Resistance Monitoring 2.0

True monitoring instead of surveying problem cases

All important information at a glance

This year we carried out a weed monitoring on 1369 representative fields all over Germany.


  • Surveying the extent of the resistance with problem grasses
  • Identification of priority regions
  • Detection of previously undetected resistance problems

Scope of the work

We have:

  • 11,598 ha in 13 federal states
  • carried out 2,583 infestation estimates of 49 different weeds befor the harvest in grain, beet and corn crop rotations
  • collected 1,940 seeds or leaf samples from 41 different weeds

Current work pipeline

  • Determination of the resistance status of material collected in the greenhouse using biotests
  • Collection of important crop management and location parameters for better interpretation of the data

What we offer

We provide data,summaries,supportand know-how with:

  • strategic decisions and the identification of research priorities for future product development
  • survey of risk areas and crop rotations at risk
  • assessment of the success of preventive measures (IWM-integrated weed management)
  • early identification of new resistance problems
  • investigation of the causes of poor efficacy without resistance (weather conditions, dose levels, …) , )
  • resistance analysis of individual fields or parcels in field tests
  • support of baseline studies for new products and the creation of sensitivity profiles
  • or to put it simply: all projects requiring expert knowledge on herbicide resistance

Not convinced yet? Then please read on for further details!

Background: The problem of insufficient data

To date, there have been no comprehensive studies on the prevalence of weed resistance in Germany. Knowledge about the causes and prevalence of the problem has so far been largely based on suspected cases , in which a reduced efficacy has been demonstrated in the field.. Furthermore, there are few field tests that experimentally test current ideas on resistance. However, we consider this approach to be insufficient for such a complex issue as the prevalence of resistant weeds. Even due to this imperfect data situation, opinions on the extent of the proliferation of resistance often vary between a kind of exaggerated alarmism and a trivialization of the problem.

Although research has shown that the resistance situation can vary greatly from field to field andbetween neighboring fields different clear risk groups have been identified based on the crop management method and location characteristics. Our approach is therefore to learn from the monitoring of the 1,000 fields. This is the only way to identify the full range of resistance-forming factors and to make targeted statements on the current prevalence and development of resistance.

The added value compared to the approach so far

Representative field selection

An estimated 90 % of the fields are not paid attention to with the examination so far of the resistance problem, as they either do not show any significant infestation due to the strong efficacy of the herbicide or a problem is not identified as such and other causes are cited to explain an observed reduced efficacy. In practice, one can observe 4 scenarios after application

  • Scenario 1: Good efficacy of application in the field application in the field, the farmer is satisfied with the efficacy of the herbicide (the larger part of the fields).
    • Scenario 1a: No or few non-resistant weeds/grass weeds remain after application
    • Scenario 1b: Individual or a few resistente weeds/grasses remain in the field after application, but are not identified as such
  • Scenario 2: Poor effect of application in the field, the farmer is not satisfied with the effect of the herbicides (so far, the minority of fields)
    • Scenario 2a: unexpectedly many non-resistant weeds/grasses remain after application. Weather, scheduling or an insufficient amount of herbicide applied are possible causes.
    • Scenario 2b: unexpectedly many resistant weeds/grasses remain after application.


Knowledge of resistance to date is currently almost exclusively based on the two aspects of the second scenario (2a+2b). However, we took all 4 scenarios into account when selecting our fields, resulting in a significantly improved data basis for our resistance analysis. The surveys conducted as part of our monitoring activities have that way also laid the foundation for future-oriented assessments of the problem.

  • 2b: schlechte Wirkung im Feld - resistent
  • 2a: schlechte Wirkung im Feld - nicht resistent
  • 1b: gute Wirkung im Feld - resistent
  • 1a: gute Wirkung im Feld - nicht resistent

Conclusion from the present into the future

In determining the fields to monitor, we took all possible scenarios (see above) that can be found in the field into account. With this, we have laid the foundation for a resilient analysis of the resistance situation of various weeds in Germany. These fields were sampled by us according to uniform criteria. The collected seed material is now tested step by step for resistance in the greenhouse of our partner, PlantaLyt GmbH. At the same time, in the coming months, we will collect important information on crop management and location. This provides us with a reliable basis of data that provides the basis for risk assessment with problem weeds in the different regions of Germany. Only this complete examination allows us to provide an actual statement about the problem and to forecast the further course of the resistance problem.


​Conclusion: By specifically including fields where, from the farmer’s point of view, strong weed control still exists today, we provide:

  1. a contribution to the detection of resistance, if possible, already in the lead-up to corresponding developments, and
  2. a better understanding of the extent of the resistance problem with of already known problems.

Goals of monitoring

  • The first real survey of the resistance situation in Germany

    The true extent of the resistance problem with different weeds is determined by random and representative sampling and regions of resistance are identified. We have identified previously unknown resistance problems. Identification of other resistance problems

  • Identification of other resistance problems

    Through a random selection of the fields, we also sample where farmers currently still experience strong weed control. Nevertheless, in many cases a tendency for weeds to occur in nests can be observed, even in such cases where resistance is still playing a minor role at present. By analyzing these samples in the greenhouse, we can identify at an early stage in which areas and with which weeds problems are developing so that these can be tackled in time. In addition, problems can be detected where several (resistant) species appear simultaneously in a field.

  • Assessment of resistance management

    By surveying the crop management measures, we obtain a differentiated picture of the measures that have led to the build-up of resistance. n addition, we can infer to what extent resistance prevention strategies are actually realized in practice and with what effect. A distinction can be made between known problem areas and other regions as well as an assessment of resistance prevention strategies as such.

  • Identifying other causes of reduced efficacy

    Resistance is only one cause of reduced efficacy of herbicides in the field. By surveying the infestation situation at the time of harvesting and comparing it with the resistance situation, we find out in which areas a suboptimal application has taken place and can infer reasons for this from the data on crop management and weather conditions.

