کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8892838 | 1628765 | 2018 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Quality assessment and discrimination of intact white and red grapes from Vitis vinifera L. at five ripening stages by visible and near-infrared spectroscopy
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کلمات کلیدی
NIRRMSECRC2RP2Vis/NIRSNVSPALS-SVMRPDSSCRMSEPPLS-DAPLSPCA - PCAStandard normal variate - استاندارد عادیSuccessive Projections Algorithm - الگوریتم پیش بینی های متوالیPrinciple component analysis - تجزیه و تحلیل اجزای اصلTotal phenolic compounds - ترکیبات فنلی کلNull hypothesis - فرضیه صفرCARS - ماشین هاNear-infrared - نزدیک مادون قرمزCompetitive adaptive reweighted sampling - نمونه گیری تطبیقی رقابتی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم کشاورزی و بیولوژیک
دانش باغداری
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
The diffuse reflection visible/near-infrared (Vis/NIR, 400-1100â¯nm) and near-infrared (NIR, 900-2500â¯nm) spectrum were used to monitor the surface color (CIE L*a*b*), total soluble solid contents (SSC) and total phenolic compounds (TP) of intact 'Manicure Finger' and 'Ugni Blanc' berries at five ripening stages (i.e., green, pre-veraison, veraison, post-veraison and ripe). The determination of quality parameters and the discrimination of five ripening stages were conducted by chemometric analysis based on full-band and selected wavelengths of Vis/NIR and NIR. The results showed that the best regression results were obtained by least squares support vector machine (LS-SVM) with the root mean squares error of prediction (RMSEP) of 5.161, 2.919, 3.275, 1.230% and 0.216â¯gâ¯kgâ1 for L*, a*, b*, SSC and TP of 'Manicure Finger' in the range of 400-1100â¯nm, respectively; and the RMSEP of 3.049, 0.710, 2.996 and 0.150â¯gâ¯kgâ1 for L*, a*, b* and TP of 'Ugni Blanc' in the range of 400-1100â¯nm, respectively, and the RMSEP of 1.288% for SSC in the range of 900-2500â¯nm. A total of 90% and 100% classification accuracies on prediction sets were reached by the total soluble solid contents based competitive adaptive reweighted sampling support vector machine discrimination analysis (SSC-based CARS SVM-DA) for 'Manicure Finger' and 'Ugni Blanc' grape berries of five ripening stages, respectively. This study provided a feasible evaluation method of quality and developing stages for grape varieties during ripening stages by Vis/NIR and NIR technology.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Scientia Horticulturae - Volume 233, 15 March 2018, Pages 99-107
Journal: Scientia Horticulturae - Volume 233, 15 March 2018, Pages 99-107
نویسندگان
Hui Xiao, Ang Li, Meiyu Li, Ye Sun, Kang Tu, Shaojin Wang, Leiqing Pan,