Application of near-infrared spectroscopy as at line method for the evaluation of histamine in tuna fish (Thunnus albacares)

Abstract

The assessment of histamine levels in fishery products has emerged as a paramount issue in the context of global food safety, given its profound implications for human health and the consequential impact on food quality and trade. Histamine intoxication, stemming from the ingestion of foods containing heightened histamine levels, results from the bacterial decarboxylation of histidine under conditions of improper handling, processing, or storage. This study endeavors to provide a thorough examination of histamine contamination in frozen-thawed tuna (Thunnus albacares) samples, employing an integrated approach that combines near-infrared spectroscopy (NIRS) with advanced machine learning techniques. One hundred and one samples were considered, and a systematic fortification process was applied to obtain samples with 4 histamine concentrations (0; 50; 150; 250 mg/kg); the fortification levels were confirmed by the LC-MS/MS analysis. Subsequently, NIRS spectra were collected and chemometric analyses, including modified partial least squares regression (MPLS) and support vector machine (SVM), were employed for quantitative and qualitative evaluation, respectively. Histamine quantification through MPLS utilizing the full spectrum exhibited good predictive performance in cross-validation and in hold-out validation (R2CV = 0.88; R2P = 0.74, respectively), confirming the potential of NIRS for estimating histamine levels in tuna. SVM classification models, both binary (presence/absence) and multiclass (four levels), demonstrated high accuracy (100% and 93%, respectively). The study highlights the effectiveness of NIRS combined with machine learning for rapid and accurate histamine detection in frozen-thawed tuna, offering a non-destructive, environmentally friendly alternative to traditional methods. This approach holds significant promise for food business operators and regulatory authorities, enhancing product safety, quality control, and decision-making processes related to histamine contamination in the seafood industry.