Executive Team News
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Further language versions of the IRM and MoA videos now available
A full list of the languages available are copied below.
Mode of Action:
English, Spanish, Portuguese, Mandarin Chinese, French, Italian, Korean, Arabic, Russian, Bahasa(Indonesian), Khmer , Japanese , Tagalog (Philippines), HindiInsecticide Resistance Management:
English, Spanish, Portuguese, Mandarin Chinese, Japanese, Hindi, French, Italian, Korean, Arabic, Russian, Bahasa (Indonesian), Russian, Tagalog (Philippines) -
Insecticide Resistance Training – Basic Module: Crop Protection
This module is designed to introduce the basic concepts behind the development and management of insecticide resistance in agricultural and horticultural crops. The presentation is targeted to those that may be being exposed to the concept of insecticide resistance for the first time or simply wishing to refresh their knowledge. More detailed information on the factors which influence resistance development and its management will be provided in future modules produced by IRAC International.
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IRAC Nematicide MoA Classification now available
The IRAC Nematode Working Group is the most recently established IRAC team. The initial objectives of the team were to investigate the resistance risk of nematicides and to develop a mode of action classification scheme similar to that available for insecticides and acaricides.
Both these objectives have now been completed with the publication of the Nematicide Resistance Risk Statement at the end of 2018 and more recently the release of the Nematicide MoA Classification and corresponding MoA poster in September 2019
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UPL is the latest IRAC International Member Company
CropLife formally confirmed the UPL membership of IRAC International on the 23rd August 2019. With the mergers and acquisitions of various crop protection companies, along with the joining of UPL, this brings the number of IRAC International company members to 11. Good representation across the industry enables IRAC to continue providing a global coordinated response to insect resistance management strategies.
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New IRAC MoA App with updated classification and search function
The IRAC Mode of Action App in IOS and Android has been updated to include the latest changes to the MoA Classification (Ver. 9.3, June 2019). This incorporates some additional MoA Groups including bio-insecticides. The update also includes some additional features such as an active ingredient search and links to the latest IRAC News on the IRAC website.
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Updates to the IRAC MoA Classification – Tetraniliprole and Spiropidion added
Tetraniliprole, a new anthranilic diamide has been added to Group 28 and Spiropidion has been added to Group 23, Tetronic and Tetramic Acid Derivatives. The MoA Classification, the MoA poster with the chemical structures and the Website MoA Classification have been updated with the new information.
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Successful Puerto Rico IRM FAW Training Workshop
Fall armyworm (FAW) (Spodoptera frugiperda) is a serious pest in corn, if uncontrolled; this pest can cause a severe damage of the breeding materials of the seed industry at Puerto Rico. One of the tools to manage FAW is the use of insecticides of different modes of action. However, FAW has a tremendous ability to develop resistance. Therefore, monitoring the susceptibility or resistance of FAW to insecticides is critical to establish a successful insecticide resistance management plan (IRM). Monitoring of resistance requires the knowledge of specific methods of insecticide bioassays and analysis of data. Consequently, Michigan State University, IRAC International, and Corteva Agriscience in partnership with PRABIA offered a training course in methods of bioassays for FAW.
The training consisted of classroom training and hands-on laboratory and field experience and reviewed concepts associated with insecticide mode of action and resistance to synthetic compounds. A review of the theory and practice of laboratory bioassays methods for detection of insecticide resistance including leaf disc (IRAC Method No. 007) and insecticide incorporated diet (IRAC Method No. 020) was performed by the participants. In addition, evaluation of the larval mortality was performed by the participants of this training. Probit procedure from SAS and/or POLO program were used to analyze mortality data of the laboratory bioassays, and results of the data analysis were discussed.
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IRAC approves the MoA Group 28 classification of Tetraniliprole
The IRAC Executive approved the MoA classification of Tetraniliprole as a new anthranilic diamide in Group 28 (Ryanodine receptor modulator). The IRAC MoA Classification Scheme will be updated accordingly.
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IRAC International’s 53rd Meeting, Orlando Florida, March 2019
The 2019 IRAC International Spring meeting was held at the Double Tree Suites by Hilton at Disney Springs, Orlando, March 26-28th. There were 12 sessions organised over the 3-days which were well attended by the 27 meeting participants. Day-1 was spent reviewing the work of the various international working groups and country teams during the previous year with Day 2 & 3 spent planning the work for the following year. The meeting finished with an IRAC Executive session where there was voting for the new elected officers, budget matters were discussed as well as a number of ongoing initiatives and projects.
The IRAC Chairman for the next 2-years is Nick Storer (Corteva), the Deputy Chairman is Juergen Langewald (BASF) and the Treasurer is Lixin Mao (BASF).
IRAC 53rd International Meeting Participants
Russell Slater handing over the IRAC Chair to Nick Storer
Ralf Nauen with Russell Slater
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Computer models applied to IRM – IRAC explains
In a situation in which running real-world experiments is impractical (or even impossible), computer simulations offer a powerful solution to understand complex problems. This is exactly the case of resistance-evolution prediction: Although fast from an evolutionary perspective, the time and spatial scales involved in this process are simply too large to be dealt with experimentally. The underlying evolutionary processes of resistance development are relatively well known, however. With this knowledge, researchers can build mathematical models to describe and mimic the actual systems. These models can also be calibrated based on real-world cases that have already occurred, improving their precision and accuracy. Read the full paper