Search from over 60,000 research works

Advanced Search

Rapid tannin profiling of tree fodders using untargeted mid-infrared spectroscopy and partial least squares regression

[thumbnail of Open access]
Preview
s13007-021-00715-8.pdf - Published Version (2MB) | Preview
Available under license: Creative Commons Attribution
[thumbnail of Ortuno et al. 2021 - Accepted version.pdf]
Restricted to Repository staff only
Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

Ortuño, J., Stergiadis, S. orcid id iconORCID: https://orcid.org/0000-0002-7293-182X, Koidis, A., Smith, J., Humphrey, C., Whistance, L. and Theodoridou, K. (2021) Rapid tannin profiling of tree fodders using untargeted mid-infrared spectroscopy and partial least squares regression. Plant Methods, 17. 14. ISSN 1746-4811 doi: 10.1186/s13007-021-00715-8

Abstract/Summary

Background: The presence of condensed tannins (CT) in tree fodders entails a series of productive, health and ecological benefits for ruminant nutrition. Current wet analytical methods employed for full CT characterisation are time and resource-consuming, thus limiting its applicability for silvopas-toral systems. The development of quick, safe and robust analytical techniques to monitor CT's full profile is crucial to suitably understand CT variability and biological activity, which would help to de-velop efficient evidence-based decision-making to maximise CT-derived benefits. The present study investigates the suitability of Fourier-transformed mid-infrared spectroscopy (MIR: 4000-550 cm-1) combined with multivariate analysis to determine CT concentration and structure (mean degree of polymerization - mDP, procyanidins:prodelphidins ratio – PC:PD and cis:trans ratio) in oak, field maple and goat willow foliage, using HCl:Butanol:Acetone:Iron (HBAI) and thiolysis-HPLC as reference methods. Results: The MIR spectra obtained were explored firstly using Principal Component Analysis, whereas multivariate calibration models were developed based on partial least-squares regression. MIR showed an excellent prediction capacity for the determination of PC:PD (coeffi-cient of determination for prediction (R2P) = 0.96; ratio of prediction to deviation (RPD) = 5.26, range error ratio (RER) = 14.1) and cis:trans ratio (R2P=0.95; RPD=4.24; RER=13.3); modest for CT quantification (HBAI: R2P=0.92; RPD=3.71; RER=13.1; Thiolysis: R2P=0.88; RPD=2.80; RER=11.5); and weak for mDP (R2P=0.66; RPD=1.86; RER=7.16). Conclusions: MIR combined with chemometrics allowed to characterize the full CT profile of tree foliage rapidly, which would help to assess better plant ecology variability and to improve the nutritional management of ruminant livestock.

Altmetric Badge

Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/95786
Item Type Article
Refereed Yes
Divisions Life Sciences > School of Agriculture, Policy and Development > Department of Animal Sciences > Animal, Dairy and Food Chain Sciences (ADFCS)- DO NOT USE
Publisher BioMed Central
Download/View statistics View download statistics for this item

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Search Google Scholar