TD-NMR studies of starches from different botanical origins: Hydrothermal and storage effects

Probing structural features in potato starch granules at moderate hydration through the modelling of 1H->13C polarization transfer kinetics

The structural arrangement of starch polymers in presence of water is known to impact the functional properties of starchy products. In this study, the hydration of potato starch granules was investigated at the molecular level through various 1H->13C polarization transfer solid-state Nuclear Magnetic Resonance (ss-NMR) experiments. The impact of increasing the water content from 12.3 % to 45.9 % was assessed using 13C Cross Polarization Magic Angle Spinning (CPMAS), Variable Contact Time (VCT-CPMAS), Variable Spin Lock (VSL-CPMAS), and T One Rho QUEnching (TORQUE) NMR sequences. Of these, VCT-CPMAS proved to be the most promising. When applied with an optimal number of contact times, it enabled the application of several mathematical models that provided detailed insights into the structuring of protons in the hydrated potato starch granules. At low hydration (12.3 %), the models enabled various structural domains to be distinguished, which we suggest are associated with helical and amorphous structures. At moderate hydration (45.9 %), we tested two fitting models. Two pools of protons were revealed, corresponding to loosely ordered structures on the scale of tens of nanometers. These findings suggest varying water distribution during starch hydration and are likely to indicate variable hydration levels in the multilamellar amorphous structures of starch granules.

Introducing comprehensive multiphase NMR for the analysis of food: Understanding the hydrothermal treatment of starch-based foods

Cooking is essential for preparing starch-based food, however thermal treatment promotes the complexation of biopolymers, impacting their final properties. Comprehensive Multiphase (CMP) NMR allows all phases (liquids, gels, and solids) to be differentiated and monitored within intact samples. This study acts as a proof-of-principle to introduce CMP-NMR to food research and demonstrate its application to monitor the various phases in spaghetti, black turtle beans, and white long-grain rice, and how they change during the cooking process. When uncooked, only a small fraction of lipids and structurally bound water show any molecular mobility. Once cooked, little "crystalline solid" material is left, and all components exhibit increased molecular dynamics. Upon cooking, the solid-like components in spaghetti contains signals consistent with cellulose that were buried beneath the starches in the uncooked product. Thus, CMP-NMR holds potential for the study of food and related processes involving phase changes such as growth, manufacturing, and composting.

The use of time domain 1 H NMR to study proton dynamics in starch-rich foods: A review

Starch is a major contributor to the carbohydrate portion of our diet. When it is present with water, it undergoes several transformations during heating and/or cooling making it an essential structure-forming component in starch-rich food systems (e.g., bread and cake). Time domain proton nuclear magnetic resonance (TD ¹ H NMR) is a useful technique to study starch-water interactions by evaluation of molecular mobility and water distribution. The data obtained correspond to changes in starch structure and the state of water during or resulting from processing. When this technique was first applied to starch(-rich) foods, significant challenges were encountered during data interpretation of complex food systems (e.g., cake or biscuit) due to the presence of multiple constituents (proteins, carbohydrates, lipids, etc.). This article discusses the principles of TD ¹ H NMR and the tools applied that improved characterization and interpretation of TD NMR data. More in particular, the major differences in proton distribution of various dough and cooked/baked food systems are examined. The application of variable-temperature TD ¹ H NMR is also discussed as it demonstrates exceptional ability to elucidate the molecular dynamics of starch transitions (e.g., gelatinization, gelation) in dough/batter systems during heating/cooling. In conclusion, TD NMR is considered a valuable tool to understand the behavior of starch and water that relate to the characteristics and/or quality of starchy food products. Such insights are crucial for food product optimization and development in response to the needs of the food industry.

