Detection of phenolic compounds using impedance spectroscopy measurements

Langmuir-Blodgett (LB) and layer-by-layer films (LbL) of a PPV (p-phenylenevinylene) derivative, an azo compound and tetrasulfonated phthalocyanines were successfully employed as transducers in an ""electronic tongue"" system for detecting trace levels of phenolic compounds in water. The choice of the materials was based on their distinct electrical natures, which enabled the array to establish a fingerprint of very similar liquids. Impedance spectroscopy measurements were taken in the frequency range from 10 Hz to 1 MHz, with the data analysed with principal component analysis (PCA). The sensing units were obtained from five-layer LB films of (poly[(2-methoxy-5-n-hexyloxy)-p-phenylenevinylene]), OC(1)OC(18)-PPV (poly(2-methoxy,5-(n-octadecyl)-p-phenylenevinylene)), DR (HEMA-co-DR13MA (poly-(hydroxyethylmethacrylate-co-[4`-[[2-(methacryloyloxy)-ethyl]ethylamino]-2-chloro-4-nitroazobenzene]))) and five-bilayer LbL films of tetrasulfonated metallic phthalocyanines deposited onto gold interdigitated electrodes. The sensors were immersed into phenol, 2-chloro-4-methoxyphenol, 2-chlorophenol and 3-chlorophenol (isomers) solutions at 1 x 10(-9) mol L(-1), with control experiments carried out in ultra pure water. Samples could be distinguished if the principal component analysis (PCA) plots were made with capacitance values taken at 10(3) Hz, which is promising for detection of trace amounts of phenolic pollutants in natural water.

Fabrication of disposable voltammetric electronic tongues by using Prussian Blue films electrodeposited onto CD-R gold surfaces and recognition of milk adulteration

A new approach to fabricate a disposable electronic tongue is reported. The fabrication of the disposable sensor aimed the integration of all electrodes necessary for measurement in the same device. The disposable device was constructed with gold CD-R and copper sheets substrates and the sensing elements were gold, copper and a gold surface modified with a layer of Prussian Blue. The relative standard deviation for signals obtained from 20 different disposable gold and 10 different disposable copper electrodes was below 3.5%. The performance, electrode materials and the capability of the device to differentiate samples were evaluated for taste substances model, milk with different pasteurization processes (homogenized/pasteurized, ultra high temperature (UHT) pasteurized and UHT pasteurized with low fat content) and adulterated with hydrogen peroxide. In all analysed cases, a good separation between different samples was noticed in the score plots obtained from the principal component analysis (PCA). Crown Copyright (C) 2008 Published by Elsevier B.V. All rights reserved.

Use of Metals and Anion Species with Chemometrics Tools for Classification of Unprocessed and Processed Coconut Waters

Coconut water is a natural isotonic, nutritive, and low-caloric drink. Preservation process is necessary to increase its shelf life outside the fruit and to improve commercialization. However, the influence of the conservation processes, antioxidant addition, maturation time, and soil where coconut is cultivated on the chemical composition of coconut water has had few arguments and studies. For these reasons, an evaluation of coconut waters (unprocessed and processed) was carried out using Ca, Cu, Fe, K, Mg, Mn, Na, Zn, chloride, sulfate, phosphate, malate, and ascorbate concentrations and chemometric tools. The quantitative determinations were performed by electrothermal atomic absorption spectrometry, inductively coupled plasma optical emission spectrometry, and capillary electrophoresis. The results showed that Ca, K, and Zn concentrations did not present significant alterations between the samples. The ranges of Cu, Fe, Mg, Mn, PO (4) (3-) , and SO (4) (2-) concentrations were as follows: Cu (3.1-120 A mu g L(-1)), Fe (60-330 A mu g L(-1)), Mg (48-123 mg L(-1)), Mn (0.4-4.0 mg L(-1)), PO (4) (3-) (55-212 mg L(-1)), and SO (4) (2-) (19-136 mg L(-1)). The principal component analysis (PCA) and hierarchical cluster analysis (HCA) were applied to differentiate unprocessed and processed samples. Multivariated analysis (PCA and HCA) were compared through one-way analysis of variance with Tukey-Kramer multiple comparisons test, and p values less than 0.05 were considered to be significant.

