Near infrared spectroscopy for high-throughput characterization of shea tree (Vitellaria paradoxa) nut fat profiles

Davrieux Fabrice, Allal François, Piombo Georges, Kelly Bokary Allaye, Okullo John B., Thiam Massamba, Diallo Ousmane Boukary, Bouvet Jean-Marc. 2010. Near infrared spectroscopy for high-throughput characterization of shea tree (Vitellaria paradoxa) nut fat profiles. Journal of Agricultural and Food Chemistry, 58 (13) : 7811-7819.

https://doi.org/10.1021/jf100409v

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Quartile : Outlier, Sujet : AGRICULTURE, MULTIDISCIPLINARY / Quartile : Q1, Sujet : FOOD SCIENCE & TECHNOLOGY / Quartile : Q1, Sujet : CHEMISTRY, APPLIED

Résumé : The Shea tree (Vitellaria paradoxa) is a major tree species in African agroforestry systems. Butter extracted from its nuts offers an opportunity for sustainable development in Sudanian countries and an attractive potential for the food and cosmetics industries. The purpose of this study was to develop near-infrared spectroscopy (NIRS) calibrations to characterize Shea nut fat profiles. Powders prepared from nuts collected from 624 trees in five African countries (Senegal, Mali, Burkina Faso, Ghana and Uganda) were analyzed for moisture content, fat content using solvent extraction, and fatty acid profiles using gas chromatography. Results confirmed the differences between East and West African Shea nut fat composition: eastern nuts had significantly higher fat and oleic acid contents. Near infrared reflectance spectra were recorded for each sample. Ten percent of the samples were randomly selected for validation and the remaining samples used for calibration. For each constituent, calibration equations were developed using modified partial least squares (MPLS) regression. The equation performances were evaluated using the ratio performance to deviation (RPDp) and Rp 2 parameters, obtained by comparison of the validation set NIR predictions and corresponding laboratory values. Moisture (RPDp = 4.45; Rp 2 = 0.95) and fat (RPDp = 5.6; Rp 2 = 0.97) calibrations enabled accurate determination of these traits. NIR models for stearic (RPDp = 6.26; Rp 2 = 0.98) and oleic (RPDp = 7.91; Rp 2 = 0.99) acids were highly efficient and enabled sharp characterization of these two major Shea butter fatty acids. This study demonstrated the ability of near-infrared spectroscopy for high-throughput phenotyping of Shea nuts.

Mots-clés Agrovoc : Vitellaria paradoxa, agroforesterie, spectroscopie infrarouge

Mots-clés géographiques Agrovoc : Mali, Ouganda, Sénégal, Ghana, Burkina Faso

Classification Agris : Q04 - Composition des produits alimentaires
U30 - Méthodes de recherche

Champ stratégique Cirad : Axe 3 (2005-2013) - Alimentation accessible et de qualité

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