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Estimation and Comparison of Base Temperatures for Germination of European Populations of Velvetleaf (Abutilon theophrasti) and Jimsonweed (Datura stramonium)

Published online by Cambridge University Press:  20 January 2017

Donato Loddo*
Affiliation:
Dipartimento di Agronomia Animali Alimenti Risorse Naturali e Ambiente, Università di Padova, Agripolis, Legnaro352020, Padova, ltaly
Edite Sousa
Affiliation:
Instituto Superior de Agronomia, Tapada da Ajuda 1349-017, Lisboa, Portugal
Roberta Masin
Affiliation:
Dipartimento di Agronomia Animali Alimenti Risorse Naturali e Ambiente, Università di Padova, Agripolis, Legnaro352020, Padova, ltaly
Isabel Calha
Affiliation:
Instituto Nacional de Investigação Agrária e Veterinária, Instituto Publico, Quinta do Marquês, 2780-155 Oeiras, Portugal
Giuseppe Zanin
Affiliation:
Dipartimento di Agronomia Animali Alimenti Risorse Naturali e Ambiente, Università di Padova, Agripolis, Legnaro352020, Padova, ltaly
César Fernández-Quintanilla
Affiliation:
Instituto de Ciencias Agrarias, Consejo Superior de Investigaciones Cientificas, 28006 Madrid, Spain
José Dorado
Affiliation:
Instituto de Ciencias Agrarias, Consejo Superior de Investigaciones Cientificas, 28006 Madrid, Spain
*
Corresponding author's E-mail: donato.loddo@unipd.it

Abstract

Weed emergence models require biological parameters such as base temperature for germination, determination of which is costly and time-consuming. Transferability of these parameters across different populations may therefore represent one of the main constraints for the development and practical use of emergence models at a large scale. A collaborative project was undertaken to assess the interpopulation variability of base temperature for germination in different European populations of velvetleaf and jimsonweed and evaluate possible applicative consequences in terms of weed control. Seeds were collected in Italy, Portugal, and Spain, and each population was then sown in every country, obtaining nine seed batches named as experimental lots. Base temperature for germination was estimated for each experimental lot to calculate lot-specific accumulation of growing degree days (GDD) under three dissimilar climatic scenarios. Threshold date (TD50) was calculated as the date when GDD accumulation of a given experimental lot surpassed the values corresponding to 50% of cumulative field emergence of seedlings. GDD accumulation and TD50 were then used as indicators to identify differences among experimental lots within each climatic scenario. No significant differences were detected among base temperatures estimated for velvetleaf experimental lots or among their patterns of accumulation of GDD and TD50 values within climatic scenarios. Each value of base temperature determined for a single experimental lot could therefore be adopted to model germination for all the lots regardless of the population of origin or cultivation site. In contrast, the population of origin affected the base temperature for jimsonweed, with significantly higher values for experimental lots of the Portuguese population. From an applicative perspective, differences among patterns of accumulation of GDD and TD50 of several experimental lots within each climatic scenario suggest the need to use population-specific values as base temperature for germination and emergence modeling of jimsonweed.

Type
Weed Biology and Ecology
Copyright
Copyright © Weed Science Society of America 

