Polysaccharide-water interactions: NMR and DVS data.

The data provided here relate to the research paper "Assessing the complementarity of TD-NMR, solid-state NMR and Dynamic Vapor Sorption in the characterization of polysaccharide-water interactions". The original data from TD-NMR, ss-NMR and DVS is provided in .dps, topspin and .xls formats respectively, allowing other authors to repeat our processing protocols using different parameters. We also include results obtained by varying the signal treatments. The analysis of these multimodal data have highlighted a variation in polysaccharide-water interactions depending on the type of assembly. These datasets are very useful for discriminating between water bound to polysaccharides and water absorbed or adsorbed into polysaccharide network, a key element in understanding interactions in these assemblies and an essential approach for developing tailor-made polysaccharides-based products.

Assessing the complementarity of time domain NMR, solid-state NMR and dynamic vapor sorption in the characterization of polysaccharide-water interactions.

Characterizing the hygroscopic behavior of macromolecular assemblies is crucial for understanding biological processes as well as to develop tailor-made polysaccharides-based products. In this work, assemblies consisting of nanocelluloses (CNC or CNF) and/or glucomannan in different ratio were studied at different water activity levels, using a multi-analytical approach that combined Dynamic Vapor Sorption (DVS), Time-Domain Nuclear Magnetic Resonance (TD-NMR) and solid-state NMR (ss-NMR). The water retention capacity of the films, as a function of their composition, showed that an enrichment in konjac glucomannan in association with cellulose increased the water absorption capacity but decreased the water retention capacity. In addition, the combination of CNC and glucomannan appears to reduce the water absorption capacity of each polymer. Correlating the findings from the various methods allowed us to propose the use of TD-NMR data for predicting the water retention capacity. These results, summarized in a schematic representation, offer new insights into the organization of water molecules in polysaccharide assemblies in various humidity conditions.

Determination of the lipid content of organic waste using time-domain nuclear magnetic resonance.

Time-Domain Nuclear Magnetic Resonance (TD-NMR) was used to quantify the lipid contents of 48 different organic waste substrates. Results obtained from TD-NMR were compared to those from Soxhlet extraction, currently the prevalent method for organic waste characterization, especially in the field of anaerobic digestion. Two calibration methods were tested. The first was a self-calibration process using pure oils (NMR1) which showed good repeatability compared to Soxhlet extraction with a better coefficient of variation (5%). Analyses of volatile fatty acids (VFA) and long-chain fatty acids (LCFA) by chromatography were carried out to understand why the NMR1 method produced underestimations for some samples. Statistical analysis showed that the presence of saturated fatty acids had a significant effect on differences between the Soxhlet and NMR1 methods. The second calibration method applied chemometrics to TD-NMR raw data (NMR2), taking Soxhlet extraction values as references. It provided a good prediction of lipid content and avoided the lengthy calibration procedure usually required for this type of study. Last, the NMR2 method was shown to be highly suited to the quantification of lipids in organic waste, demonstrating better repeatability than the classic Soxhlet method.

A global non-invasive methodology for the phenotyping of potato under water deficit conditions using imaging, physiological and molecular tools.

BACKGROUND: Drought is a major consequence of global heating that has negative impacts on agriculture. Potato is a drought-sensitive crop; tuber growth and dry matter content may both be impacted. Moreover, water deficit can induce physiological disorders such as glassy tubers and internal rust spots. The response of potato plants to drought is complex and can be affected by cultivar type, climatic and soil conditions, and the point at which water stress occurs during growth. The characterization of adaptive responses in plants presents a major phenotyping challenge. There is therefore a demand for the development of non-invasive analytical techniques to improve phenotyping. RESULTS: This project aimed to take advantage of innovative approaches in MRI, phenotyping and molecular biology to evaluate the effects of water stress on potato plants during growth. Plants were cultivated in pots under different water conditions. A control group of plants were cultivated under optimal water uptake conditions. Other groups were cultivated under mild and severe water deficiency conditions (40 and 20% of field capacity, respectively) applied at different tuber growth phases (initiation, filling). Water stress was evaluated by monitoring soil water potential. Two fully-equipped imaging cabinets were set up to characterize plant morphology using high definition color cameras (top and side views) and to measure plant stress using RGB cameras. The response of potato plants to water stress depended on the intensity and duration of the stress. Three-dimensional morphological images of the underground organs of potato plants in pots were recorded using a 1.5 T MRI scanner. A significant difference in growth kinetics was observed at the early growth stages between the control and stressed plants. Quantitative PCR analysis was carried out at molecular level on the expression patterns of selected drought-responsive genes. Variations in stress levels were seen to modulate ABA and drought-responsive ABA-dependent and ABA-independent genes. CONCLUSIONS: This methodology, when applied to the phenotyping of potato under water deficit conditions, provides a quantitative analysis of leaves and tubers properties at microstructural and molecular levels. The approaches thus developed could therefore be effective in the multi-scale characterization of plant response to water stress, from organ development to gene expression.

NMR signal analysis to characterize solid, aqueous, and lipid phases in baked cakes.

Proton mobility was studied in molecular fractions of some model systems and of cake using a 1H nuclear magnetic resonance (NMR) relaxation technique. For cake, five spin-spin relaxation times (T2) were obtained from transverse relaxation curves: T2 (1) approximately 20 micros, T2 (2) approximately 0.2 ms, T2 (3) approximately 3 ms, T2 (4) approximately 50 ms, and T2 (2) approximately 165 ms. The faster component was attributed to the solid phase, components 2 and 3 were associated with the aqueous phase, and the two slowest components were linked to the lipid phase. After cooking, the crust contained more fat but less water than the center part of the cake. The amount of gelatinized starch was lower in the crust, and water was more mobile due to less interaction with macromolecules. This preliminary study revealed different effects of storage on the center and crust.