Journal
JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY
Volume 56, Issue 13, Pages 4916-4922Publisher
AMER CHEMICAL SOC
DOI: 10.1021/jf7036032
Keywords
Prunus armeniaca L.; fruit quality; beta-carotene; provitamin A; HPLC; color index; FT-NIR; FT-MIR; partial least-squares regression
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The importance of carotenoid content in apricot (Prunus armeniaca L.) is recognized not only because of the color that they impart but also because of their protective activity against human diseases. Current methods to assess carotenoid content are time-consuming, expensive, and destructive. In this work, the application of rapid and nondestructive methods such as colorimeter measurements and infrared spectroscopy has been evaluated for carotenoid determination in apricot. Forty apricot genotypes covering a wide range of peel and flesh colors have been analyzed. Color measurements on the skin and flesh (L*, a*, b*, hue, chroma, and a*/b* ratio) as well as Fourier transform near-infrared spectroscopy (FT-NIR) on intact fruits and Fourier transform mid-infrared spectroscopy (FT-MIR) on ground flesh were correlated with the carotenoid content measured by high-performance liquid chromatography. A high variability in color values and carotenoid content was observed. Partial least squares regression analyses between beta-carotene content and provitamin A activity and color measurements showed a high fit in peel, flesh, and edible apricot portion (R-2 ranged from 0.81 to 0.91) and low prediction error. Regression equations were developed for predicting carotenoid content by using color values, which appeared as a simple, rapid, reliable, and nondestructive method. However, FT-NIR and FT-MIR models showed very low R-2 values and very high prediction errors for carotenoid content.
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