3.2 and 2.6 leaves for thermal time and response function, respectively). The temperature function approach has advantages in that nonlinear relationships, particularly those at warmer temperatures, can be included in a single equation with biologically meaningful parameters.

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