Compositional data analysis of Holocene sediments from the West Bengal Sundarbans, India: Geochemical proxies for grain-size variability in a delta environment

This paper is part of a special issue of Applied Geochemistry focusing on reliable applications of compositional multivariate statistical methods. This study outlines the application of compositional data analysis (CoDa) to calibration of geochemical data and multivariate statistical modelling of geochemistry and grain-size data from a set of Holocene sedimentary cores from the Ganges-Brahmaputra (G-B) delta. Over the last two decades, understanding near-continuous records of sedimentary sequences has required the use of core-scanning X-ray fluorescence (XRF) spectrometry, for both terrestrial and marine sedimentary sequences. Initial XRF data are generally unusable in ‘raw-format’, requiring data processing in order to remove instrument bias, as well as informed sequence interpretation. The applicability of these conventional calibration equations to core-scanning XRF data are further limited by the constraints posed by unknown measurement geometry and specimen homogeneity, as well as matrix effects. Log-ratio based calibration schemes have been developed and applied to clastic sedimentary sequences focusing mainly on energy dispersive-XRF (ED-XRF) core-scanning. This study has applied high resolution core-scanning XRF to Holocene sedimentary sequences from the tidal-dominated Indian Sundarbans, (Ganges-Brahmaputra delta plain). The Log-Ratio Calibration Equation (LRCE) was applied to a sub-set of core-scan and conventional ED-XRF data to quantify elemental composition. This provides a robust calibration scheme using reduced major axis regression of log-ratio transformed geochemical data. Through partial least squares (PLS) modelling of geochemical and grain-size data, it is possible to derive robust proxy information for the Sundarbans depositional environment. The application of these techniques to Holocene sedimentary data offers an improved methodological framework for unravelling Holocene sedimentation patterns.

Using Vibrational Infrared Biomolecular Spectroscopy to Detect Heat-Induced Changes of Molecular Structure in Relation to Nutrient Availability of Prairie Whole Oat Grains on a Molecular Basis

Background To our knowledge, there is little study on the interaction between nutrient availability and molecular structure changes induced by different processing methods in dairy cattle. The objective of this study was to investigate the effect of heat processing methods on interaction between nutrient availability and molecular structure in terms of functional groups that are related to protein and starch inherent structure of oat grains with two continued years and three replication of each year. Method The oat grains were kept as raw (control) or heated in an air-draft oven (dry roasting: DO) at 120 °C for 60 min and under microwave irradiation (MIO) for 6 min. The molecular structure features were revealed by vibrational infrared molecular spectroscopy. Results The results showed that rumen degradability of dry matter, protein and starch was significantly lower (P <0.05) for MIO compared to control and DO treatments. A higher protein α-helix to β-sheet and a lower amide I to starch area ratio were observed for MIO compared to DO and/or raw treatment. A negative correlation (−0.99, P < 0.01) was observed between α-helix or amide I to starch area ratio and dry matter. A positive correlation (0.99, P < 0.01) was found between protein β-sheet and crude protein. Conclusion The results reveal that oat grains are more sensitive to microwave irradiation than dry heating in terms of protein and starch molecular profile and nutrient availability in ruminants.