# Investigation of Oil Extracted from Roasted and Unroasted Oats with Use of Chemometrics
## 1 Introduction
In research conducted by scientists, it was found that oxidative stability was slightly elevated with the increased temperature and longer duration of the roasting process [18]. The crucial Maillard reaction could partially explain this increase, the interaction of proteins with reducing sugars during high-temperature roasting treatment, leading to Maillard reaction products' formation [19]. As reported by [20], melanoidins, products of non-enzymatic browning, reportedly show strong antioxidant activity, which can positively affect the oxidative stability of roasted seeds and nuts. Pressure differential scanning calorimetry (PDSC) is an appropriate unbiased method for assessing oxidative stability [18]. The acid value (AV) and peroxide value (PV) are two critical measures of the quality of vegetable oils. The AV indicates the level of oil hydrolysis and is expressed as the amount of KOH (in milligrams) required to neutralise the free fatty acids present in 1 g of oil [21]. Determining the PV of edible oils is imperative, as PV is one of the most typically utilised quality parameters for monitoring lipid oxidation and controlling oil quality. Various methodologies have been devised to determine the PV of oils, but iodometric titration is the generally preferred and widely used method for PV determination [22]. The PV of edible oils is measured in milliequivalents (meq) of active oxygen per kilograme of oil. If the PV exceeds the critical value, the oil can taste rancid and cause food poisoning [23]. The spectral data model, a tool that has gained significant traction in various research fields over the past decade, is known for its reliability in calibrating parameters like the peroxide value. Its consistent delivery of accurate and dependable results has made it a trusted ally for researchers, who have used it to enhance the reliability of their studies in diverse research areas. IR spectroscopy is thoroughly used for spectral analysis of edible oils, as presented in the literature [19; 24]. The methodology utilises the PCA and MCR [24]. It also uses SVM-DA, SIMCA, and PLS-DA techniques [19]. The spectral models established for oils can accurately determine the level of saturation or unsaturation in edible oils and provide precise quantitative measures for the amount of oleic and linoleic acids present [11]. They can also be used to study the oxidation of edible oils and the determination of peroxide value in olive, sunflower, and rapeseed oils [24]. They can also serve to classify edible oils, e.g., to differentiate canola, sunflower, corn, and soybean oils [19]. The purpose of the current investigation was to use the chemometrics approach to construct a series of statistical reference and discriminant models based on spectral and classical reference data to show the ability of IR spectroscopy to evaluate the sample of unknown oil versatilely. It aimed to model/determine the oxidative induction time, acid value, and peroxide value of oil extracted from thermally treated oats (160 \({}^{\circ}\)C). Next, the reconstruction of technological process details, i.e., the time of roasting oats and the oil extracted from them, was planned. Finally, rapid discrimination of oil extracted from unroasted and roasted oats was intended. Additionally, with the use of instrumental methods and the application of a constructed model, the effect of the roasting process on the quality of oil contained in oats was designed. In general, chemometrics is the activity that combines and correlates data from different analytical methods. As a result, the most appropriate method for a given purpose can be used instead of other, more laborious, or more expensive methods. From the literature survey, only a few scientific positions dealing with applying IR spectroscopy to investigate chemical changes in roasted oat grain oils have been found. Hence, the current topic covers a particular scientific gap.