با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد).
دسته بندی:
داده کاوی - data mining
سال انتشار:
2018
عنوان انگلیسی مقاله:
Combination of complementary data mining methods for geographical characterization of extra virgin olive oils based on mineral composition
ترجمه فارسی عنوان مقاله:
ترکیبی از روش های داده کاوی مکمل برای تعیین ویژگی های جغرافیایی روغن زیتون فوق العاده با استفاده از ترکیبات معدنی
منبع:
Sciencedirect - Elsevier - Food Chemistry, 261 (2018) 42-50. doi:10.1016/j.foodchem.2018.04.019
نویسنده:
Ana Sayagoa,b, Raúl González-Domíngueza,b,⁎, Rafael Beltrána,b, Ángeles Fernández-Recamalesa,b
چکیده انگلیسی:
This work explores the potential of multi-element fingerprinting in combination with advanced data mining
strategies to assess the geographical origin of extra virgin olive oil samples. For this purpose, the concentrations
of 55 elements were determined in 125 oil samples from multiple Spanish geographic areas. Several un
supervised and supervised multivariate statistical techniques were used to build classification models and in
vestigate the relationship between mineral composition of olive oils and their provenance. Results showed that
Spanish extra virgin olive oils exhibit characteristic element profiles, which can be differentiated on the basis of
their origin in accordance with three geographical areas: Atlantic coast (Huelva province), Mediterranean coast
and inland regions. Furthermore, statistical modelling yielded high sensitivity and specificity, principally when
random forest and support vector machines were employed, thus demonstrating the utility of these techniques in
food traceability and authenticity research.
Keywords: Olive oil ، Geographical traceability ، Mineral profile ، Inductively coupled plasma-mass spectrometry ، Data mining
قیمت: رایگان
توضیحات اضافی:
تعداد نظرات : 0