|Peng, Yankun - MICHIGAN ST UNIVERSITY|
Submitted to: Journal of Food Engineering
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: December 4, 2006
Publication Date: February 18, 2007
Citation: Peng, Y., Lu, R. 2007. Prediction of apple fruit firmness and soluble solids content using characteristics of multispectral scattering images. Journal of Food Engineering. 82(2):142-152. Interpretive Summary: Firmness is an important textural property for apples, whereas soluble solids content is a main flavor component. They are key parameters in determining the maturity and postharvest quality of apple fruit. A multispectral scattering technique was recently developed in our laboratory for nondestructive assessment of fruit firmness and soluble solids content, which is based on measuring light scattering characteristics in the fruit at multiple wavelengths or wavebands. This paper reports on the further development of improved methods for processing and analyzing multispectral scattering images for predicting fruit firmness and soluble solids content. A new mathematical function was used for describing the scattering characteristics of apples. A scattering image calibration procedure was proposed to correct the effect of light source variation on the scattering images. Results demonstrated that the new mathematical function was more effective than the function used previously for describing the scattering characteristics of apples. This new function gave good prediction of the fruit firmness and soluble solids content of Golden Delicious apples with the correlation coefficient of 0.896 and 0.816, respectively. The new function and calibration procedure will help to design and build a better multispectral imaging system for rapid, real time measurement of fruit firmness and soluble solids content. The multispectral scattering technique will provide an effective means for sorting and grading fruit to ensure their quality and consistency.
Technical Abstract: Multispectral scattering is a promising technique for nondestructive sensing of multiple quality attributes of apple fruit. This research developed new, improved methods for processing and analyzing multispectral scattering profiles in order to design and build a better multispectral imaging system for real-time measurement of apple fruit firmness and soluble solids content. Spectral scattering images were obtained from Golden Delicious apples at four selected wavebands (680, 800, 900 and 950 nm) using a common-aperture multispectral imaging system. The scattering intensity and distance were corrected by incorporating the effect of individual apples’ size. A new method of correcting scattering image profiles was proposed to minimize the effect of light source variation on the calculation of scattering function parameters. Modified Gompertz and Lorentzian functions with four parameters and their variants were evaluated and compared for predicting fruit firmness and soluble solids content using multi-linear regression and cross-validation methods. The modified Gompertz function had better prediction results with a correlation coefficient (r) of 0.896 and a standard error of prediction (SEP) of 6.50 N for firmness, and r = 0.816 and SEP = 0.92% for soluble solids content. This new function, coupled with the scattering profile correction methods, improved the multispectral scattering technique for measuring fruit quality.