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Tolerance of Six Zoysiagrass Cultivars to Aminocyclopyrachlor

Published online by Cambridge University Press:  20 January 2017

Michael L. Flessner*
Affiliation:
Department of Agronomy and Soils, Auburn University, Auburn, AL 36849
James D. McCurdy
Affiliation:
Department of Agronomy and Soils, Auburn University, Auburn, AL 36849
J. Scott McElroy
Affiliation:
Department of Agronomy and Soils, Auburn University, Auburn, AL 36849
*
Corresponding author's E-mail: [email protected]

Abstract

Aminocyclopyrachlor (AMCP) is labeled for use on zoysiagrass, but some injury has been observed. Differential zoysiagrass cultivar response to herbicide treatment has been previously reported. This greenhouse study evaluated the response of ‘BK-7’, ‘Cavalier’, ‘Emerald’, ‘Empire’, ‘Meyer’, and ‘Zorro’ zoysiagrass to 0, 0.005, 0.02, 0.11, 0.52, and 2.4, 11 kg ai ha−1, AMCP. Visual estimation of percent necrosis and normalized difference vegetative index (NDVI) analysis were conducted. Based on rating dates and data types three tolerance groups were established: Cavalier, Meyer, and Zorro are the most tolerant; Emerald and Empire are intermediate; and BK-7 is the least tolerant to AMCP. All zoysiagrass cultivars had sufficient tolerance at the labeled rate. Visual and NDVI analyses were highly correlated; however, NDVI data were subject to greater standard error and pseudo R2 values.

El aminocyclopyrachlor (AMCP) se recomienda para usar en zoysia, aunque se ha observado cierto daño. En el pasado se han reportado diferentes respuestas de los cultivares de zoysia a los tratamientos del herbicida. Este estudio en invernadero evaluó la respuesta de los cultivares de este césped ‘BK-7’, ‘Cavalier’, ‘Emerald’, ‘Empire’, ‘Meyer’ y ‘Zorro’ a 0, 0.005, 0.02, 0.11, 0.52, 2.4 y 11 kg ia ha−1 de AMCP. Se analizó la estimación visual del porcentaje de necrosis y el índice normalizado de la diferencia vegetativa (NDVI). Basado en las fechas de evaluación y los tipos de datos, se establecieron tres tipos de tolerancia: Cavalier, Meyer y Zorro fueron los más tolerantes; Emerald y Empire exhibieron tolerancia intermedia y BK-7 fue el menos tolerante al AMCP. Todos los cultivares de zoysia tuvieron suficiente tolerancia a la dosis recomendada. Los análisis visuales y de NDVI fueron altamente correlacionados. Sin embargo, la información NDVI fue sujeta a mayores errores estándar y seudo valores R2.

Type
Weed Management—Other Crops/Areas
Copyright
Copyright © Weed Science Society of America 

