Location: Grain Quality and Structure ResearchTitle: Performance of a handheld Micro NIR instrument in comparison with laboratory benchtop NIR instrument for determining protein levels in harvested sorghum grain samples
|SEXTON-BOWSER, SARAH - Kansas State University
|TESSO, TESFAYE - Kansas State University
Submitted to: Foods
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/8/2023
Publication Date: 8/18/2023
Citation: Peiris, K.H., Bean, S.R., Wu, X., Sexton-Bowser, S., Tesso, T. 2023. Performance of a handheld Micro NIR instrument in comparison with laboratory benchtop NIR instrument for determining protein levels in harvested sorghum grain samples. Foods. https://doi.org/10.3390/foods12163101.
Interpretive Summary: Near infrared spectroscopy (NIR) is a rapid, non-destructive method for analyzing grain samples. Because NIR is capable of analyzing large numbers of samples quickly, it is a useful tool for screening samples for breeding programs. However, a limitation in this process is the requirement to clean and ship samples from the field to the lab for analysis. To help overcome this limitation, this research compared the ability of a small handheld NIR instrument to a larger benchtop instrument for predicting protein content in sorghum grain. The handheld instrument was found to produce acceptable results and could potentially be used directly in the field.
Technical Abstract: Near infrared (NIR) spectroscopy is widely used for evaluating certain quality traits of cereal grains. For evaluating protein content of intact sorghum grains, NIR calibrations were developed using a benchtop (Perten DA-7250) and a hand-held (VIAVI MicroNIR OnSite-W) NIR instruments. Spectra were collected from 87 samples using the two instruments at the same time. Cross-validated calibration models developed with 44 samples were validated with 43 test samples. The best calibration model for DA-7250 with a coefficient of determination (R2) = 0.96 and Root-Mean-Square Error of Cross-Validation (RMSECV) = 0.40% predicted the protein content of test set with R2=0.93, Root-Mean-Square Error of Prediction (RMSEP) = 0.62% with a Ratio of Performance to Deviation (RPD) of 3.74. The best model for the MicroNIR with R2 = 0.84 and RMSECV=0.50% predicted the protein content of the test set with R2=0.88, RMSEP= 0.83% with a RPD of 2.82. Cross-validated models with all spectra for DA-7250 had R2= 0.94, RMSECV=0.58% and slope = 0.97 and the MicroNIR model had R2=0.92, RMSECV=0.65% and slope=0.93. In comparison, the performance of the DA-7250 was better than MicroNIR, however, the performance of MicroNIR is also acceptable for screening intact sorghum grain protein levels. Therefore, MicroNIR instrument may be used as a potential tool for screening sorghum samples where benchtop instruments are not appropriate such as for screening samples in the field or as a less expensive option compared to benchtop instruments.