Abstract
Spectral imaging (SI) in analytical chemistry is widely used for the assessment of spatially distributed physicochemical properties of samples. Although massive development in instrument and chemometrics modelling has taken place in the recent years, the main challenge with SI is that available sensors require extensive system integration and calibration modelling before their use for routine analysis. Further, the models developed during one experiment are rarely useful once the system is reintegrated for a new experiment. To avoid system reintegration and reuse calibrated models, this study presents an intelligent All-In-One SI (ASI) laboratory system allowing standardised automated data acquisition and real-time spectral model deployment. The ASI system supplies a controlled standardised illumination environment, an in-built computing system, embedded software for automated image acquisition, and model deployment to predict the spatial distribution of sample properties in real-time. To show the capability of the ASI framework, exemplary cases of fruit property prediction in different fruits are presented. Furthermore, ASI is also benchmarked in performance against the current commercially available portable as well as high-end laboratory spectrometers.
Highlights
IntroductionOptical spectroscopy can be performed over a wide range of EMR, the most frequently and routinely used technique for non-destructive prediction of physicochemical properties is based on the visible (Vis) and near-infrared (NIR) range of EMR i.e. 3502500 nm [5]
Optical spectroscopy is the study of the interaction of pharmaceutical, and many more, that require non-invasive assessment of physicochemical properties of samples matrices [1e4]. optical spectroscopy can be performed over a wide range of EMR, the most frequently and routinely used technique for non-destructive prediction of physicochemical properties is based on the visible (Vis) and near-infrared (NIR) range of EMR i.e. 3502500 nm [5]
The first modelling was performed to show the functioning of the all-in-one spectral imaging (ASI) system, and the second modelling was performed to benchmark the performance of the ASI system with respect to the commercially available spectrometer systems
Summary
Optical spectroscopy can be performed over a wide range of EMR, the most frequently and routinely used technique for non-destructive prediction of physicochemical properties is based on the visible (Vis) and near-infrared (NIR) range of EMR i.e. 3502500 nm [5]. The main development from the perspective of rapid samples analysis is the availability of portable low-cost spectral sensors (both point as well as imaging) which allows easy measurement of spectral signals from samples in either reflection or interaction mode [8e10]. Almost all spectral sensors require calibration and model development, unless models from a similar instrument are available. In the latter case, the models can be transferred between instruments using advanced calibration transfer techniques [11,12]. Major developments have taken place in the domain of chemometric data analysis such as the development of ensemble modelling approaches [13] as well as the combination of chemometrics and deep learning [14e17] which have outperformed classical chemometric approaches used for traditional modelling of spectral data
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