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United States Department of Agriculture

Agricultural Research Service

Research Project: TECHNOLOGIES FOR ASSESSING AND GRADING QUALITY AND CONDITION OF CUCUMBERS AND TREE FRUITS

Location: Sugarbeet and Bean Research

Title: Characterization of Spatially-Resolved Hyperspectral Scattering Images for Assessing Apple Fruit Firmness

Authors
item Peng, Yankun - CHINA AGR UNIV - BEIJING
item Lu, Renfu

Submitted to: ASABE Annual International Meeting
Publication Type: Proceedings
Publication Acceptance Date: April 21, 2007
Publication Date: June 17, 2007
Citation: Peng, Y., Lu, R. 2007. Characterization of Spatially-Resolved Hyperspectral Scattering Images for Assessing Apple Fruit Firmness. ASABE Annual International Meeting. Paper No. 076270.

Technical Abstract: This research evaluated and compared different mathematical models for describing the hyperspectral scattering profiles over the spectral region between 450 nm and 1000 nm in order to select an optimal model for predicting fruit firmness of Golden Delicious apples. Four modified Lorentzian distribution functions of various forms were proposed to fit the spectral scattering profiles at individual wavelengths with the average correlation coefficient (r) greater than 0.995. Mathematical equations were derived to correct the spectral scattering intensity and distance by taking into account the individual apples’ size. The four modified Lorentzian distribution functions were compared for predicting fruit firmness using multi-linear regression and cross-validation methods. The modified Lorentzian function with three parameters (representing scattering peak value, width and slope) had better firmness predictions over the other functions with r = 0.893 and the standard error of prediction (SEP) of 6.14 N. Twenty-one wavelengths were needed to obtain the best predictions. This new function, coupled with the scattering profile correction methods, improved the hyperspectral scattering technique for measuring fruit quality.

Last Modified: 7/30/2014
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