[논문]Near Infrared Spectroscopy for High-Throughput Characterization of Shea Tree (Vitellaria paradoxa) Nut Fat Profiles

Davrieux, Fabrice; Allal, Franç; ois; Piombo, Georges; Kelly, Bokary; Okulo, John B.; Thiam, Massamba; Diallo, Ousmane B.; Bouvet, Jean-Marc

doi:10.1021/jf100409v

Near Infrared Spectroscopy for High-Throughput Characterization of Shea Tree (Vitellaria paradoxa) Nut Fat Profiles

Journal of agricultural and food chemistry, v.58 no.13, 2010년, pp.7811 - 7819

Davrieux, Fabrice (CIRAD, Performance of Tropical Production and Processing Systems Department, UMR QUALISUD, TA B-95) , Allal, François (ois Breton, 34398 Montpellier Cedex 5, France) , Piombo, Georges (CIRAD, Biological Systems Department, Research Unit 39, “Genetic Diversity and Breeding of Forest Tree Species”, Campus international de Baillarguet TA A-39) , Kelly, Bokary (CIRAD, Performance of Tropical Production and Processing Systems Department, UMR IATE, TA B 62) , Okulo, John B. (ois Breton, 34398 Montpellier Cedex 5, France) , Thiam, Massamba (Institut d’Economie Rurale, PRF) , Diallo, Ousmane B. (Department of Forest Biology & Ecosystems Management, Faculty of Forestry and Nature Conservation, Makerere University, PO Box 7062 Kampala, Uganda) , Bouvet, Jean-Marc (Institut Sé)

Abstract ▼ AI-Helper

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 Rp2 parameters, obtained by comparison of the validation set NIR predictions and corresponding laboratory values. Moisture (RPDp = 4.45; Rp2 = 0.95) and fat (RPDp = 5.6; Rp2 = 0.97) calibrations enabled accurate determination of these traits. NIR models for stearic (RPDp = 6.26; Rp2 = 0.98) and oleic (RPDp = 7.91; Rp2 = 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.

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Near Infrared Spectroscopy for High-Throughput Characterization of Shea Tree (Vitellaria paradoxa) Nut Fat Profiles

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