Mycotoxin contamination in the animal feed production chain:An emerging risk?C.J.H. Booij, Plant Research InternationalH.J. van der Fels-Klerx, RIKILT - Institute of Food SafetyWageningen UR

Why are mycotoxins important?

1. Serious threat to Animal welfare and healthHuman healthEconomics and image of the feed supply chain

2. EU legal maximum limits and guidance values3. Increasing problems with known and new toxins

by changingMarkets / commodity useProduction systemsEnvironmental conditions

Mycotoxins in feed

Products AFL ZON DON FUM T2 OTACorn ** ** *** *** ** **Soy meal - ** ** ** - *Wheat/bran - * ** ** * *Corn gluten meal ** *** *** *** - *DDGS * ** *** *** - -Finished feed ** ** *** *** ** **Straw/silage * *** ** *** - *

Current mycotoxin control systems

1. Good Agricultural Practices at field level2. HACCP in the chain3. Early warning / notification systems, e.g.

EU Rapid Alert System for Feed and Food (RASFF)TrusQ

4. Diagnostic tools 5. Predictive modeling

Quantitative, e.g. DONcast, Canada & Dutch DON model Semi-quantitative, e.g. FusaProg, Swiss

All (1-5) focus on known mycotoxins; re-active (1-4) and pro-active (5)In addition (to 1-5), proactive identification of emerging mycotoxins is

needed

What is an emerging mycotoxin?

A potential feed (or food) related mycotoxin that may become a risk for animal or human health in the (near) futureTypes of emerging mycotoxins

Unidentified new forms of a mycotoxinsNot well-known mycotoxins Known mycotoxin not previously associated with feed or foodKnown mycotoxin that was under control, but suddenly increases (re-emerging)

Identification emerging mycotoxins (1) Why ?

Important for timely recognition of critical situationsOffers an increased number of options for actions to risk management (inspection and trade)

→ Crucial part of effective and dynamic food policy→ Additional to current systems (known

mycotoxins)

Identification emerging mycotoxins (2)

Aim of MYCONET: to develop an information system that pro-actively identifies emerging mycotoxins

(and prevents them from becoming risks)

Characteristics:Anticipatory instead of responsive approachDifferent from and additional to current systemsUse of different kind of indicators and signals

Indicators

Signals that indicate (directly or indirectly) the possibility of occurrence of an emerging mycotoxinDerived from critical factors, measurable (information sources attached)Directly or indirectly related to feed/food chainFrom several influential sectors (“holistic approach”), as proposed in a.o. EMRISK and PERI-APT

Host environmental analysis

How to select relevant information?

Influential Sectors

Critical factors

Indicators

Information sources

Wheat infected with fusarium head blight

(www.ncsu.edu/news)

MYCONET- SafeFoodEraDevelop a system for identification of emerging

mycotoxins Focus on Fusarium related toxinsIn European wheat based feed and food supply chains

Objectives1. Selection of most important indicators

2. Identification of information sources

3. Definition of an information model

4. Form and type of information needed by stakeholders

Selection of indicators

Aims:Select key indicators using holistic approach Semi-quantify the importance of the selected indicators Define potential interactions

Methods:Expert judgement studyEU expert panel of 43 expertsDelphi approach, 3 rounds held by mail

Selected indicators

12 key indicator selected for each stage 1 Cultivation 2 Transport and Storage 3

ProcessingConsensus among experts panelSemi-quantitative ranking of indicatorsPotential interactions definedCultivation (Fusarium) most important stage Most indicators relevant for known mycotoxins, but …. some additional selected

Key indicators for EM in wheat cultivationIndicator (Cultivation stage) Total score (N=24) Median Average SD

Relative humidity/rainfall (air and soil) 216 10 9.4 1.0

Crop rotation 154 7 6.7 2.5

Temperature 145 8 6.9 2.5

Tillage practice 125 6 6.0 2.4

Water activity in kernels 118 8 6.9 2.9

Crop variety / Cultivars 107 5 5.4 1.8

Harvest conditions 88 4 4.9 2.2

Changes in composition of fungal populations 85 3 4.3 2.8

Pesticide/fungicide use 79 4 4.2 1.9

Plant health (stress factors) 60 3.5 3.8 2.4

Regional infection pressure 60 2 2.9 1.7

Awareness of food safety 28 2 2.5 1.6

Information sourcesInformation sources EU countries both public and private.

Results:Information on many key indicators is available, but not easily accessiblePrecision (time, space) is variableInformation from cultivation - storage is most relevantDetailed info farm level for collectors and trade industryMonitoring program needed to collect farmers’ data Information management should be organized in the chain

Model developmentAim: To define a theoretical model for EM

identificationBased on the key-indicatorsUsing data from information sources

The model should handle Different types of information• quantitative and qualitative • technical and expert information

Region specific informationDifferent levels of information detail (in time and space)

EM modeling approach

1) Start from basic regression equation:Predicted EM is function of indicators

2) Supply chain approachEM(s1)=c1 + α1*ind1 + α2*ind2 + … EM(s2)= EM(s1) + α11*ind11 + α12*ind12 + …EM(s3)= EM(s2) + α21*ind21 + α22*ind22 + …

3) Extend with qualitative indicators and interactions

Basic statistical models too far fetched due to lack of information (relationships unknown)Adapt modeling approach according to available information Models for “known” mycotoxins are assumed to be valid for EM, with additional indicators taken into account

Basic quantitative regression + qualitative risk influencing factors

Risk is “batch” or “location” linked, modeling in GIS context could be the futureEM models should fulfill stakeholder needs

Thoughts on EM modeling

Stakeholder needs

Aim: Investigation of the aims and needs of potential end-users regarding information on EM occurrence

Two groups of stakeholders:Risk managers / assessorsFeed and food industry

Stakeholder investigation

Two elicitation sessions with the 2 groupsOne day-workshop

Scenario based approach in 2 sub-groupsTwo scenarios in both sub-groups

Series of individual in-depth interviews13 structured interviews: 9 with risk managers and 4 with industry

Results stakeholder investigation

General interest in envisioned EM identification system Improve risk management, control & monitoring

Facilitate purchase decisions More targeted sampling

Central database EU-level informationInvolve all major actors in the chain Easy to use, interactive

Region specific risk maps linked to databaseApproved information reliability/quality Information sources are anonymous Transparency about uncertainty

Demo EM identification system

Risk is location specific and “risk origin” is relevant to most stakeholdersGIS (as databases and maps) are an appropriate tool for the envisioned EM identification systemA demo for a Geographic EM Identification System (GEMIS) © has been developed

How does it look?

Maps of Europe Input maps for indicators (can be any relevant indicator)e.g. weather, wheat cultivar, storage quality, fungal speciesModeling tool to assess EM occurrence, based on region specific indicator information Output maps for assessed occurrence of EMScenarios (“what if”) can be added, e.g., regarding climate change, biofuel production

Demo GEMIS

Scenario: temp +2, rain+3

Conclusions

1. Emerging mycotoxins in the feed supply chain could be prevented by early identification

2. Modeling Flexible regarding approach and output

Depending on needs of specific stakeholders (farmers, traders/ processors)

Origin based: GIS and mapsStart from quantitative models and factors involved, and extended to include

Qualitative indicators Uncertainty

Extension needed to other mycotoxins and feed commodities, and their related factors/indicators

Thank you for your attention