Submitted to: ASAE Annual International Meeting
Publication Type: Proceedings
Publication Acceptance Date: 5/16/2005
Publication Date: 7/17/2005
Citation: Peng, Y., Lu, R. 2005. An improved multispectral imaging system for apple fruit firmness prediction. ASAE Annual International Meeting. Paper No. 056172.
Interpretive Summary: Firmness is an important internal quality attribute of fruits. Currently, the techniques for measuring fruit firmness are destructive, and they cannot be used for grading or sorting fruit to ensure consistent product quality for the consumer. In this study, a nondestructive technique was developed for apple fruit firmness prediction. The technique was based on measuring light scattering images from apple fruit at selected wavelengths in the visible and near-infrared (longer than the visible) spectrum. We found that there was a close relationship between the firmness of apples and light scattering. Thus, apple fruit firmness could be predicted from the scattering images taken from apples. We proposed two methods to improve the processing of signals in the scattering images and minimize the effect of apple size/shape on light scattering measurements. These correction methods resulted in 23% improvements in the firmness prediction precision for Red Delicious apples and 25% for Golden Delicious apples. The improved multispectral imaging system makes it feasible to measure and grade apple fruit firmness. The sensing technique will allow the fruit industry to deliver superior, consistent apples to the marketplace and assure consumer acceptance and satisfaction. The technique is also promising for measuring the firmness of other horticultural products.
Technical Abstract: Firmness is an important internal quality attribute of fruits. Nondestructive measurement of fruit firmness will help the industry provide better fruit for the consumer. The objective of this research was to improve the multispectral imaging system used in our previous studies and refine scattering analysis methods for more effectively measuring apple fruit firmness. An improved multispectral imaging system equipped with a light intensity controller was used to measure light scattering from Red Delicious apples at seven wavelengths and Golden Delicious apples at eight wavelengths. A filtering method was applied to reduce noise signals in scattering images during radial averaging of image pixels. Apple size/shape affected scattering intensity and distance, and two methods were proposed for correcting their effect. Firmness prediction models were developed by multi-linear regression against Lorentzian parameters. The improved system yielded better firmness predictions with the correlation (r) of 0.898 and the standard error of validation (SEV) of 6.41 N for Red Delicious and r = 0.897 and SEV = 6.14 N for Golden Delicious.