Multivariate statistics is a tool for examining the relationship of multiple variables simultaneously. Principal component analysis (PCA) is an unsupervised multivariate analysis technique that simplifies the complexity of data by transforming them in a few dimensions showing their trends and correlations. Interests in XLSTAT as statistical software program of choice for routine multivariate statistics has been growing due in part to its compatibility with Microsoft Excel data format. As a case of study, multivariate analysis is used to study the effects of unfiltered beer-based marination on the volatile terpenes and thiols, and sensory attributes of grilled ruminant meats. PCA was conducted to determine the correlations between the abundances of volatile terpenes and thiols and sensory attribute scores in marinated grilled meats, as well as to analyze if there was any clustering based on the type of meat and marination treatments employed.•XLSTAT PCA output successfully reduced the number of variables into 2 components that explained 90.47% of the total variation of the data set.•PCA clustered marinated and unmarinated meats based on the presence and abundances of volatile terpenes, thiols and consumer sensory attribute scores.•PCA could be applied to explore relationships between volatile compounds and sensory attributes in different food systems.

Lipids are important biomolecules in all biological systems and serve numerous essential cellular functions. The global analysis of complex lipids is very challenging due to the extreme diversity in lipid structures. Variation in linkages and positions of fatty acyl chain(s) on the lipid backbone, functional group modification, occurrence of the molecular species as isomers or isobars are among some of the greatest challenges to resolve in lipidomics. In this work, we describe a routine analytical approach combining two liquid chromatography platforms: hydrophilic interaction (HILIC) and C30 reversed-phase chromatography (C30RP) coupled to high resolution mass spectrometry (HRMS) as complementary high throughput platforms to analyze complex lipid mixtures. Vascular plants (kale leaves and corn roots), rat brain and soil microbes were used as proxies to evaluate the efficiency of the enhanced approach to resolve traditional, as well as, modified lipids during routine lipidomics analysis. We report for the first time, the observation of a modified class of acylphosphatidylglycerol (acylPG) in corn roots by HILIC, and further resolution of the isomers using C30RP chromatography. We also used this approach to demonstrate the presence of high levels of N-monomethyl phosphatidylethanolamine (MMPE) in soil microbes, as well as to determine the regioisomers of lysophospholipids in kale leaves. Additionally, neutral lipids were demonstrated using C30RP chromatography in positive ion mode to resolve triacylglycerol isomers in rat brain. The work presented here demonstrates how the enhanced approach can more routinely permit novel biomarker discovery, or lipid metabolism in a wide range of biological samples.

Saponification is the process in which triglycerides are combined with a strong base to form fatty acid metal salts during the soap-making process. The distribution of unsaturated and saturated fatty acid determines the hardness, aroma, cleansing, lather, and moisturizing abilities of soaps. Plant extracts, such as rosemary, vegetable, and essential oils are frequently added to soaps to enhance quality and sensory appeal. Three natural soaps were formulated using cold saponification to produce a base or control bar (BB), hibiscus rosehip bar (H), and a forest grove bar (FG). Rosemary extract (R) or essential oil (A) blends were added as additives to each formulation prior to curing to evaluate the effects of natural plant additives on the lipid composition and sensory characteristics of these natural herbal soaps. A total of seven natural soaps, three without additives (BB, H, FG) and four with additives (BBR, HA, FGR, FGA), were manufactured and studied. The majority (86–99%) of the polyunsaturated fatty acids (5.0–7.0 µg/mg) remained unsaponified in the manufactured natural soaps regardless of feedstock used. Principal component analysis (PCA) analyses showed the unsaponifiable fatty acids were different in the hibiscus bar compared to the other bars. There was a very strong correlation between the content of unsaponified C18:3n3 and C18:1n9 in all natural soaps. These results indicate that unsaponified fatty acids are important contributors to the quality and overall sensory perception and preference of natural herbal soaps following manufacturing by cold saponification.