کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
2449352 1554077 2016 5 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Classification of traditional Chinese pork bacon based on physicochemical properties and chemometric techniques
ترجمه فارسی عنوان
طبقه بندی گوشت خوک سنتی چینی بر اساس خواص فیزیکی و شیمیایی و تکنیک های شیمیایی
کلمات کلیدی
گوشت خوک سنتی چینی، تجزیه و تحلیل تبعیض آمیز، تعیین فیزیکوشیمیایی، تکنیک های شیمیایی
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک دانش تغذیه
چکیده انگلیسی


• We examined the physicochemical properties of Chinese traditional pork bacons.
• Discriminant analysis could discriminate the five styles of Chinese traditional pork bacons.
• The ratio of an overall correct classification and a cross-validation was 97.76%, 91.76%, respectively.
• The discriminated functions for Chinese traditional pork bacons were built.

Sixty-seven pork bacon samples from Hunan, Sichuan Guangdong, Jiangxi, and Yunnan Provinces in China were analyzed to understand their geographical properties. Classification was performed by determining their physicochemical properties through chemometric techniques, including variance analysis, principal component analysis (PCA), and discriminant analysis (DA). Results showed that certain differences existed in terms of nine physicochemical determinations in traditional Chinese pork bacon. PCA revealed the distinction among Hunan, Sichuan, and Guangdong style bacon. Meanwhile, seven key physicochemical determination criteria were identified in line with DA and could be reasonably applied to the classification of traditional Chinese pork bacon. Furthermore, the ratio of overall correct classification was 97.76% and that of cross-validation was 91.76%. These findings indicated that chemometric techniques, together with several physicochemical determination, were effective for the classification of traditional Chinese pork bacon with geographical features. Our study provided a theoretical reference for the classification of traditional Chinese pork bacon.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Meat Science - Volume 117, July 2016, Pages 182–186
نویسندگان
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