Modelling epidemiological and economic consequences of bovine respiratory disease in dairy heifers

Bovine respiratory disease (BRD) is an important health problem in dairy heifers. BRD causes considerable losses, particularly on farms that experience high levels of the disease. However, an exact quantification of the economic losses due to BRD was not available yet. Despite this lack of economic insight, dairy farmers have to make decisions with regard to prevention of the disease. To make these decisions as economically sound as possible, more accurate insight is necessary into the economic consequences of BRD on the individual dairy farm.The main objective of the research project described in this thesis was to obtain insight into the on-farm economic consequences of BRD in dairy heifers by means of a PC-based simulation model. The second objective was to collect information on the epidemiological consequences of the disease indispensable for model input.The research started with a literature review aimed at obtaining the necessary qualitative and quantitative information on both the effects of BRD on the productivity of dairy heifers and risk factors of the disease. Because relevant literature turned out to be scarce, a formal expert judgement study was held to obtain additional data on the(se) variables of interest.As a next step, a simulation model was developed that calculates the economic losses due to BRD in dairy heifers for individual dairy farm conditions in the Netherlands. Following the results of the expert judgement study, the model distinguishes between two BRD types, being calf pneumonia and a seasonal BRD outbreak.Model calculations showed that for most dairy farms in the Netherlands the economic losses due to BRD will be relatively small: around 1 % of the farm's net return to labour and management for average situations, increasing up to 3-4 % at worst. For individual farms that experience high levels of BRD, the associated losses can be as high as 10-15 % of the farm's net return to labour and management, up to 25 % for large farms. Besides for calculation of the economic losses due to BRD, the model showed also to be useful for evaluation of the on-farm cost-effectiveness of prevention of the disease. Moreover, the model is flexible and user-friendly, hence, can be used as a tool to support decision-making in dairy practice.</p

Impact of environmental factors on the presence of quinolizidine alkaloids in lupins: a review

Lupin seeds have a high potential as an alternative for animal proteins in feed and food. However, the possible presence of alkaloids hinders the usage of lupins in human diets. This review aims to identify the main factors that influence the presence of alkaloids in lupins. A literature study covering English-published scientific papers in Scopus from 1980 to 2022 was performed. Biotic, abiotic, and genotypic factors influence the production of these toxic secondary metabolites by lupines. In particular, sweet cultivars with high 13-hydroxylupanine and 13-tigloyloxylupanine concentrations, abundant light exposure and standard diurnal cycles, well-watering procedures, relatively cold environment, N-deficient fertilizer with 240 mg K kg−1 and 60 mg P kg−1, high soil pH, and organic growing system conditions, are the best options to avoid high global alkaloid content. Results of this study can be used to develop predictive mechanistic models, although there is still the necessity to collect additional data by performing multi-variate studies. © 2023 The Author(s). Published with license by Taylor & Francis Group, LLC.This study was financed by the Netherlands Ministry of Nature and Food Quality, under Knowledge based project [KB-37-002-038]

Kennisbasisthema: Ketens en Agrologistiek

Wageningen UR voert een meerjarig onderzoeksprogramma uit, getiteld Ketens en Agrologistiek. Deze projectbundel geeft informatie over projecten in dit thema en van elk project is een flyer opgenome

Effect of disinfectants on preventing the cross-contamination of pathogens in fresh produce washing water

The potential cross-contamination of pathogens between clean and contaminated produce in the washing tank is highly dependent on the water quality. Process wash water disinfectants are applied to maintain the water quality during processing. The review examines the efficacy of process wash water disinfectants during produce processing with the aim to prevent cross-contamination of pathogens. Process wash water disinfection requires short contact times so microorganisms are rapidly inactivated. Free chlorine, chlorine dioxide, ozone, and peracetic acid were considered suitable disinfectants. A disinfectant's reactivity with the organic matter will determine the disinfectant residual, which is of paramount importance for microbial inactivation and should be monitored in situ. Furthermore, the chemical and worker safety, and the legislative framework will determine the suitability of a disinfection technique. Current research often focuses on produce decontamination and to a lesser extent on preventing cross-contamination. Further research on a sanitizer's efficacy in the washing water is recommended at the laboratory scale, in particular with experimental designs reflecting industrial conditions. Validation on the industrial scale is warranted to better understand the overall effects of a sanitizer

Impact of Climate Change Effects on Contamination of Cereal Grains with Deoxynivalenol

Climate change is expected to aggravate feed and food safety problems of crops; however, quantitative estimates are scarce. This study aimed to estimate impacts of climate change effects on deoxynivalenol contamination of wheat and maize grown in the Netherlands by 2040. Quantitative modelling was applied, considering both direct effects of changing climate on toxin contamination and indirect effects via shifts in crop phenology. Climate change projections for the IPCC A1B emission scenario were used for the scenario period 2031-2050 relative to the baseline period of 1975-1994. Climatic data from two different global and regional climate model combinations were used. A weather generator was applied for downscaling climate data to local conditions. Crop phenology models and prediction models for DON contamination used, each for winter wheat and grain maize. Results showed that flowering and full maturity of both wheat and maize will advance with future climate. Flowering advanced on average 5 and 11 days for wheat, and 7 and 14 days for maize (two climate model combinations). Full maturity was on average 10 and 17 days earlier for wheat, and 19 and 36 days earlier for maize. On the country level, contamination of wheat with deoxynivalenol decreased slightly, but not significantly. Variability between regions was large, and individual regions showed a significant increase in deoxynivalenol concentrations. For maize, an overall decrease in deoxynivalenol contamination was projected, which was significant for one climate model combination, but not significant for the other one. In general, results disagree with previous reported expectations of increased feed and food safety hazards under climate change. This study illustrated the relevance of using quantitative models to estimate the impacts of climate change effects on food safety, and of considering both direct and indirect effects when assessing climate change impacts on crops and related food safety hazards

