Literature DB >> 32893405

Syngenta's contribution to herbicide resistance research and management.

Shiv Shankhar Kaundun1.   

Abstract

The evolution of weed resistance to herbicides is an ever-increasing problem that affects crop yield and food production. In Syngenta, we believe that this difficult and complex issue can be most efficiently addressed through a deep understanding of the evolutionary dynamics and mechanism of resistance. A profound knowledge of resistance is key to developing the next generation of resistance-breaking compounds with existing or novel herbicide sites of action. We use a multidisciplinary laboratory-based, glasshouse and field biology approach to study herbicide resistance and provide strong science-based solutions to delay the onset and manage resistance. We have developed and implemented simple early-season resistance detection methods to allow farmers make an informed decision for effective weed control. We have built mechanistic, individual-based computer models to design profitable, long-term sustainable weed management programs. Our zero tolerance approaches employ herbicides with different sites of action, applied in mixtures and sequences, to minimise the risk of resistance evolution. Weeds are targeted at the right growth stage with optimal herbicide formulation and spray technology for maximising weed control and depleting the seed bank. We are promoting the use of competitive crop varieties and other nonchemical methods for an integrated weed management strategy. We have a global web of external collaborations for studying and managing herbicide resistance. We are committed to farmers' education and training on herbicide resistance, and regularly share our methods and findings via conferences and peer-reviewed scientific publications for the benefit of the wider weed science community and field practitioners.
© 2020 Society of Chemical Industry. © 2020 Society of Chemical Industry.

Entities:  

Keywords:  Syngenta; detection methods; herbicide resistance research; integrated weed management; simulation modelling

Mesh:

Substances:

Year:  2020        PMID: 32893405      PMCID: PMC7984027          DOI: 10.1002/ps.6072

Source DB:  PubMed          Journal:  Pest Manag Sci        ISSN: 1526-498X            Impact factor:   4.845


  43 in total

1.  Measuring Rates of Herbicide Metabolism in Dicot Weeds with an Excised Leaf Assay.

Authors:  Rong Ma; Joshua J Skelton; Dean E Riechers
Journal:  J Vis Exp       Date:  2015-09-07       Impact factor: 1.355

2.  Genetic control of a cytochrome P450 metabolism-based herbicide resistance mechanism in Lolium rigidum.

Authors:  R Busi; M M Vila-Aiub; S B Powles
Journal:  Heredity (Edinb)       Date:  2010-09-29       Impact factor: 3.821

Review 3.  Mechanisms of evolved herbicide resistance.

Authors:  Todd A Gaines; Stephen O Duke; Sarah Morran; Carlos A G Rigon; Patrick J Tranel; Anita Küpper; Franck E Dayan
Journal:  J Biol Chem       Date:  2020-05-19       Impact factor: 5.157

4.  Resistance to herbicides caused by single amino acid mutations in acetyl-CoA carboxylase in resistant populations of grassy weeds.

Authors:  SoRi Jang; Jasmina Marjanovic; Piotr Gornicki
Journal:  New Phytol       Date:  2013-01-10       Impact factor: 10.151

Review 5.  Overview of glyphosate-resistant weeds worldwide.

Authors:  Ian Heap; Stephen O Duke
Journal:  Pest Manag Sci       Date:  2017-11-29       Impact factor: 4.845

6.  Mechanism of resistance to mesotrione in an Amaranthus tuberculatus population from Nebraska, USA.

Authors:  Shiv S Kaundun; Sarah-Jane Hutchings; Richard P Dale; Anushka Howell; James A Morris; Vance C Kramer; Vinod K Shivrain; Eddie Mcindoe
Journal:  PLoS One       Date:  2017-06-29       Impact factor: 3.240

7.  A Novel Single-Site Mutation in the Catalytic Domain of Protoporphyrinogen Oxidase IX (PPO) Confers Resistance to PPO-Inhibiting Herbicides.

Authors:  Gulab Rangani; Reiofeli A Salas-Perez; Raphael A Aponte; Michael Knapp; Ian R Craig; Thomas Mietzner; Ana Claudia Langaro; Matheus M Noguera; Aimone Porri; Nilda Roma-Burgos
Journal:  Front Plant Sci       Date:  2019-05-15       Impact factor: 5.753

8.  An individual-based model of seed- and rhizome-propagated perennial plant species and sustainable management of Sorghum halepense in soybean production systems in Argentina.

Authors:  Chun Liu; Julio A Scursoni; Raúl Moreno; Ian A Zelaya; María Sol Muñoz; Shiv S Kaundun
Journal:  Ecol Evol       Date:  2019-08-19       Impact factor: 2.912

9.  Derived Polymorphic Amplified Cleaved Sequence (dPACS): A Novel PCR-RFLP Procedure for Detecting Known Single Nucleotide and Deletion-Insertion Polymorphisms.

Authors:  Shiv Shankhar Kaundun; Elisabetta Marchegiani; Sarah-Jane Hutchings; Ken Baker
Journal:  Int J Mol Sci       Date:  2019-06-29       Impact factor: 5.923

10.  Multiple modes of convergent adaptation in the spread of glyphosate-resistant Amaranthus tuberculatus.

Authors:  Julia M Kreiner; Darci Ann Giacomini; Felix Bemm; Bridgit Waithaka; Julian Regalado; Christa Lanz; Julia Hildebrandt; Peter H Sikkema; Patrick J Tranel; Detlef Weigel; John R Stinchcombe; Stephen I Wright
Journal:  Proc Natl Acad Sci U S A       Date:  2019-09-30       Impact factor: 11.205

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  3 in total

1.  Resistance to a nonselective 4-hydroxyphenylpyruvate dioxygenase-inhibiting herbicide via novel reduction-dehydration-glutathione conjugation in Amaranthus tuberculatus.

Authors:  Jeanaflor Crystal T Concepcion; Shiv S Kaundun; James A Morris; Sarah-Jane Hutchings; Seth A Strom; Anatoli V Lygin; Dean E Riechers
Journal:  New Phytol       Date:  2021-09-29       Impact factor: 10.323

2.  Metabolic Pathways for S-Metolachlor Detoxification Differ Between Tolerant Corn and Multiple-Resistant Waterhemp.

Authors:  Seth A Strom; Aaron G Hager; Jeanaflor Crystal T Concepcion; Nicholas J Seiter; Adam S Davis; James A Morris; Shiv S Kaundun; Dean E Riechers
Journal:  Plant Cell Physiol       Date:  2021-12-10       Impact factor: 4.927

3.  Genome-Wide Evolutionary Analysis of Putative Non-Specific Herbicide Resistance Genes and Compilation of Core Promoters between Monocots and Dicots.

Authors:  Saket Chandra; Ramon G Leon
Journal:  Genes (Basel)       Date:  2022-06-29       Impact factor: 4.141

  3 in total

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