Optimal partner wavelength combination method with application to near-infrared spectroscopic analysis

• Optimal partner wavelength combination is proposed.
• Successfully applied for near-infrared spectroscopic analysis
• High efficient approach for extracting information wavelengths

Using binary linear regression, the optimal partner wavelength of each wavelength is selected in an initial wavelength screening region. On the basis of strategy above, a novel approach for selecting appropriate wavelengths combination, named optimal partner wavelength combination (OPWC) coupled with partial least squares (PLS), is proposed, and was successfully applied for reagent-free near-infrared spectroscopic analysis of organic matter in soil. Moving window PLS (MW-PLS), successive projections algorithm (SPA) and Monte Carlo uninformative variable elimination (MC-UVE), which are well-performed wavelength selection methods, were also conducted for comparison.The OPWC-PLS, MW-PLS, SPA-PLS and MC-UVE-PLS methods selected 14, 210, 63, 199 wavelengths, respectively. The root-mean-square error and correlation coefficients for leave-one-out cross validation were 0.165 g kg− 1 and 0.967 for OPWC-PLS, 0.163 g kg− 1 and 0.968 for MW-PLS, 0.198 g kg− 1 and 0.953 for SPA-PLS, and 0.190 g kg− 1 and 0.956 for MC-UVE-PLS, respectively. The results indicate that OPWC-PLS and MW-PLS methods were almost the same, and were obvious better than SPA-PLS and MC-UVE-PLS methods. But the OPWC only contained 14 wavelengths, which is a high efficient approach for extracting information wavelengths and mitigating redundant wavelengths. OPWC can be also provided valuable reference for designing small dedicated spectrometers with a high signal-to-noise ratio.OPWC can be programmed determined, which has small amount of calculation and high operating speed, and it is a deterministic search technique whose results are reproducible. We believe that OPWC has such applicability and can be applied to other fields of spectroscopic analysis.