Detection of Rot and Ripeness of Mango with zNoseTM Electronic Nose
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Abstract:
Mango volatiles released during postharvest ripening were quantitatively measured and analyzed with an ultrafast gas chromatography system (zNoseTM). The mango volatiles were characterized by extracting the mass spectral peaks of different volatiles and mathematical models were established to measure the blackspot rate of mango skin and degree of ripeness. Odor, skin blackspot rate, degree of ripeness, soluble solid content, respiration rate, and other experimental data were compared and analyzed. The results showed that peaks 4 and 5 from the electronic nose data could effectively determine the degree of rot, peak 7 exhibited a high correlation with the degree of ripeness, and the soluble solid content showed a small contribution to the determination of the degree of ripeness. Gaussian models were constructed between the degree of rot and values of peaks 4 and 5. The rot of mango was determined using established models and the threshold value and accuracy rate of determination was over 90%. A piecewise exponential model was constructed between the degree of ripeness and value of peak 7, an effective estimation on the degree of ripeness was achieved. The root mean square error of the estimation was controlled within 7%.
