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Extended multiplicative signal correction to improve prediction accuracy of protein content in weathered sorghum grain samples
Author(s) -
Peiris Kamaranga H. S.,
Bean Scott R.,
Jagadish S. V. Krishna
Publication year - 2020
Publication title -
cereal chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.558
H-Index - 100
eISSN - 1943-3638
pISSN - 0009-0352
DOI - 10.1002/cche.10329
Subject(s) - calibration , sorghum , chemistry , analytical chemistry (journal) , spectral line , grain size , mineralogy , soil science , mathematics , environmental science , statistics , materials science , agronomy , environmental chemistry , physics , metallurgy , astronomy , biology
Background and objectives Sorghum grains may be subjected to weathering damage in the field as naked grains on the panicle are exposed to adverse environmental conditions during grain development or dry down before harvest. A near infrared (NIR) protein calibration model did not work as expected for weathered grains. Extended multiplicative signal correction was tested as a preprocessing method for spectra to improve the prediction accuracy of the model when weathered grain samples are evaluated. Findings NIR spectra of weathered sorghum grain samples showed marked distortions with a higher apparent absorbance at lower wavelengths in the 950–1650 nm spectral range. A partial least squares calibration developed with sound grain samples using spectra preprocessed with multiplicative signal correction (MSC) predicted protein content of validation sample set of sound grains with a root mean square error of prediction (RMSEP) = 0.67% and coefficient of determination ( r 2 ) = 0.83. However, performance of this calibration model dropped with RMSEP = 13.14% and r 2 = 0.04 when used to predict proteins in weathered grain samples. Introduction of weathered grain spectra to the calibration improved predictive performance with RMSEP = 0.92% and r 2 = 0.69. Application of extended multiplicative scatter correction (EMSC) to preprocess the spectra of the calibration with weathered grain samples enhanced the prediction performance with RMSEP = 0.61% and r 2 = 0.85. Conclusions Inclusion of weathered grain spectra in the calibration and preprocessing spectra with EMSC markedly improved the robustness of the sorghum protein calibration. Significance and novelty Sorghum breeders using NIR spectroscopy for evaluation of protein levels in sorghum breeding lines can get the weathered grain samples also analyzed for protein levels by using this method.