Near-infrared spectroscopy for quick detection of chemical property changes of repetitively heated coconut oil.

Abstract

In the low-temperature regions of Sri Lanka, coconut oil vendors frequently resort to repetitive heating practices to maintain the liquid state of the oil for commercial purposes. Recurrent heating of coconut oil leads to the formation of toxic compounds like peroxides and hydrocarbons, despite health risks. This research investigated the impact of repeated heating on the quality of various coconut oil varieties in Sri Lanka, addressing a gap in existing methodologies. These include virgin, refined, milk-extracted, copra-extracted, and commercially heated coconut oils that have been heated repeatedly. With the aid of Soft Independent Modelling of Class Analogy (SIMCA) and Partial Least Squares (PLS) models and Near-Infrared (NIR) spectroscopy, the study investigated the compositional changes of different coconut oil categories, revealing varying predictive capacities for different types. Virgin coconut oil exhibits robust resistance to degradation, evidenced by a Standard Error of Prediction (SEP) of 0.018 and a correlation coefficient of 0.904. Conversely, refined coconut oil displays increased susceptibility to quality alterations upon repetitive heating, as indicated by a SEP of 0.027 and a correlation coefficient of 0.742. Milk-extracted coconut oil shows a SEP of 0.015 with a correlation coefficient of 0.767, while copra-extracted coconut oil yields a SEP of 0.017 and a correlation coefficient of 0.734. Commercially scaled repetitively heated coconut oil registers a higher SEP of 0.037 and a correlation coefficient of 0.781, signaling substantial quality degradation under commercial heating conditions. Critical wavelengths for predicting peroxide value and heating durations are identified at 1012.751nm and 663.229nm, respectively. Notably, SIMCA models for each coconut oil type demonstrate 100% validation accuracy without inconsistencies and highlights the use of NIR spectroscopy for rapid quality assessment, detecting significant quality alterations caused by repetitive heating, especially elevated peroxide values. It emphasizes the potential of NIR spectroscopy as a rapid assessment tool for evaluating repetitively heated coconut oil quality and understanding its chemical transformations during repetitive heating. The research highlights the importance of adopting prudent culinary practices to mitigate potential health hazards associated with deteriorated oil quality.