Pericarp thickness of sorghum whole grain is accurately predicted by NIRS and can affect the prediction of other grain quality parameters

• High throughput discrimination between thick and thin pericarp sorghum grains by NIRS.
• The proportion of thick/thin pericarp grains can be predicted by NIRS quantification model.
• Thick pericarp disturbs the prediction of physico-chemical traits by NIRS of whole grain.
• A two-steps prediction approach can improve the accuracy of whole grain NIRS calibrations.

The thickness of grain pericarp, the outer layer of the kernel, is an important breeding criterion for sorghum. This cereal is mainly used through traditional processing in family-based food systems in many regions of the world. We investigated in this study how pericarp thickness could be predicted by Near Infrared Reflectance Spectroscopy (NIRS), a fast and non-destructive measurement method that is commonly used to measure physico-chemical parameters of sorghum grains, and how this trait also influences the prediction of those parameters. We showed that, using a classification approach, it was possible to discriminate thick from thin pericarp whole grain samples with a good accuracy and that the proportion of thin and thick grains in mixed samples could also be predicted. In addition, pericarp thickness had a significant effect on the calibration performance for other grain parameters indicating that the pericarp can distort spectral information of whole grain samples. As a practical consequence, we suggest to develop separate whole grain calibration models for thin and thick pericarp samples, combined with a two-steps prediction approach to improve the accuracy of whole grain NIRS calibrations for grain quality parameters in sorghum.