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References

Literature Cited

Anonymous, . 2010. Imprelis™ herbicide product label. E. I. du Pont de Nemours Publication No. H-65717. Wilmington, DE E. I. du Pont de Nemours. 9 p.Google Scholar
Belcher, J. L. and Walker, R. H. 2010. Cogongrass response to aminocyclopyrachlor. Proc. South Weed Sci. Soc. 63:78.Google Scholar
Bell, G. E., Martin, D. L., Kuzmic, R. M., Stone, M. L., and Solie, J. B. 2000. Herbicide tolerance of two cold-resistant bermudagrass (Cynodon spp.) cultivars determined by visual assessment and vehicle-mounted optical sensing. Weed Technol. 14:635641.Google Scholar
Bell, G. E., Martin, D. L., Wiese, S. G., Dobson, D. D., Smith, M. W., Stone, M. W., and Solie, J. B. 2002. Vehicle-mounted optical sensing: an objective means for evaluating turf quality. Crop Sci. 42:197201.Google Scholar
Brecke, B. J., Unruh, J. B., and Partridge-Telenko, D. E. 2010. Aminocyclopyrachlor for weed management in warm-season turfgrass. Proc. South Weed Sci. Soc. 63:193.Google Scholar
Bunnell, B. T., Baker, R. D., McCarty, L. B., Hall, D. W., and Colvin, D. L. 2003. Differential response of five bahiagrass (Paspalum notatum) cultivars to metsulfuron. Weed Technol. 17:550553.Google Scholar
Carter, G. A. 1993. Responses of leaf spectral reflectance to plant stress. Am. J. Bot. 80:239243.Google Scholar
Chism, W. J., Birch, J. B., and Bingham, S. W. 1992. Nonlinear regressions for analyzing growth stage and quinclorac interactions. Weed Technol. 6:898903.Google Scholar
Claus, J. S., Turner, R. G., Meredith, J. H., Williams, C. S., and Holliday, M. J. 2010. Aminocyclopyrachlor development and registration update. Proc. South Weed Sci. Soc. 63:178.Google Scholar
Draper, N. R. and Smith, H. 1968. Applied Regression Analysis. New York John Wiley & Sons. Pp. 1726.Google Scholar
Enloe, S. F., Ducar, J. T., and Dorough, H. D. 2010. Weed control with aminocyclopyrachlor in Alabama pastures. Proc. South Weed Sci. Soc. 63:162.Google Scholar
Fenstermaker-Shaulis, L. K., Leskys, A., and Devitt, D. A. 1997. Utilization of remotely sensed data to map and evaluate turfgrass stress associated with drought. J. Turfgrass Manage. 2:6580.Google Scholar
Flessner, M. L., McElroy, J. S., and Wehtje, G. R. 2011. Quantification of warm-season turfgrass injury form triclopyr and aminocyclopyrachlor. Weed Technol 53:367373.Google Scholar
Gamon, J. A., Field, C. B., Goulden, M. L., Griffin, K. L., Hartley, A. E., Joel, G., Penuelas, J., and Valentini, R. 1995. Relationship between NDVI, canopy structure, and photosynthesis in three California vegetation types. Ecol. Appl. 5:2841.Google Scholar
Gannon, T. W., Yelverton, F. H., Warren, L. S., and Silcox, C. A. 2009. Broadleaf weed control with aminocyclopyrachlor (DPX-KJM44) in fine turf. Proc. South Weed Sci. Soc. 62:394.Google Scholar
Green, D. E., Burpee, L. L., and Stevenson, K. L. 1998. Canopy reflectance as a measure of disease in tall fescue. Crop Sci. 38:16031613.Google Scholar
Guertal, E. A. and Shaw, J. N. 2004. Multispectral radiometer signatures for stress evaluation in compacted bermudagrass turf. HortScience 39:403407.Google Scholar
Hassan, G., Mueller-Warrant, G., and Griffith, S. 2002. Differential sensitivity of Italian ryegrass (Lolium multiflorum) cultivars to fenoxaprop. Weed Sci. 50:567575.Google Scholar
Hoyle, J. A. 2009. Effect of Mowing Height in Turfgrass Systems on Pest Incidence. . Raleigh, NC North Carolina State University. 87 p.Google Scholar
Jiang, Y. and Carrow, R. N. 2007. Broadband spectral reflectance models of turfgrass species and cultivars to drought stress. Crop Sci. 47:16111618.Google Scholar
