Development and validation of a regression model for Listeria monocytogenes growth in roast beefs.

Food business operators are responsible for food safety and assessment of shelf lives for their ready-to-eat products. For assisting them, a customized software based on predictive models, ListWare, is being developed. The aim of this study was to develop and validate a predictive model for the growth of Listeria monocytogenes in sliced roast beef. A challenge study was performed comprising 51 different combinations of variables. The growth curves followed the Baranyi and Roberts model with no clear lag phase and specific growth rates in the range <0.005-0.110 hr-1. A linear regression model was developed based on 528 observations and had an adjusted R-square of 0.80. The significant predictors were storage temperature, sodium lactate, interactions between sodium acetate and temperature, and MAP packaging and temperature. The model was validated in four laboratories in three countries. For conditions where the model predicted up to + log 2 cfu/g Listeria concentration, the observed concentrations were true or below the predicted concentration in 90% of the cases. For the remaining 10%, the roast beef was coated with spices and therefore different from the others. The model will be implemented in ListWare web-application for calculation of "Listeria shelf life".

Corrigendum to "The STARTEC Decision Support Tool for Better Tradeoffs between Food Safety, Quality, Nutrition, and Costs in Production of Advanced Ready-to-Eat Foods".

[This corrects the article DOI: 10.1155/2017/6353510.].

Novel polyclonal-monoclonal-based ELISA utilized to examine lupine (Lupinus species) content in food products.

Sweet lupines are increasingly used in food production. Cause for concern has been expressed due to the increase in reported lupine-induced allergic incidents and the association between lupine and peanut allergies. In the current study, a polyclonal-monoclonal antibody-based sandwich ELISA for the detection of lupine proteins in foods was developed. The assay was sensitive to both native and processed proteins from Lupinus angustifolius and Lupinus albus and had a detection limit of 1 mug/g. Intra- and interassay coefficients of variation were <5 and <17%, respectively. A selection of 112 food samples, both with and without lupine declaration, was evaluated for their content of lupine. The data showed that the majority were in agreement with the respective labeling. However, some inconsistency was seen, typically in bread/rolls and soy flours.

The STARTEC Decision Support Tool for Better Tradeoffs between Food Safety, Quality, Nutrition, and Costs in Production of Advanced Ready-to-Eat Foods.

A prototype decision support IT-tool for the food industry was developed in the STARTEC project. Typical processes and decision steps were mapped using real life production scenarios of participating food companies manufacturing complex ready-to-eat foods. Companies looked for a more integrated approach when making food safety decisions that would align with existing HACCP systems. The tool was designed with shelf life assessments and data on safety, quality, and costs, using a pasta salad meal as a case product. The process flow chart was used as starting point, with simulation options at each process step. Key parameters like pH, water activity, costs of ingredients and salaries, and default models for calculations of Listeria monocytogenes, quality scores, and vitamin C, were placed in an interactive database. Customization of the models and settings was possible on the user-interface. The simulation module outputs were provided as detailed curves or categorized as "good"; "sufficient"; or "corrective action needed" based on threshold limit values set by the user. Possible corrective actions were suggested by the system. The tool was tested and approved by end-users based on selected ready-to-eat food products. Compared to other decision support tools, the STARTEC-tool is product-specific and multidisciplinary and includes interpretation and targeted recommendations for end-users.

Sterol demethylation inhibitor fungicides as disruptors of insect development and inducers of glutathione S-transferase activities in Mamestra brassicae.

To study physiological and biochemical effects of demethylation inhibitor (DMI) fungicides on non-target insects, larvae of the cabbage moth, Mamestra brassicae L., were exposed orally to propiconazole, (R,S)-1-[2-(2,4-diclophenyl)-4-propyl-1,3-dioolan-2-ylmetyl]-1H-1,2,4-triazole (100, 200 and 600 mg L(-1)) and fenpropimorph, (+/-)-cis-4-[3-(4-tert-butylphenyl)-2-methylpropyl] 2,6-dimethylmorpholinc (10, 100, 200 and 600 mg L(-1)) in a semi-synthetic diet. Ten mg L(-1) of fenpropimorph reduced larval weight and induced in vitro glutathione S-transferase activity. Reduced larval and pupal growth rate, reduced survival, prolonged developmental time, and altered patterns of larval survival and adult emergence were found for one or both fungicides in at least one of the concentrations tested. The results suggest, that although the use of agricultural fungicides is generally regarded as of minor ecotoxicological consequence for insects, feeding on DMI-treated crops may influence insect fitness, and may also leave them susceptible to pesticide treatments or to residues of pesticides and other pollutants in their food. Standard methods to detect such effects should be developed for use in the environmental risk assessment of these products.