There has been growing consumer demand for the products and services of the short food supply chains (SFSCs) in recent times. A procedure was developed to identify the technological and technological innovations that can improve the performance and competitiveness of the SFSCs. The needs of the SFSCs for innovative solutions were collected by interviewing 18 SFSCs from 9 countries. An inventory was prepared to contain 136 technological and non-technological innovations, meeting these needs. The innovations were collected from the good practices of the 18 SFSCs, experiences of the project partners and state of the art. The success factors and bottlenecks of each short food supply chain operation and their current value propositions were identified. From the inventory, those innovations were selected for each short food chain case study which can be applied to eliminate or reduce the bottlenecks or enhance the success factors leading to new, upgraded value propositions with increased added value for the consumers. The new, upgraded value propositions can serve as a starting point for developing a strategy for improving the competitiveness of a short food chain organisation through the application of innovations.
Ultrasonic testing is an emerging non-destructive testing technology with high repeatability and precision. Milk is a very complex liquid and the change of its viscosity is a highly relevant property throughout conversion into other dairy products. In the following paper, we propose a novel method for the monitoring of viscosity during enzymatic milk clotting by ultrasonic spectroscopy. An ultrasonic transducer–receiver couple with a 250 kHz nominal frequency was submerged in the samples and an enveloped sweep (“chirp”) signal was applied in a through-transmission mode. Simultaneously, the change in viscosity was measured with a rotational viscometer at a constant shearing speed. The data were analyzed with an algorithm developed by the authors for spectral ultrasonic testing. Estimations yielded a high adjusted R2 (0.963–0.998) and low cross-validated estimation error (RPD: 4.38–14.22), suggesting that the method is suitable for industrial use given the right instrumentation.
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