{"title":"生姜焯水后根茎干燥特性的统计预测","authors":"A. Gbasouzor, Jude Ezechi Dara, C. Mgbemena","doi":"10.37121/JASE.V4I2.147","DOIUrl":null,"url":null,"abstract":"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. ","PeriodicalId":92218,"journal":{"name":"International journal of advances in science, engineering and technology","volume":"9 1","pages":"98-107"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Statistical prediction of the drying behavior of blanched ginger rhizomes\",\"authors\":\"A. Gbasouzor, Jude Ezechi Dara, C. Mgbemena\",\"doi\":\"10.37121/JASE.V4I2.147\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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. \",\"PeriodicalId\":92218,\"journal\":{\"name\":\"International journal of advances in science, engineering and technology\",\"volume\":\"9 1\",\"pages\":\"98-107\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-04-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International journal of advances in science, engineering and technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.37121/JASE.V4I2.147\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of advances in science, engineering and technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37121/JASE.V4I2.147","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.