Detection of fraud of palm, sunflower, and corn oil in butter using HPLC profile of tocopherols and tocotrienols by response surface method

Machine learning-enabled high-throughput industry screening of edible oils

Long-term consumption of mixed fraudulent edible oils increases the risk of developing of chronic diseases which has been a threat to the public health globally. The complicated global supply-chain is making the industry malpractices had often gone undetected. In order to restore the confidence of consumers, traceability (and accountability) of every level in the supply chain is vital. In this work, we shown that machine learning (ML) assisted windowed spectroscopy (e.g., visible-band, infra-red band) produces high-throughput, non-destructive, and label-free authentication of edible oils (e.g., olive oils, sunflower oils), offers the feasibility for rapid analysis of large-scale industrial screening. We report achieving high-level of discriminant (AUC > 0.96) in the large-scale (n ≈ 11,500) of adulteration in olive oils. Notably, high clustering fidelity of 'spectral fingerprints' achieved created opportunity for (hypothesis-free) self-sustaining large database compilation which was never possible without machine learning. (137 words).

Effect of Roasting on the Chemical Composition and Oxidative Stability of Tomato (Solanum lycopersicum L.) Seed Oil

In this study, tomato seed (TS) samples were subjected to different roasting conditions (90-170 °C and 10-30 min) to compare their effects on the chemical composition and oxidative stability of tomato seed oil (TSO). Unroasted TS was considered as a control sample. Our results revealed that moderate roasting (130 °C/20 min) can significantly increase the content of linoleic acid (54.01-54.89%), linolenic acid (2.17-2.41%), phytosterols (2789.56-3037.31 mg/kg), squalene (5.06-13.10 mg/kg), total phenols (22.37-22.67 mg GAE/100 g), and other functional components (p < 0.05) in TSO, while the antioxidant activity (via DPPH, ABTS, and FRAP assays) also increased. In addition, the tocopherol content decreased significantly (758.53-729.50 mg/kg). Accelerated oxidation experiments showed that roasting (170 °C/30 min) increased the oxidative stability index (OSI) of TSO from 5.35 to 7.07 h (p < 0.05). Furthermore, roasting gradually increased the content of 5-hydroxymethylfurfural (HMF) (0-1.74 mg/kg), which indicates that the oxidative stability and the degree of the Maillard reaction increased upon roasting. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) showed that moderate roasting (130 °C/20 min) improved the chemical composition, antioxidant activity, and oxidative stability of TSO. Furthermore, this work provides a useful theoretical basis for the processing and wide application of TSO in the pharmaceutical and food industries.

A pretreatment method combined matrix solid-phase dispersion with dispersive liquid-liquid micro-extraction for polybrominated diphenyl ethers in vegetables through quantitation of gas chromatography-tandem mass spectrometry (GC-MS)

Herein, a novel pretreatment method for extraction of polybrominated diphenyl ethers (PBDEs) using matrix solid phase dispersion (MSPD) and depth purification using dispersive liquid-liquid micro-extraction (DLLME) from vegetables was designed. The vegetables included three leafy vegetables (Brassica chinensis, Brassica rapa var. glabra Regel and Brassica rapa L.), two root vegetables (Daucus carota and Ipomoea batatas (L.) Lam.), and Solanum melongena L. First, the freeze-dried powders of vegetables and sorbents were evenly ground to a mixture, which was then loaded into a solid phase column containing two molecular sieve spacers, one positioned at the top and the other at the bottom. The PBDEs were eluted with a small amount of solvent, concentrated, redissolved in acetonitrile, and then mixed with extractant. Next, 5 mL water was added to form an emulsion and centrifuged. Finally, the sedimentary phase was collected and injected into a gas chromatography-tandem mass spectrometry (GC-MS) system. The main factors such as the type of adsorbent, ratio of sample mass and adsorbents, volume of elution solvent used in the MSPD process, as well as the types and volume of dispersant and the, extractant used in DLLME were all evaluated using the single factor method. Under optimal conditions, the proposed method showed good linearity (R² > 0.999) within the range of 1 to 1000 g kg^-1 for all PBDEs and satisfactory recoveries of spiked samples (82.9-113.8%, except for BDE-183 (58.5-82.5%)) and matrix effects (-3.3-18.2%). The limits of detection and the limits of quantification were in the range of 1.9-75.1 g kg^-1 and 5.7-25.3 g kg^-1, respectively. Moreover, the total pretreatment and detection time was within 30 min. This method proved to be a promising alternative to other high-cost and time-consuming and multi-stage procedures for determination of PBDEs in vegetables.

