Spot On Special: That Little Sample Has a Big Story to Tell

Special Issue Mycotoxin Survey A Romer LabsÂŽ Publication

That Little Sample Has a Big Story to Tell

Latest BIOMIN Global Mycotoxin Survey Results Multi-Mycotoxin Risk Assessment: Beyond Regulations

Photo: dusanpetkovic

Contents

4-7

2018 BIOMIN Mycotoxin Survey Results Findings and trends from the most comprehensive survey around.

By Alexandro Marchioro, Mycotoxin Product Manager, BIOMIN

Spot On is a publication of Romer Labs Division Holding GmbH, distributed free-of-charge.

ISSN: 2414-2042

Editors: Joshua Davis, Cristian Ilea

Contributors: Martina Bellasio, Alexandro Marchioro, Yong Wee Liau Graphic: GraphX ERBER AG

8-11

Research: Kurt Brunner

Publisher: Romer Labs Division Holding GmbH Erber Campus 1 3131 Getzersdorf, Austria Tel: +43 2782 803 0 www.romerlabs.com

©Copyright 2019, Romer Labs All rights reserved. No part of this publication may be reproduced in any material form for commercial purposes without the written permission of the copyright holder. ®

Mycotoxin Risk Assessment: Telling the Full Story Of the approximately 400 mycotoxins out there, only 6 or so are subject to regulations.

How can we get a full picture of the occurrence of emerging and masked mycotoxins as well as the “usual suspects”?

By Yong Wee Liau, Managing Director, Romer Labs Asia

All photos herein are the property of Romer Labs or used with license.

Romer Labs is part of ERBER Group

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Spot On Special Issue Mycotoxins

Editorial

That One Little Sample Has a Big Story to Tell Every year, the experts from our sister company BIOMIN issue the results of their World Mycotoxin Survey. Those in the feed and livestock industries hold it in high regard, and it’s easy to see why; with over 80,000 samples analyzed in nearly 80 countries, the survey is the industry leader in identifying patterns of mycotoxin contamination in raw materials and feed. It has played no small part in raising awareness about the myriad ways that mycotoxins can affect swine, poultry, ruminants and other animals. In an uncertain marketplace and a rapidly changing climate, the survey provides clarity about the occurrence of both regulated and unregulated mycotoxins.

It is also a useful tool in the analytical community. In last year’s survey issue of Spot On, I pointed out the importance of having reliable methods of mycotoxin detection in place before instituting a mycotoxin management program: You can’t manage what you don’t measure. This year, the survey results are adding a bit of complexity; according to our friends at BIOMIN, we are witnessing patterns of increasing co-occurrence of mycotoxins. In other words, there is an increased chance that the average sample of grain or feed will contain detectable levels of more than one mycotoxin.

The problems that co-occurrence may cause are seldom predictable. However, we have been able to observe synergistic effects between certain mycotoxins. By “synergistic,” we mean that the combined effects of the two mycotoxins in question are greater than the mere sum of their individual effects. What’s more, this applies to several mycotoxins, not just the “usual suspects”, the regulated mycotoxins such as deoxynivalenol and aflatoxin. The more we learn about the dangers of cooccurrence, the more important it is to have validated analytical methods at our disposal that can detect several mycotoxins within the same sample.

In this issue of Spot On, my colleague at BIOMIN, Alexandro Marchioro, reviews some of the results of the BIOMIN World Mycotoxin Survey and analyzes the occurrence of mycotoxins throughout different regions around the world. My colleague from Romer Labs Asia, Yong Wee Liau, discusses emerging and masked mycotoxins as well as some examples of the effects of mycotoxin co-occurrence.

She also introduces methods for analyzing samples of grain and feed for the simultaneous presence of multiple mycotoxins. As we like to say, that one little sample has a big story to tell. Multi-mycotoxin analysis shows great potential in bringing that story to light.

Enjoy this issue of Spot On.

A Romer Labs® Publication

Martina Bellasio, PhD

Product Manager Mycotoxins

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Photo: eclipse_images

BIOMIN World Mycotoxin Survey 2018

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Spot On Special Issue Mycotoxins

The latest edition of the annual survey, covering 18,424 agricultural commodity samples from 79 countries with over 81,900 analyses, highlights the main dangers from the most important mycotoxins in primary feedstuffs and their potential risk to livestock animal production.

