Spikes and seeds from diploid ‘einkorn’ wheat Triticum monococcum and two near-isogenic hard and soft common wheat (Triticum aestivum) lines were harvested at regular intervals from 7 days post-anthesis (dpa) and analysed by non-destructive magnetic resonance imaging (MRI) and time domain-nuclear magnetic resonance (TD-NMR). A large amount of free water occurred in rachises, glumes and awns of spikes collected at 7 dpa, and accumulated in the physiologically active cells of the endosperm at 21 dpa. In the final stages of kernel development, awns and seed embryos exhibited a high MR signal due to the presence of free water likely associated with biological activities. TD-NMR relaxation time distributions obtained by discrete exponential fitting, distributed exponential fitting and SLICING multivariate analysis offered detailed information on mobility behaviour of water molecules in developing seeds and were able to differentiate two soft and hard isolines from common wheat cv. Enesco at early stages of seed development.

To shed light on the specific contribution of HDA101 in modulating metabolic pathways in the maize seed, changes in the metabolic profiles of kernels obtained from hda101 mutant plants have been investigated by a metabonomic approach. Dynamic properties of chromatin folding can be mediated by enzymes that modify DNA and histones. The enzymes responsible for the steady-state of histone acetylation are histone acetyltransferase and histone deacetylase (HDA). Therefore, it is interesting to evaluate the effects of up- and down-regulation of a Rpd-3 type HDA on the development of maize seeds in terms of metabolic changes. This has been reached by analysing nuclear magnetic resonance spectra by different chemometrician approaches, such as Orthogonal Projection to Latent Structure-Discriminant Analysis, Parallel Factors Analysis, and Multi-way Partial Least Squares-Discriminant Analysis (N-PLS-DA). In particular, the latter approaches were chosen because they explicitly take time into account, organizing data into a set of slices that refer to different steps of the developing process. The results show the good discriminating capabilities of the N-PLS-DA approach, even if the number of samples ought be increased to obtain better predictive capabilities. However, using this approach, it was possible to show differences in the accumulation of metabolites during development and to highlight the changes occuring in the modified seeds. In particular, the results confirm the role of this gene in cell cycle control.

The aim of this research was to show that the application of multiway partial least square-discriminant analysis to nuclear magnetic resonance spectra is a valuable tool to analyze metabonomic data of transgenic maize. We evaluated the effects, on the development of seeds, of the introduction of the antisense-mediated downregulation and overexpression of the Rpd3 gene (ZmRpd3) in the genome of a maize inbred line, we identified the metabolites involved in the differentiation between classes of samples, directly integrating the evolution of each metabolic perturbation over time in the model. Major differences were found at the beginning of development, confirming the results obtained by transcript analysis: ZmRpd3 transcripts and proteins accumulate during the initial stage of development, suggesting a role for this gene in cell cycle control.

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.

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.

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.

Determining the time constants and amplitudes of exponential decays from relaxation data is a common task in LF-NMR. In this communication, we present an application of the SLICING algorithm to evaluate its possibilities for solving this problem. The method, originally introduced to compare different samples, is applied here to analyse a single relaxation curve, using the embedding technique. To test this procedure, we acquired data sets from samples of liquids properly separated, and characterized by different relaxation times. The results show a good estimation of parameters, comparable with those obtained applying Marquardt's algorithm, when the components have sufficiently different relaxation times.