Predicting the Soluble Solids of Apples by Near Infrared Spectroscopy (I) - Multiple Linear Regression Models -

근적외선을 이용한 사과의 당도예측 (I) - 다중회귀모델 -

  • ;
  • W. R. Hruschka (U.S.A. USDA, ARS, NRI, Instrumentation & Sensing Laboratory) ;
  • J. A. Abbott (U.S.A. USDA, ARS, NRI, Instrumentation & Sensing Laboratory) ;
  • ;
  • B. S. Park (U.S.A. USDA, ARS, NRI, Instrumentation & Sensing Laboratory)
  • 이강진 (농촌진흥청 농업기계화연구소) ;
  • ;
  • ;
  • 노상하 (서울대학교 생물자원공학부 농업기계전공) ;
  • Published : 1998.12.01

Abstract

The MLR(Multiple Linear Regression) models to estimate soluble solids content non-destructively were presented to make a selection of optimal photosensor utilized to measure the soluble solids content of apples. Visible and NIR absorbance in the 400 to 2498 nanometer(nm) wavelength region, soluble solids content(sugar content), hardness, and weight were measured for 400 apples(gala). Spectrophotometer with fiber optic probe was utilized for spectrum measurement and digital refractometer was used for soluble solids content. Correlation between absorbance spectrum and soluble solids content was analyzed to pick out the optimal wavelengths and to develop corresponding prediction model by means of MLR. For the coefficient of determination($R^2$) to be over 0.92, the MLR models out of the original absorbance were built based on 7 wavelengths of 992, 904, 1096, 1032, 880, 824, 1048nm, and the ones of the second derivative absorbance based on 5 wavelengths of 784, 1056, 992, 808, 872nm. The best model of the second derivative absorbance spectrum had $R^2$=0.91, bias= -0.02bx, SEP=0.28bx for unknown samples.

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