Aspects and Applications of Pulse Sequence Design for Solution-State Nuclear Magnetic Resonance Spectroscopy

NMR spectroscopy enables the study of biomolecules from peptides and carbohydrates to proteins at atomic resolution. The technique uniquely allows for structure determination of molecules in solution-state. It also gives insights into dynamics and intermolecular interactions important for determining biological function. Detailed molecular information is entangled in the nuclear spin states. The information can be extracted by pulse sequences designed to measure the desired molecular parameters. Advancement of pulse sequence methodology therefore plays a key role in the development of biomolecular NMR spectroscopy. A range of novel pulse sequences for solution-state NMR spectroscopy are presented in this thesis. The pulse sequences are described in relation to the molecular information they provide. The pulse sequence experiments represent several advances in NMR spectroscopy with particular emphasis on applications for proteins. Some of the novel methods are focusing on methyl-containing amino acids which are pivotal for structure determination. Methyl-specific assignment schemes are introduced for increasing the size range of 13C,15N labeled proteins amenable to structure determination without resolving to more elaborate labeling schemes. Furthermore, cost-effective means are presented for monitoring amide and methyl correlations simultaneously. Residual dipolar couplings can be applied for structure refinement as well as for studying dynamics. Accurate methods for measuring residual dipolar couplings in small proteins are devised along with special techniques applicable when proteins require high pH or high temperature solvent conditions. Finally, a new technique is demonstrated to diminish strong-coupling induced artifacts in HMBC, a routine experiment for establishing long-range correlations in unlabeled molecules. The presented experiments facilitate structural studies of biomolecules by NMR spectroscopy.

TlBr raw material purification, crystal growth, annealing, detector fabrication and characterisation for gamma-ray detector applications

The research reported in this thesis dealt with single crystals of thallium bromide grown for gamma-ray detector applications. The crystals were used to fabricate room temperature gamma-ray detectors. Routinely produced TlBr detectors often are poor quality. Therefore, this study concentrated on developing the manufacturing processes for TlBr detectors and methods of characterisation that can be used for optimisation of TlBr purity and crystal quality. The processes under concern were TlBr raw material purification, crystal growth, annealing and detector fabrication. The study focused on single crystals of TlBr grown from material purified by a hydrothermal recrystallisation method. In addition, hydrothermal conditions for synthesis, recrystallisation, crystal growth and annealing of TlBr crystals were examined. The final manufacturing process presented in this thesis deals with TlBr material purified by the Bridgman method. Then, material is hydrothermally recrystallised in pure water. A travelling molten zone (TMZ) method is used for additional purification of the recrystallised product and then for the final crystal growth. Subsequent processing is similar to that described in the literature. In this thesis, literature on improving quality of TlBr material/crystal and detector performance is reviewed. Aging aspects as well as the influence of different factors (temperature, time, electrode material and so on) on detector stability are considered and examined. The results of the process development are summarised and discussed. This thesis shows the considerable improvement in the charge carrier properties of a detector due to additional purification by hydrothermal recrystallisation. As an example, a thick (4 mm) TlBr detector produced by the process was fabricated and found to operate successfully in gamma-ray detection, confirming the validity of the proposed purification and technological steps. However, for the complete improvement of detector performance, further developments in crystal growth are required. The detector manufacturing process was optimized by characterisation of material and crystals using methods such as X-ray diffraction (XRD), polarisation microscopy, high-resolution inductively coupled plasma mass (HR-ICPM), Fourier transform infrared (FTIR), ultraviolet and visual (UV-Vis) spectroscopy, field emission scanning electron microscope (FESEM) and energy-dispersive X-ray spectroscopy (EDS), current-voltage (I-V) and capacity voltage (CV) characterisation, and photoconductivity, as well direct detector examination.

