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Upgrading the RIM Model for Improved Support of Integrated Weed Management Extension Efforts in Cropping Systems

Published online by Cambridge University Press:  20 January 2017

Myrtille Lacoste*
Affiliation:
Australian Herbicide Resistance Initiative (AHRI), School of Plant Biology, University of Western Australia, Perth WA 6009, Australia
Stephen Powles
Affiliation:
Australian Herbicide Resistance Initiative (AHRI), School of Plant Biology, University of Western Australia, Perth WA 6009, Australia
*
Corresponding author's E-mail: myrtille.lacoste@gmail.com.

Abstract

RIM, or “Ryegrass Integrated Management,” is a user-friendly weed management software that integrates long-term economics. As a model-based decision support system, RIM enables users to easily build 10-year cropping scenarios and evaluate the impacts of management choices on annual rigid ryegrass populations and long-term profitability. Best used in a workshop format to enable learning through interactions, RIM can provide insights for the sustainable management of ryegrass through “what-if” scenarios in regions facing herbicide resistance issues. The upgrade of RIM is presented, with changes justified from an end-user perspective. The implementation of the model in a new, intuitive software format is presented, as well as the revision, update, and documentation of over 40 management options. Enterprises, establishment systems, and control options were redefined to represent current practices, with the notable inclusion of customizable herbicide options and techniques for weed seed control at harvest. Several examples of how RIM can be used with farmers to demonstrate the benefits of adopting recommended practices for managing or delaying the onset of herbicide resistance are presented. Originally designed for the dryland broadacre systems of the Australian southern grainbelt, RIM's underlying modeling was restructured to facilitate future updates and adaptation to other weed species and cropping regions.

RIM (por sus siglas en inglés) o “Manejo Integrado de Lolium rigidum” es un programa amigable con el usuario para el manejo de malezas que integra factores económicos en el largo plazo. Como un sistema de apoyo para la toma de decisiones basado en un modelo, RIM permite a los usuarios construir escenarios de producción de cultivos de 10 años de duración y evaluar el impacto de las decisiones de manejo en las poblaciones de L. rigidum y en la rentabilidad a largo plazo. Al usarse en un formato de taller que facilite el aprendizaje mediante interacciones, RIM puede brindar una visión para el manejo sostenible de L. rigidum a través de escenarios “y qué pasa si” en regiones con problemas de resistencia a herbicidas. Aquí se presenta una actualización de RIM con cambios justificados desde una perspectiva del usuario final. Se presenta la implementación del modelo en un formato nuevo e intuitivo, además de la revisión, actualización y documentación de 40 opciones de manejo. Proyectos productivos, sistemas de establecimiento, y las opciones de control fueron redefinidas para representar prácticas actuales, con la notable inclusión de opciones de herbicidas personalizables para el control de semillas de malezas durante la cosecha. Adicionalmente, se presentan varios ejemplos de cómo se puede usar RIM con los productores para demostrar los beneficios de la adopción de prácticas recomendadas para el manejo o el atraso en la aparición de resistencia a herbicidas. Aunque originalmente se diseñó para sistemas de producción extensiva sin riego de la zona productora de granos del sur de Australia, el modelaje en el que se basa RIM fue estructurado para facilitar actualizaciones futuras y la adaptación a otras especies de malezas y otras regiones agrícolas.

