scholarly journals A New Method for Olive Oil Screening Using Multivariate Analysis of Proton NMR Spectra

Molecules ◽  
2021 ◽  
Vol 27 (1) ◽  
pp. 213
Author(s):  
Colleen L. Ray ◽  
James A. Gawenis ◽  
C. Michael Greenlief
Keyword(s):  
Principal Component Analysis ◽  
Olive Oil ◽  
Nmr Spectra ◽  
Principal Component ◽  
Component Analysis ◽  
Processing Parameters ◽  
Seed Oils ◽  
Virgin Olive Oils ◽  
Olive Oils ◽  
Novel Processing

A new NMR-based method for the discrimination of olive oils of any grade from seed oils and mixtures thereof was developed with the aim of allowing the verification of olive oil authenticity. Ten seed oils and seven monovarietal and blended extra virgin olive oils were utilized to develop a principal component analysis (PCA) based analysis of 1H NMR spectra to rapidly and accurately determine the authenticity of olive oils. Another twenty-eight olive oils were utilized to test the principal component analysis (PCA) based analysis. Detection of seed oil adulteration levels as low as 5% v/v has been shown using simple one-dimensional proton spectra obtained using a 400 MHz NMR spectrometer equipped with a room temperature inverse probe. The combination of simple sample preparation, rapid sample analysis, novel processing parameters, and easily interpreted results, makes this method an easily accessible tool for olive oil fraud detection by substitution or dilution compared to other methods already published.

Detection of olive oil adulteration using principal component analysis applied on total and regio FA content

2003 ◽  
Vol 80 (3) ◽  
pp. 203-208 ◽  
Author(s):  
V. G. Dourtoglou ◽  
Th. Dourtoglou ◽  
A. Antonopoulos ◽  
E. Stefanou ◽  
S. Lalas ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Olive Oil ◽  
Principal Component ◽  
Component Analysis

Quantitation of Resonances in Biological31P NMR Spectra via Principal Component Analysis: Potential and Limitations

1996 ◽  
Vol 9 (3) ◽  
pp. 93-104 ◽  
Author(s):  
Annette C. Kuesel ◽  
Radka Stoyanova ◽  
Nanci R. Aiken ◽  
Chun-Wei Li ◽  
Benjamin S. Szwergold ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Nmr Spectra ◽  
Principal Component ◽  
Component Analysis

The application of principal component analysis and gray relational method in the optimization of the melt spinning process using the cooling air system

2012 ◽  
Vol 83 (4) ◽  
pp. 371-380 ◽  
Author(s):  
Chung-Feng Jeffrey Kuo ◽  
Sheng-Siang Syu ◽  
Chien-Hung Lin ◽  
Kai-Ching Peng
Keyword(s):  
Principal Component Analysis ◽  
Melt Spinning ◽  
Principal Component ◽  
Component Analysis ◽  
Processing Parameters ◽  
Composite Fiber ◽  
Flow Equation ◽  
Optimal Parameters ◽  
Air System ◽  
Cooling Air

This study attempted to optimize the manufacturing process of polyethylene terephthalate (PET) and titanium dioxide-containing (TiO2) composite fibers. The composite fiber is made by the melt spinning processing method, and has the characteristics of the high strength of PET and the sterilization function of TiO2. To obtain the optimal processing parameters, this study applied the Taguchi method in planning the research experiment, and set one parameter of two levels and seven parameters of three levels using the L18 orthogonal array. The flow equation was used to design a cooling air system for the manufacturing, and the results showed that using one parameter of two levels can give a stable air pressure to cool the fiber to obtain the characteristics of excellent quality. Finally, field emission scanning electron microscope (FE-SEM) was used to observe the distribution of TiO2 particles in the PET fiber produced in the experiment, in order to verify the experimental effectiveness. This study used principal component analysis combined with the gray relational method to obtain the optimal parameters of the experiment, because the former has the advantage of data simplicity, while the latter can determine the factors influencing power ranking. Confirmation experiments were conducted to test the quality characteristics, and found that the properties of the fiber produced with the optimal parameters showed improvements.

scholarly journals Physico-chemical and sensory evaluation of virgin olive oils from several Algerian olive-growing regions

OCL ◽  
2021 ◽  
Vol 28 ◽  
pp. 55
Author(s):  
Malika Douzane ◽  
Mohamed-Seghir Daas ◽  
Amel Meribai ◽  
Ahmed-Hani Guezil ◽  
Abdelkrim Abdi ◽  
...  
Keyword(s):  
Olive Oil ◽  
Virgin Olive Oil ◽  
Principal Component ◽  
Great Variability ◽  
Olive Cultivar ◽  
Virgin Olive Oils ◽  
Olive Oils ◽  
Physical Chemical ◽  
Physico Chemical

Olive cultivar diversity is rich in Algeria but most remain unexplored in terms of quality traits. This work aimed to evaluate the physicochemical and organoleptic quality of twenty olive oil samples belonging to four Algerian cultivars (Chemlal, Sigoise, Ronde de Miliana and Rougette de Mitidja) collected throughout the national territory. Physical-chemical and sensory results showed that 60% of the oils belong to the extra virgin category, while 40% were classified as “virgin olive oil”. The results of the principal component analysis (PCA) revealed a great variability in fatty acids composition between the samples depending on the cultivar and origin. Oleic acid was the most abundant and varied between 64.84 and 80.14%. Extra virgin olive oils with quality attributes are eligible for a label. Rougette de Mitidja, Ronde de Miliana and Sigoise from Oran showed great potential.

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