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ARS Home » Midwest Area » East Lansing, Michigan » Sugarbeet and Bean Research » Research » Publications at this Location » Publication #166946
Title: MULTISPECTRAL SCATTERING FOR ASSESSING PEACH FIRMNESS

Author
item Lu, Renfu
item PENG, YANKUN - FAS

Submitted to: Agricultural Engineering International Conference
Publication Type: Proceedings
Publication Acceptance Date: 8/15/2004
Publication Date: 10/11/2004
Citation: Lu, R., Peng, Y. 2004. Multispectral scattering for assessing peach firmness. Agricultural Engineering International Conference Proceedings.

Interpretive Summary: Currently peaches are sorted and graded for color and size or weight in the packinghouse before they are delivered to the marketplace. This postharvest operation, however, cannot guarantee the eating quality of individual peach fruit. Firmness is an important quality attribute for peach fruit, and it is routinely measured with destructive methods. This research investigated a nondestructive optical technique for predicting fruit firmness from intact peaches. A multispectral imaging technique, which acquires spectral images for multiple wavelengths, was used for measuring light scattering from peaches in the visible and near-infrared (nonvisible) region. Mathematical models were developed on relating light scattering features to fruit firmness. Our research showed good correlation between optical measurements and standard destructive firmness measurements with the correlation coefficient of 0.87. The technique is nondestructive, fast and easy to implement, and therefore is promising for sorting and grading peach fruit for firmness. This would enable the fruit industry to deliver high quality fruit to the marketplace and improve consumer satisfaction and acceptance, leading to increased profitability for the industry.

Technical Abstract: The objective of this research was to investigate a multispectral scattering technique for measuring peach fruit firmness. A multispectral imaging system, which is capable of acquiring four spectral scattering images simultaneously, was used to measure spectral scattering from 'Red Haven' peaches for wavelengths of 680, 880, 905, and 940 nm. Soft peaches had broader scattering profiles than firmer ones, which was most pronounced at the wavelength of 680 nm that is related to chlorophyll absorption. A Lorentzian distribution function with three parameters was found to fit scattering profiles for all four wavelengths accurately with the mean coefficient of determination (r2) equal to or greater than 0.998. A multi-linear regression model relating Lorentzian parameters to fruit firmness was developed from the training samples and validated with an independent set of samples. The model was able to predict peach firmness with r=0.87 and the standard error for validation of 14.57 N. A minimum of two wavelengths including 680 nm was required for improved firmness prediction. The multispectral scattering technique is nondestructive, fast and easy to implement, and it can provide a nondestructive means for measuring peach fruit firmness.