Phenolic compounds extracted from cactus seed oil were identified for the first time by HPLC-ESI-qToF-MS and subsequently quantified by HPLC-DAD. A total of 7 compounds were identified, vanillin, syringaldehyde, and ferulaldehyde were found to be the most abundant ones. The effect of geographical origin and roasting process of cactus seeds was evaluated. Differences between different locations were not found, however the roasting process had a significant effect on the amount of phenolic compounds. The amount of syringaldehyde, p-coumaric acid, p-coumaric acid ethyl ester, and ferulaldehyde increased during the roasting process. Nevertheless, the concentration of vanillin was not influenced by roasting. It was demonstrated that the increase of those compounds was due to the thermal degradation of lignin from the seeds during the roasting process of seeds.

The European Parliament identifies virgin olive oil (VOO) as one of the foods which are often subject to fraudulent activities. Possibilities of adulteration are the application of illegal soft deodorization of extra virgin olive oil (EVOO) or the commercialization of blends of EVOO with soft‐deodorized EVOO or refined vegetable oils. Despite the search for possibilities to prove the illegal soft deodorization of EVOO or the addition of cheaper vegetable oils to EVOO, suitable methods are still missing. Therefore, the aim of the study is to develop a new analytical and statistical approach addressing detection of mild deodorization or addition of refined foreign oils. For this purpose, VOOs are treated in lab‐scale for 1 h up to 28 days at different temperatures (20, 50, 60, 80,100, 110, and 170 °C) in order to simulate and study the effect of heat treatment on known analytical parameters by near infrared spectroscopy (NIR). A logit regression model enabling the calculation of the probability for a heat treatment is developed. This new methodology allows detecting both soft deodorized olive oils and blends of EVOO with cheaper full refined vegetable oils. Adding only 10% of full refined oil could be detected in extra VOO.Practical Applications: NIR methods combined with chemometrics have become one of the most attractive analytical tools to control quality of food. It is a simple, precise, and rapid method. All relevant analytical parameters of oxidative and thermal fat degradation can be determined in a single run and be used to detect adulterated virgin olive oils (VOOs). The use of a simple equation developed from the logistic regression using peroxide value, K‐values, p‐anisidine value, pyropheophytine, 1,2‐diacylglycerols, total polar compounds and monomeric oxidized triacylglycerols, and other well‐known parameters allows to detect mild deodorized olive oils or also blends of VOO with soft‐deodorized ones or the addition of low amounts of foreign vegetable oils. This technique has potential to be used as a screening method for the detection of adulterated olive oils using both the traditional laboratory methods and the corresponding NIR‐methods.

Volatile compounds from oils extracted from cactus seeds (Opuntia ficus-indica) of five regions of Morocco were analyzed by dynamic headspace-GC/MS. Aroma active compounds were characterized by olfactometry. A total of 18 compounds was detected with hexanal, 2-methyl propanal, acetaldehyde, acetic acid, acetoin and 2,3-butanedione as most abundant. Olfactometric analysis showed that those compounds are aroma active; therefore, cactus seed oil flavor can be attributed to those compounds. Moreover, the effect of roasting of cactus seeds on the composition of volatile compounds in the oil was investigated. Especially the concentration of compounds known as products from the Maillard reaction increased significantly with roasting time such as furfural, furan, 3-methyl furan, 2-butanone, thiophene, 2, 3- dithiabutane, methyl pyrazine, 2-methyl pyrimidine, 2-metoxy phenol, dimethyl trisulfide and 5-methyl furfural.

The verification of the geographical origin of olive oils by analytical techniques is still a challenge. The goal of this work is to explore the application and accuracy of different chemometric tools combined with near infrared spectroscopy (NIR) based analytical methods in the field of geographical authenticity of olive oils. As olive oils associated with different geographical origins are mainly characterized by different fatty acid (FA) and triacylglycerol (TAG) compositions, NIR methods for the fast and reliable determination of these parameters are developed. Next, these NIR methods are used to characterize a comprehensive set of olive oils (n > 5000) derived from 19 different countries. This set of data is used to build a statistical workflow, which allows the determination of the geographical origin of unknown olive oil samples. First of all, the untreated data set is pretreated by k‐means clustering and the selection of the relevant analytical variables by principal component analysis (PCA) and linear discriminant analysis (LDA) and min/max normalization of all parameters. Subsequently, classification is performed with a reduced sample set of the 200 most similar samples identified by k‐nearest neighbor tool (kNN). For classification purpose kNN, LDA, naïve Bayes classifier, and logit regression are applied.Practical Applications: The established statistical workflow can be used to verify the geographical origin of olive oils. The application and usage of up to four different statistical models for classification purpose results in a superior probability of the predicted origin in comparison to the application of only one single statistical classification test. As standardized methods are used as reference methods for building the NIR methods, the FA and TAG composition and the iodine value can be either determined by the standard methods or by the described NIR method. The presented statistical approach will help to build up a system for the verification of the geographical origin of olive oils.

In the presented study a non-targeted approach using high-performance liquid chromatography coupled to electrospray ionization quadrupole time-of-flight mass spectrometry (HPLC-ESI-qToF-MS) combined with chemometric techniques was used to build a statistical model to verify the geographic origin of virgin olive oils. The sample preparation by means of liquid/liquid extraction of polar compounds was optimized regarding the number of multiple extractions, application of ultrasonic treatment and temperature during concentration of the analytes. The presented workflow for data processing aimed to identify the most predictive features and was applied to a set of 95 olive oils from Spain, Italy, Portugal and Greece. Different strategies for data reduction and multivariate analysis were compared. Stepwise variable selection showed for both applied multivariate models—linear discriminant analysis (LDA) and logit regression (LR)—to be the most suitable variable selection strategy. The 10-fold cross validation of the LDA showed a classification rate of 83.1% for the test set. For the LR models the prediction accuracy of the test set was even higher with values of 90.4% (Portugal), 86.2% (Italy), 93.8% (Greece) and 88.3% (Spain). Moreover, the reduction of features allows an easier following up strategy for identification of the unknowns and defining marker substances.

Physicochemical parameters, nutritional composition and therapeutic effect of Opuntia ficus-indica seed oil extracted by different standard extraction techniques were reviewed. Cactus seeds contain between 3.4 and 14.4% oil with linoleic acid and oleic acid as major fatty acids. The most prominent triacylglycerols are trilinolein (LLL), dilinoleic-monoolein (LLO), dilinoleic-monopalmitin (LLP) and dioleinic-monolinolein (OOL). γ-tocopherol amounts to 90% and higher of the total tocopherols. The main phytosterol is β-sitosterol varying from 71.6% to 79.1% of the total content (0.9–16.06 g/kg). The most dominant volatile compounds are aldehydes. Cactus seed oil is rich in phenolic compounds, where vanillin, syringaldehyde, and ferulaldehyde are the main representatives.