By Alexandro Marchioro Mycotoxin Product Manager, BIOMIN

T

he results of the BIOMIN Mycotoxin Survey provide insight into the incidence of aflatoxins (Afla), zearalenone (ZEN), deoxynivalenol (DON), T-2 toxin (T-2), fumonisins (FUM) and ochratoxin A (OTA) in the primary components used for feed. These include corn (maize), wheat, barley, rice, soybean meal, corn gluten meal, dried distillers grains (DDGS) and silage, among others.

Risk levels Because of the powerful sensitivity of state-of-theart detection tools, it is no longer sufficient to talk about the mere presence of mycotoxins; concentration levels must also be considered. Consequently, the latest results feature a mycotoxin risk map based upon both the presence of mycotoxins and their potential harm to livestock depending on concentration levels associated with known health risks.

Figure 1 shows mycotoxin occurrence data for each region as a percentage of all samples tested. The overall risk level for a particular region is determined by the percentage of mycotoxins that exceed the risk threshold levels for livestock. The risk thresholds are Article continues on p. 8.

A Romer LabsÂŽ Publication

5

Afla 15% ZEN 56% DON 64% T-2 44% FUM 47% OTA 16%

Northern Europe Total Risk 56%

Central Europe Total Risk 46%

Afla 1% ZEN 42% DON 66% T-2 49% FUM 44% OTA 10%

Afla 21% ZEN 67% DON 58% T-2 24% FUM 84% OTA 31%

Middle East Total Risk 60%

Afla 8% ZEN 34% DON 67% T-2 3% FUM 44% OTA 3%

Southern Europe Total Risk 61%

North America Total Risk 73%

Figure 1. Global map of mycotoxin occurrence and risk in different regions. Squares indicate the percentage of the analyzed samples that were contaminated with the

Afla 15% ZEN 71% DON 65% T-2 15% FUM 87% OTA 15%

DON and FUM

South America Total Risk 72%

North America.

Afla 27% ZEN 48% DON 67% T-2 25% FUM 72% OTA 7%

Afla 26% ZEN 81% DON 77% T-2 10% FUM 71% OTA 6%

South Africa Total Risk 67%

livestock animals in

Afla 14% ZEN 10% DON 70% T-2 0% FUM 84% OTA 3%

Africa Total Risk 65%

greatest threats to

Central America Total Risk 70%

represented the

Afla 7% ZEN 72% DON 72% T-2 1% FUM 74% OTA 6%

Legend Moderate risk

6

Extreme risk

n n n n

Moderate risk: 0 – 25% of samples above risk threshold High risk: 26 – 50% of samples above risk threshold Severe risk: 51 – 75% of samples above risk threshold Extreme risk: 76 – 100% of samples above risk threshold Spot On Special Issue Mycotoxins

respective mycotoxins in a region. Colors indicate different risk levels according to the legend.

Afla 28% ZEN 77% DON 90% T-2 1% FUM 87% OTA 7%

Oceania Total Risk 17%

Afla 87% ZEN 22% DON 33% T-2 0% FUM 86% OTA 73%

Afla 10% ZEN 55% DON 82% T-2 2% FUM 72% OTA 14%

81, 936

79

Co-contamination 70%

South-East Asia Total Risk 70%

China & Taiwan Total Risk 85%

East Asia Total Risk 60%

Afla 3% ZEN 53% DON 66% T-2 54% FUM 37% OTA 35%

South Asia Total Risk 86%

Eastern Europe Total Risk 36%

18, 424

Afla 54% ZEN 51% DON 68% T-2 1% FUM 81% OTA 30%

20%

10%

Number of mycotoxins per sample based on samples tested for 3 or more mycotoxins.

Risk Level

Afla 4% ZEN 19% DON 47% T-2 0% FUM 27% OTA 5%

The risk level expresses the percentage of samples testing positive for at least one mycotoxin above the threshold level in parts per billion (ppb). A severe risk level indicates that >50% of samples may represent a risk to productivity or disease susceptibility.

