Mid-Infrared Spectral Characteristics of Lipid Molecular Structures in Brassica carinata Seeds: Relationship to Oil Content, Fatty Acid and Glucosinolate Profiles, Polyphenols, and Condensed Tannins

• Published in: Journal of agricultural and food chemistry 2014-08, Vol.62 (32), p.7977-7988
• Main Authors: Xin, Hangshu, Khan, Nazir A, Falk, Kevin C, Yu, Peiqiang
• Format: Article
• Language: English
• Subjects: Brassica - chemistry; Brassica - metabolism; Brassica carinata; Breeding; canola; chemical structure; Chile; Cluster Analysis; Crops, Agricultural - chemistry; Crops, Agricultural - metabolism; Dietary Fats - analysis; Discriminant Analysis; equations; fatty acids; Fatty Acids - analysis; Fatty Acids - chemistry; Fourier transform infrared spectroscopy; glucosinolates; Glucosinolates - analysis; Glucosinolates - chemistry; Isomerism; lipid content; Molecular Structure; oils; Pigments, Biological - metabolism; Plant Oils - analysis; Plant Oils - chemistry; Polyphenols - analysis; Polyphenols - chemistry; Principal Component Analysis; proanthocyanidins; Proanthocyanidins - analysis; Proanthocyanidins - chemistry; seeds; Seeds - chemistry; Seeds - metabolism; Species Specificity; spectral analysis; Spectroscopy, Fourier Transform Infrared; Triglycerides - chemistry; Triglycerides - metabolism
• ISSN: 0021-8561; 1520-5118
• DOI: 10.1021/jf502209x

The objectives of this study were to quantify lipid-related inherent molecular structures using a Fourier transform infrared spectroscopy (FT-IR) technique and determine their relationship to oil content, fatty acid and glucosinolate profile, total polyphenols, and condensed tannins in seeds from newly developed yellow-seeded and brown-seeded Brassica carinata lines. Canola seeds were used as a reference. The lipid-related molecular spectral band intensities were strongly correlated to the contents of oil, fatty acids, glucosinolates, and polyphenols. The regression equations gave relatively high predictive power for the estimation of oil (R 2 = 0.99); all measured fatty acids (R 2 > 0.80), except C14:0, C20:3n-3, C22:2n-9, and C22:2n-6; 3-butenyl, 2-OH-3-butenyl, 4-OH-3-CH3-indolyl, and total glucosinolates (R 2 > 0.686); and total polyphenols (R 2 = 0.935). However, further study is required to obtain predictive equations based on large numbers of samples from diverse sources to illustrate the general applicability of these regression equations.