Effect of agronomical practices on carpology, fruit and oil composition, and oil sensory properties, in olive (Olea europaea L.).

We examined whether some agronomical practices (i.e. organic vs. conventional) affect olive fruit and oil composition, and oil sensory properties. Fruit characteristics (i.e. fresh and dry weight of pulp and pit, oil content on a fresh and dry weight basis) did not differ. Oil chemical traits did not differ except for increased content of polyphenols in the organic treatments, and some changes in the acidic composition. Sensory analysis revealed increased bitterness (both cultivars) and pungency (Frantoio) and decreased sweetness (Frantoio) in the organic treatment. Fruit metabolomic analysis with HRMAS-NMR indicated significant changes in some compounds including glycocholate, fatty acids, NADPH, NADP+, some amino acids, thymidine, trigonelline, nicotinic acid, 5,6-dihydrouracil, hesanal, cis-olefin, ß-D-glucose, propanal and some unassigned species. The results suggest that agronomical practices may have effects on fruit composition that may be difficult to detect unless a broad-spectrum analysis is used.

NMR-based metabolomics for organic farming traceability of early potatoes.

(1)H HRMAS-NMR spectroscopy was successfully used to determine the metabolic profiles of 78 tubers obtained from three early genotypes grown under organic and conventional management. The variation in total hydrogen, carbon, and nitrogen contents was also assessed. A PLS-DA multivariate statistical analysis provided good discrimination among the varieties and cropping systems (100% unknown samples placed in a cross-validation blind test), suggesting that this method is a powerful and rapid tool for tracing organic potatoes. As a result of the farming system, the nitrogen content decreased by 11-14% in organic tubers, whereas GABA and lysine accumulated in the organic tubers of all clones. Clear variations in primary metabolites are discussed to provide a better understanding of the metabolic pathway modifications resulting from agronomical practices.

PGI chicory (Cichorium intybus L.) traceability by means of HRMAS-NMR spectroscopy: a preliminary study.

BACKGROUND: Analytical traceability of PGI and PDO foods (Protected Geographical Indication and Protected Denomination Origin respectively) is one of the most challenging tasks of current applied research. RESULTS: Here we proposed a metabolomic approach based on the combination of (1)H high-resolution magic angle spinning-nuclear magnetic resonance (HRMAS-NMR) spectroscopy with multivariate analysis, i.e. PLS-DA, as a reliable tool for the traceability of Italian PGI chicories (Cichorium intybus L.), i.e. Radicchio Rosso di Treviso and Radicchio Variegato di Castelfranco, also known as red and red-spotted, respectively. The metabolic profile was gained by means of HRMAS-NMR, and multivariate data analysis allowed us to build statistical models capable of providing clear discrimination among the two varieties and classification according to the geographical origin. CONCLUSION: Based on Variable Importance in Projection values, the molecular markers for classifying the different types of red chicories analysed were found accounting for both the cultivar and the place of origin.

Traceability of Italian garlic (Allium sativum L.) by means of HRMAS-NMR spectroscopy and multivariate data analysis.

(1)H High Resolution Magic Angle Spinning-Nuclear Magnetic Resonance (HRMAS-NMR) spectroscopy was used to analyse garlic (Allium sativum L.) belonging to red and white varieties and collected in different Italian regions, in order to address the traceability issue. 1D and 2D NMR spectra, performed directly on untreated small pieces of garlic, so without any sample manipulation, allowed the assignment of several compounds: organic acids, sugars, fatty acids, amino acids and the nutritionally important fructo-oligosaccharides and allyl-organosulphur compounds. Application of Partial Least Squares projections to latent structures-Discrimination Analysis provided an excellent model for the discrimination of both the variety and, most important, the place origin, allowing the identification of the metabolites contributing to such classifications. The presence of organosulphurs, allicin and some allyl-organosulphurs found by HRMAS-NMR, was confirmed also by SPME-GC-MS; 11 molecules were identified, containing from one up to three sulphur atoms and with and without allyl moieties.

HRMAS-NMR spectroscopy and multivariate analysis meat characterisation.

¹H-High resolution magic angle spinning-nuclear magnetic resonance spectroscopy was employed to gain the metabolic profile of longissimus dorsi and semitendinosus muscles of four different breeds: Chianina, Holstein Friesian, Maremmana and Buffalo. Principal component analysis, partial least squares projection to latent structure - discriminant analysis and orthogonal partial least squares projection to latent structure - discriminant analysis were used to build models capable of discriminating the muscle type according to the breed. Data analysis led to an excellent classification for Buffalo and Chianina, while for Holstein Friesian the separation was lower. In the case of Maremmana the use of intelligent bucketing was necessary due to some resonances shifting allowed improvement of the discrimination ability. Finally, by using the Variable Importance in Projection values the metabolites relevant for the classification were identified.

Classification of prostatic diseases by means of multivariate analysis on in vivo proton MRSI and DCE-MRI data.

