Analytical FT‐Raman spectroscopy to chemotype Leptospermum scoparium and generate predictive models for screening for dihydroxyacetone levels in floral nectar. (8th September 2014)

• Record Type: Journal Article
• Authors: Nickless, Elizabeth M.; Holroyd, Stephen E.; Stephens, Jonathan M.; Gordon, Keith C.; Wargent, Jason J.
• Is Part Of: Journal of Raman spectroscopy. Volume 45:Number 10(2014:Oct.)
• Page Start: 890
• Page End: 894
• Publication Date: 2014-09-08
• Subjects: Raman spectroscopy -- Periodicals; 535.846
• DOI: 10.1002/jrs.4576
• Languages: English
• ISSNs: 0377-0486

Abstract

<abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <p> <italic>Leptospermum scoparium</italic> (Mānuka) is the source of nectar for Unique Mānuka Factor (UMF) honey. The chemical component of interest to this study is dihydroxyacetone (DHA). DHA is the precursor for the chemical methylglyoxyl which is the main chemical responsible for the UMF activity in Manuka honey. Screening commercially bred plants for increased DHA synthesis in <italic>L. scoparium</italic> is a critical factor in growing the Manuka Honey industry in New Zealand. FT‐Raman spectroscopy, in combination with principal component analysis and partial least squares regression analysis, was investigated as an analytical tool for building a screening model for DHA in the nectar of <italic>L. scoparium.</italic> Leaf samples of seven cultivars of the species <italic>L. scoparium</italic> were collected in an attempt to correlate metabolic factors in the plant with DHA synthesis in the nectar. Leaf material was analysed using Fourier transform‐raman spectroscopy (FT‐Raman). The DHA levels in nectar samples of the same cultivars were measured using standard LC‐MS methods. This study showed that the application of multivariate analysis of FT‐Raman spectra from leaf material is a useful tool to screen for DHA potential in <italic>L. scoparium</italic>. The PLS regression shows that we can screen for DHA concentrations in the range of 3300–7600 mg/kg plus or minus 20% standard error and can distinguish low medium and high DHA synthesis in the group of plants studied. The model for predicting DHA concentrations is influenced by a significant contribution from the spectral variance due to beta‐carotene and other highly scattering compounds that are not directly correlated with UMF. Copyright © 2014 John Wiley & Sons, Ltd.</p> </abstract>