Factoren van invloed op voedselveiligheid

In dit rapport van Agrotechnology & Food Innovations, Rikilt en het LEI wordt ingegaan op de factoren die van invloed zijn op de veiligheid van voedingsmiddelen. Deze factoren zijn onderverdeeld in twee hoofdgroepen, namelijk productaspecten en bedrijfsaspecten. Bij deze laatste zijn ook opgenomen de relevante aspecten uit de omgeving van het bedrijf, zoals de relaties met leveranciers en afnemers. Met behulp van deze aspecten zijn de hoofdgroepen van de CBL-indeling van levensmiddelen op kwalitatieve wijze ingedeeld naar de mate van risico voor voedselveiligheid. This report by Agrotechnology & Food Innovations, Rikilt and LEI looks at the factors that influence the safety of foodstuffs. These factors are subdivided into two main groups: product aspects and farm aspects. The latter also includes the relevant aspects from the farm's environment, such as the relationships with suppliers and buyers. With the aid of these aspects, the main groups of the CBL classification of foodstuffs are divided on the basis of quality according to the risk in terms of food safety

Safe food and feed through an integrated toolbox for mycotoxin management: the MyToolBox approach

There is a pressing need to mobilise the wealth of knowledge from the international mycotoxin research conductedover the past 25-30 years, and to perform cutting-edge research where knowledge gaps still exist. This knowledgeneeds to be integrated into affordable and practical tools for farmers and food processors along the chain inorder to reduce the risk of mycotoxin contamination of crops, feed and food. This is the mission of MyToolBox – a four-year project which has received funding from the European Commission. It mobilises a multi-actorpartnership (academia, farmers, technology small and medium sized enterprises, food industry and policystakeholders) to develop novel interventions aimed at achieving a significant reduction in crop losses due tomycotoxin contamination. Besides a field-to-fork approach, MyToolBox also considers safe use options ofcontaminated batches, such as the efficient production of biofuels. Compared to previous efforts of mycotoxin reduction strategies, the distinguishing feature of MyToolBox is to provide the recommended measures to theend users along the food and feed chain in a web-based MyToolBox platform (e-toolbox). The project focuseson small grain cereals, maize, peanuts and dried figs, applicable to agricultural conditions in the EU and China. Crop losses using existing practices are being compared with crop losses after novel pre-harvest interventionsincluding investigation of genetic resistance to fungal infection, cultural control (e.g. minimum tillage or cropdebris treatment), the use of novel biopesticides suitable for organic farming, competitive biocontrol treatment and development of novel modelling approaches to predict mycotoxin contamination. Research into post-harvestmeasures includes real-time monitoring during storage, innovative sorting of crops using vision-technology, novelmilling technology and studying the effects of baking on mycotoxins at an industrial scale

Comparing antimicrobial exposure based on sales data

This paper explores the possibilities of making meaningful comparisons of the veterinary use of antimicrobial agents among countries, based on national total sales data. Veterinary antimicrobial sales data on country level and animal census data in both Denmark and the Netherlands were combined with information about estimated average dosages, to make model calculations of the average number of treatment days per average animal per year, at first based on the assumption that the treatment incidence is the same in all species and production types. Secondly, the exposure in respectively animals for meat production and dairy and other cattle (excluding veal and young beef) was estimated, assuming zero use in the dairy and other cattle, and thirdly by assuming respectively 100% oral and 100% parenteral administration. Subsequently, the outcomes of these model calculations were compared with treatment incidences calculated from detailed use data per animal species from the national surveillance programmes in these two countries, to assess their accuracy and relevancy. In Denmark and in the Netherlands, although the computed antimicrobial exposure would seem to be a reasonable estimation of the exposure for all animals as a whole, it differs significantly from the measured exposure for most species. The differences in exposure among animal species were much higher than the overall difference between the two countries. For example, the overall model estimate of 9 treatment days per year for Denmark is a severe overestimation of the true use in poultry (i.e. 3 days), and the overall model estimate of 13 treatment days per year for the Netherlands is a severe underestimation of the true use in veal calves (i.e. 66 days). The conclusion is that simple country comparisons, based on total sales figures, entail the risk of serious misinterpretations, especially if expressed in mg per kg. The use of more precise model calculations for making such comparisons, taking into account differences in dosages and in farm animal demographics, only slightly reduces this risk. Overall model estimates are strongly influenced by animal demographics and a very inaccurate indication of the true differences in exposure, per animal species. To get an appropriate certainty about the true differences in antimicrobial exposure between countries it is an absolute necessity to have reliable information about the use per animal species

Critical review of methods for risk ranking of food related hazards, based on risks for human health.

This study aimed to critically review methods for ranking risks related to food safety and dietary hazards on the basis of their anticipated human health impacts. A literature review was performed to identify and characterize methods for risk ranking from the fields of food, environmental science and socio-economic sciences. The review used a predefined search protocol, and covered the bibliographic databases Scopus, CAB Abstracts, Web of Sciences, and PubMed over the period 1993-2013. All references deemed relevant, on the basis of of predefined evaluation criteria, were included in the review, and the risk ranking method characterized. The methods were then clustered - based on their characteristics - into eleven method categories. These categories included: risk assessment, comparative risk assessment, risk ratio method, scoring method, cost of illness, health adjusted life years, multi-criteria decision analysis, risk matrix, flow charts/decision trees, stated preference techniques and expert synthesis. Method categories were described by their characteristics, weaknesses and strengths, data resources, and fields of applications. It was concluded there is no single best method for risk ranking. The method to be used should be selected on the basis of risk manager/assessor requirements, data availability, and the characteristics of the method. Recommendations for future use and application are provided