Technologies for Quality Assessment of Fruits and Vegetables
Sugarbeet and Bean Research
2010 Annual Report
1a.Objectives (from AD-416)
1) Develop a spectral imaging system for assessing and grading quality of pickling vegetables;.
2)Develop a prototype optical instrument for measuring the optical properties of horticultural and food products.
1b.Approach (from AD-416)
Hyperspectral imaging technique in reflectance and transmittance modes will be used for assessing both internal and external quality characteristics of pickling cucumbers and pickles. Algorithms will be developed for sorting and grading these products for quality and defect. Effective wavebands will be identified for efficient detection of product internal defect. Further, light source configuration will be investigated for more efficient assessment of internal quality attributes and defect. Moreover, a computer program will be developed for acquiring and processing spectral scattering profiles from fruit and other foods to determine their spectral absorption and scattering properties. Optimization of the instrument design will be conducted to improve the acquisition of spectral scattering images from fruit samples. Integration of the program into the prototype optical property analyzing instrument will be performed so that the prototoype can automatically acquire and process scattering image data and determine the optical properties.
Research in FY10 has been focused on design, assembling and testing of a laboratory optical property measuring prototype for automatic acquisition, processing, and analyzing spatially-resolve diffuse reflectance from fruit and food products to extract the optical absorption and scattering properties. Hardware improvements in light source design, imaging device calibration, and system integration were made to ensure the optical designs were optimized for accurate measurement of spatially-resolved diffuse reflectance data. Computer programs were developed for controlling the instrument, acquiring diffuse reflectance data, and automatically extracting the optical property information for the wavelengths of 500-1,000 nm. Instrumental calibrations were performed against reference samples with known optical properties. In addition, optimization of algorithms was performed to improve the accuracy of the diffusion model for determining the absorption and scattering properties. Extensive testing of the prototype against three reference methods was done to evaluate its performance. Results showed that the prototype achieved measurement accuracies that are either equal to or superior to other reported studies using more sophisticated instrumentation or different designs.
Furthermore, laser scattering images acquired for fresh pickling cucumbers before and after internal damage was induced by mechanical stress were analyzed. Different image analysis methods were applied to the laser scattering images for segregating defective cucumbers from normal cucumbers. The effect of laser incident angle with respect to the imaging device was examined. Results showed that laser scattering image analysis had great potential for internal defect detection. The best classification accuracy of 96% was achieved when the laser was positioned at 0 degree incident angle relative to the optical axis under transmittance mode. The ability to detect internal defect decreased as the incident angle increased. Further study on this technique with more cucumber samples is needed and other image processing algorithms for laser scattering classification of defective cucumbers should be investigated. Project progress was monitored via meetings, emails, and joint sessions on planning, execution, and analysis of research with the collaborating researchers.