Abstract
Monitoring product quality is essential to reduce food waste in the fruit and vegetable chain. Retailers demand high quality products and consumers expect products with a good flavor and a long shelf-life. Growers want to produce high quality products without sacrificing yield. To assess product quality, quick and objective tools are necessary. One of the available tools is the tomato flavor model that can predict the flavor liking of tomato based on various destructive measurements, such as sugar content, titratable acidity, firmness and juiciness. The current study aims to take the next step by modelling tomato quality based on non-destructive measurements of shelf-life and freshness. Advanced imaging techniques and sensor systems are used to monitor products in the supply chain, including spectroscopy, microwave sensors and RGB imaging. The non-destructive parameters will give insight in both the external and internal quality properties of the fruits, for example fruit colour, fruit shininess, visual defects and sugar content. Parallel to the non-destructive measurements, the tomatoes are assessed by an expert and consumer panel on their freshness and shelf-life properties, and finally the products are measured destructively. Real-time data access, data integration and modelling will allow for prediction of product properties at each moment of its lifetime. With these elements, a predictive model for the freshness and shelf-life of tomato in the food supply chain will be created and continuously updated. The predictive model will allow for simulation of future product quality in various scenarios, and thereby enables chain actors to make optimal decisions at each moment in time.
Original language | English |
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Pages (from-to) | 159-168 |
Number of pages | 10 |
Journal | Acta Horticulturae |
Issue number | 1396 |
DOIs | |
Publication status | Published - 20 Jun 2024 |
Keywords
- non-destructive sensing
- product quality
- sensor technology
- shelf-life