Abstract
Brassica carinata is one of the oilseeds in the Brassicaceae family, possessing seed quality traits such as oil with various fatty acid profiles suitable for many industrial applications. Determination of such quality traits using conventional methods is often expensive, time-consuming, and destructive. In contrast, the Near-Infrared Spectroscopic (NIRS) technique has been proven fast, cost-effective, and non-destructive for the determination of seed compositions. This study aimed to demonstrate that NIRS is a rapid and non-destructive method for determining the fatty acid profile and oil content in diverse germplasms of B. carinata. A total of 96 genetically diverse B. carinata germplasms that include accessions, advanced breeding lines, and varieties were used in this study. Reference data sets were generated using gas chromatography and the Soxhlet oil extraction method for fatty acid profile and oil content, respectively. Spectra data were taken from the wavenumber range of 11,500 to 4000 cm−1 using the Fourier-transform near-infrared (FT-NIR) method. NIRS calibration equations were developed using partial least square (PLS) regression with OPUS software, version 7.5.1. Higher coefficient of determination (R2val) and ratio of performance to deviation (RPD) > 3 were obtained for oleic acid (R2val = 0.92, RPD = 3.6), linoleic acid (R2val = 0.89, RPD = 3.2), linolenic acid (R2val = 0.93, RPD = 3.8), erucic acid (R2val = 0.92, RPD = 3.5), and oil content (R2val = 0.93, RPD = 3.6). Thus, the NIRS calibration models for the aforementioned fatty acids and oil content were found to be strong enough for prediction. However, the calibration models for palmitic acid (R2val = 0.78, RPD = 2.1) and stearic acid (R2val = 0.75, RPD = 2.0) showed relatively smaller R2val and thus became weaker in their prediction capacity. Despite their relatively lower R2, the calibration equations for palmitic and stearic acids could be used for approximate estimation and rough screening purposes. In conclusion, the calibration models that we have developed will be useful in applying NIRS as a high-throughput, non-destructive method for the screening of large germplasms in terms of their fatty acid profiles and oil content during the oil quality breeding efforts conducted on B. carinata.
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