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United States Department of Agriculture

Agricultural Research Service

Research Project: TECHNOLOGIES FOR ASSESSING AND GRADING QUALITY AND CONDITION OF CUCUMBERS AND TREE FRUITS

Location: Sugarbeet and Bean Research

Title: A Lctf Based Multispectral Imaging System for Estimation of Apple Fruit Firmness: Part Ii: Selection of Optimal Wavelengths and Development of Prediction Models

Authors
item Peng, Yankun - MICHIGAN ST UNIVERSITY
item Lu, Renfu

Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: November 16, 2005
Publication Date: February 22, 2006
Citation: Peng, Y., Lu, R. 2006. A LCTF based multispectral imaging system for estimation of apple fruit firmness: Part II: selection of optimal wavelengths and development of prediction models. Transactions of the ASABE. 49(1):269-275.

Interpretive Summary: Firmness is an important quality attribute for apples and other fruits. A nondestructive measurement technique will be valuable for measuring, monitoring, and sorting apple fruit so that high quality, consistent fresh products can be delivered to the marketplace. Our recent research demonstrated that light scattering at multiple wavelengths is useful for measuring fruit firmness and selection of appropriate wavelengths is critical for meeting firmness measurement requirements. This research developed a multispectral imaging system for acquiring light scattering from apple fruit at any wavelength over the visible and near-infrared (longer than the visible) region. The multispectral imaging technique was compared with conventional near-infrared spectroscopy (NIRS) for measuring fruit firmness. Optimal wavelengths were determined for each apple cultivar. With these wavelengths, the system was able to predict fruit firmness with r=0.82 and 0.81 for Red Delicious and Golden Delicious, respectively, which were significantly better than the results obtained with NIRS. The research findings provide researchers and instrumentation engineers with critical information on selecting appropriate wavelengths for developing an offline or online multispectral imaging sensor or sensing system when light scattering or other optical principles are used. The research also demonstrated that a cost effective sensing system can be developed, which will be valuable for laboratory and field measurement of apples and other fruits.

Technical Abstract: Firmness of apple fruit is an important quality attribute, which varies in the same lot of fruit due to inherent biological variability, climatic condition, cultural practice, harvest time or maturity level, and postharvest handling and storage. This paper reports on using modified Lorentzian distribution (MLD) parameters of light scattering images, which were acquired by a compact multispectral imaging system over wavelengths between 650 nm and 1,000 nm, to predict apple fruit firmness. Optimal wavelengths for firmness prediction were determined with multi-linear regression and cross-validation. For Red Delicious, seven wavelengths (690, 770, 790, 810, 920, 980, and 1000 nm) were optimal, whereas for Golden Delicious, eight wavelengths (650, 690, 740, 750, 820, 880, 910, and 990 nm) were needed. The prediction models established based on the optimal wavelengths gave good firmness predictions with the correlation coefficient (r) of 0.82 and the standard error of validation (SEV) of 6.64 N for Red Delicious apples, and r = 0.81 and SEV = 6.58 N for Golden Delicious apples. These results were considerably better than those obtained with visible/near-infrared spectroscopy. The multispectral scattering imaging technique is potentially useful for sorting and grading apples and other fruits for firmness.

Last Modified: 9/10/2014
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