FT-NIR spectra analysis and processing to determine the quality parameters of various edible oils and chicken fat


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Mecit A., Keçeli Mutlu T.

RIVISTA ITALIANA DELLE SOSTANZE GRASSE, cilt.100, sa.1, ss.29-37, 2023 (SCI-Expanded)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 100 Sayı: 1
  • Basım Tarihi: 2023
  • Dergi Adı: RIVISTA ITALIANA DELLE SOSTANZE GRASSE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, CAB Abstracts
  • Sayfa Sayıları: ss.29-37
  • Çukurova Üniversitesi Adresli: Evet

Özet

Valorisation of chicken fat as a fat source in chicken meat products or as a low-cost source

of biodiesel could be a viable option for the poultry industry’s long-term sustainability and

pollution reduction. The acidity and peroxide levels of culinary oils and fats are important

grading and safety factors. FT-NIR techniques with chemometric treatment are a rapid,

reliable, and convenient alternative to wet-chemical characterisation by reference analysis.

This research demonstrated that using FT-NIR spectroscopy (1122-902 nm) and (1090-

898 nm) with PLS-R, PCA, and Discriminant Analysis (DA) was sufficient to analyse data,

predict, and discriminate edible oils and chicken fat according to their quality parameters

regardless of whether they are present in low or high amounts. The PLS-R regression

models can predict FFA and PV because they have a perfect agreement with reference

analysis (R2, 0.94 and 0.99) and have RPD >2 showing FT-NIR is suitable for quality

control applications of edible oils and chicken fat. DA was able to discriminate between

the groups chicken fat and virgin olive oil, from other edible oils with a 98% accuracy,

based on their FFA and PV by both methods. The FT-NIR method with a multivariate

approach is an excellent alternative to reference methods, using a small sample and no

chemical, fast, reliable, and as green technique that could be used as a quality control

tool for both predictions of quality and discrimination purposes.