Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-27T09:46:14.811Z Has data issue: false hasContentIssue false
  • English
  • Français

Temperature-dependent Model for Non-dormant Seed Germination and Rhizome Bud Break of Johnsongrass (Sorghum halepense)

Published online by Cambridge University Press:  12 June 2017

David L. Holshouser ,
James M. Chandler  and
Hsin-I Wu
David L. Holshouser
Affiliation:
Dep. Agron., Northeast Res. & Ext. Ctr., University of Nebraska, Concord, NE 68728
James M. Chandler
Affiliation:
Dep. Soil & Crop Sci., Texas Agric. Exp. Stn., College Station, TX 77843
Hsin-I Wu
Affiliation:
Ctr. for Biosystems Modeling, Dep. Industrial Eng., Texas A&M Univ., College Station, TX 77843
Get access Rights & Permissions [Opens in a new window]

Abstract

Research was conducted to formulate a temperature-dependent population level model for johnsongrass seed germination and rhizome bud break. A nonlinear poikilotherm rate equation was used to describe development rate as a function of temperature, and a temperature-independent Weibull function was used to distribute development times for the population. Seed germination and initiation of rhizome bud break of johnsongrass were collected under constant temperature conditions to parameterize the model. Seed germination rate increased with temperature up to 36 C, then declined at 40 C. Rate of rhizome bud break increased with temperature up to 32 C, then rapidly decreased with further temperature increases. Rate of rhizome bud break was higher than for seed germination at temperatures of 32 C or below, but lower at higher temperatures. Time to first germination or bud break event was longer for seed than for rhizomes, but subsequent progression of development was higher for seed. A population level temperature-dependent model was developed by coupling the poikilotherm equation with the Weibull function. The model was validated against two independent seed germination and three independent rhizome bud germination data sets.

Keywords

Johnsongrass, Sorghum halepense (L.) Pers. ♯ SORHADistributionphenologypoikilothermsimulationtemperatureWeibull functionSORHA
Type
Weed Biology and Ecology
Information
Weed Science , Volume 44 , Issue 2 , June 1996 , pp. 257 - 265
Copyright
Copyright © 1996 by the Weed Science Society of America 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Literature Cited

