Prediction of Stem Diameter Variations Based on Principal Component Regression
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    Abstract:

    Among the various factors affecting the variation of plant stem diameter, meteorological conditions and soil water content are very important ones,besides natural growth. Soil water content together with four main meteorological parameters in greenhouse, including air temperature, relative humidity, pressure and photosynthetically active radiation, were selected for observing with four sunflower samples and two tomato samples at late stage of growth. Using part of the data measured from one sunflower sample, the principal component analysis was performed to set up a regression model. Data from sunflower samples and tomato samples were input to the model to predict the stem diameter variations of the sunflower samples and tomato samples and compared with the observed stem diameter variations. Comparison results showed that the regression model had a good prediction for the dynamics of stem diameter variations in sunflowers and tomatoes at late growth stage. The coefficients of determination in correlation analysis were above 0.6 and reached 0.649~0.782, while the root mean square errors were 0.029~0.143.

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History
  • Received:March 03,2014
  • Revised:
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  • Online: January 10,2015
  • Published: January 10,2015