Simultaneous fluorometric determination of chlorophylls a and B and pheophytins a and B in olive oil by partial least-squares calibration

The resolution of quaternary mixtures of chlorophylls a and b and pheophytins a and b has been accomplished by partial least-squares (PLS) multivariate calibration, applied to the fluorescence signals of these pigments. The total luminescence information of the compounds has been used to optimize the spectral data set to perform the calibration. After preliminary studies, a method is described in acetone media, to avoid emulsions with the olive oil samples. Different scanning paths have been selected for each method. For the simultaneous determination of the pigments in olive oil samples, a comparative study of the results found by using excitation, emission, and synchronous spectral data, as analytical signal, was performed. The excitation spectra were selected as the better analytical signals for the determination of the pigments in olive oil samples. The optimum wavelength range to record the excitation spectra (lambda(em) = 662 nm) was selected to minimize the contribution of pheophytin a and to maximize the contribution of the other pigments, which are the minor constituents in olive oil. Determination of these pigments in olive oil samples was effected from the excitation spectra of dissolutions o suitable aliquots in acetone. Recovery values from olive oil, spiked with chlorophylls a and b and pheophytins a and b, were in the ranges of 70-112, 71-111, 76-105, and 82-109%, respectively.     

Feasible application of a portable NIR-AOTF tool for on-field prediction of phenolic compounds during the ripening of olives for oil production

Olive fruits of three different cultivars (Moraiolo, Dolce di Andria, and Nocellara Etnea) were monitored during ripening up to harvest, and specific and total phenols were measured by HPLC (High Pressure Liquid Chromatography). On the same olive samples (n = 450), spectral detections were performed using a portable NIR (Near Infrared)-AOTF (Acousto Optically Tunable Filter) device in diffuse reflectance mode (1100-2300 nm). Prediction models were developed for the main phenolic compounds (e.g., oleuropein, verbascoside, and 3,4-DHPEA-EDA) and total phenols using Partial Least Squares (PLS). Internal cross-validation (leave-one-out method) was applied for calibration and prediction models developed on the data sets relative to each single cultivar. Validation of the models obtained as the sum of the three sample sets (total phenols, n = 162; verbascoside, n = 162; oleuropein, n = 148; 3,4-DHPEA-EDA, n = 162) were performed by external sets of data. Obtained results in term of R(2) (in calibration, prediction and cross-validation) ranged between 0.930 and 0.998, 0.874-0.942, and 0.837-0.992, respectively. Standard errors in calibration (RMSEC), cross-validation (RMSECV), and prediction (RMSEP) were calculated obtaining minimum error in prediction of 0.68 and maximum of 6.33 mg/g. RPD ratios (SD/SECV) were also calculated as references of the model effectiveness. This work shows how NIR-AOTF can be considered a feasible tool for the on-field and nondestructive measurement of specific and total phenols in olives for oil production.     

Detection of rancid defect in virgin olive oil by the electronic nose

A sensor array of 32 conducting polymer sensors has been used to detect the rancid defect in virgin olive oils. A training set, composed of admixtures of a Portuguese virgin olive oil with different percentages (0-100%) of a rancid standard oil, was used for the selection of the best sensors classifying correctly the samples. Information on volatile compounds responsible for rancidity and the sensory evaluation of samples by assessors were used for explaining the mathematical selection of sensors. A tentative calibration, using unsupervised procedures (PCA and MDS) and a nonlinear regression, was carried out, with the training set, and later confirmed with a test set with which rancid commercial samples of different varieties were used to spike a Greek extra virgin olive oil at low levels of rancidity (0.5-6%).     