Healthier Oils: A New Scope in the Development of Functional Meat and Dairy Products: A Review

In the present day, it has been widely established that a high intake of animal fat that contains a high content of saturated fatty acids may cause several life-threatening diseases, including obesity, diabetes-type 2, cardiovascular diseases, as well as several types of cancer. In this context, a great number of health organizations and government agencies have launched campaigns to reduce the saturated fat content in foods, which has prompted the food industry, which is no stranger to this problem, to start working to develop foods with a lower fat content or with a different fatty acid profile. Nevertheless, this is not an easy task due to the fact that saturated fat plays a very important role in food processing and in the sensorial perception of foods. Actually, the best way to replace saturated fat is with the use of structured vegetable or marine oils. The main strategies for structuring oils include pre-emulsification, microencapsulation, the development of gelled emulsions, and the development of oleogels. This review will examine the current literature on the different (i) healthier oils and (ii) strategies that will be potentially used by the food industry to reduce or replace the fat content in several food products.

An effective and stability-indicating method development and optimization utilizing the Box-Behnken design for the simultaneous determination of acetaminophen, caffeine, and aspirin in tablet formulation

Analytical techniques must be sensitive, specific, and accurate to assess the active pharmaceutical ingredients in pharmaceutical dosage forms. The quality-by-design (QbD) application has proven to be a practical method for magnifying HPLC operations. This article discusses the successfully developed QbD-based stability-indicative LC method for evaluating acetaminophen, caffeine, and aspirin (ASP) in tablet dosage form. To achieve the necessary chromatographic separation, Milli-Q water, methanol, and glacial acetic acid were employed in the following ratios: 63:35:2 (v/v/v) for mobile phase A and 18:80:2 (v/v/v) for mobile phase B. The flow rate, column temperature, and detecting wavelength were 1.0 ml/min, 40°C, and 275 nm, respectively, and an InertSustain C18 analytical column (150 × 4.6 mm, 3 μm) was used. Linearity was between 10.0 and 150.0 μg/ml for ASP and acetaminophen and between 2.6 and 39.0 μg/ml for caffeine. The accuracy findings were more than 97%, and the correlation coefficient for all three components was found to be greater than 0.999. The validated HPLC method yielded reliable and accurate results. ASP was shown to be vulnerable to both acid and alkaline hydrolysis in the forced degradation study. The described method is capable of separating the degradants produced during stress testing and is regarded as stability indicating. The proposed method can be used for a wider range of other formulations with an appropriate diluent selection and sample preparation procedure optimization.

Compact low-field NMR spectroscopy and chemometrics applied to the analysis of edible oils

Compact nuclear magnetic resonance (NMR) spectroscopy combined with chemometric tools opens new perspectives for NMR use. This work compares the potential of 43, 60 and 400 MHz NMR spectroscopy for quality control of edible oils. Partial least squares regression (PLSR) and support vector regression (SVR) models built on the three NMR devices had equivalent performances for fatty acids and iodine value, and the models built with the low field spectra were equivalent to the high field. Moreover, performances for calibration indicated that most of the models built with medium/or high-resolution fields presented reproducibility values lower than the minimum accepted by the American Oil Chemists' Society (AOCS). Compared to classical methods, this new approach allows the application of medium resolution devices as a sample screening tool in analytical laboratories since it allows the spectrum obtention in a few seconds, without the need for sample preparation or the use of deuterated solvents.