Volsurf Descriptors to Analyse Anti-HCV and Cytotoxic Activities of Sesquiterpene Lactones from Asteraceae Family

Various significant anti-HCV and cytotoxic sesquiterpene lactones (SLs) have been characterized. In this work, the chemometric tool Principal Component Analysis (PCA) was applied to two sets of SLs and the variance of the biological activity was explored. The first principal component accounts for as much of the variability in the data as possible, and each succeeding component accounts for as much of the remaining variability as possible. The calculations were performed using VolSurf program. For anti-HCV activity, PC1 (First Principal Component) explained 30.3% and PC2 (Second Principal Component) explained 26.5% of matrix total variance, while for cytotoxic activity, PC1 explained 30.9% and PC2 explained 15.6% of the total variance. The formalism employed generated good exploratory and predictive results and we identified some structural features, for both sets, important to the suitable biological activity and pharmacokinetic profile.

Chemical profile of rums as a function of their origin. The use of chemometric techniques for their identification

To identify chemical descriptors to distinguish Cuban from non-Cuban rums, analyses of 44 samples of rum from 15 different countries are described. To provide the chemical descriptors, analyses of the the mineral fraction, phenolic compounds, caramel, alcohols, acetic acid, ethyl acetate, ketones, and aldehydes were carried out. The analytical data were treated through the following chemometric methods: principal component analysis (PCA), partial least square-discriminate analysis (PLS-DA), and linear discriminate analysis (LDA). These analyses indicated 23 analytes as relevant chemical descriptors for the separation of rums into two distinct groups. The possibility of clustering the rum samples investigated through PCA analysis led to an accumulative percentage of 70.4% in the first three principal components, and isoamyl alcohol, n-propyl alcohol, copper, iron, 2-furfuraldehyde (furfuraldehyde), phenylmethanal (benzaldehyde), epicatechin, and vanillin were used as chemical descriptors. By applying the PLS-DA technique to the whole set of analytical data, the following analytes have been selected as descriptors: acetone, sec-butyl alcohol, isobutyl alcohol, ethyl acetate, methanol, isoamyl alcohol, magnesium, sodium, lead, iron, manganese, copper, zinc, 4-hydroxy3,5-dimethoxybenzaldehyde (syringaldehyde), methaldehyde (formaldehyde), 5-hydroxymethyl-2furfuraldehyde (5-HMF), acetalclehyde, 2-furfuraldehyde, 2-butenal (crotonaldehyde), n-pentanal (valeraldehyde), iso-pentanal (isovaleraldehyde), benzaldehyde, 2,3-butanodione monoxime, acetylacetone, epicatechin, and vanillin. By applying the LIDA technique, a model was developed, and the following analytes were selected as descriptors: ethyl acetate, sec-butyl alcohol, n-propyl alcohol, n-butyl alcohol, isoamyl alcohol, isobutyl alcohol, caramel, catechin, vanillin, epicatechin, manganese, acetalclehyde, 4-hydroxy-3-methoxybenzoic acid, 2-butenal, 4-hydroxy-3,5-dimethoxybenzoic acid, cyclopentanone, acetone, lead, zinc, calcium, barium, strontium, and sodium. This model allowed the discrimination of Cuban rums from the others with 88.2% accuracy.

A quantum chemical study on a set of non-imidazole H(3) antihistamine molecules

Molecular orbital calculations were carried out on a set of 28 non-imidazole H(3) antihistamine compounds using the Hartree-Fock method in order to investigate the possible relationships between electronic structural properties and binding affinity for H3 receptors (pK(i)). It was observed that the frontier effective-for-reaction molecular orbital (FERMO) energies were better correlated with pK(i) values than highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy values. Exploratory data analysis through hierarchical cluster (HCA) and principal component analysis (PCA) showed a separation of the compounds in two sets, one grouping the molecules with high pK(i) values, the other gathering low pK(i) value compounds. This separation was obtained with the use of the following descriptors: FERMO energies (epsilon(FERMO)), charges derived from the electrostatic potential on the nitrogen atom (N(1)), electronic density indexes for FERMO on the N(1) atom (Sigma((FERMO))c(i)(2)). and electrophilicity (omega`). These electronic descriptors were used to construct a quantitative structure-activity relationship (QSAR) model through the partial least-squares (PLS) method with three principal components. This model generated Q(2) = 0.88 and R(2) = 0.927 values obtained from a training set and external validation of 23 and 5 molecules, respectively. After the analysis of the PLS regression equation and the values for the selected electronic descriptors, it is suggested that high values of FERMO energies and of Sigma((FERMO))c(i)(2), together with low values of electrophilicity and pronounced negative charges on N(1) appear as desirable properties for the conception of new molecules which might have high binding affinity. 2010 Elsevier Inc. All rights reserved.

