American Potato Journal

, Volume 55, Issue 8, pp 431–436 | Cite as

Prediction of potato yield using temperature and insolation data

  • T. K. Hartz
  • F. D. Moore


A linear polynomial model is presented
$$Y = \beta _0 + \beta _1 X_1 + \beta _2 X_2 + \beta _3 X_3 + \xi $$
where Y = plant yield of tubers > 1 cm diameter, X1 = revised growing degree days
$$\begin{gathered} RGDD = \frac{{max temp \left( { \leqslant 30^ \circ C} \right) + \min temp \left( { \geqslant 4.4^ \circ C} \right)}}{2} - 4.4^ \circ C \hfill \\ - \frac{{min temp \left( { > 4.4^ \circ C} \right) - 4.4^ \circ C}}{2} \hfill \\ \end{gathered} $$
X2 = total insolation in cal cm-2 at 350 to 1150 nm and X3 = mean daily air temperature range in °C. The β0 and ξ, (Y intercept and error term) and β1, β2 and β3 coefficients are derived from fitting the experimental data.

The model was developed by growing ‘Kennebec’ in large containers at sites ranging from 1533 m to 3198 m elevation under shaded (48% insolation reduction) and unshaded conditions at 39° to 41° N latitude. Mean maximum and minimum temperatures and insolation ranged from 29°C to 19°C, 14°C to 6°C, and 200 cal cm−2 day−1 to 530 cal cm2 day−1 respectively. Soil matric potential and soil fertility were not included as variables in the model since they were physically controlled. The model does not include the period from planting to emergence since environment was not permitted to vary differentially. A highly significant multiple linear model with a coefficient of determination of 0.93 was obtained.

It is suggested that including the revision
$$ - \frac{{min temp \left( { > 4.4^ \circ C} \right) - 4.4^ \circ C}}{2}$$
in the heat input estimation (GDD) as well as air temperature range, emphasizes the influence of respiration on productivity. The model should be tested further and adapted as a practical method for predicting potato yield under “grower” conditions.

Key Words

Kennebec model shade growing degree day enironmental parameters elevation altitude latitude stepwise regression multiple linear regression 


Se présenta un modelo linear polinomial
$$Y = \beta _0 + \beta _1 X_1 + \beta _2 X_2 + \beta _3 X_3 + \xi $$
donde Y = rendimiento de tubérculos > 1 cm de diámetro, X1 = grados días de crecimiento revisado.
$$\begin{gathered} RGDD = \frac{{max temp \left( { \leqslant 30^ \circ C} \right) + \min temp \left( { \geqslant 4.4^ \circ C} \right)}}{2} - 4.4^ \circ C \hfill \\ - \frac{{min temp \left( { > 4.4^ \circ C} \right) - 4.4^ \circ C}}{2} \hfill \\ \end{gathered} $$
X2 = insolación total en cal cm−2 a 350 a 1150 nm y X3 = promedio diario de rango de temperatura del aire en °C. Los términos β0 y ξ (intercepción de Y y el término de error) y los coeficientes β1, β2, y β3 son derivados después de ajustar los datos expérimentales.

El modelo se desarrolló cultivando “Kennebec” en depósitos grandes en un rango de lugares desde 1533 m hasta 3198 m de elevación bajo sombra (48% de reducción de insolación) y sin sombra a 39–41° de latitud Norte. El promedio máximo y mínimo de temperatura e insolación varió desde 29°C a 19°C, 14°C a 6°C, y 200 cal cm−2 día−1 a 530 cal cm−2 día{−1}, respectivamente.

El potencial de la matriz del suelo y la fertilidad del suelo no fueron incluídos como variables en el modelo ya que fueron controlados físicamente. El modelo no incluye el período desde la plantación a la emergencia, ya que no se permitió variar el ambiente diferencialmente.

Se obtuvo un modelo linear múltiple altamente significante, con un coeficiente de determinatión de 0.93.

Se sugiere que incluyendo la recisión
$$ - \frac{{min temp \left( { > 4.4^ \circ C} \right) - 4.4^ \circ C}}{2}$$
en la estimación de la entrada de calor (GDD) tanto como el rango de la temperatura del aire, enfatiza la influencia de la respiración en la productividad. El modelo debe ser probado mucho más y adoptado como un método práctico para predecir el rendimiento de la papa bajo las condiciones del agricultor.


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Copyright information

© Springer 1978

Authors and Affiliations

  • T. K. Hartz
    • 1
  • F. D. Moore
    • 2
  1. 1.GRA, Dept. of HorticultureVirginia Polytechnic InstituteBlacksburg
  2. 2.Colorado State UniversityFort Collins

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