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Modeling germination of smallflower umbrella sedge (Cyperus difformis L.) seeds from rice fields in California across suboptimal temperatures

Published online by Cambridge University Press:  15 July 2019

Rafael M. Pedroso Open the ORCID record for Rafael M. Pedroso [Opens in a new window] ,
Durval Dourado Neto ,
Ricardo Victoria Filho ,
Albert J. Fischer  and
Kassim Al-Khatib
Rafael M. Pedroso*
Affiliation:
Graduate Student, Department of Plant Sciences, University of California, Davis, Davis, CA, USA
Durval Dourado Neto
Affiliation:
Professor, Crop Science Department, University of Sao Paulo (ESALQ/USP), Sao Paulo, Brazil
Ricardo Victoria Filho
Affiliation:
Professor, Crop Science Department, University of Sao Paulo (ESALQ/USP), Sao Paulo, Brazil
Albert J. Fischer
Affiliation:
Professor, Department of Plant Sciences, University of California, Davis, Davis, CA, USA
Kassim Al-Khatib
Affiliation:
Professor, Department of Plant Sciences, University of California, Davis, Davis, CA, USA
*
Author for correspondence: Rafael M. Pedroso, Crop Science Department, 11 Padua Dias Avenue, University of Sao Paulo (ESALQ/USP), Piracicaba, Sao Paulo, Brazil, 13418-900. (Email: rmpedroso@usp.br)
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Abstract

Smallflower umbrella sedge is a prolific C3 weed commonly found in rice fields in 47 countries. The increasing infestation of herbicide-resistant smallflower umbrella sedge populations threatens rice production. Our objectives for this study were to characterize thermal requirements for germination of smallflower umbrella sedge seeds from rice fields in California and to parameterize a population thermal-time model for smallflower umbrella sedge germination. Because the use of modeling techniques is hampered by the lack of thermal-time model parameters for smallflower umbrella sedge seed germination, trials were carried out by placing field-collected seeds in a thermogradient table set at constant temperatures of 11.7 to 41.7 C. Germination was assessed daily for 30 d, and the whole experiment was repeated a month later. Using probit regression analysis, thermal time to median germination [θT(50)], base temperature for germination (Tb), and SD of thermal times for germination [σθT(50)] were estimated from germination data, and model parameters were derived using the Solver tool in Microsoft Excel®. Germination rates increased linearly below the estimated optimum temperatures of 33.5 to 36 C. Estimated Tb averaged 16.7 C, whereas θT(50) equaled 17.1 degree-days and σθT(50) was only 0.1 degree-day. The estimated Tb for smallflower umbrella sedge is remarkably higher than that of japonica and indica types of rice, as well as Tb of important weeds in the Echinochloa complex. Relative to the latter, smallflower umbrella sedge has lower thermal-time requirements to germination and greater germination synchronicity. However, it would also initiate germination much later because of its higher Tb, given low soil temperatures early in the rice growing season in California. When integrated into weed growth models, these results might help optimize the timing and efficacy of smallflower umbrella sedge control measures.

Keywords

Eric Webster, Louisiana State University AgCentersmallflower umbrella sedgeCyperus difformis L.; CYPDIriceOryza sativa L.Thermal-time modelprobit analysisseed germination biologygrowing degree-days
Type
Research Article
Information
Weed Technology , Volume 33 , Issue 5 , October 2019 , pp. 733 - 738
Copyright
© Weed Science Society of America, 2019 

