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Fundamental Studies on Yam Slices Mechanical Drying
Static Equilibrium Moisture Content
Dynamic Equilibrium Moisture Content
|摘要:||This research began with the study of an appropriate layer number of yam slices in drying operations. Using the hot-air temperature 50℃ with the optimum drying thickness obtained, the best pre-processing conditions of two pre-processing methods, physical and chemical respectively were then explored based on the quality indexes of drying products such as the hue, the cubic and the weight rehydration rates, and the viscosity of the dried yam slices. Under the best condition of each pre-processing method, five hot-air drying temperatures 40, 50, 60, 70, and 80℃and five desiccant dehumidification drying temperatures 20, 25, 30, 35, and 40℃ were followed to process the single temperature drying tests to find the optimum drying temperature for the hot-air and the desiccant dehumidification drying, respectively. The experimental results show that the optimum drying thickness is 1.5 cm with three yam slices. The best pre-processing condition of the physical method is blanching one minute with the water solution of temperature 70℃and then cooling with the indoor air sixteen minutes, whereas the chemical method is soaking one minute under the citric acid solution of concentration 0.5%. The optimum drying temperatures are 40℃ for the hot-air drying and 30℃for the desiccant dehumidification drying. Both can obtain the optimum quality of the drying products for those two pre-processing methods. However, the quality of the desiccant dehumidification drying is better than that by the operation of hot-air.
This study uses the Equilibrium Relative Humidity (ERH) scheme to measure the static Equilibrium Moisture Content (EMC) Me of yam slices during the dehydration. Four different ERH/EMC models including the Henderson, Chung-Pfost, Halsey and Oswin equations were used to investigate the fitting agreement of the measured data. Through the comparison of the residual distributions, the coefficient of determination R2, the residual sum of squares SSE, and the mean relative percentage deviation P obtained from the regression analysis, the Oswin model with two parameters and the modified Oswin model with three parameters are the best predicting models for the desorption isotherms of yam slices in both of the physical and chemical pre-processing methods. Applying the analysis of variance test for a specified pre-processing method, the difference of two individual sets of the residual absolute values in each temperature is not significant and both models with two and three parameters obtain similar predicting abilities. Hence, in each pre-processing method the model with three parameters can be used for the prediction of ERH/EMC values. Further comparing the predicted values of ERH calculated from each established equation with three parameters for both pre-processing methods within the valid range at a given temperature, the results of the analysis of variance test indicate that no significant difference between these two predicted values is obtained in each temperature. Both equations with three parameters have the equivalent representative to the prediction of ERH/EMC values for the samples of yam slices.
