Journal
JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE
Volume 94, Issue 11, Pages 2239-2245Publisher
WILEY
DOI: 10.1002/jsfa.6548
Keywords
rapeseed; photoacoustic spectroscopy; protein content; quantification; partial least squares (PLS); interval selection
Funding
- National Natural Scientific Foundation of China [40871113]
- Innovative Project for Young Scientists from the Chinese Academy of Sciences [KZCX2-YW-QN411]
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BACKGROUND: Fast and non-destructive determination of rapeseed protein content carries significant implications in rapeseed production. This study presented the first attempt of using Fourier transform mid-infrared photoacoustic spectroscopy (FTIR-PAS) to quantify protein content of rapeseed. The full-spectrum model was first built using partial least squares (PLS). Interval selection methods including interval partial least squares (iPLS), synergy interval partial least squares (siPLS), backward elimination interval partial least squares (biPLS) and dynamic backward elimination interval partial least squares (dyn-biPLS) were then employed to select the relevant band or band combination for PLS modeling. RESULTS: The full-spectrum PLS model achieved an ratio of prediction to deviation (RPD) of 2.047. In comparison, all interval selection methods produced better results than full-spectrum modeling. siPLS achieved the best predictive accuracy with an RPD of 3.215 when the spectrum was sectioned into 25 intervals, and two intervals (1198-1335 and 1614-1753 cm(-1)) were selected. iPLS excelled biPLS and dyn-biPLS, and dyn-biPLS performed slightly better than biPLS. CONCLUSION: FTIR-PAS was verified as a promising analytical tool to quantify rapeseed protein content. Interval selection could extract the relevant individual band or synergy band associated with the sample constituent of interest, and then improve the prediction accuracy of the full-spectrum model. (C) 2013 Society of Chemical Industry
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