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Liu Y.-Y.,Henan Academy of Agricultural science HAAS | Mei H.-X.,Henan Academy of Agricultural science HAAS | Du Z.-W.,Henan Academy of Agricultural science HAAS | Wu K.,Henan Academy of Agricultural science HAAS | And 2 more authors.
JAOCS, Journal of the American Oil Chemists' Society | Year: 2015

A rapid and efficient method for oil constituent estimation in intact sesame seeds was developed through near-infrared reflectance spectroscopy (NIRS) and was used to evaluate a sesame germplasm collection conserved in China. A total of 342 samples were scanned by reflectance NIR in a range of 950-1650 nm, and the reference values for oil content and fatty acid (FA) profiles were measured by Soxhlet and gas chromatograph methods. Useful chemometric models were developed using partial least squares regression with full cross-validation. The equations had low standard errors of cross-validation, and high coefficient of determination of cross-validation (R2c) values (>0.8) except for stearic acid (0.794). In external validation, r2 values of oil and FA composition equations ranged from 0.815 (arachidonic acid) to 0.877 (linoleic acid). The relative predictive determinant (RPDv) values for all equations were more than 2.0. The whole-seed NIR spectroscopy equations for oil content and FA profiles can be used for sesame seed quality rapid evaluation. The background information of the 4399 germplasm resources and accessions with high linoleic acid content identified in this study should be useful for developing new sesame cultivars with desirable FA compositions in future breeding programs. © AOCS 2015. Source

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