Cluster analysis applied to the exploratory analysis of commercial spanish olive oils by means of excitation-emission fluorescence spectroscopy

Olive oil fluorescence is related to oil composition. Here it is shown that the natural clustering of different types of commercial Spanish olive oils depends on their fluorescence excitation-emission matrices (EEMs). Fifty-six commercial samples of olive oil (29 virgin olive oils, 20 pure olive oils, and 7 olive-pomace oils) were used. The clustering method was hierarchical agglomerative clustering using the Euclidean distance as a similarity measure and the average linkage. Two spectral ranges were considered (which either contained the fluorescence peak of the chlorophylls or did not), and various methods for preprocessing the fluorescence spectra were compared. The oils were clearly distinguished using the unfolded EEMs measured between lambda(ex) = 300-400 nm and lambda(em) = 400-600 nm. The optimal preprocessing was normalization of the unfolded spectra followed by column autoscaling. Also shown are the advantages of using second-order data (EEMs) instead of first-order data (a single fluorescence spectrum) for each sample.     

分提橄榄油中主要脂肪酸成分傅里叶变换红外光谱法测量（英）

为了测量从橄榄油中分提的高、低熔点油脂的脂肪酸成分,在4 000～600 cm-1 的范围测量了31个含有不同脂肪酸成分植物油的傅里叶变换红外光谱,用于建立偏最小二乘（PLS）回归分析校正模型。在油脂的傅里叶变换红外光谱变量和脂肪酸组成变量之间建立了交叉验证的PLS校正模型。为了校正油酸和亚油酸含量,在4?000～600 cm-1 的频率范围,经平滑,二阶导数,规范化处理的红外光谱获得了最好的交叉验证校正模型和最佳的预测结果。PLS校正模型预测结果表明,与高熔点橄榄油（油酸,72.29%,亚油酸,9.98%）相比,低熔点橄榄油含有较高的油酸含量和亚油酸含量（油酸,77.46%,亚油酸,12.51%）,预测的结果与气相色谱测量的结果有很好的一致性。建立的PLS校正模型预测橄榄油的不饱和脂肪酸含量具有较好的相关性。该研究为分提油脂质量的判别评价提供了便捷的方法。     

利用可见光近红外的尾矿区农田土壤Cu含量反演

矿山开采普遍存在土壤重金属污染问题,有效的进行尾矿区农田土壤重金属含量估算迫在眉睫。以陕西金堆城矿区尾矿为研究区,采集土壤样本,测量土壤可见光近红外光谱,测试分析土壤铜元素含量。将Isomap（Isometrio mapping）和LLE（locally linear embedding）流形学习方法应用于土壤高光谱降维,基于随机森林构建估算模型,反演土壤铜含量。结果表明：降维后的高光谱数据反演精度更高,Isomap降维后模型预测结果均方根误差为30.50,R2=0.76,优于LLE降维结果。研究为尾矿区土壤Cu元素含量的快速反演估算提供了理论依据。     

基于近红外光谱技术的茶油原产地快速鉴别

为研究茶油原产地溯源问题,维护其市场秩序,促进公平竞争。该文利用近红外光谱技术采集湖南、江西、安徽和浙江4个不同产地茶油的光谱数据,并运用 Savitzky-Golay 平滑（savitzky-golay, SG）、多元散射校正（multiplicative scatter correction, MSC）、一阶导数（first derivation, FD）和矢量归一化（vector normalization, VN）等4种方法对其进行预处理。采用偏最小二乘法（partial least squares, PLS）提取最佳主成分,构建 PLS 回归模型;同时,采用主成分分析（principal component analysis, PCA）和 PLS 算法提取最佳主成分,作为 BP 人工神经网络（BP artificial neural network, BPANN）输入变量,构建 PCA-BPANN 和 PLS-BPANN 模型。以验证集相关系数 RP 和验证集均方根误差 RMSEP 为模型的评价指标,分别优选最佳 PLS 和 BPANN 模型。试验结果表明,SG-PLS-DA 和 SG-PLS-BPANN-DA 模型对未知样本的整体分类准确率均大于90%。其中,SG-PLS-BPANN-DA 的鉴别效果优于前者,其建模集相关系数 RC、均方根误差 RMSEC 分别为0.974、0.170,验证集相关系数 RP、均方根误差 RMSEP 分别为0.972、0.172,对上述两类样本集的总体分类准确率分别为98.15%、95.83%,该模型能较准确鉴别茶油原产地。研究结果可为快速辨别茶油原产地提供参考。     