Computerized identification of motor complications in Parkinson's disease

Objective: To investigate whether spirography-based objective measures are able to effectively characterize the severity of unwanted symptom states (Off and dyskinesia) and discriminate them from motor state of healthy elderly subjects. Background: Sixty-five patients with advanced Parkinson’s disease (PD) and 10 healthy elderly (HE) subjects performed repeated assessments of spirography, using a touch screen telemetry device in their home environments. On inclusion, the patients were either treated with levodopa-carbidopa intestinal gel or were candidates for switching to this treatment. On each test occasion, the subjects were asked trace a pre-drawn Archimedes spiral shown on the screen, using an ergonomic pen stylus. The test was repeated three times and was performed using dominant hand. A clinician used a web interface which animated the spiral drawings, allowing him to observe different kinematic features, like accelerations and spatial changes, during the drawing process and to rate different motor impairments. Initially, the motor impairments of drawing speed, irregularity and hesitation were rated on a 0 (normal) to 4 (extremely severe) scales followed by marking the momentary motor state of the patient into 2 categories that is Off and Dyskinesia. A sample of spirals drawn by HE subjects was randomly selected and used in subsequent analysis. Methods: The raw spiral data, consisting of stylus position and timestamp, were processed using time series analysis techniques like discrete wavelet transform, approximate entropy and dynamic time warping in order to extract 13 quantitative measures for representing meaningful motor impairment information. A principal component analysis (PCA) was used to reduce the dimensions of the quantitative measures into 4 principal components (PC). In order to classify the motor states into 3 categories that is Off, HE and dyskinesia, a logistic regression model was used as a classifier to map the 4 PCs to the corresponding clinically assigned motor state categories. A stratified 10-fold cross-validation (also known as rotation estimation) was applied to assess the generalization ability of the logistic regression classifier to future independent data sets. To investigate mean differences of the 4 PCs across the three categories, a one-way ANOVA test followed by Tukey multiple comparisons was used. Results: The agreements between computed and clinician ratings were very good with a weighted area under the receiver operating characteristic curve (AUC) coefficient of 0.91. The mean PC scores were different across the three motor state categories, only at different levels. The first 2 PCs were good at discriminating between the motor states whereas the PC3 was good at discriminating between HE subjects and PD patients. The mean scores of PC4 showed a trend across the three states but without significant differences. The Spearman’s rank correlations between the first 2 PCs and clinically assessed motor impairments were as follows: drawing speed (PC1, 0.34; PC2, 0.83), irregularity (PC1, 0.17; PC2, 0.17), and hesitation (PC1, 0.27; PC2, 0.77). Conclusions: These findings suggest that spirography-based objective measures are valid measures of spatial- and time-dependent deficits and can be used to distinguish drug-related motor dysfunctions between Off and dyskinesia in PD. These measures can be potentially useful during clinical evaluation of individualized drug-related complications such as over- and under-medications thus maximizing the amount of time the patients spend in the On state.

Mercado brasileiro: aplicação de análise de componentes principais no cálculo de VAR para carteiras de renda fixa

A abordagem do Value at Risk (VAR) neste trabalho será feita a partir da análise da curva de juros por componentes principais (Principal Component Analysis – PCA). Com essa técnica, os movimentos da curva de juros são decompostos em um pequeno número de fatores básicos independentes um do outro. Entre eles, um fator de deslocamento (shift), que faz com que as taxas da curva se movam na mesma direção, todas para cima ou para baixo; de inclinação (twist) que rotaciona a curva fazendo com que as taxas curtas se movam em uma direção e as longas em outra; e finalmente movimento de torção, que afeta vencimentos curtos e longos no mesmo sentido e vencimentos intermediários em sentido oposto. A combinação destes fatores produz cenários hipotéticos de curva de juros que podem ser utilizados para estimar lucros e perdas de portfolios. A maior perda entre os cenários gerados é uma maneira intuitiva e rápida de estimar o VAR. Este, tende a ser, conforme verificaremos, uma estimativa conservadora do respectivo percentual de perda utilizado. Existem artigos sobre aplicações de PCA para a curva de juros brasileira, mas desconhecemos algum que utilize PCA para construção de cenários e cálculo de VAR, como é feito no presente trabalho.Nesse trabalho, verificaremos que a primeira componente principal produz na curva um movimento de inclinação conjugado com uma ligeira inclinação, ao contrário dos resultados obtidos em curvas de juros de outros países, que apresentam deslocamentos praticamente paralelos.

