Reduction of spoilage in fresh and chilled products
The significant efforts applied to developing new predictive models for microbial spoilage and sensorial decay for fresh-cut iceberg lettuce, minced meat and tenderloin have paid off. Researchers from TNO and Wageningen UR Food & Biobased research have developed new models for the lettuce and NIZO food research for the meats. Research showed that, for both the lettuce and the meat, sensorial decay declines much faster than microbial growth-related quality decay. For fresh-cut iceberg lettuce this means limpness, colour changes (becoming brown and red) and developing off-flavour, and for meat it means discolouration/greying. New algorithms and ‘smart’ order policies are being developed, alongside new models that not only take the more-usual elements into account, but also factor-in the shelf life of the specific consumer package by including the different best-before or use-by dates of the products.
An important milestone is that the first operational version of the Decision Support Model (DSS) is ready for use. Due to the involvement of producers and retailers – in both the lettuce and meat chains – real life data and daily practice and insight are being fed into the DSS. These producers and retailers also formulated several innovative scenarios that could considerably reduce food waste at the retailer level. Running and analysing these scenarios will be the main goal for the coming year. We expect to be able to identify the most-relevant scenarios and measure their potential for reducing food wastage.
|Scientific papers in peer-reviewed journals||2014 An MILP approximation for ordering perishable products with non-stationary demand and service level constraints||View summary|
||2015 Measures for reducing chilled-food waste at the retail outlet|
|Invited lectures||2015 Organic acids produced by lactic acid bacteria (Leuconostoc sp.) are related to sensorial quality decrease inmodified atmosphere packed fresh-cut iceberg lettuce|
|Scientific publications||2015 KeCo: Kernel-Based Online Co-agreement Algorithm|