Recommended risk threshold of major mycotoxins in ppb Afla

ZEN

DON

T-2

FUM

OTA

2

50

150

50

500

10

©Copyright BIOMIN Holding GmbH, 2019. Used by permission.

A Romer Labs® Publication

7

South Asia and the China/ Taiwan region face the most severe threats of mycotoxin-related risks to livestock.

Regional insights

Continued from p. 5. based on worldwide practical experience in the field and in scientific trials that were conducted to reflect field situations as closely as possible; they also take into account the most sensitive species for each mycotoxin.

The average risk levels used as a basis do not preclude specific, severe instances of mycotoxin contamination in farms or fields locally, nor do they account for the negative impacts of multiple mycotoxin presence.

The mycotoxin risk map relies upon single mycotoxin occurrence. This may understate the threat posed by mycotoxins to animals given their known synergistic effects (the presence of multiple mycotoxins compounds the potential harm) and subclinical effects (even low levels of mycotoxin contamination can impair animal health and performance).

Table 1. Detailed results of mycotoxin occurrence by region

Europe

Number of samples Positive (%)

Average of Positive (ppb) Maximum (ppb)

Asia

Number of samples Positive (%)

Average of Positive (ppb) Maximum (ppb)

North America

Number of samples Positive (%)

Average of Positive (ppb) Maximum (ppb)

South America

Middle East

Number of samples Positive (%)

Average of Positive (ppb)

Afla

ZEN

DON

T-2

FUM

OTA

2831

4080

4311

3208

2983

2878

12% 5

56% 154

63% 601

176

248000

40700

33%

65%

80%

3360 44

3371 139

3371 602

4890

10256

53796

8%

34%

67%

1705 17

1772 362

280

10790

27%

48%

6023 8

5276 130

41% 61

15

26204

5912

1%

82%

15%

3212 34

181

1596

735

461

3%

13641

1143

67%

25%

1008

664

26%

6062

1597

5107

57%

2188 43

3345

1833

123444

3212 7

126

1749

1773

3001

13

44%

3%

130724

317

72%

7%

5465

2184

835 10

402

5020

24880

583

72100

Positive (%)

15%

71%

65%

15%

87%

15%

15

926

2021

37

14427

5

8%

72%

72%

2%

74%

105

4336

12220

34

9373

Number of samples Average of Positive (ppb) Number of samples Positive (%)

Average of Positive (ppb) Maximum (ppb)

Source: 2018 BIOMIN Mycotoxin Survey

8

Europe Europe ranked as a moderate to severe risk region, with more than half of the samples testing above the risk threshold levels; a notable exception was Central

Maximum (ppb)

Maximum (ppb)

Africa

South Asia and the China/Taiwan region face the most severe threats of mycotoxin-related risks to livestock. Both regions are confronted with extreme risk, as more than 85% of samples showed a contamination level above the risk threshold levels. Table 1 provides an overview of the number of samples tested, occurrence, average contamination levels and maximum contamination values. In general worldwide, fumonisins and deoxynivalenol were the top threat, with several samples exhibiting co-occurrence of these two mycotoxins.

161 3

556 12

165 48

552 67

173

316

165 15

552

552

736

15

174

1074 552

422

75

158 2

552 6% 5

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Spot On Special Issue Mycotoxins

Photo: Dr. Microbe 69

Europe, which exhibited a risk threshold of 45%.

Samples from Southern Europe showed a very high incidence of FUM, at 84% and an average of 1031 ppb.

DON levels in Central and Northern Europe increased in 2018; in Central Europe, the prevalence was also high at 64% with an average of 776 ppb. Northern Europe showed similar levels of DON, with a prevalence of 66% at an average of 724 ppb. DON was especially high, in cereals like wheat, barley, etc., with an average of 912 ppb.

Asia Asia has the highest level of risk this year. In China, FUM and DON are prevalent, particularly in corn. 96% of all corn samples were contaminated with these two mycotoxins. The average contamination of FUM was at 3438 ppb, while DON levels were at 540 ppb on average.

South Asia stood apart from other regions, as there were other concerns aside from FUM and DON there.

