کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7598307 | 1492132 | 2014 | 5 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Predicting soluble solid content in intact jaboticaba [Myrciaria jaboticaba (Vell.) O. Berg] fruit using near-infrared spectroscopy and chemometrics
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موضوعات مرتبط
مهندسی و علوم پایه
شیمی
شیمی آنالیزی یا شیمی تجزیه
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
The aim of this study was to evaluate the potential of near-infrared reflectance spectroscopy (NIR) as a rapid and non-destructive method to determine soluble solid content (SSC) in intact jaboticaba [Myrciaria jaboticaba (Vell.) O. Berg] fruit. Multivariate calibration techniques were compared with pre-processed data and variable selection algorithms, such as partial least squares (PLS), interval partial least squares (iPLS), a genetic algorithm (GA), a successive projections algorithm (SPA) and nonlinear techniques (BP-ANN, back propagation of artificial neural networks; LS-SVM, least squares support vector machine) were applied to building the calibration models. The PLS model produced prediction accuracy (R2 = 0.71, RMSEP = 1.33 °Brix, and RPD = 1.65) while the BP-ANN model (R2 = 0.68, RMSEM = 1.20 °Brix, and RPD = 1.83) and LS-SVM models achieved lower performance metrics (R2 = 0.44, RMSEP = 1.89 °Brix, and RPD = 1.16). This study was the first attempt to use NIR spectroscopy as a non-destructive method to determine SSC jaboticaba fruit.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Food Chemistry - Volume 159, 15 September 2014, Pages 458-462
Journal: Food Chemistry - Volume 159, 15 September 2014, Pages 458-462
نویسندگان
Nathália Cristina Torres Mariani, Rosangela Câmara da Costa, Kássio Michell Gomes de Lima, Viviani Nardini, LuÃs Carlos Cunha Júnior, Gustavo Henrique de Almeida Teixeira,