Type
Research Article
Copyright
Copyright © Weed Science Society of America 

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References

Literature Cited

[ABARES] Australian Bureau of Agricultural and Resource Economics and Sciences (2010) Land Use in Australia at a Glance 2006. Australian Collaborative Land Use and Management Program (ACLUMP). 4 pGoogle Scholar
[AHRI] Australian Herbicide Resistance Initiative (2013) RIM: Ryegrass Integrated Management — Australian Herbicide Resistance Initiative, The University of Western Australia. www.ahri.uwa.edu.au/RIM. Accessed March 12, 2014Google Scholar
Bagavathiannan, MV, Norsworthy, JK (2012) Late-season seed production in arable weed communities: management implications. Weed Sci 60:325334 Google Scholar
Bagavathiannan, MV, Norsworthy, JK, Lacoste, M, Powles, SB (2014) PAM: a decision support tool for guiding integrated management of Palmer amaranth in Proceedings of the Weed Science Society of America 2014 Conference, Vancouver. http://wssaabstracts.com/public/22/proceedings.html. Accessed March 12, 2014Google Scholar
Beltran, J, Pannell, D, Doole, G (2012b) Economic implications of herbicide resistance and high labour costs for management of annual barnyardgrass (Echinochloa crus-galli) in Philippine rice farming systems. Crop Prot 31:3139 Google Scholar
Beltran, J, Pannell, D, Doole, G, White, B (2012a) A bioeconomic model for analysis of integrated weed management strategies for annual barnyardgrass (Echinochloa crus-galli complex) in Philippine rice farming systems. Agric Sys 112:110 Google Scholar
Borger, CPD, Michael, PJ, Mandel, R, Hashem, A, Bowran, D, Renton, M (2012) Linking field and farmer surveys to determine the most important changes to weed incidence. Weed Res 52:564574 Google Scholar
Boutsalis, P, Gill, GS, Preston, C (2012) Incidence of herbicide resistance in rigid ryegrass (Lolium rigidum ) across south-eastern Australia. Weed Technol 26:391398 Google Scholar
Broster, JC, Koetz, EA, Wu, H (2011) Herbicide resistance levels in annual ryegrass (Lolium rigidum Gaud.) in Southern New South Wales. Plant Prot Q 26:2228 Google Scholar
Broster, JC, Koetz, EA, Wu, H (2013) Herbicide resistance levels in annual ryegrass (Lolium rigidum Gaud.) and wild oat (Avena spp.) in southwestern New South Wales. Plant Prot Q 28:(4)126132 Google Scholar
Doole, GJ (2008) Increased cropping activity and herbicide resistance: the case of rigid ryegrass in Western Australian dryland agriculture. Pages 140 in Berklian, YU, ed. Crop Rotation: Economics, Impact, and Management. Hauppauge, NY: Nova Science Publishers Google Scholar
Doole, GJ, Revell, CK (2010) Delayed pasture germination allows improved rigid ryegrass (Lolium rigidum) control through grazing and broad-spectrum herbicide application. Crop Prot 29:153162 Google Scholar
Draper, AD, Roy, B (2002) Ryegrass RIM model stands the test of IWM field trial data. Pages 4950 in Proceedings of AgriBusiness Crop Updates 2002. Perth, Department of Agriculture and Food Western Australia Google Scholar
Goggin, DE, Powles, SB, Steadman, KJ (2012) Understanding Lolium rigidum seeds: the key to managing a problem weed? Agronomy 2:222239 Google Scholar
Heap, I (2013) The International Survey of Herbicide Resistant Weeds. www.weedscience.org. Accessed October 10, 2013Google Scholar
Holst, N, Rasmussen, IA, Bastiaans, L (2007) Field weed population dynamics: a review of model approaches and applications. Weed Res 47:114 Google Scholar
Jones, RE, Vere, DT, Alemseged, Y, Medd, RW (2005) Estimating the economic cost of weeds in Australian annual winter crops. Agric Econ 32:253265 Google Scholar
Lacoste, M (2012) Insights into agriculture, weed control and herbicide resistance: presentation and RIM sessions guide. Pages 2744 in Russell, D, ed. Science Taking You Places 4: a resource for science teachers. Burnie, Australia: PICSE (Primary Industry Centre for Science Education) and GRDC (Grains Research & Development Corporation),Google Scholar
Lacoste, M (2013) RIM, Ryegrass Integrated Management - User guide. Australian Herbicide Resistance Initiative, The University of Western Australia, Perth. 9 pp. www.ahri.uwa.edu.au/RIM. Accessed March 12, 2014Google Scholar
Lacoste, M (2014) RIM 2013: default settings. Australian Herbicide Resistance Initiative & School of Agricultural and Resource Economics, The University of Western Australia, Perth Google Scholar
Lacoste, M, Llewellyn, R, Powles, SB, Pannell, DJ (2013) RIM 2004 workshops: evaluation – Farmers and consultants surveys. Australian Herbicide Resistance Initiative & School of Agricultural and Resource Economics, The University of Western Australia, Perth. www.ahri.uwa.edu.au/Research/RIM/RIM-Publications. Accessed March 12, 2014Google Scholar
Lawes, R, Renton, M (2010) The Land Use Sequence Optimiser (LUSO): a theoretical framework for analysing crop sequences in response to nitrogen, disease and weed populations. Crop Past Sci 61:835843 Google Scholar
Llewellyn, RS, D'Emden, FH, Kuehnea, G (2012) Extensive use of no-tillage in grain growing regions of Australia. Field Crop Res 132:204212 Google Scholar
Llewellyn, RS, Pannell, DJ (2009) Managing the herbicide resource: an evaluation of extension on management of herbicide-resistant weeds. AgBioForum 12:358369 Google Scholar
