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Predicting condensed tannin concentrations in Lotus uliginosus Schkuhr using near‐infrared reflectance spectroscopy
Author(s) -
Smith Kevin F,
Kelman Walter M
Publication year - 1997
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/(sici)1097-0010(199710)75:2<263::aid-jsfa874>3.0.co;2-l
Subject(s) - partial least squares regression , near infrared reflectance spectroscopy , linear regression , stepwise regression , calibration , standard error , lotus , regression analysis , mathematics , regression , diffuse reflectance infrared fourier transform , reflectivity , chemistry , statistics , remote sensing , near infrared spectroscopy , optics , botany , biology , biochemistry , physics , photocatalysis , geology , catalysis
Near‐infrared reflectance spectroscopy (NIRS) was used to develop equations to predict condensed tannins (CT) in greater lotus ( Lotus uliginosus Schkuhr) with a precision satisfactory for the screening of genotypes in a plant breeding programme. NIRS equations were developed using both partial least squares and stepwise multiple linear regression techniques, and a wide range of mathematical treatments of the log 1/reflectance NIRS data. In general, equations developed using partial least squares regression techniques had 10–15% lower standard errors than those developed using stepwise multiple linear regression, during both calibration and prediction. Standard errors of calibration ranged from 10 to 17 g kg −1 , standard errors of prediction from 12 to 17 g kg −1 . These errors equate to coefficients of variation in the order of 20% The use of NIRS to predict CT in greater lotus will allow more rapid evaluation and selection of genotypes than could be achieved using butan‐1‐ol/HCl hydrolysis. © 1997 SCI.