Rapid screening of olive oil cultivar differentiation based on selected physicochemical parameters, pigment content and fatty acid composition using advanced chemometrics

被引:16
|
作者
Karabagias, Ioannis K. [1 ]
Badeka, Anastasia [1 ]
Casiello, Grazia [2 ]
Longobardi, Francesco [2 ]
Kontominas, Michael G. [1 ]
机构
[1] Univ Ioannina, Dept Chem, Lab Food Chem, GR-45110 Ioannina, Greece
[2] Univ Bari Aldo Moro, Dipartimento Chim, Via Orabona 4, I-70126 Bari, Italy
关键词
Olive oil; Cultivar classification; Physicochemical parameters; MANOVA; LDA; Pareto chart; GEOGRAPHICAL ORIGIN; CLASSIFICATION; SPECTROSCOPY; FOOD;
D O I
10.1007/s00217-019-03310-3
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
Thirty-seven olive oil samples belonging to cultivars: Ntopia, Koroneiki, Thiaki, Asprolia and Lianolia were collected from four Western Greek islands. Samples were subjected to the following physicochemical analyses: acidity, peroxide value, K-232, K-270, Delta K indices, chlorophyll and carotenoid contents, along with fatty acids in an effort to characterize and mainly classify olive oil samples according to cultivar. Multivariate analysis of variance (MANOVA) showed that the following parameters: acidity, chlorophyll, carotenoid, myristic acid, margaric acid, stearic acid, arachidic acid, and eicosenoic acid were significant (p < 0.05) for the classification of olive oil cultivars. The aforementioned parameters were subjected to linear discriminant analysis (LDA) providing a correct classification rate of 91.9% and 81.1% using the original and cross-validation methods, respectively. Finally, the application of quality control analysis such as Pareto chart showed that with only two variables namely acidity and chlorophyll content, the investigated cultivars could be differentiated, providing thus, a rapid and costless methodology for olive oil cultivar differentiation.
引用
收藏
页码:2027 / 2038
页数:12
相关论文
共 6 条
  • [1] Rapid screening of olive oil cultivar differentiation based on selected physicochemical parameters, pigment content and fatty acid composition using advanced chemometrics
    Ioannis K. Karabagias
    Anastasia Badeka
    Grazia Casiello
    Francesco Longobardi
    Michael G. Kontominas
    European Food Research and Technology, 2019, 245 : 2027 - 2038
  • [2] Differentiation of Fresh Greek Orange Juice of the Merlin Cultivar According to Geographical Origin Based on the Combination of Organic Acid and Sugar Content as well as Physicochemical Parameters Using Chemometrics
    Christos Nikolaou
    Ioannis K. Karabagias
    Ilias Gatzias
    Stavros Kontakos
    Anastasia Badeka
    Michael G. Kontominas
    Food Analytical Methods, 2017, 10 : 2217 - 2228
  • [3] Differentiation of Fresh Greek Orange Juice of the Merlin Cultivar According to Geographical Origin Based on the Combination of Organic Acid and Sugar Content as well as Physicochemical Parameters Using Chemometrics
    Nikolaou, Christos
    Karabagias, Ioannis K.
    Gatzias, Ilias
    Kontakos, Stavros
    Badeka, Anastasia
    Kontominas, Michael G.
    FOOD ANALYTICAL METHODS, 2017, 10 (07) : 2217 - 2228
  • [4] Differentiation of Greek extra virgin olive oils according to cultivar based on volatile compound analysis and fatty acid composition
    Kosma, Ioanna
    Badeka, Anastasia
    Vatavali, Kornilia
    Kontakos, Stavros
    Kontominas, Michael
    EUROPEAN JOURNAL OF LIPID SCIENCE AND TECHNOLOGY, 2016, 118 (06) : 849 - 861
  • [5] Characterization and differentiation of sheep's milk from Greek breeds based on physicochemical parameters, fatty acid composition and volatile profile
    Gatzias, Ilias S.
    Karabagias, Ioannis K.
    Kontakos, Stavros P.
    Kontominas, Michael G.
    Badeka, Anastasia V.
    JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE, 2018, 98 (10) : 3935 - 3942
  • [6] QTL mapping for fatty acid composition in olive oil using a high-density genetic map based on SNP markers
    Kaya, Ali Can
    Ipek, Meryem
    Ipek, Ahmet
    Gundogdu, Mehmet Ali
    Tangu, Nesrin Aktepe
    Duran, Sevin Teoman
    Seker, Murat
    Akbulut, Mustafa
    TURKISH JOURNAL OF AGRICULTURE AND FORESTRY, 2024, 48 (04) : 490 - 501