Parent and harvest year effects on near-infrared reflectance spectroscopic analysis of olive (Olea europaea L.) fruit traits

The influence of parent and harvest year on the determination of oil, moisture, oleic acid, and linoleic acid contents in intact olive fruit was studied by near-infrared spectroscopy (NIRS). Spectral data from 400 to 1700 nm were recorded on 437 fruit samples collected in 1996 and 1997 from seedling plants derived from three different female parents. Partial least squares models were developed using samples for each year and for each female parent separately and were validated against the other groups. Calibration models were accurate enough to predict all constituents in new samples from a different female parent but were not transferable across years. However, a calibration equation of sufficient accuracy was obtained from the combined data set (r values of 0.94, 0.93, 0.84, and 0.88 and RMSECV values of 1.33, 1.88, 4.73, and 2.91 for oil, moisture, oleic acid, and linoleic acid contents, respectively). These results demonstrate the utility of NIRS as a selection tool in olive breeding programs.     

基于PCA和SRRI的潮土土壤属性与田间光谱关系研究

应用光谱分析技术可以快速无损地对土壤属性进行定量分析,是提高农田管理效率的有效途径。使用ASD Field Hand Held光谱仪测定了46个潮土土样在田间环境中350～1075nm的光谱。采用主成分分析方法和逐步线性回归方法得到了土壤反射辐射指数(SRRI)。该指数描述了土壤属性对光谱的综合作用和反射辐射能的强弱程度。结果表明潮土pH和CEC与SOC、Fe2O3、Mn和TN等对光谱的影响是不同的。采用PCA和SRRI方法进行土壤属性的光谱估计,其结果精度优于偏最小二乘回归方法(PLS),而且利用土壤属性对SRRI的贡献可准确衡量光谱估计土壤属性的可行性。     

Detection of vinegary defect in virgin olive oils by metal oxide sensors

An array of metal oxide sensors has been set up for detecting the vinegary defect in virgin olive oil. The optimization process was carried out evaluating the variables affecting the process by three desirability functions. Repeatability studies for 6 months and within day were done to evaluate the sensor responses and remove those with high relative standard deviation. The sensor responses were preprocessed applying five weight functions previously to build a regression model. Samples of Spanish Arbequina and Picual virgin olive oil varieties spiked with different amounts of acetic acid (15-200 mg/L) were used as a training set for the regression model. The test set was composed of samples of Italian Coratina virgin olive oil spiked with the vinegary standard at five percentages (10, 25, 40, 50, and 75). A fine-adjusted regression coefficient (R(adj)(2) = 0.98) was computed with the test set.     

Detection of extra virgin olive oil adulteration with lampante olive oil and refined olive oil using nuclear magnetic resonance spectroscopy and multivariate statistical analysis

High-field 31P NMR (202.2 MHz) spectroscopy was applied to the analysis of 59 samples from three grades of olive oils, 34 extra virgin olive oils from various regions of Greece, and from different olive varieties, namely, 13 samples of refined olive oils and 12 samples of lampante olive oils. Classification of the three grades of olive oils was achieved by two multivariate statistical methods applied to five variables, the latter being determined upon analysis of the respective 31P NMR spectra and selected on the basis of one-way ANOVA. The hierarchical clustering statistical procedure was able to classify in a satisfactory manner the three olive oil groups. Subsequent application of discriminant analysis to the five selected variables of oils allowed the grouping of 59 samples according to their quality with no error. Different artificial mixtures of extra virgin olive oil-refined olive oil and extra virgin olive oil-lampante olive oil were prepared and analyzed by 31P NMR spectroscopy. Subsequent discriminant analysis of the data allowed detection of extra virgin olive oil adulteration as low as 5% w/w for refined and lampante olive oils. Further application of the classification/prediction model allowed the estimation of the percent concentration of refined olive oil in six commercial blended olive oils composed of refined and virgin olive oils purchased from supermarkets.     