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References

Literature Cited

Bedmar, F., Manetti, P., and Monterubbianesi, G. 1999. Determination of the critical period of weed control in corn using a thermal basis. Pesqui. Agropecu. Bras. 34:187193.Google Scholar
Benvenuti, S. and Macchia, M. 1993. Calculation of threshold temperature for the development of various weeds. Agric. Med. 123:252256.Google Scholar
Benvenuti, S. and Macchia, M. 1997. Light environment, phytochrome and germination of Datura stramonium L. seeds. Environ. Exp. Bot. 38:6171.Google Scholar
Benvenuti, S., Macchia, M., and Miele, S. 2001. Quantitative analysis of emergence of seedlings from buried weed seeds with increasing soil depth. Weed Sci. 49:528535.Google Scholar
Borza, J. K., Westerman, P. R., and Liebman, M. 2007. Comparing estimates of seed viability in three foxtail (Setaria) species using the imbibed seed crush test with and without additional tetrazolium testing. Weed Technol. 21:518522.Google Scholar
Bradford, K. J. 2002. Applications of hydrothermal time to quantifying and modeling seed germination and dormancy. Weed Sci. 50:248260.Google Scholar
Christal, A., Davies, D.H.K., and Van Gardingen, P. R. 1998. The germination ecology of Chenopodium album populations. Pages 127134 in Aspects of Applied Biology 51—Weed Seedbanks: Determination, Dynamics and Manipulation Oxford, UK: Association of Applied Biologists.Google Scholar
Conklin, M. E. 1976. Genetic and biochemical aspects of development of Datura . Monogr. Dev. Biol. 12:170.Google Scholar
Danuso, F., Zanin, G., and Sartorato, I. 2012. A modelling approach for evaluating phenology and adaptation of two congeneric weeds (Bidens frondosa and Bidens tripartita). Ecol. Model. 243:3341.Google Scholar
Del Monte, J. P. and Tarquis, A. M. 1997. The role of temperature in the seed germination of two species of the Solanum nigrum complex. J. Exp. Bot. 48:20872093.Google Scholar
Dorado, J., Fernández-Quintanilla, C., and Grundy, A. C. 2009a. Germination patterns in naturally chilled and non-chilled seeds of fierce thornapple (Datura ferox) and velvetleaf (Abutilon theophrasti). Weed Sci. 57:155162.CrossRefGoogle Scholar
Dorado, J., Sousa, E., Cahla, I. M., González-Andújar, J. M., and Fernández-Quintanilla, C. 2009b. Predicting weed emergence in maize crops under two contrasting climatic conditions. Weed Res. 49:251260.Google Scholar
Efron, B. 1979. Bootstrap methods: another look at the jackknife. Ann. Stat. 7:126.CrossRefGoogle Scholar
European Parliament. 2009. Directive 2009/128/EC of the European Parliament and of the Council of 21 October 2009 establishing a framework for Community action to achieve the sustainable use of pesticides. Off. J. Eur. Union 309:7186.Google Scholar
[FAO] Food and Agricultural Organization of the United Nations. 2006. World Reference Base for Soil Resources 2006. A Framework for International Classification, Correlation and ommunication. Rome FAO World Soil Resources Reports 103. 145 p.Google Scholar
Ferrero, A., Scanzio, M., and Acutis, M. 1996. Critical period of weed interference in maize. Pages 171176 in Proceedings of the Second International Weed Control Congress. Copenhagen, Denmark Department of Weed Control and Pesticide Ecology.Google Scholar
Grundy, A. C. 2003. Predicting weed emergence: a review of approaches and future challenges. Weed Res. 43:111.CrossRefGoogle Scholar
Grundy, A. C., Peters, N.C.B., Rasmussen, I. A., Hartman, K. M., Sattin, M., Andersson, L., Mead, A., Murdoch, A. J., and Forcella, F. 2003. Emergence of Chenopodium album and Stellaria media of different origins under different climatic conditions. Weed Res. 43:163176.Google Scholar
Gummerson, R. J. 1986. The effect of constant temperatures and osmotic potential on the germination of sugar beet. J. Exp. Bot. 41:14311439.Google Scholar
Horowitz, M. and Taylorson, R. B. 1984. Hardseedness and germination of velvetleaf (Abutilon theophrasti Medic.) as affected by temperature and moisture. Weed Sci. 32:111115.Google Scholar