Product placement in movies: a cross cultural study between Brazil and the USA

The broader objective of this study undertaking can briefly be articulated in particulate aims as follows: to measure the attitudes of consumers regarding the brand displayed by this strategy as well as to highlight recall, recognition and purchase intentions generated by product placement on consumers. In addition, check the differences and similarities between the behavior of Brazilian and American consumers caused by the influence of product placements. The study was undertaken targeting consumer audience in Brazil and the U.S. A rang3 modeling set ups were performed in order to realign study instruments and hypothesis towards the research objectives. This study gave focus on the following hypothesized models. H1: Consumers / Participants who viewed the brands / products in the movie have a higher brand / product recall compared to the consumers / participants who did not view the brands / products in the movie. H2: US Consumers / Participants are able to recognize and recall brands / products which appear in the background of the movie than Brazil. H3: Consumers / participants from USA are more accepting of product placements compared to their counterparts in Brazil. H4: There are discernible similarities in consumer / participant brand attitudes and purchase intentions in consumers / participants from USA and Brazil in spite of the fact that their country of origin is different. Cronbach’s Alpha Coefficient ensured the reliability of survey instruments. The study involved the use of the Structural Equation Modeling (SEM) for the hypothesis testing. This study used the Confirmatory Factor Analysis (CFA) to assess both the convergent and discriminant validities instead of using the Exploratory Factor Analysis (EFA) or the Principal Component Analysis (PCA). This reinforced for the use of the regression Chi Square and T statistical tests in further. Only hypothesis H3 was rejected, the rest were not. T test provided insight findings on specific subgroup significant differences. In the SEM testing, the error variance for product placement attitudes was negative for both the groups. On this The Heywood Case came in handy to fix negative values. The researcher used both quantitative and qualitative approach where closed ended questionnaires and interviews respectively were used to collect primary data. The results were additionally provided with tabulations. It can be concluded that, product placement varies markedly in the U.S. from Brazil based on the influence a range of factors provided in the study. However, there are elements of convergence probably driven by the convergence in technology. In order, product placement to become more competitive in the promotional marketing, there will be the need for researchers to extend focus from the traditional variables and add knowledge on the conventional marketplace factors that is the sell-ability of the product placement technologies and strategies.

Relação entre as componentes principais da estrutura a termo da taxa de juros brasileira e as variáveis macroeconômicas

Este trabalho observa como as variáveis macroeconômicas (expectativa de inflação, juro real, hiato do produto e a variação cambial) influenciam a dinâmica da Estrutura a Termo da Taxa de Juros (ETTJ). Esta dinâmica foi verificada introduzindo a teoria de Análise de Componentes Principais (ACP) para capturar o efeito das componentes mais relevantes na ETTJ (nível, inclinação e curvatura). Utilizando-se as estimativas por mínimos quadrados ordinários e pelo método generalizado dos momentos, foi verificado que existe uma relação estatisticamente significante entre as variáveis macroeconômicas e as componentes principais da ETTJ.

Classification of Boal, Malvazia, Sercial and Verdelho wines based on terpenoid patterns

Thirty-six Madeira wine samples from Boal, Malvazia, Sercial and Verdelho white grape varieties were analyzed in order to estimate the free fraction of monoterpenols and C13 norisoprenoids (terpenoid compounds) using dynamic headspace solid phase micro-extraction (HS-SPME) technique coupled with gas chromatography–mass spectrometry (GC–MS). The average values from three vintages (1998–2000) show that these wines have characteristic profiles of terpenoid compounds. Malvazia wines exhibits the highest values of total free monoterpenols, contrary to Verdelho wines which had the lowest levels of terpenoids but produced the highest concentration of farnesol. The use of multivariate analysis techniques allows establishing relations between the compounds and the varieties under investigation. Principal component analysis (PCA) and linear discriminant analysis (LDA) were applied to the obtained matrix data. A good separation and classification power between the four groups as a function of their varietal origin was observed.

