Skip to main content
ARS Home » Midwest Area » East Lansing, Michigan » Sugarbeet and Bean Research » Research » Publications at this Location » Publication #196032
Title: NEW APPROACHES OF ANALYZING MULTISPECTRAL SCATTERING PROFILES FOR PREDICTING APPLE FRUIT FIRMNESS AND SOLUBLE SOLIDS CONTENT

Author
item PENG, YANKUN - MICHIGAN ST UNIVERSITY
item Lu, Renfu

Submitted to: ASABE Annual International Meeting
Publication Type: Proceedings
Publication Acceptance Date: 5/13/2006
Publication Date: 7/9/2006
Citation: Peng, Y., Lu, R. 2006. New approaches of analyzing multispectral scattering profiles for predicting apple fruit firmness and soluble solids content. ASABE Annual International Meeting. Paper No. 066234.

Interpretive Summary: Firmness and soluble solids content are two important quality parameters in inspecting and grading apple fruit. While destructive methods are still routinely used for measuring apple fruit, there is a growing need for nondestructive sorting and grading of individual fruit to meet the increasing demand from the consumer for better and more consistent fruit. Technology for sorting and grading of apples for soluble solids content is recently available; however, firmness sorting is still a challenge. A new technique based on measuring light scattering in apple fruit at selected wavelengths was developed recently in our laboratory for assessing fruit firmness and soluble solids content. The technique requires accurate measurement and mathematical modeling of spectral scattering profiles to achieve good firmness measurement. This research was performed on improving the multispectral scattering imaging system developed in our laboratory by proposing a new function for describing the scattering profiles, determining a set of optimum function parameters, and incorporating individual fruit’s size for better description of light scattering. The new mathematical function performed better than the function used in previous studies. The four-waveband multispectral imaging system coupled with the new function achieved a correlation of 0.896 for firmness and 0.816 for soluble solids content against standard destructive methods. This research demonstrated that using four wavelengths and appropriate scattering profile parameters can achieve better assessment of apple fruit firmness and soluble solids content. The technique is promising for online sorting and grading of apples for firmness and soluble solids content.

Technical Abstract: The objective of this research was to improve the multispectral imaging system developed in our earlier studies and light scattering profile analysis methods for designing and building a better real-time apple quality inspection system. Spectral scattering images were obtained from ‘Golden Delicious’ apples at four selected wavelengths using a common-aperture multispectral imaging system. The scattering intensity and distance were corrected for individual apples’ size. Gompertz and Lorentzian functions were compared in describing the corrected scattering profiles for fruit firmness and soluble solids content (SSC) prediction. Firmness and SSC prediction models were developed using multi-linear regression against the scattering profile parameters. A cross-validation method was used to determine the best set of function parameters for the firmness and SSC prediction models. Better prediction results were obtained for the Gompertz function 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 SSC.