2026-06-27http://hdl.handle.net/123456789/22990Strong evidence that near-infrared (NIR) transmittance and reflectance spectroscopy can detect Burkholderia glumae contamination in bacterial suspensions and in individual rice seeds, respectively, is shown in this proof-of-concept study. For the B. glumae suspension (0.0 to 1.42 × 104 CFU ml−1), NIR transmittance spectroscopy using a partial least squares (PLS) regression calibration model (1,000 to 1,650 nm) showed a coefficient of determination (R2) of 0.984 and root mean square error of 0.031. For rice seeds treated in varying dilutions of B. glumae (0.0 to 4.52 log10 CFU ml−1 bacterial load in seeds), NIR reflectance spectroscopy using a selected PLS second derivative with Savitzky–Golay smoothing calibration model (1,000 to 1,650 nm) resulted in a coefficient of determination of calibration (R2Cal) of 0.97, root mean square error of calibration of 0.06, coefficient of determination of cross-validation (R2CV) of 0.93, and standard error of cross-validation of 0.08 at 7 factors; the independent validation showed a coefficient of determination of validation (R2Val) of 0.83 and standard error of prediction of 0.11. A two-category qualitative PLS calibration model (1,000 to 1,650 nm) correctly classified 94.7% of uninoculated and 100% of inoculated seeds, with independent validation of 90 and 100%, respectively. Predictions may be attributable to differences in aliphatic hydrocarbons, cellulose, amide, oil, protein, and starch contents across rice seeds that are uninoculated and inoculated at varying dilution levels. Developing NIR-based instrumentation for individual seed segregation of healthy from contaminated rice seeds can support a clean seed program and can be a useful tool for quarantine officers for seed exchange and farmers’ seed production.application/pdfOpen Accessinfrared spectrophotometryblightseed healthseed qualityricepaniclespathogensseed certificationJournal Article