Solid phase microextraction, mass spectrometry and metabolomic approaches for detection of potential urinary cancer biomarkers: a powerful strategy for breast cancer diagnosis

A sensitive assay to identify volatile organic metabolites (VOMs) as biomarkers that can accurately diagnose the onset of breast cancer using non-invasively collected clinical specimens is ideal for early detection. Therefore the aim of this study was to establish the urinary metabolomic profile of breast cancer patients and healthy individuals (control group) and to explore the VOMs as potential biomarkers in breast cancer diagnosis at early stage. Solid-phase microextraction (SPME) using CAR/PDMS sorbent combined with gas chromatography–mass spectrometry was applied to obtain metabolomic information patterns of 26 breast cancer patients and 21 healthy individuals (controls). A total of seventy-nine VOMs, belonging to distinct chemical classes, were detected and identified in control and breast cancer groups. Ketones and sulfur compounds were the chemical classes with highest contribution for both groups. Results showed that excretion values of 6 VOMs among the total of 79 detected were found to be statistically different (p < 0.05). A significant increase in the peak area of (−)-4-carene, 3-heptanone, 1,2,4-trimethylbenzene, 2-methoxythiophene and phenol, in VOMs of cancer patients relatively to controls was observed. Statiscally significant lower abundances of dimethyl disulfide were found in cancer patients. Bioanalytical data were submitted to multivariate statistics [principal component analysis (PCA)], in order to visualize clusters of cases and to detect the VOMs that are able to differentiate cancer patients from healthy individuals. Very good discrimination within breast cancer and control groups was achieved. Nevertheless, a deep study using a larger number of patients must be carried out to confirm the results.

Solid phase microextraction as a reliable alternative to conventional extraction techniques to evaluate the pattern of hydrolytically released components in Vitis vinifera L. grapes

In present research, headspace solid-phase microextraction (HS-SPME) followed by gas chromatography–mass spectrometry (GC–qMS), was evaluated as a reliable and improved alternative to the commonly used liquid–liquid extraction (LLE) technique for the establishment of the pattern of hydrolytically released components of 7 Vitis vinifera L. grape varieties, commonly used to produce the world-famous Madeira wine. Since there is no data available on their glycosidic fractions, at a first step, two hydrolyse procedures, acid and enzymatic, were carried out using Boal grapes as matrix. Several parameters susceptible of influencing the hydrolytic process were studied. The best results, expressed as GC peak area, number of identified components and reproducibility, were obtained using ProZym M with b-glucosidase activity at 35 °C for 42 h. For the extraction of hydrolytically released components, HS-SPME technique was evaluated as a reliable and improved alternative to the conventional extraction technique, LLE (ethyl acetate). HS-SPME using DVB/CAR/PDMS as coating fiber displayed an extraction capacity two fold higher than LLE (ethyl acetate). The hydrolyzed fraction was mainly characterized by the occurrence of aliphatic and aromatic alcohols, followed by acids, esters, carbonyl compounds, terpenoids, and volatile phenols. Concerning to terpenoids its contribution to the total hydrolyzed fraction is highest for Malvasia Cândida (23%) and Malvasia Roxa (13%), and their presence according previous studies, even at low concentration, is important from a sensorial point of view (can impart floral notes to the wines), due to their low odor threshold (μg/L). According to the obtained data by principal component analysis (PCA), the sensorial properties of Madeira wines produced by Malvasia Cândida and Malvasia Roxa could be improved by hydrolysis procedure, since their hydrolyzed fraction is mainly characterized by terpenoids (e.g. linalool, geraniol) which are responsible for floral notes. Bual and Sercial grapes are characterized by aromatic alcohols (e.g. benzyl alcohol, 2-phenylethyl alcohol), so an improvement in sensorial characteristics (citrus, sweet and floral odors) of the corresponding wines, as result of hydrolytic process, is expected.

