کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7562102 | 1491504 | 2018 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Classification of 1-methylcyclopropene treated apples by fluorescence fingerprint using partial least squares discriminant analysis with stepwise selectivity ratio variable selection method
ترجمه فارسی عنوان
طبقه بندی سیب های 1-متیسی سلیلوپروپین با استفاده از اثر انگشت فلورسنت با استفاده از روش تجزیه و تحلیل خرده مقیاس های جزئی و روش انتخاب متغیر مرحله ای
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
شیمی
شیمی آنالیزی یا شیمی تجزیه
چکیده انگلیسی
In this study, we investigated the potential of using fluorescence fingerprint (FF) for nondestructive identification of apples treated with 1-methylcyclopropene (1-MCP). In total, 442 apples of two cultivars (Fuji and Orin) and different storage times (0, 4, 5, 6, and 8 months) were assessed. The classification model used in this study was built using partial least squares discriminant analysis (PLSDA) with the stepwise selectivity ratio (SR) method. The stepwise SR method is a recursive variable selection method proposed in this study. FF was capable of classifying 1-MCP-treated apples with accuracies of 91.23%, 89.74%, and 90.17% for calibration, cross-validation, and validation results, respectively. PLSDA with the stepwise SR method could identify four aggregations of wavelength conditions, which are important to the classification. In addition, a non-targeted approach was taken to screen the metabolites characterizing 1-MCP-treated and control apples by liquid chromatography-mass spectrometry (LC/MS) and nuclear magnetic resonance (NMR) spectroscopy. The observed difference in metabolic profiles may contribute to the difference in the fluorescence profiles of 1-MCP treated and control apples.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Chemometrics and Intelligent Laboratory Systems - Volume 175, 15 April 2018, Pages 30-36
Journal: Chemometrics and Intelligent Laboratory Systems - Volume 175, 15 April 2018, Pages 30-36
نویسندگان
Vipavee Trivittayasil, Mizuki Tsuta, Satoshi Kasai, Yosuke Matsuo, Yasuyo Sekiyama, Toshihiko Shoji, Ryoko Aiyama, Mito Kokawa, Junichi Sugiyama,