Infrared spectroscopy as a rapid tool to detect methylglyoxal and antibacterial activity in Australian honeys

Methylglyoxal (2-oxopropanal) is a compound known to contribute to the non-peroxide antimicrobial activity of honeys. The feasibility of using infrared spectroscopy as a predictive tool for honey antibacterial activity and methylglyoxal content was assessed. A linear relationship was found between methylglyoxal content (279–1755 mg/kg) in Leptospermum polygalifolium honeys and bacterial inhibition for Escherichiacoli (R2 = 0.80) and Staphylococcusaureus (R2 = 0.64). A good prediction of methylglyoxal (R2 0.75) content in honey was achieved using spectroscopic data from the mid infrared (MIR) range in combination with partial least squares regression. These results indicate that robust predictive equations could be developed using MIR for commercial application where the prediction of bacterial inhibition is needed to ‘value’ honeys with methylglyoxal contents in excess of 200 mg/kg.

Flaws in the current method for calculating methane emissions during dairy manure management in New Zealand

New Zealand's Greenhouse Gas Inventory (the NZ Inventory) currently estimates methane (CH4) emissions from anaerobic dairy effluent ponds by: (1) determining the total pond volume across New Zealand; (2) dividing this volume by depth to obtain the total pond surface area; and (3) multiplying this area by an observational average CH4 flux. Unfortunately, a mathematically erroneous determination of pond volume has led to an imbalanced equation and a geometry error was made when scaling-up the observational CH4 flux. Furthermore, even if these errors are corrected, the nationwide estimate still hinges on field data from a study that used a debatable method to measure pond CH4 emissions at a single site, as well as a potentially inaccurate estimation of the amount of organic waste anaerobically treated. The development of a new methodology is therefore critically needed.

A novel method for the age estimation of Saddletail snapper (Lutjanus malabaricus) using Fourier Transform-near infrared (FT-NIR) spectroscopy

Near infrared (NIR) spectroscopy was investigated as a potential rapid method of estimating fish age from whole otoliths of Saddletail snapper (Lutjanus malabaricus). Whole otoliths from 209 Saddletail snapper were extracted and the NIR spectral characteristics were acquired over a spectral range of 800–2780 nm. Partial least-squares models (PLS) were developed from the diffuse reflectance spectra and reference-validated age estimates (based on traditional sectioned otolith increments) to predict age for independent otolith samples. Predictive models developed for a specific season and geographical location performed poorly against a different season and geographical location. However, overall PLS regression statistics for predicting a combined population incorporating both geographic location and season variables were: coefficient of determination (R2) = 0.94, root mean square error of prediction (RMSEP) = 1.54 for age estimation, indicating that Saddletail age could be predicted within 1.5 increment counts. This level of accuracy suggests the method warrants further development for Saddletail snapper and may have potential for other fish species. A rapid method of fish age estimation could have the potential to reduce greatly both costs of time and materials in the assessment and management of commercial fisheries.

The utility of near infrared spectroscopy for age estimation of deepwater sharks

Reliable age information is vital for effective fisheries management, yet age determinations are absent for many deepwater sharks as they cannot be aged using traditional methods of growth bands counts. An alternative approach to ageing using near infrared spectroscopy (NIRS) was investigated using dorsal fin spines, vertebrae and fin clips of three species of deepwater sharks. Ages were successfully estimated for the two dogfish, Squalus megalops and Squalus montalbani, and NIRS spectra were correlated with body size in the catshark, Asymbolus pallidus. Correlations between estimated-ages of the dogfish dorsal fin spines and their NIRS spectra were good, with S. megalops R2=0.82 and S. montalbani R2=0.73. NIRS spectra from S. megalops vertebrae and fin clips that have no visible growth bands were correlated with estimated-ages, with R2=0.89 and 0.76, respectively. NIRS has the capacity to non-lethally estimate ages from fin spines and fin clips, and thus could significantly reduce the numbers of sharks that need to be lethally sampled for ageing studies. The detection of ageing materials by NIRS in poorly calcified deepwater shark vertebrae could potentially enable ageing of this group of sharks that are vulnerable to exploitation.

