Compositional analysis in sorghum (Sorghum bicolor) NIR spectral techniques based on mean spectra from single seeds

Authors: GOKHAN, HACISALIHOGLU - Florida A & M University; Armstrong, Paul; MENDOZA, PRINCESS - Kansas State University; Seabourn, Bradford

Submitted to: Frontiers in Plant Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/21/2022
Publication Date: 10/17/2022
Citation: Gokhan, H., Armstrong, P.R., Mendoza, P.D., Seabourn, B.W. 2022. Compositional analysis in sorghum (Sorghum bicolor) NIR spectral techniques based on mean spectra from single seeds. Frontiers in Plant Science. 13:995328. https://doi.org/10.3389/fpls.2022.995328.
DOI: https://doi.org/10.3389/fpls.2022.995328

Interpretive Summary: Sorghum (Sorghum bicolor) is an economically important cereal crop that can be used as human food, animal feed, and for industrial use such as bioenergy. Breeding of new sorghum cultivars with desirable seed quality characteristics is important and development of rapid low-cost screening methods for seed nutritional traits are desired, since most standard methods are destructive, costly and slow. A single kernel near infrared instrument (SKNIRS), previously developed for small seeds, was tested for rapid determination of the individual sorghum seed components of protein, oil, and weight in sorghum. The results showed good accuracy for measuring protein content that ranged from 8.92% to 18.7% and oil content ranging from 1.96% to 5.61%. Weight measurements, which ranged from 4.4 mg to 77 mg, were not as accurate but can still give an estimate of the size range within a sample.

Technical Abstract: Sorghum (Sorghum bicolor) is an economically important cereal crop that can be used as human food, animal feed, and for industrial use such as bioenergy. In sorghum breeding programs, development of cultivars with desirable seed quality characteristics is important and development of rapid low-cost screening methods for seed nutritional traits are desired, since most standard methods are destructive, slow, and less environmentally friendly. This study investigates the feasibility of single kernel NIR spectroscopy (SKNIRS) for rapid determination of individual sorghum seed components. We developed successful multivariate prediction models based on partial least squares (PLS) regression for protein, oil, and weight in sorghum. The results showed that for sorghum protein content ranging from 8.92% to 18.7%, the model coefficients of determination obtained were R2CAL= 0.95 (RMSEC= 0.44) and R2PRED= 0.87 (RMSEP= 0.69). The model coefficients of determination for oil prediction were R2CAL= 0.92 (RMSEC= 0.23) and R2PRED= 0.71 (RMSEP= 0.41) for oil content ranging from 1.96% to 5.61%. For weight model coefficients of determination were R2CAL= 0.81 (RMSEC= 0.007) and R2PRED= 0.63 (RMSEP= 0.007) for seeds ranging from 4.40 mg to 77.0 mg. In conclusion, mean spectra SKNIRS can be used to rapidly determine protein, oil, and weight in intact single seeds of sorghum seeds and can provide a nondestructive and quick method for screening sorghum samples for these traits for sorghum breeding and industry use.