Johnsen, A. R., Horgan, B. P., Hulke, B. S., and Cline, V. 2009. Evaluation of remote sensing to measure plant stress in creeping bentgrass (Agrostis stolonifera L.) fairways. Crop. Sci. 49:22612274.Google Scholar
Johnson, B. J. 1976. Bermudagrass tolerance to consecutive butralin and oxadiazon treatments. Weed Sci. 24:302305.Google Scholar
Johnson, B. J. 1978. Response of zoysia (Zoysia spp.) and bermudagrass (Cynodon dactylon) cultivars to herbicide treatments. Weed Sci. 26:493497.Google Scholar
Johnson, B. J. 1995. Tolerance of four seeded common bermudagrass (Cynodon dactylon) types to herbicides. Weed Technol. 9:794800.Google Scholar
Johnson, B. J. and Carrow, R. N. 1999. Tolerance of zoysiagrass (Zoysia spp.) cultivars to preemergence herbicides. Weed Technol. 13:706712.Google Scholar
Karcher, D. E. and Richardson, M. D. 2003. Quantifying turfgrass color using digital image analysis. Crop. Sci. 43:943951.Google Scholar
Knipling, E. B. 1970. Physical and physiological bases for the reflectance of visible and near-infrared radiation from vegetation. Remote Sens. Environ. 1:155159.Google Scholar
Lewis, D. F., Gannon, T. W., Yelverton, F. H., Richardson, R. J., and Jeffries, M. D. 2010. Effects of ambient moisture on aminocyclopyrachlor efficacy. Proc. South Weed Sci. Soc. 63:221.Google Scholar
McCalla, J. H., Richardson, M. D., Karcher, D. E., and Boyd, J. W. 2004. Tolerance of seedling bermudagrass to postemergence herbicides. Crop Sci. 44:13301336.Google Scholar
McCarty, L. B. 2005. Best Golf Course Management Practices. 2nd ed. Upper Saddle River, NJ Pearson Prentice Hall. Pp. 358.Google Scholar
McElroy, J. S., Breeden, G. K., Yelverton, F. H., Gannon, T. W., Askew, S. D., and Derr, J. F. 2005. Response of four improved seeded bermudagrass cultivars to postemergence herbicides during seeded establishment. Weed Technol. 19:979985.Google Scholar
Patton, A. J., Hardebeck, G. A., Williams, D. W., and Reicher, Z. J. 2004. Establishment of bermudagrass and zoysiagrass by seed. Crop Sci. 44:21602167.Google Scholar
Richardson, M. D., Karcher, D. E., and Purcell, L. C. 2001. Quantifying turfgrass cover using digital image analysis. Crop Sci. 41:18841888.Google Scholar
Ritz, C., Cedergreen, N., Jensen, J. E., and Streibig, J. C. 2006. Relative potency of nonsimilar-dose-response curves. Weed Sci. 54:407412.Google Scholar
Seefeldt, S. S., Jensen, J. E., and Fuerst, E. P. 1995. Log-logistic analysis of herbicide dose-response relationships. Weed Technol. 9:218227.Google Scholar
Sterling, T. C. and Hall, J. C. 1997. Mechanism of action of natural auxins and the auxinic herbicides. Pages 111141 in Roe, R. M., Burton, J. D., and Kuhr, R. J., eds. Herbicide Activity: Toxicology, Biochemistry, and Molecular Biology. Netherlands IOS Press.Google Scholar
Streibig, J. C. 1988. Herbicide bioassay. Weed Res. 28:479484.Google Scholar
Trenholm, L. E., Carrow, R. N., and Duncan, R. R. 1999. Relationship of multispectral radiometry data to qualitative data in turfgrass research. Crop Sci. 39:763769.Google Scholar
Trenholm, L. E., Schlossberg, M. J., Lee, G., and Parks, W. 2000. An evaluation of multi-spectral responses on selected turfgrass species. Int. J. Remote Sens. 21:709721.Google Scholar
Turgeon, A. J., Beard, J. D., Martin, D. P., and Meggitt, W. F. 1974. Effects of successive applications of preemergence herbicides on turf. Weed Sci. 22:349352.Google Scholar
Turner, R. G., Claus, J. S., Hidalgo, E., Holliday, M. J., and Armel, G. R. 2009. Technical introduction of the new DuPont vegetation management herbicide aminocyclopyrachlor. Proc. South Weed Sci. Soc. 62:405.Google Scholar
Xiong, X., Bell, G. E., Solie, J. B., Smith, M. W., and Martin, B. 2007. Bermudagrass seasonal responses to nitrogen fertilization and irrigation detected using optical sensing. Crop Sci. 47:16031610.Google Scholar