Premium
Non‐destructive Determination of High Oleic Acid Content in Single Soybean Seeds by Near Infrared Reflectance Spectroscopy
Author(s) -
Han SangIk,
Chae JongHyun,
Bilyeu Kristin,
Shan J. Grover,
Lee JeongDong
Publication year - 2014
Publication title -
journal of the american oil chemists' society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.512
H-Index - 117
eISSN - 1558-9331
pISSN - 0003-021X
DOI - 10.1007/s11746-013-2369-y
Subject(s) - oleic acid , soybean oil , near infrared reflectance spectroscopy , reflectivity , glycine , chemistry , calibration , near infrared spectroscopy , food science , biology , biochemistry , mathematics , amino acid , statistics , neuroscience , optics , physics
Soybean [ Glycine max (L.) Merr] with increased oleic acid is desirable to improve oxidative stability and functionality of soybean seed oil. Recently, soybean genotypes with high oleic acid (≥70 %) were developed by breeding programs. Efficient and effective identification of high oleic acid soybean genotypes using non‐destructive near infrared reflectance (NIR) on whole seeds would greatly enhance progress in breeding programs. The objective of this study was to develop a calibration equation for NIR determination of high oleic acid from single soybean seeds. A total of 600 intact, single F 2 seeds were scanned by NIR. Spectral data were collected between 400 and 2,500 nm at 2 nm intervals. The relationship between NIR spectral patterns of each soybean seed and its oleic acid content was examined. The best predicted equations for oleic acid were selected on the basis of minimizing the standard error of cross‐validation and increasing the coefficient of determination. Validation demonstrated that the equations for determining total oleic acid and over 50 % oleic acid content had high predictive ability ( r 2 = 0.91 and r 2 = 0.99, respectively). To validate the newly developed equation, F 2 seeds from a different genetic background were tested. Again, high oleic acid from single soybean seeds was accurately predicted from various genetic backgrounds. Therefore, applying the calibration equations to NIR will be useful to rapidly and efficiently select high oleic acid soybean genotypes in breeding programs.