Updating a synchronous fluorescence spectroscopic virgin olive oil adulteration calibration to a new geographical region

Detecting and quantifying extra virgin olive adulteration is of great importance to the olive oil industry. Many spectroscopic methods in conjunction with multivariate analysis have been used to solve these issues. However, successes to date are limited as calibration models are built to a specific set of geographical regions, growing seasons, cultivars, and oil extraction methods (the composite primary condition). Samples from new geographical regions, growing seasons, etc. (secondary conditions) are not always correctly predicted by the primary model due to different olive oil and/or adulterant compositions stemming from secondary conditions not matching the primary conditions. Three Tikhonov regularization (TR) variants are used in this paper to allow adulterant (sunflower oil) concentration predictions in samples from geographical regions not part of the original primary calibration domain. Of the three TR variants, ridge regression with an additional 2-norm penalty provides the smallest validation sample prediction errors. Although the paper reports on using TR for model updating to predict adulterant oil concentration, the methods should also be applicable to updating models distinguishing adulterated samples from pure extra virgin olive oil. Additionally, the approaches are general and can be used with other spectroscopic methods and adulterants as well as with other agriculture products.     

Biosensor measurements of polar phenolics for the assessment of the bitterness and pungency of virgin olive oil

Bitterness and pungency, sensory quality attributes of virgin olive oil, are related to the presence of phenolic compounds. Fast and reliable alternatives for the evaluation of sensory attributes and phenolic content are desirable, as sensory and traditional analytical methods are time-consuming and expensive. In this study, two amperometric enzyme-based biosensors (employing tyrosinase or peroxidase) for rapid measurement of polar phenolics of olive oil were tested. The biosensor was constructed using disposable screen-printed carbon electrodes with the enzyme as biorecognition element. The sensor was coupled with a simple extraction procedure and optimized for use in flow injection analysis. The performance of the biosensor was assessed by measuring a set of virgin olive oils and comparing the results with data obtained by the reference HPLC method and sensory scores. The correlations between the tyrosinase- and peroxidase-based biosensors and phenolic content in the samples were high (r = 0.82 and 0.87, respectively), which, together with a good repeatability (rsd = 6%), suggests that these biosensors may represent a promising tool in the analysis of the total content of phenolics in virgin olive oils. The correlation with sensory quality attributes of virgin olive oil was lower, which illustrates the complexity of sensory perception. The two biosensors possessed different specificities toward different groups of phenolics, affecting bitterness and pungency prediction. The peroxidase-based biosensor showed a significant correlation (r = 0.66) with pungency.     

Development of a sensitive and specific solid phase extraction--gas chromatography-tandem mass spectrometry method for the determination of elenolic acid, hydroxytyrosol, and tyrosol in rat urine

A novel gas chromatography-tandem mass spectrometry (GC-MS/MS) method was developed, using an ion trap mass spectrometer, for the simultaneous determination of olive oil bioactive components, elenolic acid, hydroxytyrosol, and tyrosol, in rat urine. Samples were analyzed by GC-MS/MS prior to and after enzymatic treatment. A solid phase extraction sample pretreatment step with greater than 80% analytical recoveries for all compounds was performed followed by a derivatization reaction prior to GC-MS/MS analysis. The calibration curves were linear for all compounds studied for a dynamic range between 1 and 500 ng. The limit of detection was in the mid picogram level for tyrosol and elenolic acid (300 pg) and in the low picogram level for hydroxytyrosol (2.5 pg). The method was applied to the analysis of rat urine samples after sustained oral intake of oleuropein or extra virgin olive oil as a diet supplement.     

