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United States Department of Agriculture

Agricultural Research Service

Title: Integration of Hyperspectral Reflectance and Fluorescence Imaging for Assessing Apple Maturity

Authors
item Noh, Hyun Kwon
item Peng, Yankun - MICHIGAN ST UNIVERSITY
item Lu, Renfu

Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: April 8, 2007
Publication Date: June 19, 2007
Citation: Noh, H., Peng, Y., Lu, R. 2007. Integration of Hyperspectral Reflectance and Fluorescence Imaging for Assessing Apple Maturity. Transactions of the ASABE. 50(3):963-971.

Interpretive Summary: The maturity of apples is an important indicator in determining harvest time, postharvest storage potential and handling procedure, and fruit quality. Maturity determination requires measuring multiple quality attributes of the fruit, including skin and flesh color, firmness, sugar, starch, acidity, etc. The maturity measurement methods currently used are largely destructive and prone to experimental error. Although different nondestructive methods have been researched for measuring apple maturity, they are only suitable for measuring one or two single maturity parameters. Reflectance and fluorescence are two promising techniques for measuring fruit quality, and they are based on different principles and hence can be complementary with each other. This research was aimed to develop a nondestructive sensing technique integrating reflectance and fluorescence for better measurement of apple maturity. A hyperspectral imaging system was used to measure both reflectance and fluorescence scattering images from freshly harvested ‘Golden Delicious’ apples. Standard destructive measurements were performed to evaluate individual maturity parameters. Mathematical models using reflectance or fluorescence data and their combined data were developed to predict maturity parameters. Results showed that hyperspectral reflectance had better measurement of fruit maturity in comparison with hyperspectral fluorescence. Integration of reflectance and fluorescence led to improved predictions of maturity parameters over either reflectance or fluorescence; the improvements were noticed for all maturity parameters as measured by the correlation coefficient (up to 11%) or standard error (up to 14%). The integrated sensing technique provides a better means for evaluating apple maturity and is potentially useful for measuring the maturity of apple fruit in the orchard. The technique can help the fruit growers and packers in better managing harvest time and postharvest storage operations.

Technical Abstract: Fluorescence and reflectance are two different forms of light interaction with matter, and they can be complementary in measuring fruit quality and condition. The objective of this research was to develop an integrated hyperspectral reflectance and fluorescence imaging technique for measuring apple maturity. Both fluorescence and reflectance scattering images were acquired using a hyperspectral imaging system covering the wavelengths of 500-1000 nm from 'Golden Delicious' apples harvested over a 4-week period. Standard destructive tests were performed to measure multiple maturity parameters (flesh and skin color, firmness, soluble solids, starch, and titratable acid). The spectral fluorescence and reflectance scattering profiles were described by a two-parameter Lorentzian function. Multi-linear regression prediction models were developed relating Lorentzian parameters to individual maturity parameters for each sensing mode and their combined data. The reflectance prediction models had consistently better correlations with individual maturity parameters than did the fluorescence models. The integration of reflectance and fluorescence improved maturity measurements over either reflectance or fluorescence; the improvements in correlation were noticeable for most parameters (up to 11% for titratable acid). Since fluorescence and reflectance measurements were performed with the same imaging system, the integrated technique can provide better assessment of apple fruit maturity and quality.

Last Modified: 12/26/2014
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