  • Provision of sample material for further studies (sensitivity profiles, series of doses and more)

    In addition to content analyses, we also provide sample material for independent queries based on sensitive or resistant biotypes. By characterizing the resistance profile of our samples, we are in a position to deal with detailed questions or theoretical considerations through the carrying out of tests on the topic of weed resistance using suitable sample material.

Scope of monitoring

From Rügen to Lake Constance, from Bautzen to Bocholt – Altogether we dispose of results from 1.369 fields from 13 federal states. While at it, we recorded 2,583 weed observations and collected 1,940 seed or leaf samples. The fields surveyed consist of grain, beet and corn crop rotations.

Number of samples available

  • 500 samples and more

    • Blackgrass (Alopecurus myosuroides)
  • 100 samples and more

    • Loose Silky-Bent Grass(Apera spp.)
    • Brome species (Bromus spp.)
  • 50 samples and more

    • Wild oats (Avena fatua)
    • Ryegrass species (Lolium spp.)
    • Lamb’s quarters species (Chenopodium spp.)
    • Foxtails (Setaria spp.)
    • Barnyard-grass (Echinochloa crus-galli)
  • 20 samples and more

    • Anthriscus (Anthriscus caucalis)
    • Cornflower (Centaurea cyanus)
    • Chamomile species (Matricaria spp.)
  • Up to 20 samples

    • Knotweed species (Polygonum spp.)
    • Finger Millet (Digitaria spp.)
    • Black Nightshade (Solanum nigrum)
    • 25 other species

What advantages does our monitoring offer?

For pesticide manufacturers

Note: More details about each sub-item can be found by clicking on “+”

Our monitoring provides an overview of the current prevalence of resistance of the most important weeds and grass in Germany. Since resistance is a “creeping problem”, the proactive and representative nature allows for early identification of problems that at present are not yet acute. Using the data, future problem solutions can be better planned and market potentials estimated.

We test our samples for possible resistance using a selection of herbicides specified by us. In addition, interested parties have the opportunity to have selected samples tested using a customer-defined selection of herbicides.

Our monitoring provides insight into the incidence of several resistant species at the same time with possibly different resistance mechanisms, since weeds growing as a group are sampled together. This can be incorporated into the development of complex and sophisticated preventive measures.

By surveying the weed infestation at harvest time, our monitoring provides information on fields with inadequate weed control in addition to information on the resistance situation. This insufficient control can then have several causes – in addition to resistance, it can, for example, also be caused by unfavorable weather conditions.


This way we can answer questions such as: How successful are the control measures measured against the degree of infestation pressure of surviving plants prior to harvesting? Is there an increase in insufficient control measures either due to resistance or due to other causes? Are there regional differences, perhaps due to unfavorable weather conditions or higher levels of resistance?

We identify regions with imminent outbreaks of resistance so that preventive measures can be taken in a targeted manner and the communication of integrated crop management measures, including active ingredient changes and tank mixtures, can be boosted.


The project also allows a success check to be made as to whether preventive measures are successful. Could the incidence of new cases be reduced or even prevented altogether? Or do the measures need to be boosted or other measures taken? What attitude do farmers have towards resistance prevention strategies in areas that are not yet considered problem areas?

For consulting and trade

Note: More details about each sub-item can be found by clicking on “+”

Preparation of the resistance problems found in various weeds for specified regions and derivation of possible courses of action.

Creation of a detailed resistance profile according to the customer’s requirements for selected fields. Here we take into account, and point out, possible alternative courses of action. In addition, we offer comparisons with already known samples to assess the extent of the problem.

Questions and answers about our monitoring

Note: More details about each sub-item can be found by clicking on “+”

Priority weeds arranged by crop rotation:

Cereals: Silky bent and black grass and other grass weeds (e.g. brome grass and rye grass), in addition, dicot root species with simultaneous seed maturity.

Beet: Grasses, ggoosefoot, chamomile and other dicot root species with simultaneous seed maturity.

Corn: Millets and Foxtails (Digitaria spp., Setaria spp., Echinochloa spp.) and other grasses; Goosefoot, knotweed and other dicot root species with simultaneous seed maturity.

  1. The pre-harvest infestation: Estimation of the infestation before harvest (sampling period). This estimate provides a better picture of the prevalence of remaining weeds after a herbicide treatment.
  2. The efficacy of herbicides: We perform greenhouse tests with the collected seed samples to measure the remaining efficacy. On request, molecular genetic analyses can also be carried out in the laboratory.
  3. The field record: The crop management measures are an important part of the analysis as they provide conclusions about the origin of the problem.
  4. The location properties: In combination with the field record, the location provides us with important information for evaluating the resistance situation found.

HRAC A (ACCase): Grasses

HRAC B (ALS): Grasses and dicotyle weeds

HRAC K3 (flufenacet): Grasses from cereal areas

Further substance groups on request

When selecting the substances, we focus in the standard test on the herbicide most frequently used for the respective substance group. However, a customer-specific enhancement is always taken into account.

More than 1000 fields in 13 federal states were surveyed by the team of Agris42 and PlantaLyt, before harvesting. We selected the fields and farmers. Here the criteria for the selection of the regions were insights into the current prevalence of resistant black grass and silky bent as well as the crop management priorities in the regions. In addition, we aimed for a uniform geographical distribution of the samples. There existed also the option for consultants or farmers to name additional regions for monitoring.


Selection of fields by employees of Agris42 and PlantaLyt.


Fieldwork: Infestation and collection of weed seeds by employees of Agris42 or Plantalyt. You can also submit additional samples (see below).


Resistance studies:

Collected samples are analyzed in the greenhouse with selected herbicides.