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Herbicide Tolerance of Two Cold-Resistant Bermudagrass (Cynodon spp.) Cultivars Determined by Visual Assessment and Vehicle-Mounted Optical Sensing

Published online by Cambridge University Press:  20 January 2017

Gregory E. Bell ,
Dennis L. Martin ,
Roseanne M. Kuzmic ,
Marvin L. Stone  and
John B. Solie
Gregory E. Bell*
Affiliation:
Department of Horticulture and Landscape Architecture
Dennis L. Martin
Affiliation:
Department of Horticulture and Landscape Architecture
Roseanne M. Kuzmic
Affiliation:
Department of Horticulture and Landscape Architecture
Marvin L. Stone
Affiliation:
Department of Biosystems and Ag Engineering, Oklahoma State University, Stillwater, OK, 74078-6027
John B. Solie
Affiliation:
Department of Biosystems and Ag Engineering, Oklahoma State University, Stillwater, OK, 74078-6027
*
Corresponding author's E-mail: [email protected].
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Abstract

This study assessed the tolerance of ‘Midlawn’ (Cynodon dactylon × C. transvaalensis) and ‘OKS 91-11’ (C. dactylon) bermudagrass to commonly used postemergence herbicides and compared visual assessment with vehicle-mounted optical sensing (V-MOS) for evaluating herbicide phytotoxicity. Two postemergence herbicides were applied to mature stands of Midlawn and OKS 91-11 at two and four times label rates, and seven postemergence herbicides were applied at standard and two times label rates. Visual evaluation and spectral assessments were made for turf color 2, 7, 14, and 21 d after treatment (DAT). Triclopyr and triclopyr plus clopyralid at 2× and 4× label rates caused significant damage on OKS 91-11 and Midlawn bermudagrass in both July and September experiments. MSMA at 2× rate and MSMA + metribuzin at 1× and 2× rate caused up to 73% color reductions that disappeared within 21 DAT in both cultivars. During July, 2,4-D plus mecoprop plus dicamba at the 2× rate caused at least 18% injury to Midlawn bermudagrass for 21 d. Metribuzin was safe at the 1× rate but caused significant injury for up to 7 d at the 2× rate. Imazaquin and halosulfuron-methyl each caused significant damage on one rating date. Pronamide caused no change in color regardless of rate or time of application. OKS 91-11 tolerated 2× rates of 2,4-D plus mecoprop plus dicamba better than Midlawn, but cultivar responses to other herbicide treatments were similar. V-MOS was effective for measuring green color reduction on bermudagrass turf. V-MOS and visual evaluation were linearly related (P < 0.01) at a strength of r = 0.58. Statistical results obtained using visual rating and V-MOS were the same in 86% of all cases.

Keywords

2,4-Dbentazondicambahalosulfuron-methylimazaquinmecopropmetribuzinMSMAprodiaminepronamidetriclopyrcommon bermudagrass, Cynodon dactylon (L.) Pers. OKS 91-11hybrid bermudagrass, Cynodon dactylon (L.) Pers. × C. transvaalensis Burtt-Davy, MidlawnNDVI, phytotoxicity, postemergence herbicide, spectral acquisition, turfgrass injury, turfgrass quality, variable-rate technologyCA, commercially availableDAT, days after treatmentNDVI, normalized difference vegetative indexNIR, near infraredOSU, Oklahoma State UniversityR, redV-MOS, vehicle-mounted optical sensing
Type
Research Article
Information
Weed Technology , Volume 14 , Issue 3 , September 2000 , pp. 635 - 641
Copyright
Copyright © Weed Science Society of America 

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References

Literature Cited

Anonymous. 1995. National Bermudagrass Test—1992. National Turfgrass Evaluation Program. Beltsville, MD: United States Department of Agriculture NTEP 96-4.Google Scholar
Beck, J. and Vyse, T. 1994. Structure and method for differentiating one object from another object. U.S. patent No. 5,296,702.Google Scholar
Blackmer, T. M., Schepers, J. S., and Varvel, G. E. 1994. Light reflectance compared with other nitrogen stress measurements in corn leaves. Agron. J. 86: 934–938.CrossRefGoogle Scholar
Bryson, C. T. and Wills, G. D. 1985. Susceptibility of bermudagrass (Cynodon dactylon) biotypes to several herbicides. Weed Sci. 33: 848–852.Google Scholar
Chandler, J. M. 1982. Susceptibility of nine bermudagrass biotypes to postemergence herbicides. Proc. South. Weed Sci. Soc. 35:93.Google Scholar
Duncan, J., Stow, D., Franklin, J., and Hope, A. 1993. Assessing the relationship between spectral vegetation indices and shrub cover in the Jornada Basin, New Mexico. Int. J. Remote Sens. 14: 3395–3416.Google Scholar
Howell, B. M. 1999. The Effectiveness of Sensor Based Technology to Determine Nitrogen Deficiencies in Turfgrasses. . Oklahoma State University, Stillwater, OK.Google Scholar
Johnson, B. J. 1983. Response of four bermudagrass (Cynodon dactylon) cultivars to fall-applied herbicides. Weed Sci. 31: 771–774.Google Scholar
Johnson, B. J. 1995. Tolerance of four seeded common bermudagrass (Cynodon dactylon) types to herbicides. Weed Technol. 9: 794–800.Google Scholar
Kleman, J. and Fagerlund, E. 1987. Influence of different nitrogen and irrigation treatments on the spectral reflectance of barley. Remote Sens. Environ. 21: 1–14.CrossRefGoogle Scholar
McCarty, L. B., Miller, L. C., and Colvin, D. L. 1991. Bermudagrass (Cynodon spp.) cultivar response to diclofop, MSMA, and metribuzin. Weed Technol. 5: 27–32.Google Scholar
Murdoch, C. L., Nishimoto, R. K., and Hensley, K. L. 1997. Henry's crabgrass control and phytotoxicity to bermudagrass turf of four organic arsenical herbicides. J. Turfgrass Manage. 2 (2): 37–41.Google Scholar
Perry, C. R. Jr. and Lautenschlager, L. F. 1984. Functional equivalence of spectral vegetation indices. Remote Sens. Environ. 14: 169–182.CrossRefGoogle Scholar
Rochecouste, E. 1962. Studies on the biotypes of Cynodon dactylon L. Pers. II. Growth response to trichloroacetic and 2,2-dichloropropionic acids. Weed Res. 2: 136–145.CrossRefGoogle Scholar
Stone, M. L., Solie, J. B., Raun, W. R., Whitney, R. W., Taylor, S. L., and Ringer, J. D. 1996. Use of spectral radiance for correcting in-season fertilizer nitrogen deficiencies in winter wheat. Trans. Am. Soc. Agric. Eng. 39: 1623–1631.Google Scholar
Trenholm, L. E., Carrow, R. N., and Duncan, R. R. 1999. Relationship of mutispectral radiometry data to qualitative data in turfgrass research. Crop Sci. 39: 763–769.Google Scholar
Walburg, G., Bauer, M. E., Daughtry, C.S.T., and Housley, T. L. 1982. Effects of nitrogen nutrition on the growth, yield, and reflectance characteristics of corn canopies. Agron. J. 74: 677–683.Google Scholar
Wanjura, D. F. and Hatfield, J. L. 1987. Sensitivity of spectral vegetative indices to crop biomass. Trans. Am. Soc. Agric. Eng. 30: 810–816.CrossRefGoogle Scholar