کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7594617 | 1492119 | 2015 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Predicting the anthocyanin content of wine grapes by NIR hyperspectral imaging
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کلمات کلیدی
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 demonstrate the capability of hyperspectral imaging in predicting anthocyanin content changes in wine grapes during ripening. One hundred twenty groups of Cabernet Sauvignon grapes were collected periodically after veraison. The hyperspectral images were recorded by a hyperspectral imaging system with a spectral range from 900 to 1700Â nm. The anthocyanin content was measured by the pH differential method. A quantitative model was developed using partial least squares regression (PLSR) or support vector regression (SVR) for calculating the anthocyanin content. The best model was obtained using SVR, yielding a coefficient of validation (P-R2) of 0.9414 and a root mean square error of prediction (RMSEP) of 0.0046, higher than the PLSR model, which had a P-R2 of 0.8407 and a RMSEP of 0.0129. Therefore, hyperspectral imaging can be a fast and non-destructive method for predicting the anthocyanin content of wine grapes during ripening.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Food Chemistry - Volume 172, 1 April 2015, Pages 788-793
Journal: Food Chemistry - Volume 172, 1 April 2015, Pages 788-793
نویسندگان
Shanshan Chen, Fangfang Zhang, Jifeng Ning, Xu Liu, Zhenwen Zhang, Shuqin Yang,