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References

Ali, MG, Naylor, REL, Matthews, S (2006) Distinguishing the effects of genotype and seed physiological age on low temperature tolerance of rice (Oryza sativa L.). Exp Agric 7:337–349CrossRefGoogle Scholar
Baskin, CC, Baskin, JM (2001) Seeds: Ecology, Biogeography, and Evolution of Dormancy and Germination. 2nd edn. Cambridge, MA: Academic PressGoogle Scholar
Bewick, TA, Binning, LK, Yandell, B (1988) A degree-day model for predicting the emergence of swamp dodder in cranberry. J Am Soc Hortic Sci 113:839–841Google Scholar
Boddy, LG, Bradford, KJ, Fischer, AJ (2012) Population-based threshold models describe weed germination and emergence patterns across varying temperature, moisture and oxygen conditions. J Appl Ecol 49:1225–1236CrossRefGoogle Scholar
Bradford, KJ (1990) A water relations analysis of seed-germination rates. Plant Physiol 94:840–849CrossRefGoogle ScholarPubMed
Bradford, KJ (2002) Applications of hydrothermal time to quantifying and modeling seed germination and dormancy. Weed Sci 50:248–260CrossRefGoogle Scholar
Chauhan, BS, Johnson, DE (2009) Ecological studies on Cyperus difformis, Cyperus iria and Fimbristylis miliacea: three troublesome annual sedge weeds of rice. Ann Appl Biol 155:103–112CrossRefGoogle Scholar
Derakhshan, A, Gherekhloo, J (2013) Factors affecting Cyperus difformis seed germination and seedling emergence. Planta Daninha 31:823–832CrossRefGoogle Scholar
Dyer, WE, Chee, PW, Fay, PK (1993) Rapid germination of sulfonylurea resistant Kochia scoparia L. accessions is associated with elevated seed levels of branched-chain amino-acids. Weed Sci 41:18–22CrossRefGoogle Scholar
Eberlein, CV, Guttieri, MJ, Berger, PH, Fellman, JK, Mallory-Smith, CA, Thill, DC, Baerg, RJ, Belknap, WR (1999) Physiological consequences of mutation for ALS-inhibitor resistance. Weed Sci 47:383–392CrossRefGoogle Scholar
Ellis, RH, Butcher, PD (1988) The effects of priming and natural differences in quality amongst onion seed lots on the response of the rate of germination to temperature and the identification of the characteristics under genotypic control. J Exp Botany 39:35–950CrossRefGoogle Scholar
Forcella, F, Arnold, RLB, Sanchez, R, Ghersa, C (2000) Modeling seedling emergence. Field Crops Res 67:123–139CrossRefGoogle Scholar
Garcia-Huidobro, J, Monteith, JL, Squire, GR (1982) Time, temperature and germination of pearl millet (Pennisetum typhoides).1. Constant temperature. J Exp Bot 33:288–296CrossRefGoogle Scholar
Heap, I (2019) The International Survey of Herbicide Resistant Weeds. http://www.weedscience.org. Accessed: January 5, 2019Google Scholar
Huarte, HR, Benech-Arnold, RL (2010) Hormonal nature of seed responses to fluctuating temperatures in Cynara cardunculus (L.). Seed Sci Res 20:39–45CrossRefGoogle Scholar
Ismail, BS, Mansor, N, Rahman, MM (2007) Factors affecting germination and emergence of Cyperus difformis L. seeds. Malaysian Appl Biol 36:41–45Google Scholar
Kim, JS, Mercado, BL (1987) Viability and emergence of buried seeds of Echinochloa glabrescens, Monochoria vaginalis and Cyperus difformis. Proc 11th Asian Pacific Weed Sci Soc 9:469–476Google Scholar
Lee, MH (2001) Low temperature tolerance in rice: the Korean experience. Pages 109–117 in Fukai, S, Basnayake, J, eds. ACIAR Proceedings 101; Increased Lowland Rice Production in the Mekong Region. Canberra, ACT, Australia: Australian Center for International Agricultural ResearchGoogle Scholar
Mayer, DG, Butler, DG (1993) Statistical validation. Ecol Model 68:21–32.CrossRefGoogle Scholar
Park, K, Mallory-Smith, CA, Ball, DA, Mueller, Warrant, GW (2004) Ecological fitness of acetolactate synthase inhibitor–resistant and–susceptible downy brome (Bromus tectorum) biotypes. Weed Sci 52:768–773CrossRefGoogle Scholar
Pedroso, RM, Al-Khatib, K, Alarcón-Reverte, R, Fischer, AJ (2016) A psbA mutation (Val219 to Ile) causes resistance to propanil and increased susceptibility to bentazon in Cyperus difformis. Pest Manag Sci 72:1673–1680CrossRefGoogle ScholarPubMed
Sanders, BA (1994) The life cycle and ecology of Cyperus difformis (rice weed) in temperate Australia: a review. Aust J Exp Agri 34:1031–1038CrossRefGoogle Scholar
Satorre, EH, Ghersa, CM, Pataro, AM (1985) Prediction of Sorghum halepense (L.) Pers rhizome sprout emergence in relation to air-temperature. Weed Res 25:103-109CrossRefGoogle Scholar
Spokas, K, Forcella, F (2006). Estimating hourly incoming solar radiation from limited meteorological data. Weed Sci 54:182–189CrossRefGoogle Scholar
Steinmaus, SJ, Prather, TS, Holt, JS (2000) Estimation of base temperatures for nine weed species. J Exp Bot 51:275–286CrossRefGoogle ScholarPubMed
[UC IPM] University of California Agriculture and Natural Resources Statewide Integrated Pest Management Program (2013) Weather, models, & degree-days. http://www.ipm.ucdavis.edu/WEATHER/index.html Accessed: December 5, 2018Google Scholar