Top: DR-Vis spectrum of ‘Scarlet’ apples, showing Chl a and Chl b peaks, (in addition to the antocyanins signal). Bottom left: integral of the Chl band during all the ripening period. Bottom right: ...plot of predicted and measured values for harvest periods (days), provided by the final PLS model developed from UV–Vis and NIR spectra using GA algorithm, test set validation. Data were reported as average of every harvest. RMSEP of the PLS model is reported. Display omitted
► UV–Vis analysis was used to monitor the chlorophyll content in the skin of apples. ► Calibrations for ripening parameters were obtained from processing of NIR data. ► BiPLS and GA–PLS algorithms were applied to NIR and UV–Vis datasets. ► These techniques provide a reliable tool to predict optimum harvest dates.
Identification of harvest date plays a key role in the agro-food chain as the quality of fruit depends on the right harvesting time and appropriate storage conditions during the postharvest period. Destructive techniques, such as the use of some ripening parameters, suffer from several drawbacks that highlight the need for reliable non-destructive tools to determine ripeness stage. This work is focused on the study of ripening of red apples (‘Scarlet’), with the aim of better identifying the harvest date, by means of non-destructive analysis, through the characterization of each fruit ripening stage on the trees, with classical methods as a reference. UV–Vis analysis was applied in diffuse reflectance (DR) mode to monitor variations in the chlorophyll content of the skin of red apples during ripening on the tree, since the colour variation in red apples is difficult to observe during ripening, and the ground colour cannot be considered a valid tool to identify ripening. On the other hand, variation in the chlorophyll content, measured by means of in situ DR-UV–Vis spectroscopy, is a reliable indicator of the ripeness stage. The novelty of this work is that a backward interval–GA–partial least squares (PLS) model, based both on NIR and UV–Vis data, was used to predict the optimal harvesting time in a direct way. We also established an overview of fruit maturation through a comparison with UV–Vis analysis and calibrations of the ripening parameters.
In this work, nanoparticles with a negative or positive surface charge were prepared through electrostatic interaction of an anionic cisplatin–alginate complex with a cationic polyelectrolyte, namely ...chitosan or
N-trimethyl chitosan (substitution degree of 85%). Statistical experimental design allowed the study of the influence of component amounts on the characteristics of nanoparticles. Mean particle diameter ranged from 180 nm to 350 nm. After 24 h, while the cisplatin–alginate complex released almost all the drug in saline-buffered solution at pH 7.4, approximately 40% w/w of total cisplatin was released from negative nanoparticles and roughly 50% w/w from positive ones. The same cumulative amounts of released drug were found after 48 h, with a progressive reduction to lower values up to 6 days. Drug loading of nanoparticles with a positive zeta potential (43 mV–60 mV) ranged from 13% w/w to 21% w/w and particle yield, referred to total polymers, was about 15% w/w (50% w/w if referred to cisplatin–alginate complex). Nanoparticles with a negative zeta potential (−
34 mV) were obtained with a yield of 40% w/w and a drug loading of 18% w/w. These nanoparticles were the least active on all cell lines tested, while the cytotoxic activity of the positive nanoparticles was similar to or lower than that of cisplatin, probably depending on the combination of sizes and zeta potential values, on P388 murine and A2780 human cells. On A549 human cells, the nanoparticles with the smallest size and the lowest positive zeta potential were more active than cisplatin and showed a similar capability in inducing apoptosis in A2780 human cells. These results indicate that cisplatin complexes with polycarboxylate polymers can be transformed into cisplatin particulate carriers of high potential interest.
A genetic algorithm (GA) combined with partial least squares (PLS) regression was applied in order to reduce the considerable number of variables of electrochemical signals recorded by a voltammetric ...electronic tongue. The algorithm was specifically designed for improving the analysis of data matrices with high collinearity, providing good solutions in terms of both predictive ability and interpretability and, at the same time, minimising the risk of overfitting.
The variable reduction was carried out within a wine characterisation performed with an electronic tongue based on voltammetric sensors. In more detail, the aim was the evaluation of differences among wines aged by means of two different processes: the traditional ageing process in oak wood barrels and an alternative method based on the use of stainless steel tanks and oak wood chips or staves. The results show that the variables selected are at least as good as the full signals to separate the two different classes, even though the number of parameters has been reduced from 1980 to 280 variables; furthermore, the models obtained are simpler and more easily interpretable. In fact, it is important to point out that the variables selected by the genetic algorithm are related to the electrochemical activity of the polyphenolic fraction of wine.
A solubility phase study was carried out to investigate the ability of Poloxamer 407 (P407) to solubilise tolfenamic acid. P407 considerably enhanced the solubility of this anti-inflammatory agent, ...by increasing its concentration in aqueous solution at least 2000-fold (up to
C
=
4
mM), when present at 12% (w/w) at 25
°C. The solubilisation process was spontaneous and exothermic, as indicated by thermodynamic parameters. A mixture experimental design was used to investigate the physical and release properties of P407-based gel formulations. The experimental design allowed verifying that drug release, occurring through a Fickian diffusion mechanism, was independent of the bulk viscosity of the system. The sustained release of tolfenamic acid towards the receptor phase constituted by isopropyl myristate was accompanied, in its early stage, by the concomitant release of ethanol and tetrahydrofurfuryl alcohol (THFA) used as cosolvents to obtain a drug loading of 0.6% (w/w). The poloxamer micellar phase was directly involved in the late stage of drug release, thus indicating that a strong interaction occurred in the gel between the poloxamer and tolfenamic acid. Results point out the possibility of both the systemic and topical administration of tolfenamic acid by means of aqueous solutions or gels containing P407 at an adequate concentration.