Newton's, modified Newton's, and Page's models were used to study the fitting accuracy of the moisture content change of yam slices during the drying process. Through the comparison of two statistical values, the coefficient of determination R2 and the standard error of estimate S.E. obtained from the regression analysis, and the curves of the measured data and the predicted values, the Page model is the optimum drying model by applying the measured dynamic Equilibrium Moisture Content Med and the calculated static Equilibrium Moisture Content Me into each model for both pre-processing methods in each drying temperature. The regression analysis using the dynamic Equilibrium Moisture Content Med into the above drying models for the cases of 40℃ of the optimum hot-air drying and 30℃ of the optimum desiccant dehumidification drying in both pre-processing methods, only the drying constant K obtained by Page's model is reduced as the drying time increased. Its correlative equation then established for the drying constant K is in the form of a polynomial equation with third order in temperature (℃) and first order in relative humidity RH(%). While utilizing the static Equilibrium Moisture Content Me, the drying constant K, exclusive of the case using 40℃ hot-air drying with the chemical pre-processing method, obtained has the same characteristics of distribution as using Med during the initial and middle drying stages. In the final drying stage, only the drying constant K obtained with both pre-processing methods of hot-air drying 40℃ by Newton's and modified Newton's models retains the same performance as the value of K obtained by using Med, and the characteristics K of the others is different. After comparing the statistical values and the predicted curves for each drying model, the predicted values obtained by using Me is equivalent to those values obtained by using Med in the hot-air drying operations. While in the desiccant dehumidification drying, the predicted values obtained by using Me is worse than those obtained by using Med. Therefore, the utilization of the dynamic Equilibrium Moisture Content Med for the establishment of the drying model is more appropriate than the use of the static Equilibrium Moisture Content Me. It could also achieve better predicting accuracy.|
本研究首先探討山藥片乾燥時最適之乾燥層數，於最適乾燥厚度時，進行兩種前處理方法之研究，物理前處理條件包括殺菁溫度、冷卻方式與殺菁時間，化學前處理則包含浸漬溶液種類、濃度與浸漬時間。兩種前處理條件探討時，山藥片樣本皆以50℃單溫進行乾燥，獲致之乾燥試驗乾品經由品質指標分析，品質指標以色澤、體積復水率、重量復水率與黏度四項為基準，尋求最佳物理與化學前處理之設定條件。並在兩種最佳前處理方法下，進行烤箱熱風40、50、60、70與80℃五溫階與吸附除濕20、25、30、35與40℃五溫階之單溫乾燥試驗，以尋求山藥片在烤箱熱風與吸附除濕乾燥作業時之最佳乾燥溫度。乾燥試驗結果獲致最適之乾燥層厚度為1.5cm，即三層山藥片，最佳之物理前處理條件為以70℃水溶液殺菁1分鐘後室溫冷卻16分鐘，而最佳之化學前處理條件則為檸檬酸濃度0.5%之溶液浸漬1分鐘，在烤箱熱風與吸附除濕乾燥之最佳乾燥溫度則分別為40與30℃，各別皆可獲致最佳品質之乾燥試驗乾品，品質分析結果又以吸附除濕乾燥之樣本乾品最佳。 靜態平衡含水率Me之量測，是採用平衡相對濕度法。四種平衡含水率模式，即Henderson、Chung-Pfost、Halsey與Oswin方程式，經由量測數據適稱性之探討，綜合迴歸分析之殘差圖及決定係數R2、殘差平方和SSE與平均相對偏差百分比P比較後，獲得Oswin二參數模式與修正Oswin三參數模式，均為物理與化學前處理去濕平衡含水率之最佳預測模式。且由殘差絕對值進行變異數分析，得知二參數與三參數模式之預測能力相近，因此可直接使用三參數模式來進行預測。進一步比較兩種前處理所獲致各溫階之預測平衡相對濕度值，變異數分析結果，亦顯示兩三參數方程式之預測值於各溫階時，彼此間無顯著差異，即具有相等之代表性。 以Newton、修正Newton與Page三乾燥模式，對本試驗之山藥片樣本含水率變化進行模式預測準確性探討，並以兩種前處理各溫階之動態平衡含水率Med與靜態平衡含水率Me分別代入各模式，比較各溫階迴歸分析所得之決定係數R2與預測值標準誤差S.E.及實測與預測曲線圖，皆顯示Page模式為最佳乾燥模式。使用兩前處理乾燥之最佳烤箱熱風40℃與最佳吸附除濕30℃兩溫階之Med值代入上述三種模式進行迴歸分析，所獲致之乾燥常數K，只有Page模式之K值會隨著時間增長而減小。同時獲致乾燥常數K之關係式為溫度T(℃)三階與相對濕度RH(%)一階之多項式方程式。以30與40℃兩溫階之靜態平衡含水率Me值代入上述三模式中，所獲致之K值，於乾燥初中期之變化趨勢，除了Page模式在化學前處理烤箱熱風乾燥40℃溫階外，其餘皆與Med值代入者相近，但至乾燥後期，除了Newton與修正Newton兩模式在兩前處理之烤箱熱風乾燥40℃溫階者之K值分布仍與Med值代入者相似外，其餘皆不同；且比較三乾燥模式之迴歸分析結果與預測曲線，顯示於烤箱熱風乾燥各溫階代入靜態平衡含水率Me者與代入動態平衡含水率Med者相近，然於吸附除濕乾燥各溫階則皆比代入Med者差，因此本研究獲致乾燥模式之建立，動態平衡含水率Med比靜態平衡含水率Me合適，可獲致較佳之預測準確性。
|Appears in Collections:||生物產業機電工程學系|
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