Multivariate analysis has been applied on proton magnetic resonance spectroscopic imaging ((1)H-MRSI) and dynamic contrast enhanced MRI (DCE-MRI) data of patients with different prostatic diseases such as chronic inflammation, fibrosis and adenocarcinoma. Multivariate analysis offers a global view of the entire range of information coming from both the imaging and spectroscopic side of NMR technology, leading to an integrated picture of the system relying upon the entire metabolic and dynamic profile of the studied samples. In this study, we show how this approach, applied to (1)H-MRSI/DCE-MRI results, allows us to differentiate among the various prostatic diseases in a non-invasive way with a 100% accuracy. These findings suggest that multivariate analysis of (1)H-MRSI/DCE-MRI can significantly improve the diagnostic accuracy for these pathological entities. From a more theoretical point of view, the complementation of a single biomarker approach with an integrated picture of the entire metabolic and dynamic profile allows for a more realistic appreciation of pathological entities.

Identification by means of low-field nuclear magnetic resonance of the chemical-physical characteristics of multidose artificial tear solutions in interaction with hydrogel model contact lenses.

In this paper, the chemical-physical interactions between two commercially available ophthalmic solutions and hydrogel contact lenses classified according to the four Food and Drug Administration groups were studied by measuring transversal relaxation times (T(2)) of water molecules by low-field nuclear magnetic resonance techniques. The aim was to evaluate possible modifications to the contact lens structure, with particular emphasis on their hydration mechanism. No significant variations in the T(2) values were observed when the T(2) values of the first component of samples swollen with saline solution as the reference were compared with samples of the same set of lenses swollen in the two commercially available ophthalmic solutions. We can, therefore, assume that the hydration characteristics remained unchanged in all the samples studied, and that the experimental ophthalmic solutions ensured an adequate hydration of the sample hydrogel contact lenses without any negative effects on the structure of their polymer chains.

A metabonomic study of transgenic maize (Zea mays) seeds revealed variations in osmolytes and branched amino acids.

The aim of the research was to investigate metabolic variations associated with genetic modifications in the grains of Zea mays using metabonomic techniques. With this in mind, the non-targeted characteristic of the technique is useful to identify metabolites peculiar to the genetic modification and initially undefined. The results obtained showed that the genetic modification, introducing Cry1Ab gene expression, induces metabolic variations involving the primary nitrogen pathway. Concerning the methodological aspects, the experimental protocol used has been applied in this field for the first time. It consists of a combination of partial least square-discriminant analysis and principal component analysis. The most important metabolites for discrimination were selected and the metabolic correlations linking them are identified. Principal component analysis on selected signals confirms metabolic variations, highlighting important details about the changes induced on the metabolic network by the presence of a Bt transgene in the maize genome.

LF-NMR and multivariate data analysis: compression of data to classify hydrogel contact lenses.

Hydrogel contact lenses swollen in viscoelastic artificial tears solution have been studied, measuring transversal relaxation times of water molecules using LF-NMR techniques. Data were processed by classical multiexponential fitting, by principal component analysis and by SLICING, a multi-way analysis method. The reason for using multivariate data analysis was not to obtain a better fitting, but rather more effective data description. The single-sample relaxation curves were projected in a space spanned by the loading curves, and in this space it was simpler to compare data. In particular, it contributed to the description of the variability of motion characteristics of the water molecule 'families' contained in the studied samples. Applying multivariate techniques, we were able to group lenses with different Equilibrium Water Content (EWC) and with the same water content but different compositions. Accordingly, we were able to point out that, if the lenses are swollen first in physiological solution and then in viscoelastic artificial tears solution, hydration characteristics remained unchanged in all the studied samples, except for 38% EWC lenses.

NMR-based metabonomic study of transgenic maize.

The aim of this research was to verify the possibility of identifying and classifying maize seeds obtained from transgenic plants, in different classes according to the modification, on the basis of the concerted variation in metabolite levels detected by NMR spectra. It was possible to recognise the discriminant metabolites of transgenic samples as well as to classify non-a priori defined samples of maize. It is important to underline that the obtained results are useful to point out the metabolic consequences of a specific genic modification on a plant, without using a targeted analysis of the different metabolites, in fact it was possible to classify the seeds also without the complete assignment of the spectra. The analysis was performed by applying multivariate techniques (principal component analysis and partial least squares-discriminant analysis) to NMR data.

LF-NMR water self-diffusion and relaxation time measurements of hydrogel contact lenses interacting with artificial tears.

The different swelling properties of ionic and non-ionic lenses, immersed in sodium chloride or artificial tears, were investigated by Low-Field Nuclear Magnetic Resonance (LF-NMR) through relaxation time and self-diffusion coefficient measurements. A new model was developed to estimate the water self-diffusion coefficient inside the lenses, the results of which revealed a different mechanism of interaction for ionic versus non-ionic materials with artificial tears. The consequence of this finding suggests clinical implications.