Process samples of esters have been analysed by transmittance near infrared (NIR) at temperatures between 60 and 70°C (±0.2). Apart from density changes, these small temperature variations affect molecular associations by Hbonding. Partial Least Square (PLS) models based on the first OH overtone (1350-1500nm) have been made for hydroxyl value determination, including implicitly the temperature variable. The sensitivity of these NIR calibrations to temperature has been evaluated by an analysis of variance and the "Taguchi principle", using both average model performance and model variance. An accurate and precise control of the sample temperature prior to scanning leads to the lowest prediction error. When temperature fluctuations can not be avoided, introduction of temperature variance in the calibration set can improve the model robustness; this strategy is only beneficial if temperature range, temperature distribution and number of PLS factors have been carefully optimised.

Regular maintenance of (multivariate) near infrared (NIR) calibration models is a crucial but time-consuming step to ensure a successful NIR application in industry. Naturally, robustness of these models is essential to minimise both maintenance time and cost. In this paper, a method combining Taguchi philosophy, experimental design and artificially-derived spectra, is proposed to evaluate and improve the robustness of NIR calibrations. This approach is based upon a typical industrial NIR application, the determination of hydroxyl value of ester products. Experiments have been designed to investigate which parameters (control and signal) influence the performance of the calibration. Two calibration models have been selected for the robustness investigation. One benchmark model was based on general criteria applied for NIR calibration and another based on Taguchi's criteria. Artificially-derived spectra were produced by adding severe fluctuations of simulated wavelength shifts into original spectra for both models, then, the models' performance was evaluated six months after the calibration. The model selected based on Taguchi's criteria, is clearly more tolerant to wavelength shifts and less sensitive for overfitting in comparison with the “benchmark” model.

The hydroxyl value is an indicator for the stages of esterification reaction. Instead of the wet chemistry titration method, the near-infrared (NIR) spectroscopic technique was utilized to monitor the hydroxyl values during the reaction. Because of the various raw materials and reaction conditions, the shifting of the -OH absorption band in the NIR spectra of esters was observed. The molecular structure, the reaction environment, and the state of the -OH groups are the most likely parameters responsible for the shifting of the -OH band.

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Near infrared (NIR) spectroscopy has been widely applied in the areas of agriculture, food, pharmaceutical and chemical industries because of its advantages such as its speed, non-destructive nature and simultaneous detection of multiple components. However, most existing NIR instruments are too large to be carried into the field. Herein, we have developed an interface by which the application (app) runs on a smart phone (or tablet) to drive a miniature NIR spectrometer (MicroNIR, a product of the JDSU Uniphase Corporation). This app has three modules; the first drives the hardware to control the spectrometer; the second facilitates graphical display of spectral data, spectral pretreatment according to method provided by the model file and production of a calculated result while the third is the management of models, samples, spectral parameter setting and an address book. We have used this app with the MicroNIR to measure soluble solids content (SSC) in Fuji apples in the field; results were compatible with the reference results based on an Abbé refractometer analysis. To conclude, this new hand-held NIR spectroscopy system based on android device is convenient and practical in rapid measurement of SSC of Fuji apples in the field. It has potential to be used for in situ measurement of other constituents of agriculture products.