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ARS Home » Midwest Area » East Lansing, Michigan » Sugarbeet and Bean Research » Research » Publications at this Location » Publication #172391

Title: NONDESTRUCTIVE DETECTION OF FRUIT POSTHARVEST QUALITY

Author
item Lu, Renfu

Submitted to: Michigan State University Controlled Atmosphere Clinic
Publication Type: Experiment Station
Publication Acceptance Date: 8/8/2004
Publication Date: 8/13/2004
Citation: Lu, R. 2004. Nondestructive detection of fruit postharvest quality. Michigan State University Controlled Atmosphere Clinic. p. 14-19.

Interpretive Summary:

Technical Abstract: Currently apple fruit are sorted for color and size in most packinghouses, but sorting for appearance cannot guarantee the eating quality of individual fruit. There is a critical need for developing sensing technologies to sort and grade apple fruit based on internal quality attributes including firmness, soluble solids content (SSC), and acid. In our recent research, we proposed and investigated a new concept and technique for measuring apple fruit firmness and SSC, with the ultimate goal of developing a practical and cost effective technology for sorting and grading apples and other tree fruits for these quality attributes. Specifically, we used the hyperspectral and multispectral imaging technique to measure light scattering and absorption from individual fruit (apples and peaches) and then related them to fruit firmness and SSC. A hyperspectral imaging system was assembled and tested for measuring apple fruit firmness and SSC. A multispectral imaging prototype was designed and built for real time sensing of apple fruit quality. We also assembled and tested a compact multispectral imaging unit with a low cost digital camera. The hyperspectral imaging system was able to predict fruit firmness with the correlation coefficient of 0.85 for Golden Delicious and 0.72 for Red Delicious apples, and r=0.90 for Red Haven peaches. Good predictions of SSC were obtained for Golden Delicious apples (r=0.89). The compact multispectral imaging unit was able to predict fruit firmness with r=0.84 and 0.82 for Golden Delicious and Red Delicious apples, respectively. The multispectral imaging prototype could inspect individual apples at a speed up to 2 fruit/s. Several areas of improvement for the prototype were identified, which should lead to improved performance. The hyperspectral/multispectral imaging technique is useful for measuring fruit internal quality and will provide the industry with a means to deliver consistent, better quality fruit to the marketplace.