Characterization of volatile substances in apples from rosaceae family by headspace solid‐phase microextraction followed by GC‐qMS

The volatile composition of different apple varieties of Malus domestica Borkh. species from different geographic regions at Madeira Islands, namely Ponta do Pargo (PP), Porto Santo (PS), and Santo da Serra (SS) was established by headspace solid-phase microextraction (HS-SPME) procedure followed by GC-MS (GC-qMS) analysis. Significant parameters affecting sorption process such as fiber coating, extraction temperature,extractiontime,sampleamount,dilutionfactor,ionicstrength,anddesorption time,wereoptimizedanddiscussed.TheSPMEfibercoatedwith50/30 lmdivinylbenzene/carboxen/PDMS (DVB/CAR/PDMS) afforded highest extraction efficiency of volatile compounds, providing the best sensitivity for the target volatiles, particularly whenthesampleswereextractedat508Cfor30 minwithconstantmagneticstirring. A qualitative and semi-quantitative analysis between the investigated apple species has been established. It was possible to identify about 100 of volatile compounds amongpulp(46,45,and39),peel(64,60,and64),andentirefruit(65,43,and50)inPP, PS,andSSapples,respectively.Ethylesters,terpenes,andhigheralcoholswerefound tobethemostrepresentativevolatiles. a-Farnesene,hexan-1-olandhexyl2-methylbutyratewerethecompoundsfoundinthevolatileprofileofstudiedappleswiththelargestGCarea,representing,onaverage,24.71,14.06,and10.80%ofthetotalvolatilefractionfromPP,PS,andSSapples.InPPentireapple,themostabundantcompoundsidentified were a-farnesene (30.49%), the unknown compound m/z (69, 101, 157) (21.82%) andhexylacetate(6.57%).RegardingPSentireapplethemajorcompoundswere a-farnesene(16.87%),estragole(15.43%),hexan-1-ol(10.94),andE-2-hexenal(10.67).a-Farnesene(30.3%),hexan-1-ol(18.90%),2-methylbutanoicacid(4.7%),andpentan-1-ol(4.6%) werealsofoundasSSentireapplevolatilespresentinahigherrelativecontent.Principal component analysis (PCA) of the results clustered the apples into three groups according to geographic origin. Linear discriminant analysis (LDA) was performed in order to detect the volatile compounds able to differentiate the three kinds of apples investigated. The most important contributions to the differentiation of the PP, PS, and SS apples were ethyl hexanoate, hexyl 2-methylbutyrate, E,E-2,4-heptadienal, pethylstyrene,andE-2-hexenal.

Headspace solid-phase microextraction-gas chromatography-quadrupole mass spectrometric methodology for the establishment of the volatile composition of Passiflora fruit species

Dynamic headspace solid-phase microextraction (HS-SPME) followed by thermal desorption gas chromatography-quadrupole mass spectrometry analysis (GC-qMS), was used to investigate the aroma profile of different species of passion fruit samples. The performance of five commercially available SPME fibres: 65 μm polydimethylsiloxane/divinylbenzene, PDMS/DVB; 100 μm polydimethylsiloxane, PDMS; 85 μm polyacrylate, PA; 50/30 μm divinylbenzene/carboxen on polydimethylsiloxane, DVB/CAR/PDMS (StableFlex); and 75 μm carboxen/polydimethylsiloxane, CAR/PDMS; was evaluated and compared. Several extraction times and temperature conditions were also tested to achieve optimum recovery. The SPME fibre coated with 65 μm PDMS/DVB afforded the highest extraction efficiency, when the samples were extracted at 50 °C for 40 min with a constant stirring velocity of 750 rpm, after saturating the sample with NaCl (17%, w/v — 0.2 g). A comparison among different passion fruit species has been established in terms of qualitative and semi-quantitative differences in volatile composition. By using the optimal extraction conditions and GC-qMS it was possible to tentatively identify seventy one different compounds in Passiflora species: 51 volatiles in Passiflora edulis Sims (purple passion fruit), 24 in P. edulis Sims f. flavicarpa (yellow passion fruit) and 21 compounds in Passiflora mollissima (banana passion fruit). It was found that the ethyl esters comprise the largest class of the passion fruit volatiles, including 82.8% in P. edulis variety, 77.4% in P. edulis Sims f. flavicarpa variety and 39.9% in P. mollissima. The semi-quantitative results were then submitted to principal component analysis (PCA) in order to establish relationships between the compounds and the different passion fruit species under investigation.