Journal article published in Journal of Agricultural and Food Chemistry, volume 61, pp. 8752–8764.

Authors: Luca Rolle, Simone Giacosa, Fabrizio Torchio, Daniele Perenzoni, Susana Río Segade, Vincenzo Gerbi and Fulvio Mattivi.

Abstract

The use of instrumental acoustic parameters produced during a compression test as reliable predictors of the extractable phenolic composition in intact winegrape seeds, determined by reference chemical methods, was evaluated by means of the analytical performance of calibration models. These models were developed only for those phenolic compounds most significantly and strongly correlated with the acoustic parameters. The analytical performance of the models was expressed in terms of standard error of cross-validation (SECV) and residual predictive interquartile amplitude (RPIQ), among other statistics. Several acoustic parameters showed satisfactory predictive accuracy for the percentage of galloylation in the terminal units, the content of (-)-epicatechin and the mean degree of polymerization. Most of the reliable models developed are fairly recommended not for quantitative purposes but for fast screening (SECV%<19, 1.6<RPIQ<2.1).

Key words instrumental texture analysis, acoustic parameters, seeds crunchiness, extractable phenols, LC-MS

BibTeX entry: click to show

@article{
	2318_138502,
	url = {https://hdl.handle.net/2318/138502},
	author = {Rolle, Luca and Giacosa, Simone and Torchio, Fabrizio and Perenzoni, Daniele and Río Segade, Susana and Gerbi, Vincenzo and Mattivi, Fulvio},
	title = {Use of instrumental acoustic parameters of winegrape seeds as possible predictors of extractable phenolic compounds},
	year = {2013},
	journal = {Journal of Agricultural and Food Chemistry},
	volume = {61},
	abstract = {The use of instrumental acoustic parameters produced during a compression test as reliable predictors of the extractable phenolic composition in intact winegrape seeds, determined by reference chemical methods, was evaluated by means of the analytical performance of calibration models. These models were developed only for those phenolic compounds most significantly and strongly correlated with the acoustic parameters. The analytical performance of the models was expressed in terms of standard error of cross-validation (SECV) and residual predictive interquartile amplitude (RPIQ), among other statistics. Several acoustic parameters showed satisfactory predictive accuracy for the percentage of galloylation in the terminal units, the content of (-)-epicatechin and the mean degree of polymerization. Most of the reliable models developed are fairly recommended not for quantitative purposes but for fast screening (SECV\%<19, 1.6<RPIQ<2.1).},
	keywords = {instrumental texture analysis, acoustic parameters, seeds crunchiness, extractable phenols, LC-MS},
	doi = {10.1021/jf4024382},	
	pages = {8752--8764}
}

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