Aflatoxin was present in 44% of all samples tested in South Asia. Furthermore, 87% of samples contained aflatoxins, which for the most part occurred in finished feed samples. The highest regional contamination of Afla was 697 ppb, while that of FUM was at 47,285 ppb.

While this last value is high, it is less than a third of last year’s highest occurrence of FUM. ZEN was the third highest occurring mycotoxin in samples from Asia, detected in 65% of those tested.

North America DON and FUM represented the greatest threats to livestock animals in North America. DON contamination in cereals rose from 65% in 2017 to 86% in 2018 with an average of 1853 ppb. Fumonisins were present in 70% of corn samples analyzed, with a high average of 3497 ppb. The average concentration of FUM contamination was relatively high for the region (3001 ppb).

An important corn sub-product, DDGS, was especially subject to DON contamination: the prevalence was at 98% and there was an average contamination of 1420 ppb. ZEN, Afla and OTA were detected in 34%, 8% and 3% of samples at average levels of 362 ppb, 17 ppb and 13 ppb, respectively. The world’s highest concentration of FUM was detected in North America (130,724 ppb).

South and Central America Risk was generally high in these regions. Central America exhibited a risk level of 70%, while South America surpassed it at 72%. In South America, DON was present in 88% of cereal samples, testing at high average concentrations (1949 ppb). Further, a maximum concentration of 24,880 ppb was detected. FUM is the A Romer Labs® Publication

most abundant mycotoxin in this region. It contaminates 86% of corn, 100% of DDGS and 89% of finished feed samples. A concentration as high as 72,100 ppb of FUM was found. One particular hotspot for FUM was Argentina; there, FUM was high at 4762 ppb on average.

In Brazil, the most prevalent mycotoxin is FUM with a 73% rate of occurrence and an average contamination of 2144 ppb. The second most prevalent mycotoxin is DON (70%; 1073 ppb). In corn, FUM is the most prevalent mycotoxin with 86% and an average of 2605 ppb.

Middle East The Middle East showed a severe level of risk with a total threshold level of 60%. In particular, the prevalence of FUM, DON and ZEN is on the rise here, with contamination levels of 87%, 65% and 71%, respectively. There was an even bleaker picture for samples of corn, with a 100% prevalence of FUM at an average of 3101 ppb.

In general worldwide, fumonisins and deoxynivalenol were the top threat, with several samples exhibiting cooccurrence of these two mycotoxins.

Africa As in 2017, the most common mycotoxin in Africa was DON, detected in 77% of all samples analyzed; the average concentration was 736 ppb. FUM occurred in 77% of all samples, and ZEN occurred in 72% of all samples. The total risk level in South Africa alone (67%) was higher than that of the entire continent (65%).

Conclusion The analysis of the 18,424 samples in this survey once again underscores that the continuous monitoring and measuring of mycotoxins in grains and feed is important. Only with reliable data on mycotoxin contamination can professionals in the feed industries mount a defense in the form of an effective mycotoxin risk management program and, in so doing, protect animals from the negative impacts of mycotoxins on their health and performance.

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Spot On Special Issue Mycotoxins

Mycotoxin Risk Assessment:

Telling the Full Story The research is clear: producers of food and feed need to take the synergistic effects of mycotoxin co-occurrence into account.

Yet how do we get a sample to spill all its secrets? As a method of multi-mycotoxin analysis, LC/MS-MS is already showing great promise.

By Yong Wee Liau, Managing Director, Romer Labs Asia

A Romer LabsÂŽ Publication

11

Often, the host plant will further modify compounds coming from the fungus.

This chemical modification provides the “mask” that obscures the true identity of the mycotoxin.

T

here are approximately 400 compounds of low molecular weight that are recognized as mycotoxins, each with its own toxic effects for humans and animals. Yet national and international regulations and recommendations typically cover only a handful of mycotoxins: aflatoxins B1, B2, G1, G2 and M1; fumonisins B1, B2 and B3; ochratoxin A, deoxynivalenol, zearalenone, HT-2 toxin and T-2 toxin. These mycotoxins are well characterized and frequently covered in available research literature.

