An improved Fourier-Transform Infrared Spectroscopy combined with partial least squares regression for rapid quantification of total aflatoxins in commercial chicken feeds and food grains

Objective: This study aims to develop and validate an Attenuated Total Reflectance–Fourier Transform Infrared Spectroscopy (ATR-FTIR) spectroscopic technique combined with a partial least squares regression (PLSR) model for rapid quantification and monitoring of aflatoxins in chicken feeds and food grains. Materials and Methods: A model of ATR-FTIR-PLSR was developed using ATR-FTIR spectra of mixed aflatoxin standards in 100% acetonitrile (112 samples) and 75% methanol (112 samples), validated by testing its prediction on 125 feed/food samples spiked with variable concentrations of aflatoxins, and applied to screen 660 samples of commercial chicken feeds and food grains from Nigerian and Malaysian markets for total aflatoxins, for which the dietary exposure risks to aflatoxins (DERA) and associated hepatocellular carcinoma (HCC) risks were evaluated for both countries. Results: The ATR-FTIR-PLSR model demonstrated excellent prediction power [R2 = 99.59%, p = 0.001, root mean square error of calibration (RMSEC) = 1.69, RMSE p = 1.98, bias = −0.26], sensitivity (limit of quantitation and limit of the method < 5.0 ng/gm), precision (coefficient of variation = 0.97–1.72), and accuracy (% recovery of 88%–106%) in all the spiked samples. The model’s prediction was statistically reliable (R2 = 99.8%, p < 0.05) when compared with a high-performance liquid chromatography method. Levels of aflatoxins in the commercial samples signify high DERA (0.92–138.2 ng of aflatoxins/kg BW/day) and HCC risk (1.07%–159.91% of HCC/100,000 people/ year) in the exposed populations. Conclusions: Results feature the conceivable implementation of the proposed ATR-FTIR-PLSR model for rapid, accurate determination and monitoring of aflatoxinsin commercial chicken feeds and food grains; and the need to strengthen aflatoxin control/prevention strategies in the study populations. J. Adv. Vet. Anim. Res., 9(3): 546–564, September 2022 http://doi.org/10.5455/javar.2022.i624