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► Wine samples were analytically characterised according to their ageing process. ► Signals from a sensor-based electronic nose were fused with GC–MS and UV–visible data. ► The study ...involved 6 periodical determinations of 20 variables on 6 different wines. ► Multi-way analysis allowed to efficiently extract the maximum information from data. ► Multi-way methods represent the most suitable tool for processing three-mode data.
In this study, a multi-way method (Tucker3) was applied to evaluate the performance of an electronic nose for following the ageing of red wines. The odour evaluation carried out with the electronic nose was combined with the quantitative analysis of volatile composition performed by GC–MS, and colour characterisation by UV–visible spectroscopy. Thanks to Tucker3, it was possible to understand connections among data obtained from these three different systems and to estimate the effect of different sources of variability on wine evaluation. In particular, the application of Tucker3 supplied a global visualisation of data structure, which was very informative to understand relationships between sensors responses and chemical composition of wines. The results obtained indicate that the analytical methods employed are useful tools to follow the wine ageing process, to differentiate wine samples according to ageing type (either in barrel or in stainless steel tanks with the addition of small oak wood pieces) and to the origin (French or American) of the oak wood. Finally, it was possible to designate the volatile compounds which play a major role in such a characterisation.
► The study of the thermal stability of edible oils is of great importance to industries that use them to create foods incorporating these oils. ► We consider a new way to evaluate the thermal ...stability of oils by using proton nuclear magnetic resonance spectroscopy combined with chemometrics tools. ► Relatively simple mathematical methods using part of the NMR spectra are used to compare the thermal stability at 170°C, 190°C and 210°C. ► Olive oil remains always more stable than rapeseed and sunflower oil.
The degradation process of edible oils of different nature, submitted to heating at 170°C, 190°C and 210°C with aeration, was studied by means of 1H nuclear magnetic resonance spectroscopy (NMR). In this study, secondary products such as aldehydes were detected and monitored over time. Two complementary analytical approaches were adopted to characterize the kinetics of the appearance of aldehydes in the heated oils. This first was a classical kinetic approach based on the assumption that the overall degradation reaction to form aldehydes follows a rate law of order 1. This approach allowed us to calculate a thermal stability criterion for classifying the oils according to their heat stability. A second approach was to use the spectral fingerprint corresponding to aldehydes in a multivariate data analysis procedure in order to give the major trend in the studied phenomena, taking into account the multiway nature of recorded data. The application of different 3-way and 4-way Tucker3 models led to a better understanding of the chemical stability of the oils studied and was used to determine the order of stability of these oils. This multiway approach provides additional information that 2-way processing (PCA) does not provide clearly, such as the overall contribution of the heating time factor on the chemical evolution of oils. In conclusion, this work shows that a fully chemometric study of NMR spectra allows to order the oils according to their thermal stability and to achieve a result in good agreement with existing analytical and kinetic studies in the literature.
An impedentiometric electronic tongue based on the combination of a composite sensor array and chemometric techniques aimed at the discrimination of soluble compounds able to elicit different ...gustative perceptions is presented. A composite array consisting of chemo-sensitive layers based on carbon nanotubes or carbon black dispersed in polymeric matrices and doped polythiophenes was used. The electrical impedance of the sensor array was measured at a frequency of 150 Hz by means of an impedance meter. The experimental set-up was designed in order to allow the automatic selection of a test solution and dipping of the sensor array following a dedicated measurement protocol. Measurements were carried out on 15 different solutions eliciting 5 different tastes (sodium chloride, citric acid, glucose, glutamic acid and sodium dehydrocholate for salty, sour, sweet, umami and bitter, respectively) at 3 concentration levels comprising the human perceptive range. In order to avoid over-fitting, more than 100 repetitions for each sample were carried in a 4-month period. Principal component analysis (PCA) was used to detect and remove outliers. Classification was performed by linear discriminant analysis (LDA). A fairly good degree of discrimination was obtained.
Mass spectral classifiers for 15 substructures have been computed that give discrete present/absent answers. For the development of classifiers, linear discriminant analysis (LDA) and partial least ...squares discriminant PLS (DPLS) have been used. The low resolution mass spectra were transformed into a set of 400 spectral features. Because each spectrum is described with so many features, some features may not be necessary, and others may contribute only noise. Therefore, the effect of feature selection has been investigated. The methods used were selection by Fisher ratios and selection by a genetic algorithm (GA). The first method is univariate, the second is multivariate; advantages and disadvantages of both are discussed. On the average, feature selection did not significantly change the classification performance compared with results that have been obtained with all features. However, it was possible to reduce the number of features considerably without a loss of classification performance. For a few substructures GA together with LDA resulted in much better classifiers than DPLS with all features. The features selected for classifications of a benzyl substructure and for the presence of chlorine have been interpreted in terms of mass spectrometric fragmentation rules.
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