What do we know about the other unregulated mycotoxins in a particular sample? What are the hidden risks of their co-occurrence? How do we get a sample to tell its full story? This article will investigate unregulated mycotoxins, discuss the effects of mycotoxin co-occurrence, and introduce a method for analyzing samples of grain and feed for the simultaneous presence of multiple mycotoxins.

Emerging and masked mycotoxins Emerging mycotoxins are those that are potential candidates for regulation owing to their increasing frequency and their toxicological composition, i.e. their potential for harm to animals or humans that could consume them. Strategies to measure and confront them are in a nascent stage and are currently subject to rapid development.

One particular subclass of unregulated mycotoxins is “masked mycotoxins.” Fungi release a wide range of metabolites, including the well known DON and ZON,

into the plant as part of the infection process. Often, this host plant will then further modify the compounds coming from the fungus. This chemical modification provides the “mask” that obscures the true identity of the mycotoxin.

Masking, however, serves an important purpose for the host plant as it constitutes one of its major detoxification strategies. Usually, a glucose molecule or a sulfate is involved in the conjugation and detoxification. Although these masked toxins do not further harm the plant, their toxicity to humans and animals might reemerge when the added masking molecule is cleaved in the gastrointestinal tract of mammals during digestion (Figure 1). In plant breeding, the increasing occurrence and production of some masked mycotoxins could be linked to novel resistant breeds.

Deoxynivalenol-3-glucoside, for example, has been reportedly linked to resistance against Fusarium head blight. Although Fusarium-resistant plants show lower levels of total DON, higher DON-3-Glu/DON ratios have been reported in such plants, showing an increased production of this masked mycotoxin.

Modified mycotoxins and their toxicity The “modified mycotoxin” is a further term signifying the changes that mycotoxins can undergo. Modified mycotoxins refer to both the modification of a parent toxin molecule by the fungus itself and the masking of the toxin that occurs within the plant tissue. Another type of modification takes place in mammals when af-

Figure 1. Cleavage reaction of deoxynivalenol-3-glucoside to native deoxynivalenol during digestion.

H

H3C

H

H

H3C

O

H

O

OH

Digestion O

O

O HO

OH

CH3

O

HO

O HO

OH

CH3

O OH HO OH Source: Romer Labs

12

Spot On Special Issue Mycotoxins

latoxin B1 is consumed through contaminated feed and converted to aflatoxin M1. This aflatoxin M1 migrates into the milk of lactating animals and is subsequently excreted with it. In addition, modifications of toxins can also occur during food processing, in particular heating and fermentation, increasing their prevalence.

These modified mycotoxins might occur in relevant amounts in food and feed.

Of all mycotoxins, deoxynivalenol has been most researched with regard to frequently observed modifications. The modified forms of deoxynivalenol can be divided into two main groups: altered and masked forms. There are two main altered forms of deoxynivalenol secreted by the fungus itself: 3-acetyl-deoxynivalenol and 15-acetyl-deoxynivalenol, as found in Fusarium-contaminated cereals. Plants are able to mask the deoxynivalenol to deoxynivalenol-3-glucoside and, as recent studies show, this may take on two sulfonated forms: deoxynivalenol-3-sulfate and deoxynivalenol-15-sulfate.

So what specific harm can come of modified, masked and other emerging mycotoxins? Modified mycotoxins can be either more or less toxic than their parent compounds. For example, they may be more bioavailable due to modifications. Toxicological data on modified mycotoxins are scarce, and current results and knowledge on the real risks and effects of these compounds are insufficient. This lack of knowledge makes it difficult to conduct a proper risk assessment.

Nevertheless, there have been studies describing their potential threat to food safety. Masked mycotoxins can be “unmasked” in the digestive tract of animals and humans, releasing the parent compound with its toxicological effects once again. A similar situation exists with other emerging mycotoxins: toxicological data are scarce which makes it difficult to set up regulations and maximum tolerated limits to protect humans and animals from potential health risks.

