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Background: Fatty acids are the major components in extra virgin olive oil, and they are considered as a quality parameter to its authentication. As fraudulent practices are the most important problem in this sector, fast, reliable and cost-effective techniques, such as Raman spectroscopy, have been successfully applied, in combination with chemometrics, to determine the fatty acid profile of oils., Results: The huge amount of information provided by Raman spectra is reduced in a few orthogonal components of principal component analysis (PCA). The goodness-of-fit of the statistical models including only these PCA factors is considerably increased by introducing dummy variables, associated with the harvest, and some agro-climatic variables (temperature, humidity, wind speed, radiation, precipitation and evapotranspiration). Many of these additional variables are statistically relevant in models using either the global sample or subsamples of Andalusian provinces or olive varieties., Conclusions: The regression models using only Raman spectral information are clearly improved by the consideration of harvesting time and agro-climatic data, a useful result as trade standard applying to olive oils limits values for disaggregated fatty acids to authenticate olive oils. Nevertheless, the effect (or the statistical relevance) of these variables depends on the specific type of fatty acid, geographical region (province) or olive variety. © 2019 Society of Chemical Industry., (© 2019 Society of Chemical Industry.)

We have determined delta(13)C, delta(2)H and delta(18)O isotopic abundances in Andalusian olive oils. In addition, the fatty acid composition and the distribution of isomers at positions 1,3 and 2 of glycerol were determined by (1)H and (13)C nuclear magnetic resonance (NMR) spectroscopy, respectively. Isotopic results obtained for four series of oil samples extracted from olives harvested in the 2004/05 and 2005/06 seasons are discussed in terms of olive variety, ripeness, geographical origin, fatty acid composition and growing altitude. A distinction was also established between olives grown in irrigated and in dry land by studying selected samples of the previous series and others from the 2005/06, 2006/07, 2007/08 and 2008/09 seasons. The results showed that olive ripeness does not influence the abundance of any of the three isotopes studied. On the other hand, the olive variety influences the abundance of the oxygen and hydrogen isotopes, and also, less markedly, that of carbon. No clear-cut effect of height or latitude on isotope values is observed, probably because the olive variety also changes with height and latitude, thus masking such influences. The oil samples from dryland-grown olives had increased delta(13)C values relative to irrigation-grown olives. In addition, no definite relationship appears to exist between isotope distribution and fatty acid composition. Finally, oil samples from olives harvested in the 2005/06 season in Italy could be distinguished from those from Spain in terms of their isotopic values (delta(2)H mainly)., (Copyright 2010 John Wiley & Sons, Ltd.)

Fatty acids are the major compounds in olive oils, and the determination of their profile is very useful in order for the authentication of the high quality of extra virgin olive oil (EVOO) and the evaluation of its purity and traceability. This work considers the estimations of saturated (SAFA), monounsaturated (MUFA) and polyunsaturated (PUFA) fatty acids obtained by gas chromatography (GC), 13C (carbonyl, C‐16, and aliphatic carbons regions), and 1H NMR spectra. The aim of this paper is to analyze the correlation structure being between the abovementioned fatty acids estimations and some long‐run agroclimatic measurements (temperature, humidity, wind speed and direction, radiation, precipitation, and evapotranspiration), which were downloaded from the official website of the Andalusian Automatic Weather Stations (AWSs). The versatile graphical possibilities of the free software R‐project allow the design of computational programs providing interesting conclusions about the described correlations as a function of month, variety of olive, and protected designation of origin (PDO). The statistically significant correlations could determine relevant agroclimatic information to be included, in a further research, among the explanatory variables in regression models in order to improve the estimation of fatty acid profile of EVOOs, considered as a quality parameter in their authentication. Fatty acids are the major compounds in olive oils and very useful in order to the authentication of the high quality of extra virgin olive oil (EVOO). This paper analyzes the effect of agroclimatic big fata, instead of a meteorological factor, on EVOO fatty acid profile determined by GC and NMR spectra. The power of the free software R‐project and its versatile graphical possibilities allows the design of computational programs providing interesting conclusions about the described correlations as a function of month, variety of olive, and protected designation of origin (PDO). [ABSTRACT FROM AUTHOR]

Extra virgin olive oil (EVOO) is very appreciated by its taste, flavor, and benefits for health, and so, it has a high price of commercialization. This fact makes it necessary to provide reliable and cost‐effective analytical procedures, such as near‐infrared (NIR) spectroscopy, to analyze its traceability and purity, in combination with chemometrics. Fatty acids profile of EVOO, considered as a quality parameter, is estimated, firstly, from NIR data and, secondly, by adding agro‐climatic information. NIR and agro‐climatic data sets are summarized by using principal component analysis (PCA) and treated by both scalar and functional approaches. The corresponding PCA and FPCA are progressively introduced in regression models, whose goodness of fit is evaluated by the dimensionless root‐mean‐square error. In general, SFAs, MUFAs, and PUFAs (and disaggregated fatty acids) estimations are improved by adding agro‐climatic besides NIR information (mainly, temperature or evapotranspiration) and considering a functional point of view for both NIR and agro‐climatic data. [ABSTRACT FROM AUTHOR]