Calibration model building for investigating seed oil content of Jatropha curcas using near infrared spectroscopy

ObjectiveIn present study, a calibration model was established to investigate the Jatropha curcas seed oil content using near infrared spectroscopy.

MethodThe spectroscopic data of 125 Jatropha curcas seed samples was collected by a near infrared reflectance spectrometer DA7200 (designed by Perten). With the chemical test method, spectral data pre-treatments and different regression methods, a calibration model using near infrared spectroscopy for seed oil content determination was established. And then the accuracy of the model was tested by 10 validation samples.

ResultThe seed oil content ranged from 25.23% to 39.73% among 125 investigated samples in this study, mean value was 33.91% ± 2.64%, and the median was 34.31%. It indicated that these samples could cover the main cultivars of Jatropha curcas in the wild. Furthermore, second-derivative combined with standard normal variable transformation method was the best pre-treatment way in calibration model building for investigating seed oil content of Jatropha curcas using near infrared spectroscopy, and the partial least squares was the best regression method. Moreover, the significant correlation was obtained between the predicted value of near infrared spectroscopy calibration model and the chemical determination value of sample, and the coefficient was 0.955 6, while the standard deviation of prediction was 0.653 6.

ConclusionOur prediction model has high reliability, which can quickly investigate the seed oil content of Jatropha curcas in large quantities.