Hand-held Optical Fiber Smartphone Spectrometer for Classification of Vegetable Oils

Abstract A new analytical method for the differentiation of olive oil from other vegetable oils using reversed-phaseLC and applying chemometric techniques was developed. A 3 cm short column was used to obtain the chromatographic fingerprint of the methyl-transesterified fraction of each vegetable oil. The chromatographic analysis tookonly 4 min. The multivariate classification methods used were k-nearest neighbors, partial least-squares (PLS) discriminant analysis, one-class PLS, support vector machine classification, and soft independent modeling of class analogies. The discrimination of olive oil from other vegetable edible oils was evaluated by several classification quality metrics. Several strategies for the classification of the olive oil wereused: one input-class, two input-class, and pseudo two input-class.

Download Full-text

Development of Methods for the Classification of Vegetable Oils According to Their Botanical Origin

Springer Theses - Characterization and Authentication of Olive and Other Vegetable Oils ◽

10.1007/978-3-642-31418-6_5 ◽

2012 ◽

pp. 105-136

Author(s):

María Jesús Lerma García

Keyword(s):

Vegetable Oils ◽

Botanical Origin

Download Full-text

CERTIFICATION OF VEGETABLE OILS AND QUALITY CONTROL IN THE TECHNOLOGICAL PROCESS OF PRODUCTION

Technical science and innovation ◽

10.51346/tstu-01.19.4.-77-0038 ◽

2019 ◽

Vol 2019 (4) ◽

pp. 119-126

Author(s):

CH Bekmurotov ◽

Keyword(s):

Quality Control ◽

Technological Process ◽

Vegetable Oils ◽

Raw Materials ◽

Cottonseed Oil ◽

Product Classification ◽

Cotton Seeds ◽

The Cost

The article reviewed the certification and quality control of the technological process for the production of vegetable oil. There is a procedure for packaging, quality control of products, determination of quality indicators and quality control of finished products. The procedure for using refined cottonseed oil and its varieties, the requirements for placement and storage of vegetable oils, as specified in the regulatory documents, the quality control of vegetable oils and other solutions for cottonseed oil are provided. The gas analyzer shows a solution for measuring the amount of solution by painting the tubes of a mixture of gas and air in oil. Detailed information on the production of vegetable oils, the cost of raw materials, the level of fat content of cotton seeds and the methods used to produce oil from cotton seeds. Methods for certification of vegetable oils, types of quality control, methods of testing and quality determination are presented. It was shown that the procedure for refined production of cottonseed oils and their types, as well as the state of the product classification of products based on the method of producing vegetable oils for consumer purposes, analysis of the sequence of refined oils and refining processes.

Download Full-text

Fluoresence Spectra From Vegetable Oils Using Violet And Blue Ld/Led Exitation And An Optical Fiber Spectrometer

International Journal of Food Properties ◽

10.1080/10942912.2012.700536 ◽

2014 ◽

Vol 17 (6) ◽

pp. 1211-1223 ◽

Cited By ~ 3

Author(s):

K. Nikolova ◽

M. Zlatanov ◽

T. Eftimov ◽

D. Brabant ◽

S. Yosifova ◽

...

Keyword(s):

Optical Fiber ◽

Vegetable Oils

Download Full-text

FBG Intrusion Recognition Algorithm Based on SVM

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.591-593.1422 ◽

2012 ◽

Vol 591-593 ◽

pp. 1422-1427 ◽

Cited By ~ 2

Author(s):

Jian Wang

Keyword(s):

Optical Fiber ◽

Frequency Band ◽

Time Domain ◽

Recognition Algorithm ◽

Vibration Sensor ◽

Weighting Coefficient ◽

Support Vector ◽

Fiber Grating ◽

University Of Technology

The perimeter security alarm system, with the core of vibration sensor based on FBG optical fiber invented by Wuhan University of Technology optical fiber research center, uses the changes of optical fiber grating stress wavelength to detect intrusion. As FBG wavelengths change when under stress, the intrusion detection is identified by the combination of signals time domain and frequency band domain. However, it is difficult to classify the data of signals time domain and frequency band domain because of the complexity of the actual conditions and the diversity of interference and intrusion. Therefore, applying SVM to train and process the classification features extracted from the various data acquisition can help to obtain the corresponding support vector and weighting coefficient. As a result, the effective classification of the field test data can be achieved by using SVM template method.

Download Full-text