Llewellyn, RS, Pannell, DJ, Lindner, RK, Powles, SB (2005) Targeting key perceptions when planning and evaluating extension. Aust J Exp Agric 45:16271633 Google Scholar
Manalil, S, Busi, R, Renton, M, Powles, SB (2011) Rapid evolution of herbicide resistance by low herbicide dosages. Weed Sci 59:210217 Google Scholar
McCown, RL, Carberry, PS, Hochman, Z, Dalgliesh, NP, Foale, MA (2009) Reinventing model-based decision support with Australian dryland farmers. 1. Changing intervention concepts during 17 years of action research. Crop Pasture Sci 60:10171030 Google Scholar
McNee, ME (2013) Out of season cover crops - Seasonal and cumulative impacts on wheat yields and the cropping environment. Ph.D dissertation., Orange, Australia: Charles Sturt University. 249 pGoogle Scholar
Minkey, D, McNee, ME, Celenza, L, Robertson, M, Fletcher, A, Albrecht, A, Sharma, D, Diggle, A, Weeks, C, Airey, M (2013) Identification of priority RD&E areas for the practice of dry seeding into residues in the W.A. Wheat-Belt. Report for the Grains Research Development Corporation by WANTFA, CSIRO, DAFWA, Planfarm and UWA, 93 pGoogle Scholar
Monjardino, M, Pannell, DJ, Powles, SB (2003) Multispecies resistance and integrated management: a bioeconomic model for integrated management of rigid ryegrass (Lolium rigidum) and wild radish (Raphanus raphanistrum). Weed Sci 51:798809 Google Scholar
Monjardino, M, Pannell, DJ, Powles, SB (2004a) The economic value of pasture phases in the integrated management of annual ryegrass and wild radish in a Western Australian farming system. Aust J Exp Agric 44:265271 Google Scholar
Monjardino, M, Pannell, DJ, Powles, SB (2004b) The economic value of haying and green manuring in the integrated management of annual ryegrass and wild radish in a Western Australian farming system. Aust J Exp Agric 44:11951203 Google Scholar
Monjardino, M, Pannell, DJ, Powles, SB (2005) The economic value of glyphosate-resistant canola in the management of two widespread crop weeds in a Western Australian farming system. Agric Sys 84:297315 Google Scholar
Neve, P (2008) Simulation moldelling to understand the evolution and management of glyphosate resistance in weeds. Pest Manag Sci 64:392401 Google Scholar
Norsworthy, JK, Ward, SM, Shaw, DR, Llewellyn, RS, Nichols, RL, Webster, TM, Bradley, KW, Frisvold, G, Powles, SB, Burgos, NR, Witt, WW, Barrett, M (2012) Reducing the risks of herbicide resistance: best management practices and recommendations. Weed Sci 60(Special Issue):3162 Google Scholar
Owen, MJ, Martinez, NJ, Powles, SB (2014) Multiple herbicide-resistant Lolium rigidum (annual ryegrass) now dominates across the Western Australian grain belt. Weed Res 54(3): 314324 Google Scholar
Pannell, DJ, Stewart, V, Bennett, A, Monjardino, M, Schmidt, C, Powles, SB (2004) RIM: a bioeconomic model for integrated weed management of Lolium rigidum in Western Australia. Agric Sys 79:305325 Google Scholar
Pluske, JM, Pannell, DJ, Bennett, AL (2004) RIM 2004 Reference Manual. A decision tool for integrated management of herbicide-resistant annual ryegrass. Crawley: School of Agricultural and Resource Economics, University of Western Australia. 46 pGoogle Scholar
Renton, M (2011) How much detail and accuracy is required in plant growth submodels to address questions about optimal management strategies in agricultural systems? AoB Plants. www.ncbi.nlm.nih.gov/pmc/articles/PMC3072767. Accessed July 20, 2013Google Scholar
Renton, M, Diggle, A, Manalil, S, Powles, S (2011) Does cutting herbicide rates threaten the sustainability of weed management in cropping systems? J Theor Biol 283:1427 Google Scholar
Renton, M, Peltzer, S, Diggle, AJ (2008) Understanding, predicting and managing weed seedbanks in agricultural systems with the Weed Seed Wizard. Pages 7779 in Proceedings of the 16th Australian Weeds Conference, Cairns. www.caws.org.au/awc/2008/awc200810771.pdf Accessed July 20, 2013Google Scholar
Seymour, M, Kirkegaard, JA, Peoples, MB, White, PF, French, RJ (2012) Break-crop benefits to wheat in Western Australia – insights from over three decades of research. Crop Pasture Sci 63:116 Google Scholar
Steadman, KJ, Easton, DM, Plummer, JA, Ferris, DG, Powles, SB (2006) Late-season non-selective herbicide application reduces Lolium rigidum seed numbers, seed viability, and seedling fitness. Aust J Exp Agric 57:133141 Google Scholar
Torra, J, Cirujed, AA, Recasens, J, Taberner, A, Powles, SB (2010) PIM (Poppy Integrated Management): a bio-economic decision support model for the management of Papaver rhoeas in rain-fed cropping systems. Weed Res 50:127139 Google Scholar
Walkenback, J (2010) Excel® 2010 Power Programming with VBA. Hoboken: Wiley Publishing, Inc. 1052 ppGoogle Scholar
Walsh, M, Harrington, R, Powles, S (2012) Harrington Seed Destructor: a new non-chemical weed control tool for global grain crops. Crop Sci 52:13431347 Google Scholar
Walsh, M, Newman, P, Powles, S (2013) Targeting weed seeds in-crop: a new weed control paradigm for global agriculture. Weed Technol 27:431436 Google Scholar
Walsh, M, Powles, SB (2014) Management of herbicide resistance in wheat cropping systems: learning from the Australian experience. Pest Manag Sci. (DOI: )Google Scholar