Au, J;
Youngentob, KN;
Foley, WJ;
Moore, BD;
Fearn, T;
(2020)
Sample selection, calibration and validation of models developed from a large dataset of near infrared spectra of tree leaves.
Journal of Near Infrared Spectroscopy
, 28
(4)
pp. 186-203.
10.1177/0967033520902536.
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Abstract
Near infrared spectroscopy is widely used to rapidly and cost-effectively collect chemical information from plant samples. Large datasets with hundreds to thousands of spectra and reference values are increasingly becoming more common as researchers accumulate data over many years or across research groups. These datasets potentially contain great spectral and chemical variation and could produce a broadly-applicable calibration model. In this study, partial least squares regression was used to model relationships between near infrared spectra and the foliar concentration of two ecologically-important chemical traits, available nitrogen and total formylated phloroglucinol compounds in Eucalyptus leaves. The nested spatial structure within the extensive dataset of spectra and reference values from 80 species of Eucalyptus was taken into account during calibration development and model validation. Geographic variation amongst samples influenced how well available nitrogen could be predicted. Predictive error of the model was greatest when tested against samples from different Australian states and local government areas to the calibration set. In addition, the results showed that simply relying on spectral variation (assessed by Mahalanobis distance) may mislead researchers into how many reference values are needed. The prediction accuracy of the model of available nitrogen differed little whether 300 or up to 987 calibration samples were included, which indicated that an excessive number of reference values were obtained. Lastly, a suitable multi-species calibration for formylated phloroglucinol compounds was produced and the difficulties associated with predicting complex chemical traits were discussed. Directing effort towards broadly applicable models will encourage sharing of calibration models across projects and research groups and facilitate the integration of near infrared spectroscopy in many research fields.
| Type: | Article |
|---|---|
| Title: | Sample selection, calibration and validation of models developed from a large dataset of near infrared spectra of tree leaves |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1177/0967033520902536 |
| Publisher version: | https://doi.org/10.1177/0967033520902536 |
| Language: | English |
| Additional information: | This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
| Keywords: | Available nitrogen, forage quality, formylated phloroglucinol compounds, herbivore, large datasets, near infrared, partial least squares regression, sample size |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10096633 |
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