An innovative approach based on hyperspectral imaging (HSI) was developed to monitor commercial starch-based (MaterBi®) disposable bioplastic behavior during anaerobic degradation. Mater-Bi® (MB) tableware items were selected among the ones available in supermarkets and compliant with the EN 13432 standard (EN 13432:2008). The MB items were manually cut in fragments with size ranging from 0.5 to 2 cm, removing the edges and the bottom to ensure test material homogeneity in terms of thickness. The anaerobic sludge was collected at a full-scale mesophilic anaerobic digestion plant treating a mixture of organic residues from food industries and was used as inoculum. Hyperspectral images of the samples composed of MB fragments dispersed in the anaerobic sludge were acquired in the short-wave infrared range (SWIR: 1000-2500 nm). A chemometric approach was then developed to analyze HSI data. In more detail, Principal Component Analysis (PCA) was applied for data exploration, followed by the implementation of a classification model based on Partial Least Square-Discriminant Analysis (PLS-DA) able to identify MB in the sludge. The achieved results are very promising, especially with reference to the possibility to adopt a fast strategy to monitor the behavior of MB during the anaerobic biodegradation process.
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