Effect of the Architecture of Fiber-Optic Probes Designed for Soluble Solid Content Prediction in Intact Sugar Beet Slices.

Sugar beet is the second biggest world contributor to sugar production and the only one grown in Europe. One of the main limitations for its competitiveness is the lack of effective tools for assessing sugar content in unprocessed sugar beet roots, especially in breeding programs. In this context, a dedicated near infrared (NIR) fiber-optic probe based approach is proposed. NIR technology is widely used for the estimation of sugar content in vegetable products, while optic fibers allow a wide choice of technical properties and configurations. The objective of this research was to study the best architecture through different technical choices for the estimation of sugar content in intact sugar beet roots. NIR spectral measurements were taken on unprocessed sugar beet samples using two types of geometries, single and multiple fiber-probes. Sugar content estimates were more accurate when using multiple fiber-probes (up to R2 = 0.93) due to a lesser disruption of light specular reflection. In turn, on this configuration, the best estimations were observed for the smallest distances between emitting and collecting fibers, reducing the proportion of multiply scattered light in the spectra. Error of prediction (RPD) values of 3.95, 3.27 and 3.09 were obtained for distances between emitting and collecting fibers of 0.6, 1.2 and 1.8 µm respectively. These high RPD values highlight the good predictions capacities of the multi-fiber probes. Finally, this study contributes to a better understanding of the effects of the technical properties of optical fiber-probes on the quality of spectral models. In addition, and beyond this specificity related to sugar beet, these findings could be extended to other turbid media for quantitative optical spectroscopy and eventually to validate considered fiber-optic probe design obtained in this experimental study.

Potential of vis-NIR spectroscopy to monitor the silica precipitation reaction.

Controlling production online is an important issue for chemical companies. Visible and near-infrared (NIR) spectroscopy offers a number of important advantages for process monitoring, and has been used since the 1980s. For complex media such as silica precipitation samples, it is interesting to be able to study independently the scattering and absorption effects. From the scattering coefficient it is possible to extract information on the physical structure of the medium. In this work, the physical changes were monitored during a silica precipitation reaction by simple measurement of collimated transmittance NIR spectra. It is shown that it is possible to differentiate samples before and after the gel point, which is a key parameter for monitoring the process. From these NIR spectra the scattering coefficients were simply extracted, allowing a global vision of the physical changes in the medium. Then principal component analysis of the spectra allowed refinement of the understanding of the scattering effects, in combination with particle size monitoring.

Combining linear polarization spectroscopy and the Representative Layer Theory to measure the Beer-Lambert law absorbance of highly scattering materials.

Visible and Near Infrared (Vis-NIR) Spectroscopy is a powerful non destructive analytical method used to analyze major compounds in bulk materials and products and requiring no sample preparation. It is widely used in routine analysis and also in-line in industries, in-vivo with biomedical applications or in-field for agricultural and environmental applications. However, highly scattering samples subvert Beer-Lambert law's linear relationship between spectral absorbance and the concentrations. Instead of spectral pre-processing, which is commonly used by Vis-NIR spectroscopists to mitigate the scattering effect, we put forward an optical method, based on Polarized Light Spectroscopy to improve the absorbance signal measurement on highly scattering samples. This method selects part of the signal which is less impacted by scattering. The resulted signal is combined in the Absorption/Remission function defined in Dahm's Representative Layer Theory to compute an absorbance signal fulfilling Beer-Lambert's law, i.e. being linearly related to concentration of the chemicals composing the sample. The underpinning theories have been experimentally evaluated on scattering samples in liquid form and in powdered form. The method produced more accurate spectra and the Pearson's coefficient assessing the linearity between the absorbance spectra and the concentration of the added dye improved from 0.94 to 0.99 for liquid samples and 0.84-0.97 for powdered samples.

Improvement of the chemical content prediction of a model powder system by reducing multiple scattering using polarized light spectroscopy.

Near-infrared spectroscopy (NIRS) is a powerful non-destructive analytical method used to analyze major compounds in bulk materials and products and requiring no sample preparation. It is widely used in routine analysis and also in line in industries, in vivo with biomedical applications, or in field for agricultural and environmental applications. However, highly scattering samples subvert Beer-Lambert law's linear relationship between spectral absorbance and the concentration. Instead of spectral pre-processing, which is commonly used by NIR spectroscopists to mitigate the scattering effect, we put forward an optical method, i.e., coupling polarized light with NIR spectrometry, to free spectra from scattering effect. This should allow us to retrieve linear and steady conditions for spectral analysis. When tested in visible-NIR (Vis-NIR) range (400-800 nm) on model media, mixtures of scattering and absorbing particles, the setup provided significant improvements in absorber concentration estimation precision as well as in the quality and robustness of the calibration model.