An insight into tapioca and wheat starch gelatinization mechanisms using TD-NMR and complementary techniques

To provide evidence for previously proposed assumptions concerning starch gelatinization sub-mechanisms, a more detailed investigation was carried out using multiscale analysis of a starch type selected for its marked difference. Tapioca starch was chosen due to its cohesive/springy properties and its growing use in the food industry. Time-domain nuclear magnetic resonance (TD-NMR) was used to investigate the leaching of material, water absorption and crystallite melting in hydrated tapioca starch (45%). The interpretation of T2 mass intensity evolutions, especially those of the (intra- and extra-granular) aqueous phases, was discussed drawing on complementary techniques such as microscopy, Rapid Visco Analyser (RVA), differential scanning calorimetry (DSC) and swelling factor (SF) and solubility index (SI) measurements. Results show that the T2 assignments usually proposed in the literature are dependent on starch origin. The differences in T2 evolutions (value and mass intensity) observed between wheat and tapioca starches at intermediate hydration levels could be linked to the different gelatinization behaviour of tapioca starch involving the latter's higher granule rupture level, higher gelatinization temperature and greater swelling power above its gelatinization temperature.

Analysis of molecular mobility in corn and quinoa flours through 1H NMR and its relationship with water distribution, glass transition and enthalpy relaxation

Solids-water interactions of corn and quinoa flours were evaluated through ¹H NMR, DSC, and water sorption isotherms. Glass transition temperature (T_g), observed by DSC, was better distinguished through FID signals, and correlated to water content through the Gordon and Taylor model. Enthalpy relaxations, identified by thermal analysis at 50-70 °C were studied through transverse relaxation times (T₂) measured after Hahn spin-echo sequence, which revealed a rearrangement of the biopolymers structures that cause immobilization of polymer chains and reduced mobility of water molecules with weak interactions with solids (lower T₂₂). The higher lipid content of quinoa flour was manifested after the CPMG sequence (T₂ ≈ 100 ms) and caused reduced hygroscopicity and T_g values compared with corn flour systems. ¹H NMR resulted efficient for assigning proton populations and understanding the changes in their distribution with temperature, analyzing glass transition and interpreting the implications of enthalpy relaxations processes in corn and quinoa flours.

Data fusion of middle-resolution NMR spectroscopy and low-field relaxometry using the Common Dimensions Analysis (ComDim) to monitor diesel fuel adulteration

Medium-resolution (MR-NMR) and time-domain NMR relaxometry (TD-NMR) using benchtop and low-field NMR instruments are powerful tools to tackle fuel adulteration issues. In this work, for the first time, we investigate the possibility of enhancing the low-field NMR capability on fuel analysis using data fusion of MR and TD-NMR. We used the ComDim (Common Dimensions Analysis) multi-block analysis to join the data, which allowed exploration, classification, and quantification of common adulterations of diesel fuel by vegetable oils, biodiesel, and diesel of different sources as well as the sulfur content. After data exploration using ComDim, classification (applying linear discriminant analysis, LDA), and regression (applying multiple linear regression, MLR), models were built using ComDim scores as input variables on the LDA and MLR analyses. This approach enabled 100% of accuracy in classifying diesel fuel source (refinery), sulfur content (S10 or S500), vegetable oil, and biodiesel source. Moreover, in the quantification step, all MLR models showed a root mean square error of prediction (RMSEP) and the residual prediction deviation (RPD) values comparable to the literature for determining diesel, vegetable oil, and biodiesel contents.

Low field, time domain NMR in the agriculture and agrifood sectors: An overview of applications in plants, foods and biofuels

In this contribution, a selective overview of low field, time-domain NMR (TD-NMR) applications in the agriculture and agrifood sectors is presented. The first applications of commercial TD-NMR instruments were in food and agriculture domains. Many of these earlier methods have now been recognized as standard methods by several international agencies. Since 2000, several new applications have been developed, using state of the art instruments, new pulse sequences and new signal processing methods. TD-NMR is expected, in the coming years, to become even more important in quality control of fresh food and agricultural products, as well as for a wide range of food-processed products. TD-NMR systems provide excellent means to collect data relevant for use in the agricultural environment and the bioenergy industry. Data and information collected by TD-NMR systems thus may support decision makers in business and public organizations.