A simple high-performance liquid chromatography method for the determination of throat-burning oleocanthal with probated antiinflammatory activity in extra virgin olive oils

A high-performance liquid chromatography (HPLC) method was developed to quantitatively analyze oleocanthal in extra virgin olive oils. Oleocanthal, a deacetoxy ligstroside aglycone, is known to be responsible for the back of the throat irritation of olive oils and to have probated antiinflamatory activity. Oleocanthal was isolated from small amounts of olive oil sample (1 g) by liquid-liquid extraction. Hexane-acetonitrile was found to be the best solvent system to extract oleocanthal from the oil matrix. The solvent extract was analyzed by reversed-phase HPLC with UV detection at 278 nm. Chromatogaphic separation of oleocanthal from other extracted compounds and of the two geometric isomers of oleocanthal was achieved by an elution gradient with acetonitrile and water. Both the external standard calibration curve and the internal standard calibration curve were established, and quantitation using both calibration curves gave essentially the same result. The reproducibility (RSD = 4.7%), recovery (> 95%), and limit of quantitation (< 1 microg/g) were also determined. Concentrations of oleacanthal in 10 selected throat-burning extra virgin olive oils were determined using the method (ranged from 22 to 190 microg/g) with external standard calibration.     

Determination of geographical origin of olive oils using 13C nuclear magnetic resonance spectroscopy. I - Classification of olive oils of the Puglia region with denomination of protected origin

13C nuclear magnetic resonance spectroscopy was used to classify olive oils from the three production areas of the Puglia region labeled with the "denomination of protected origin" (DPO) Terra di Bari, Colline di Brindisi, and Dauno. High resolution (13)C spectra of 173 olive oil samples were measured, and the intensity data of triacylglycerol resonances were processed by using linear discriminant analysis, which was carried out stepwise for variable selection. The olive oil samples from the DPOs Colline di Brindisi and Terra di Bari were 90% correctly classified, whereas only 74% of "Dauno" DPO oils were classified in the true group. The performance of the discriminant model was verified by applying the cross-validation procedure based on the "leave one out" formalism. The discriminant model was evaluated against a blind test set of olive oils from the three DPO areas. All the oils used for the purpose were correctly assigned to their respective groups, with the exception of the Dauno oil samples based on the Coratina cv. They were misclassified as Terra di Bari oils because of a common monovarietal composition.     

Differentiation of refined and virgin edible oils by means of the trans- and cis-phytol isomer distribution

The differentiation of nonrefined (e.g., cold-pressed) and refined edible oils is an important task in food control because of the higher commercial value of the former. Here, we explored the suitability of the relative abundance of cis-phytol as a marker for authentication of nonrefined edible oils. Phytol, the tetramethyl-branched, monoenoic alcohol, is found widespread in nature as a part of chlorophyll. In chlorophyll, only trans-phytol is found. In this study, we present a method for the analysis of the phytol isomers, considering that traces of cis-phytol (contributing 0.1% to the phytol content) can be determined next to trans-phytol. For this purpose, phytol was gathered with the unsaponifiable matter from the oil, trimethylsilylated, and analyzed by gas chromatography coupled to mass spectrometry. With this method, 27 samples of edible oils (16 refined and 11 nonrefined edible oils) were analyzed for the abundance of cis-phytol relative to trans-phytol. In the nonrefined oils (e.g., olive oil, rapeseed oil, maize oil, and sunflower oil), cis-phytol contributed 0.1% (n = 3) or less (n = 8) to the phytol content. In contrast, the refined olive oils (n = 4) contained a share of 1.3-3% cis-phytol; the refined rapeseed oil (n = 3) contained a share of 0.7-1.0% cis-phytol; and the refined sunflower oil (n = 4) contained a share of 0.3-0.9% cis-phytol. Only one refined pomegranate kernel did not contain cis-phytol. The phytol concentration was not suited to distinguish nonrefined from refined oils. In contrast, our data suggest that the virtual absence of cis-phytol can be used as a marker for nonrefined (e.g., cold-pressed) edible oils.     

