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The state of the art in the optical characterization of materials is advancing rapidly. New insights have been gained into the theoretical foundations of this research and exciting developments have been made in practice, driven by new applications and innovative sensor technologies that are constantly evolving. The great success of past conferences proves the necessity of a platform for presentation, discussion and evaluation of the latest research results in this interdisciplinary field.
The state of the art in optical characterization of materials is advancing rapidly. New insights into the theoretical foundations of this research field have been gained and exciting practical developments have taken place, both driven by novel applications that are constantly emerging. This book presents latest research results in the domain of Characterization of Materials by spectral characteristics of UV (240 nm) to IR (14 μm), multispectral image analysis, X-Ray, polarimetry and microscopy.
The state of the art in the optical characterization of materials is advancing rapidly. New insights have been gained into the theoretical foundations of this research and exciting developments have been made in practice, driven by new applications and innovative sensor technologies that are constantly evolving.
Food-scanners are novel, portable and miniaturized devices, which operate on the principle of near-infrared spectroscopy (NIRS). According to the manufacturers, these devices are suitable for measuring a wide range of important quality parameters on fresh produce. This research evaluated the suitability of food-scanners for determining fruit quality along the supply chain of fruit and vegetables. Using the qualitative research approach, the first step of this research comprised interviews of experts at different positions along the fresh produce value chain in Germany. Thereby, preferences and concerns regarding the utilization and implementation of this technology for fresh produce were investigated. Based on these findings, non-destructive prediction models for various important quality characteristics and secondary plant constituents were developed using the model fruit tomato. In addition, food-scanner predictions of relevant quality traits on a wide range of produce from the fruit and vegetable assortment were examined. The evaluations showed a high degree of conformity between the results of non-destructive food-scanner predictions and conventional destructive measurement methods. The results illustrate the great potential of these novel devices for the application in everyday practice of fruit quality control along the fresh produce supply chain.