Forensic Feed Strategy: Incorporation of Multivariate and Instrumental Analyses for Authentication of Fish Feed Sources

Authors

  • Mohamed Haniff Hanafy Idris
  • Muhamad Shirwan Abdullah Sani International islamic University Malaysia (IIUM)
  • Amalia Mohd Hashim
  • Nor Nadiha Mohd Zaki
  • Yanty Noorzianna Abdul Manaf
  • Mohd Nasir Mohd Desa
  • Syariena Arshad
  • Mohd Hafis Yuswan
  • Mohd Sukri Hassan
  • Yus Aniza Yusof
  • Mohd Salleh Kamaruddin
  • Shuhaimi Mustafa

DOI:

https://doi.org/10.36877/jhis.a0000293

Abstract

This study authenticated fish feed sources and determined lard adulteration using dataset pre-processing, principal component analysis (PCA), discriminant analysis (DA) and partial least square regression (PLSR) on 19 triacylglycerols (TAGs) and 16 thermal properties (TPs). At cumulative variability (90.625%) and Keiser-Meyer Olkin (KMO) value (0.811), the PCA identified 10 TAGs and 3 TPs with strong factor loading. The dioleoyl-1-palmitoyl glycerol (POO), dipalmitoyl-3-oleoyl glycerol (PPO) and dipalmitoyl-1-linoleoyl (PPL) characterized fish feeds containing palm oil while dilinoleoyl-1-oleoyl glycerol (OLL), dilinoleoyl-1-palmitoyl (PLL), dioleoyl-3-linoleoyl glycerol (OOL), initial cooling temperature (ICT), palmitoyl-oleoyl-linoleoyl glycerol (POL), palmitoyl-stearoyl-oleoyl glycerol (PSO) and final heating temperature (FHT) characterized lard-containing fish feeds. The DA had successfully classified the fish feed sources and selected the PPL, POL, PPO, OOL, ICT, PLL, FHT, POO and OLL as the most influential biomarkers for the authentication purpose. The Z-test result (p>0.05) indicated that the PLSR could determine the percentage of lard adulteration in fish feed. Hence, incorporating multivariate and instrumental analyses could authenticate the fish feed sources.

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Published

2022-06-29

Issue

Vol. 5 No. 1 (2022)

Section

ORIGINAL RESEARCH ARTICLES

License

Copyright (c) 2022 Mohamed Haniff Hanafy Idris, Muhamad Shirwan Abdullah Sani, Amalia Mohd Hashim, Nor Nadiha Mohd Zaki, Yanty Noorzianna Abdul Manaf, Mohd Nasir Mohd Desa , Syariena Arshad; Mohd Hafis Yuswan; Mohd Sukri Hassan, Yus Aniza Yusof, Mohd Salleh Kamaruddin, Shuhaimi Mustafa

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