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Prediction of essential oil content of oregano by hand‐held and Fourier transform NIR spectroscopy
Author(s) -
Camps Cédric,
Gérard Marianne,
Quennoz Mélanie,
Brabant Cécile,
Oberson Carine,
Simonnet Xavier
Publication year - 2014
Publication title -
journal of the science of food and agriculture
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.782
H-Index - 142
eISSN - 1097-0010
pISSN - 0022-5142
DOI - 10.1002/jsfa.6427
Subject(s) - partial least squares regression , near infrared spectroscopy , spectroscopy , fourier transform , fourier transform infrared spectroscopy , analytical chemistry (journal) , chemistry , mathematics , chromatography , computer science , materials science , statistics , optics , physics , mathematical analysis , quantum mechanics
BACKGROUND In the framework of a breeding programme, the analysis of hundreds of oregano samples to determine their essential oil content ( EOC ) is time‐consuming and expensive in terms of labour. Therefore developing a new method that is rapid, accurate and less expensive to use would be an asset to breeders. The aim of the present study was to develop a method based on near‐inrared ( NIR ) spectroscopy to determine the EOC of oregano dried powder. Two spectroscopic approaches were compared, the first using a hand‐held NIR device and the second a Fourier transform ( FT ) NIR spectrometer . RESULTS Hand‐held NIR (1000–1800 nm) measurements and partial least squares regression allowed the determination of EOC with R 2 and SEP values of 0.58 and 0.81 mL per 100 g dry matter (DM) respectively. Measurements with FT‐NIR (1000–2500 nm) allowed the determination of EOC with R 2 and SEP values of 0.91 and 0.68 mL per 100 g DM respectively. RPD, RER and RPIQ values for the model implemented with FT‐NIR data were satisfactory for screening application, while those obtained with hand‐held NIR data were below the level required to consider the model as enough accurate for screening application . CONCLUSION The FT‐NIR approach allowed the development of an accurate model for EOC prediction. Although the hand‐held NIR approach is promising, it needs additional development before it can be used in practice. © 2013 Society of Chemical Industry