Isik, D., Mennen, H., Bukun, B., Oz, A., and Ngouajio, M. 2006. The critical period for weed control in corn in Turkey. Weed Technol. 20:867872.CrossRefGoogle Scholar
Leblanc, M. L. and Cloutier, D. C. 2002. Optimization of cultivation timing by using a weed emergence model. Pages 1416 in Proceedings of the 5th European Weed Research Society Workshop on Physical Weed Control. Sainte-Anne-de-Bellevue, Canada Istitut de Malherbologie.Google Scholar
Loddo, D., Masin, R., Otto, S., and Zanin, G. 2012. Estimation of base temperature for Sorghum halepense rhizome sprouting. Weed Res. 52:4249.Google Scholar
Magyar, L. and Lukacs, D. 2002. Recent data on seed dormancy and germination ecology of annual mercury (Mercurialis annua L.). Pages 374375 in Proc. of the 12th European Weed Research Soc. Symp. Doorwerth, the Netherlands European Weed Research Society.Google Scholar
Masin, R., Loddo, D., Benvenuti, S., Otto, S., and Zanin, G. 2012. Modeling weed emergence in Italian maize fields. Weed Sci. 60:254259.Google Scholar
Masin, R., Loddo, D., Benvenuti, S., Zuin, M. C., Macchia, M., and Zanin, G. 2010. Estimation of temperature and water potential thresholds for the main weed species in maize in north-central Italy. Weed Sci. 58:216222.Google Scholar
Masin, R., Vasileiadis, V. P., Loddo, D., Otto, S., and Zanin, G. 2011. A single-time survey method to predict the daily density for weed control decision-making. Weed Sci. 59:270275.Google Scholar
Masin, R., Zuin, M. C., Archer, D. W., Forcella, F., and Zanin, G. 2005. WeedTurf: a predictive model to aid control of annual summer weeds in turf. Weed Sci. 53:193201.Google Scholar
Murdoch, A. J., Isik, D., Nicholls, R. A., Gonzalez Andujar, J. L., Beloit, D., Davis, A., Forcella, F., Graziani, F., Grundy, A. C., Karlsson, L., Milberg, P., Neve, P., Rasmussen, I. A., Salonen, J., Sera, B., Sousa, E., Tei, F., Torresen, K., and Urbano, J. M. 2010. Dormancy and germination of Chenopodium album seeds from different latitudes in Europe and North America. Pages 74 in Proceedings of the 15th European Weed Research Society Symposium. Budapest, Hungary Pannonia-Print Ltd.Google Scholar
Nurse, R. E. and DiTommaso, A. 2005. Corn competition alters the germinability of velvetleaf (Abutilon theophrasti) seeds. Weed Sci. 53:479488.Google Scholar
Onofri, A. 2005. BIOASSAY97: a new EXCEL® VBA macro to perform statistical analyses on pesticide dose-response data. Ital. J. Agromet. 3:4045.Google Scholar
Otto, S., Masin, R., Casari, G., and Zanin, G. 2009. Weed–corn competition parameters in late-winter sowing in northern Italy. Weed Sci. 57:194201.CrossRefGoogle Scholar
Recasens, J., Calvet, V., Cirujeda, A., and Conesa, J. A. 2005. Phenological and demographic behaviour of an exotic invasive weed in agroecosystems. Biol. Inv. 7:1727.Google Scholar
Reisman-Berman, O., Kigel, J., and Rubin, B. 1991. Dormancy patterns in buried seeds of Datura ferox and D. stramonium . Can. J. Bot. 69:173179.CrossRefGoogle Scholar
Rochè, C. T., Thill, D. C., and Shafii, B. 1997. Estimation of base and optimum temperatures for seed germination in common crupina (Crupina vulgaris). Weed Sci. 45:529533.CrossRefGoogle Scholar
Sartorato, I. and Pignata, G. 2008. Base temperature estimation of 21 weed and crop species. Pages 112113 in Proceedings of the 5th International Weed Science Congress. Vancouver, Canada International Weed Science Society.Google Scholar
Taab, A. and Andersson, L. 2009. Primary dormancy and seedling emergence of black nightshade (Solanum nigrum) and hairy nightshade (Solanum physalifolium). Weed Sci. 57:526532.Google Scholar
Winter, D. M. 1960a. The development of the seed of Abutilon theophrasti . I. Ovule and embryo. Am. J. Bot. 47:814.Google Scholar
Winter, D. M. 1960b. The development of the seed of Abutilon theophrasti . II. Seed coat. Am. J. Bot. 47:157162.Google Scholar
Young, S. L. 2012. True integrated weed management. Weed Res. 52:107111.Google Scholar