生姜焯水后根茎干燥特性的统计预测

A. Gbasouzor, Jude Ezechi Dara, C. Mgbemena
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引用次数: 0

摘要

本研究采用ARS-680环境箱对生姜切片的干燥行为进行了研究。在干燥温度为40℃,干燥时间为2 ~ 24 h的条件下,对生姜进行了焯水处理和未焯水处理。采用线性和非线性回归分析,建立了干燥时间与水分比之间的相关性。采用相关分析、均方根误差(RMSE)和估计标准误差(SEE)分析选择最佳薄层干燥模型。决定系数R2值越高,拟合越好,SEE值越低,相关性越好;和RMSE值也用于确定拟合优度。将不同处理的生姜样品的干燥数据拟合到12个薄层干燥模型中,并采用多元非线性回归技术进行拟合。与未漂白的62.03%的样品相比,漂白后的样品表现出更好的干燥性能,水分含量损失约82.87%。两项指数干燥模型被证明是最适合预测生姜干燥行为的模型。该模型对漂白和未漂白样品均显示出较高的R2值,为0.9349-0.9792(接近1)。两种处理的RMSE和SEE值均较低,分别为3.6865 ~ 2.0896和3.6564 ~ 2.7486。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Statistical prediction of the drying behavior of blanched ginger rhizomes
ARS-680 environmental chamber was employed in this study to determine the drying behavior of sliced ginger rhizomes. Blanched and unblanched treated ginger rhizomes were considered at drying temperature of 40 °C for a period of 2 – 24 h. Linear and non-linear regression analyses were employed to establish the correlation that exits between the drying time and the moisture ratio. Correlation analysis, root mean square error (RMSE) and standard error of estimate (SEE) analysis were chosen in selecting the best thin layer drying models. Higher values of determination coefficient (R2) show goodness of fit and lower values of SEE implies better correlation; and RMSE values were also utilized in determining the goodness of fit. The drying data of the variously treated ginger samples were fitted into the twelve thin layer drying models and the data obtained were fitted by multiple non-linear regression technique. Blanched treated sample exhibited a better drying behavior losing about 82.87 % moisture content compared with unbleached sample that lost about 62.03 % of moisture content. Two-term exponential drying model proved to be the most suitable model for predicting the drying behavior of ginger rhizome. The model exhibited high R2 values of 0.9349-0.9792 (which are close to unity) for both blanched and unbleached samples. Also, it recorded relatively low values of RMSE and SEE (3.6865 - 2.0896 and 3.6564-2.7486 respectively) for both treatments.  
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