Literature DB >> 29892132

Prediction of fatty acid composition of sunflower seeds by near-infrared reflectance spectroscopy.

Murat Reis Akkaya1.   

Abstract

This study was performed in order to evaluate efficiency of near-infrared reflectance spectroscopy (NIRS) for the determination of fatty acid composition ratio of sunflower seeds and to compare performance of calibration methods. Calibration equations were developed using modified partial least squares (MPLS) and partial least squares (PLS) regression methods. Ninety-three sunflower seed varieties were from test field of East Mediterranean Agricultural Research Institute. In order to determine the reference fatty acid values needed to construct calibration in NIRS analysis, sunflower seed samples were analyzed by gas chromatography method. Coefficients of determination (R2) in calibration were developed using MPLS and PLS as follows: for palmitic acid 0.706-0.664, for stearic acid 0.615-0.654, for oleic acid 0.996-0.994, for linoleic acid 0.995-0.994, for arachidic acid 0.768-0.643, for linolenic acid 0.818-0.763, for behenic acid 0.891-0.776, for eicosapentaenoic 0.933-0.892, for unsaturated fatty acid 0.837-0.890 and for saturated fatty acid 0.837-0.890 respectively. The results showed that NIRS was a reliable technique that can be used as a tool for rapid pre-screening of fatty acid composition of sunflower seeds.

Entities:  

Keywords:  NIRS; Oleic acid; Palmitic acid; Sunflower; Unsaturated fatty acid

Year:  2018        PMID: 29892132      PMCID: PMC5976617          DOI: 10.1007/s13197-018-3150-x

Source DB:  PubMed          Journal:  J Food Sci Technol        ISSN: 0022-1155            Impact factor:   2.701


  2 in total

1.  Determination of fat, protein and moisture in ricotta cheese by near infrared spectroscopy and multivariate calibration.

Authors:  Elisângela Serenato Madalozzo; Elenise Sauer; Noemi Nagata
Journal:  J Food Sci Technol       Date:  2013-08-16       Impact factor: 2.701

2.  Design and develop a nondestructive infrared spectroscopy instrument for assessment of mango (Mangifera indica) quality.

Authors:  Basem Abu Izneid; M I Fadhel; Tareq Al-Kharazi; Malek Ali; Souiyah Miloud
Journal:  J Food Sci Technol       Date:  2012-11-06       Impact factor: 2.701

  2 in total
  4 in total

1.  Analysis and prediction of the major fatty acids in vegetable oils using dielectric spectroscopy at 5-30 MHz.

Authors:  Masyitah Amat Sairin; Samsuzana Abd Aziz; Chan Yoke Mun; Alfadhl Yahya Khaled; Fakhrul Zaman Rokhani
Journal:  PLoS One       Date:  2022-05-26       Impact factor: 3.752

2.  Metabolite Profile, Ruminal Methane Reduction, and Microbiome Modulating Potential of Seeds of Pharbitis nil.

Authors:  Rajaraman Bharanidharan; Krishnaraj Thirugnanasambantham; Ridha Ibidhi; Myunggi Baik; Tae Hoon Kim; Yookyung Lee; Kyoung Hoon Kim
Journal:  Front Microbiol       Date:  2022-05-09       Impact factor: 6.064

3.  Rapid Determination of the Oil and Moisture Contents in Camellia gauchowensis Chang and Camellia semiserrata Chi Seeds Kernels by Near-infrared Reflectance Spectroscopy.

Authors:  Yingzhong Zhang; Liangbo Zhang; Jing Wang; Xuxiao Tang; Hong Wu; Minghuai Wang; Wu Zeng; Qihui Mo; Yongquan Li; Jianwei Li; Yijuan Huang; Baohua Xu; Mengyu Zhang
Journal:  Molecules       Date:  2018-09-12       Impact factor: 4.411

Review 4.  Near-Infrared Hyperspectral Imaging Pipelines for Pasture Seed Quality Evaluation: An Overview.

Authors:  Priyanka Reddy; Kathryn M Guthridge; Joe Panozzo; Emma J Ludlow; German C Spangenberg; Simone J Rochfort
Journal:  Sensors (Basel)       Date:  2022-03-03       Impact factor: 3.576

  4 in total

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