Quantitative determination based on the differences between spectra-temperature relationships

• A temperature-induced spectral variation coefficient is obtained by LSS.
• The relationship between TSVC and temperature is proposed and validated.
• Quantitative determination can be established using relationship differences.
• Our method is an effective tool for investigating effect of temperature quantitatively.

In the Near-infrared (NIR) spectral measurement it is not always possible to keep the experimental conditions constant. The fluctuations in external variables, such as temperature, will result in a nonlinear shift and a broadening of the spectral bands. In this study, the temperature-induced spectral variation coefficient (TSVC) was obtained by using loading space standardization (LSS). The relationship between TSVC and normalized squared temperature was quantitatively analyzed and applied to the quantitative determination of the compositions in mixtures. NIR spectra of peanut-soy-corn oil mixtures measured at seven temperatures were analyzed. It was found that, the relationship between TSVC and normalized squared temperature can be established by using LSS. Furthermore, the quantitative determination of the compositions in a mixture can be achieved by using the difference between the relationships, i.e., the slope of the relationship. The calibration curves between slope and composition volume are found to be reliable with the correlation coefficients (R2) as high as 0.9992. Quantitative determination by the calibration curves were also validated. Therefore, the method can be an effective tool for investigating the effect of temperature and quantitatively analysis.

Calibration curve for the volume of peanut oil (Vpeanut) and the volume of corn oil (Vcorn) established with slopes in the relationship between TSVC and normalized squared temperature in all the groupsFigure optionsDownload as PowerPoint slide