Spectroscopy and photochemistry of hydrogen peroxide and its complexes in solid rare gases

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Biological control of prickly acacia: Current research and future prospects

Prickly acacia, Vachellia nilotica subsp. indica (syn. Acacia nilotica subsp. indica) (Fabaceae), a major weed in the natural grasslands of western Queensland, has been a target of biological control since the 1980s with limited success to date. Surveys in India, based on genetic and climate matching, identified five insects and two rust pathogens as potential agents. Host-specificity tests were conducted for the insects in India and under quarantine conditions in Australia, and for the rust pathogens under quarantine conditions at CABI in the UK. In no-choice tests, the brown leaf-webber, Phycita sp. A, (Lepidoptera: Pyralidae) completed development on 17 non-target plant species. Though the moth showed a clear preference for prickly acacia in oviposition choice trials screening of additional test-plant species was terminated in view of the potential non-target risk. The scale insect Anomalococcus indicus (Hemiptera: Lecanodiaspididae) developed into mature gravid females on 13 out of 58 non-target plant species tested. In the majority of cases very few female scales matured but development was comparable to that on prickly acacia on four of the non-target species. In multiple choice tests, the scale insect showed a significant preference for the target weed over non-target species tested. In a paired-choice trial under field conditions in India, crawler establishment occurred only on prickly acacia and not on the non-target species tested. Further choice trials are to be conducted under natural field conditions in India. A colony of the green leaf-webber Phycita sp. B has been established in quarantine facilities in Australia and host-specificity testing has commenced. The gall-rust Ravenelia acaciae-arabicae and the leaf-rust Ravenelia evansii (Puccineales: Raveneliaceae) both infected and produced viable urediniospores on Vachellia sutherlandii (Fabaceae), a non-target Australian native plant species. Hence, no further testing with the two rust species was pursued. Inoculation trials using the gall mite Aceria liopeltus (Acari: Eriophyidae) from V. nilotica subsp. kraussiana in South Africa resulted in no gall induction on V. nilotica subsp. indica. Future research will focus on the leaf-weevil Dereodus denticollis (Coleoptera: Curculionidae) and the leaf-beetle Pachnephorus sp. (Coleoptera: Chrysomelidae) under quarantine conditions in Australia. Native range surveys for additional potential biological control agents will also be pursued in northern and western Africa.

High-Throughput Prediction of Acacia and Eucalypt Lignin Syringyl/Guaiacyl Content Using FT-Raman Spectroscopy and Partial Least Squares Modeling

High-throughput techniques are necessary to efficiently screen potential lignocellulosic feedstocks for the production of renewable fuels, chemicals, and bio-based materials, thereby reducing experimental time and expense while supplanting tedious, destructive methods. The ratio of lignin syringyl (S) to guaiacyl (G) monomers has been routinely quantified as a way to probe biomass recalcitrance. Mid-infrared and Raman spectroscopy have been demonstrated to produce robust partial least squares models for the prediction of lignin S/G ratios in a diverse group of Acacia and eucalypt trees. The most accurate Raman model has now been used to predict the S/G ratio from 269 unknown Acacia and eucalypt feedstocks. This study demonstrates the application of a partial least squares model composed of Raman spectral data and lignin S/G ratios measured using pyrolysis/molecular beam mass spectrometry (pyMBMS) for the prediction of S/G ratios in an unknown data set. The predicted S/G ratios calculated by the model were averaged according to plant species, and the means were not found to differ from the pyMBMS ratios when evaluating the mean values of each method within the 95 % confidence interval. Pairwise comparisons within each data set were employed to assess statistical differences between each biomass species. While some pairwise appraisals failed to differentiate between species, Acacias, in both data sets, clearly display significant differences in their S/G composition which distinguish them from eucalypts. This research shows the power of using Raman spectroscopy to supplant tedious, destructive methods for the evaluation of the lignin S/G ratio of diverse plant biomass materials.