Bioaccessibility and antioxidant activity stability of phenolic compounds from extra-virgin olive oils during in vitro digestion

The impact of an in vitro procedure that mimics the physiochemical changes occurring in gastric and small intestinal digestion on the bioaccessibility and antioxidant activity of phenols from 10 extra-virgin olive oil samples was assessed. Extra-virgin olive oil phenols were totally extracted in the aqueous phase, which reproduces gastric fluids during the digestion procedure. A linear bioaccessibility model, based on tyrosol behavior in model oil samples, was used to estimate the bioaccessibility index (BI%) of extra-virgin olive oil phenols. The BI% varied amongst samples from a maximum of 90% to a minimum of 37%, thus indicating that only a fraction of phenols can be considered bioaccessible. The specific antioxidant activity of olive oil phenols proved to be negatively affected by the digestion procedure. By computing a principal component analysis, it was possible to show that differences in the potential bioactive effect of extra-virgin olive oil samples were related to different phenolic profiles.     

Correlations of the phenolic compounds and the phenolic content in some Spanish and French olive oils

The total content of phenolic compounds (TAP) in 29 different monocultivar olive oil samples from France (Aglandau and Tanche) and Spain (Cornicabra, Picual, and Verdial) was assessed by the colorimetric Folin-Ciocalteu method. Also, individual phenolic compounds were determined and quantified by liquid chromatography coupled to mass spectrometry (LC-MS). The French olive oil samples had a lower TAP compared to Spanish samples. The quantity of individual phenolics was similar except for pinoresinol, which was lower in the French olive oil samples. TAP moderately correlated to the sum of quantified compounds (r = 0.64 and p < 0.01) Partial least-squares (PLS) regression analysis emphasized the importance of hydroxytyrosol and the total amount of quantified phenolic compounds by LC-MS in the prediction of the total amount of phenolic compounds as determined by the Folin-Ciocalteu method. The amount of alpha-tocopherol was generally different among the cultivars (Tanche > Picual > Verdial > Aglandau > Cornicabra). Of all quantified phenolic compounds in French olive oil samples, only luteolin correlated well to the altitude of the olive orchards (r = 0.76, p < 0.01).     

Determination of pesticides and PCBs in virgin olive oil by multicolumn solid-phase extraction cleanup followed by GC-NPD/ECD and confirmation by ion-trap GC-MS

A multicolumn solid-phase extraction cleanup for the determination of organophosphorus (OP) and organochlorine (OC) pesticides plus PCB congeners in virgin olive oil is presented. The method involves dissolution of the olive oil in hexane, followed by a cleanup system using a diatomaceous earth column (Extrelut-QE) with reversed (C(18)) and normal (alumina) phase SPE columns. Determination of OPs was by GC-NPD, while the OCs and PCBs were analyzed using GC-ECD. Recovery assays for OPs varied from 81.7% to 105.3%, for OCs ranged between 74.3% and 99.4%, while for PCBs were from 60.1% to 119.2%. Quantitation limits ranged from 10 to 25 microg/kg olive oil for OPs, and from 1 to 6 microg/kg olive oil for OCs and PCBs. In the case of positive samples, the confirmation of pesticide identity was performed by ion-trap GC-MS/MS. The applicability of the method was assayed with 19 virgin olive oil samples collected from different olive mills of Aragón (Spain). Only one OP pesticide (acephate) was detected in one sample at a concentration of 10 microg/kg. Organochlorine pesticides were found in 5-47% of samples at very low levels ranging from 1.5 to 5.2 microg/kg. PCBs were found in 20-90% of samples, showing concentrations between 2.3 and 17.3 microg/kg.