1. Baxendale, F. P., Teetes, G. L., and Sharpe, P.J.H. 1984. Temperature-dependent model for sorghum midge (Diptera: Cecidomyiidae) spring emergence. Environ. Entomol. 13: 1566–1571.Google Scholar
2. Baxendale, F. P., Teetes, G. L., Sharpe, P.J.H., and Wu, H. 1984. Temperature-dependent model for development of nondiapausing sorghum midges (Diptera: Cecidomyiidae). Environ. Entomol. 13: 1572–1576.Google Scholar
3. Benech Arnold, R. L., Ghersa, C. M., Sanchez, R. A., and Insausti, P. 1990. A mathematical model to predict Sorghum halepense (L.) Pers. seedling emergence in relation to soil temperature. Weed Res. 30: 91–99.Google Scholar
4. Benech Arnold, R. L., Ghersa, C. M., Sanchez, R. A., and Insausti, P. 1990. Temperature effects on dormancy release and germination rate in Sorghum halepense (L.) Pers. seeds: a quantitative analysis. Weed Res. 30: 81–89.Google Scholar
5. Bridges, D. C. 1987. Techniques for modeling phenological development of weed populations. ; Texas A&M University, College Station, Texas.Google Scholar
6. Bridges, D. C. and Chandler, J. M. 1989. A population level temperature-dependent model of seedling johnsongrass (Sorghum halepense) flowering. Weed Sci. 37: 471–477.Google Scholar
7. Bridges, D. C., Wu, H., Sharpe, P.J.H., and Chandler, J. M. 1989. Modeling distributions of crop and weed seed germination time. Weed Sci. 37: 724–729.CrossRefGoogle Scholar
8. Brown, R. F. and Mayer, D. G. 1988. Representing cumulative germination. 2. The use of the Weibull function and other empirically derive curves. Ann. Bot. 61: 127–138.Google Scholar
9. Gagne, J. A., Wagner, T. L., Sharpe, P.J.H., Coulson, R. N., and Fargo, W. S. 1982. Reemergence of Dendroctonus frontalis (Coleoptera: Saolytidae) at constant temperatures. Environ. Entomol. 11: 1216–1222.Google Scholar
10. Garcia Huidobro, J., Monteith, J. L., and Squire, G. R. 1982. Time, temperature, and germination of pearl millet (Pennisetum typhoides S. & H.). I. Constant temperature. J. Exp. Bot. 33: 288–296.Google Scholar
11. Hodges, T. 1991. Predicting Crop Phenology. CRC Press, Boca Raton, Florida, 233 pp.Google Scholar
12. Holm, L. G., Plucknett, D. L., Pancho, J. V., and Herberger, J. P. 1977. Sorghum halepense (L.) Pers. Pages 54–61 in The world's worst weeds—distribution and biology. Univ. Press of Hawaii, Honolulu.Google Scholar
13. Horowitz, M. 1972. Early development of johnsongrass. Weed Sci. 20: 271–273.CrossRefGoogle Scholar
14. Huang, W. Z. and Hsiao, A. I. 1987. Factors affecting seed dormancy and germination of johnsongrass (Sorghum halepense (L.) Pers.). Weed Res. 27: 1–12.Google Scholar
15. Hull, R. J. 1970. Germination control of johnsongrass rhizome buds. Weed Sci. 18: 118–121.Google Scholar
16. Ingle, M. and Rogers, B. J. 1961. The growth of a midwestern strain of Sorghum halepense under controlled conditions. Am. J. Bot. 48: 392–396.Google Scholar
17. Keeley, P. E. and Thullen, R. J. 1979. Influence of planting date on the growth of johnsongrass (Sorghum halepense) from seed. Weed Sci. 27: 554–558.Google Scholar
18. King, C. A. and Oliver, L. R. 1993. Effect of soil water content and temperature on emergence of entireleaf morningglory (Ipomoea hederacea var. hederacea Gray) and large crabgrass [Digitaria sanguinalis (L.) Scop.]. Abst. Weed Sci. Soc. Am. 33: 140.Google Scholar
19. NeSmith, D. S. and Bridges, D. C. 1992. Modeling chilling influence of cumulative flowering: a case study using ‘Tifblue’ rabbiteye blueberry. J. Amer. Soc. Hort. Sci. 117: 698–702.Google Scholar
20. Palmer, W. A., Bay, D. E., and Sharpe, P.J.H. 1981. Influence of temperature on the development and survival of the immature stages of horn fly, Haematoba irritans irritans (L.). Prot. Ecol. 3: 299–309.Google Scholar
21. Satorre, E. H., Ghersa, C. M., and Pataro, A. M. 1985. Prediction of Sorghum halepense (L.) Pers. rhizome sprout emergence in relation to air temperature. Weed Res. 25: 103–109.CrossRefGoogle Scholar
22. Sharpe, P.J.H. and DeMichele, D. W. 1977. Reaction kinetics of poikilotherm development. J. Theo. Biol. 64: 649–670.CrossRefGoogle ScholarPubMed
23. Wagner, T. L., Wu, H., Feldman, R. M., Sharpe, P.J.H., and Coulson, R.N. 1985. Multiple-cohort approach for simulating development of insect populations under variable temperatures. Ann. Entomol. Soc. Am. 78: 691–704.CrossRefGoogle Scholar
24. Wagner, T. L., Wu, H., Sharpe, P.J.H., and Coulson, R. N. 1984. Modeling distributions of insect development time: A literature review and application of the Weibull function. Ann. Entomol. Soc. Am. 77: 475–487.CrossRefGoogle Scholar
25. Wagner, T. L., Wu, H., Sharpe, P.J.H., Schoolfield, R. M., and Coulson, R. N. 1984. Modeling insect development rates: A literature review and application of a biophysical model. Ann. Entomol. Soc. Am. 77: 208–225.CrossRefGoogle Scholar
26. Wang, J. Y. 1960. A critique of the heat unit approach to plant response studies. Ecology 41: 785–790.Google Scholar
27. Warwick, S. I., Thompson, B. K., and Black, L. D. 1983. Population variation in Sorghum halepense, Johnson grass, at the northern limits of its range. Can. J. Bot. 62: 1781–1790.Google Scholar
28. Went, F. W. 1953. The effect of temperature on plant growth. In Ann. Rev. Plant Physiol. 4: 347–361.CrossRefGoogle Scholar