Application of hue spectra fingerprinting during cold storage and shelf-life of packaged sweet cherry
Journal of Food Measurement and Characterization(2020)
摘要
Presented work investigated the application of a new color analysis technique in post-harvest life of sweet cherry ( Prunus avium L. ‘Hudson’). The hue spectra fingerprinting creates a histogram of image colors by summarizing the saturation. The advantage of this calculation method is that vivid colors make peaks while neutral background color is eliminated without object segmentation. Partial Least Squares (PLS) regression was used to estimate reference parameters during 9 d cold storage at 10 ± 0.5 °C (RH = 90 ± 1%) and following 2 d shelf-life at 20 ± 0.5 °C. The reference parameters of respiration, weight loss, fruit firmness and total soluble solid (TSS) content were measured. Samples were split into seven groups according to the number of perforations of polypropylene film and fructose concentration of moisture absorber. It was observed that parameters TSS and fruit firmness were the most sensitive to the length of storage. Weight loss was affected significantly by packaging. All reference parameters were estimated by PLS model with R 2 > 0.917, but weight loss and respiration obtained high estimation error of RMSE% = 48.02% and 11.76%, respectively. TSS and fruit firmness prediction were successful with RMSE% = 0.84% and 1.85%, respectively. Desiccation and color change of peduncle became visible in the green range of hue spectra. Color change of red fruit was observed with decreasing saturation in the red range of hue spectra. Our findings suggest that hue spectra fingerprinting can be a useful nondestructive method for monitoring quality change of sweet cherry during post-harvest handling and shelf-life.
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关键词
Surface color, Prunus avium L., Computer vision, Digital image processing
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