کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
222568 464278 2016 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Rapid assessment of black tea quality using diffuse reflectance spectroscopy
ترجمه فارسی عنوان
ارزیابی سریع با کیفیت چای سیاه با استفاده از طیف سنجی بازتاب منتشر
کلمات کلیدی
مجموع پلی فنل؛ Thearubigin؛ تیفلاوین؛ روشنایی مشروب؛ رنگ مشروب مجموع؛ رگرسیون جزئی حداقل مربعات
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی مهندسی شیمی (عمومی)
چکیده انگلیسی


• Diffuse reflectance spectroscopy can be considered as rapid and non-invasive tool to assess the black tea quality.
• Chemometric models can be used to estimate black tea quality parameters.
• Chemometric models with variable importance of projection can be used to accelerate the spectral analysis of black tea quality.
• Spectral pre-processing techniques can improve the prediction accuracy of the chemometric models.

Tea quality assessment methods generally require elaborate sample preparation steps and often yield in consistent results. Over the last two decades, the diffuse reflectance spectroscopy (DRS) is emerging as a rapid and non-invasive tool for assessing quality parameters of several materials. In this study¸ we examined the DRS approach by creating a reflectance spectral imaging of 81 black crush, tear and curl (CTC) tea samples and eight tea quality parameters. Spectral models for each parameter were developed using the partial-least-squares regression (PLSR) approach. The ratio of performance deviation (RPD) was used to assess such spectral models. Results showed that moisture content, thearubigin components of TRSI and TRSII, total polyphenol contents and liquor brightness were accurately predicted with RPD values 3.63, 2.32, 2.24, 2.23 and 2.02, respectively. Prediction accuracies were moderate for thearubigin, total liquor color and theaflavin. The variable important projection (VIP) showed the wavelengths around near-infrared and shortwave-infrared regions strongly influence spectral reflectance of black tea.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Food Engineering - Volume 190, December 2016, Pages 101–108
نویسندگان
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