As modified mycotoxins behave differently in their chemical reactions than their parent mycotoxins, they can be easily missed in routine analysis. Current detection methods for regulated mycotoxins in food and feed do not include routine screening for these modified mycotoxins as they are not covered by legislation. Such standard methods may show up as contamination levels below legislative limits, while contaminations from modified mycotoxins go undetected. This represents a correct result, but from a toxicological point of view the integration of modified toxins (e.g. as a sum parameter) would provide more sound data for risk assessment.

Together, all these facts point to the possible hazards posed by modified mycotoxins to human health. ReguA Romer Labs® Publication

lations on the maximum levels of modified mycotoxins as well as other emerging mycotoxins are currently under discussion at the European Food Safety Authority.

Modified mycotoxins can be either more or less toxic

Mycotoxin co-occurrence Now that we know that several mycotoxins are produced by the same fungi, it should come as no surprise that the converging effects of multiple mycotoxins have increasingly become the subject of research. Data collected in several independent studies in recent years show that agricultural commodities are often contaminated with more than one mycotoxin. The toxicological interactions of mycotoxins are typically synergistic: this means that the toxicological effect of two or more mycotoxin present in the same sample will be higher than the sum of toxicological effect of the individual mycotoxins. That said, the co-occurrence of mycotoxins can also have additive or, more rarely, antagonistic effects, by which their effects cancel each other out.

These synergistic effects vary from animal to animal and can be very complex. Figure 2 shows both the synergistic and additive effects of certain mycotoxins in poultry. Aflatoxin B1 (AFB1), for example, is a regulated mycotoxin that exhibits synergistic effects with diacetoxyscirpenol (DAS) and cyclopiazonic acid (CPA), both unregulated mycotoxins, and an additive effect with DON, another regulated mycotoxin. In swine, however, as shown in Figure 3, AFB1 has no known co-occurring effect with DON or DAS, instead demonstrating synergistic effects with T-2 toxin and ochratoxin.

than their parent compounds. For example, they may be more bioavailable due to modifications.

Figure 2. Synergistic (red line) and additive (dashed line) effects of mycotoxins in poultry.

AFB1

AFB1

FB1

MON MON

D

CPA

FA OTA

DON

DAS T-2 Toxin

FA Citrinin

OTA ZEN

FB1

Source: BIOMIN

13

The toxicological interactions of AFB1

Toxin

Figure 3. Synergistic (red line) and additive (dashed line) effects of mycotoxins in swine.

AFB1

FB1 mycotoxins are

MON

typically synergistic:

Figure 4. Summary of steps for creating a multi-mycotoxin method based on LC-MS/MS. Method development

DON

CPA

this means that the toxicological effect of two or more

FA

DAS

DON

optimization

mycotoxin present FA in the same sample

will be higher Citrinin

than the sum of toxicological effect of the individual mycotoxins.

14

DON Method

OTA

T-2 Toxin ZEN

FB1

Source: BIOMIN

These are just a couple of examples of co-occurrence.

The increasing awareness for mycotoxin co-occurrence makes it necessary to develop multi-mycotoxin detection methods that simultaneously analyze several mycotoxins. In response to this need, Romer Labs has developed the Multi-Mycotoxin Analysis 50+ method.

This analysis gives a unique insight into the contamination pattern of a sample and quantifies more than 50 mycotoxins, including aflatoxins, Alternaria toxins, ergot alkaloids, fumonisins, zearalenone, and “masked” mycotoxins such as deoxynivalenol-3-glucoside.

A discussion of the advantages, limitations and development of the method with respect to the chemical diversity of analytes and the range of agricultural commodities that can be tested follows.

AFB1 • LC and MS parameters • Sample preparation procedure • Stability testing FB1 • Selectivity • Working range

• • Method validation T-2 Toxin• •

LODs, LOQs Linearity, accuracy Precision, robustness Matrix effects, recoveries

Multi-mycotoxin analysis

tivity and selectivity, as well as the delivery of additional information about mass-to-charge ratios (m/z) and fragment ions of the analytes under investigation.

The set-up of a multi-mycotoxin method based on LC-MS/MS usually follows a three-phase process on the way to implementation: method development, method optimization and method validation. These steps and parameters are summarized in Figure 4. ­­­­During method development and optimization, the quality and reliability of the results should be evaluated carefully.

