Evaluation of Storage Stability of Date Fruit (Phoenix dactylifera L.) at Two Levels of Relative Humidity Based on Selected Functional Compounds and Image Features

基于选定的功能化合物和图像特征,评价两种相对湿度水平下椰枣(Phoenix dactylifera L.)果实的贮藏稳定性。

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Abstract

In this study, two known date fruit cultivars ('Mejhoul' and 'Boufeggous') were pre-treated using convective and infrared drying, and then subjected to cold storage at +4 °C using two levels of relative humidity (RH): 55% and 65%. The quality of the date fruit was assessed based on selected phenolic compounds, sugars, color, hardness, weight loss, and some image features at 0, 2, 4, 6, and 8 months. The results exhibited non-similar patterns in the changes of phenolic compounds according to cultivar and relative humidity level. The highly significant changes were observed for "Quercetin-Xyloside" that decreased drastically after two months of storage, especially for the 'Mejhoul' cultivar. Also, "Gallic acid" indicated a progressive and significant increase during storage. Other phenolic compounds, mainly "Quercetin-derivatives", "Chlorogenic acid derivatives", and "Ferulic acid", showed fluctuating values among treatments and during the whole period of storage. For sugar compounds, it was noticed that glucose and fructose were affected by drying technique and relative humidity, especially for the 'Boufeggous' cultivar. Weight loss increased significantly for 'Mejhoul' cultivar stored at high relative humidity (65%), and 'Boufeggous' evolved in the opposite way for samples stored at lower RH (55%). For color, the browning index exhibited a significant and progressive increase among all treatments considered in this study; this pattern was more pronounced for date cultivars stored at high relative humidity (65%). The evaluation of hardness indicated a softening phenomenon during storage, especially for the 'Mejhoul' cultivar stored at 65% of RH. Moreover, the correlation of image features with weight loss and some color attributes indicated high correlation, and the estimation of the behavior of dates under storage could be predicted using accurate image features.

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