For this purpose, analytical standards of the highest quality, with certified concentration and stated purity must be used. However, for certain analytes, analytical standards are not commercially available. In those cases, it might be possible to access standards that are still under research, or to work with available material that is less well characterized.

Analysts are increasingly turning toward LC-MS/MS (liquid chromatography/tandem mass spectrometry) as a chief method for detecting multiple mycotoxins.

Analytical methods based on LC-MS/MS have become a powerful and state-of-the-art technique in the qualitative and quantitative analysis of mycotoxins over the last decade. This technique enables the simultaneous determination of a wide range of mycotoxins belonging to different chemical families within one single measurement: acidic (fumonisins), basic (ergot alkaloids), polar (moniliformin, nivalenol) and apolar compounds (zearalenone, beauvericin) can all be simultaneously quantified with LC-MS/MS. Further advantages of this method are its high sensi-

During the development of a method based on LC-MS/MS, the MS and LC parameters, as well as the sample preparation procedure must be optimized. To optimize the MS parameters, each target compound should be injected as a pure analytical standard directly into the mass spectrometer. This allows for the selection of the best ionization mode (positive or negative) and the most abundant precursor and product ions.

Also, the chromatographic conditions can be adjusted in this phase: the ideal mobile phases and gradient as well as the optimal chromatographic column must be evaluated.

Method development

Spot On Special Issue Mycotoxins

LC/MS-MS enables the simultaneous determination of a wide range of mycotoxins in different chemical families, all within a single measurement.

Many multi-mycotoxin methods use a dilute-andshoot approach: this refers to the practice of diluting the sample extract before injecting it into the LC-MS/ MS. A clean-up step can also be implemented as part of the sample preparation. However, the mycotoxin pattern must not be altered during the sample clean-up, i.e. one must make sure that no mycotoxin of interest is retained by the material used for the clean-up.

Method optimization The optimization of the analytical method includes stability testing of the analytes in standard solutions and samples, as well as proofing selectivity and determination of the working range.

Method validation Method validation is a prerequisite for the production of reliable results in terms of comparability and traceability. Method validation must be performed separately for each target analyte in all required matrices. Typical performance characteristics that should be evaluated during validation of a quantitative method are limits of detection (LOD), limits of quantification (LOQ), linearity, precision, selectivity, robustness, accuracy, matrix effects and recoveries. For MultiMycotoxin Analysis 50+, the validated matrices are wheat, maize, swine feed and silage.

Matrix effects are encountered when matrix components interfere with the ionization process of the target analytes. Matrix effects can have a considerable impact on the quantification of mycotoxins. Therefore, A Romer LabsÂŽ Publication

it is essential to determine and compensate for such matrix effects. This can be achieved by determining the apparent recovery followed by a mathematical correction of the results with this value, by matrix-matched calibration, or by applying isotope-labeled internal standards. The latter will lead to results with the highest degree of accuracy and reliability at minimal investment of time and cost per sample.

The method can be validated by spiking blank samples with each required analyte at a range of concentrations in replicate. When available, the trueness of the method should be confirmed using certified reference materials. Furthermore, matrix-matched materials and participation in proficiency testing enable additional quality assurance.

Analysts are increasingly turning toward LC-MS/MS as a chief method for detecting multiple mycotoxins.

Conclusion The development of a multi-mycotoxin method based on LC-MS/MS shows great potential in addressing the risk of mycotoxin co-occurrence. As the research community acquires more and more know­ ledge about the synergistic effects of multiple mycotoxins, including emerging and masked mycotoxins, validated analytical methods that can detect them within the same sample will only grow in importance.

A vast number of different parameters that significantly influence the quality and reliability of the results of the LC-MS/MS method must be considered carefully for each analyte in each matrix separately. In addition, the chemical diversity of the mycotoxins necessitates making compromises during method development, which may be far from optimal for certain analytes.

Moreover, the wide range of agricultural commodities as well as the varying concentration ranges and different occurrence distributions pose further challenges to method development and optimization. Nevertheless, the development of multi-mycotoxin methods fulfills an urgent need; advances in this technology will further extend its application.

15

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