Document Type : Original Article

Authors

1 Ph.D. Student of Seed Science and Technology, Department of Agronomy, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran.

2 Associate Professor, Department of Agronomy, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran.

Abstract

Introduction
Seed germination is a complex biological process that is influenced by various environmental and genetic factors. Temperature and water potential are two primary environmental regulators of seed germination. Tall mallow (Malva sylvestris)is an important invasive weed in southwest Iran and also a medicinal plant. ). Tall mallow is native home in Western Europe, North Africa and Asia. This plant frequently found in cultivated fields, orchards, gardens, farmyards near manure piles, along roadsides, in towns, and in waste places and, can grow anywhere from 60 to 120 cm in length.Quantification of germination response to water potential is possible using hydro time model. In this study, application of hydro time model for Malva sylvestris L.
 
Material and methods
 Experiments were conducted in 2015 at the seed laboratory of Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran. Fruits of M. sylvestris were collected in April 2014 from Shushtar, Khuzestan (32°2'47"N, 48°50'18"E), located in southwest Iran. Seeds were separated manually from the fruits and stored in room conditions until their use. The laboratory temperature fluctuated between 30°C during day and 20°C during night. Germination response to water potential in different temperature were studied. Treatments included drought levels (0, -0.2, -0.4, -0.6, -0.8, -1, -1.2, -1.4 and -1.6 MPa) in temperatures of 15, 20 and 30 °C. The response of cumulative germination seeds to different potentials at different temperature was quantified using weibull function. All data were analysed by SAS ver 9.2. The hydro time model was fitted to cumulative germination. Goodness of fit of the hydro time models to all data was checked by constructing plots of the coefficient of determination (R2), the relationship between the observed and the predicted germination percentage and base water potential.
 
Results
Results indicated that temperature in addition to germination percentage also on germination rate was effective. Also results showed that germination percentage and germination rate increased with increasing temperature, while germination percentage and germination rate reduced as a result of water potential increment. Also, results showed that the hydrot time model fit to data of tall mallow had high R2 values. According to the hydro time, the hydro time constant (θH) declined significantly with increasing temperatures, so that the minimum hydro time constant (10.01 MPa h) was attained at 30 °C. The increment of temperature resulted in significant reduction of base water potential, and the highest base water potential (-1.13 and -1.11 MPa) was obtained at 15 and 20 °C, and the minimum base water potential (-0.6 MPa) was attained at 30 °C. The minimum standard deviation of base water potential in population (0.31) was obtained at 30 °C. Using hydro time model for quantitation of M. sylvestris L.
 
Conclusion
 Germination response to water potential at different temperatures, led to acceptable results. Utilizing the output of hydro time model at different temperatures can be useful in prediction of germination percentage in different water potential.

Keywords

Alimagham, S.M., Ghaderi-Far, F., 2014. Hydrotime model: Introduction and application of this model in seed researches. Environmental Stresses in Crop Sciences. 7(1), 41-52. [In Persian with English Summary].
Ansari, O., Choghazardi, H.R., Sharif Zadeh, F., Nazarli, H., 2012. Seed reserve utilization and seedling growth of treated seeds of mountain rye (Seecale montanum) as affected by drought stress. Cercetări Agronomice în Moldova. 2(150), 43-48.
Balbaki, R.Z., Zurayk, R.A., Blelk, M.M., Tahouk, S.N., 1999. Germination and seedling development of drought tolerant and susceptible wheat under moisture stress. Seed Science Technology. 27, 291-302.
Baskin, C.C., Baskin, J.M., 2001. Seeds: ecology, biogeography, and evolution ofdormancy and germination. Academic Press, San Diego, California, pp. 666.
Bradford, K.J., 1990. A water relation analysis of seed germination rates. Plant Physiology. 94, 840-849.
Bradford, K.J., 1995. Water relations in seed germination. In: J. Kigel and G. Galili[eds.], Seed Development and Germination, 351-396.Marcel Dekker Inc. New York, New York, USA.
Bradford, K.J., 1997. The hydrotime concept inseed germination and dormancy, pp 349-360. In: Ellis, R.H., Black, M., Murdoch, A.J., Hong, T.D. (eds.), Basic. Applied Aspect. Seed Biology, Boston, Kluwer AcademicPublishers.
Bradford, K.J., 2002. Application of hydrothermal time to quantifying and modelingseed germination and dormancy. Weed Science. 50, 248-260.
Bradford, K.J., Still, D.W., 2004. Application of hydrotime analysis in seed testing. SeedTechnology. 26, 74-85.
Cardoso, V.J.M., Bianconi, A., 2013. Hydrotime model can describe the response of common bean (Phaseolus vulgaris L.) seeds to temperature and reduced water potential. Acta Scientiarum. 35(2), 255-261.
Dahal, P., Bradford, K.J., 1990. Effects of priming and endosperm integrityon seed germination rates of tomato genotypes. II. Germination at reduced waterpotential. Journal of Experimental Botany. 41, 1441–1453.
Del Monte, J.P., Dorado, J., 2011. Effects of light conditions and afterripening time on seed dormancyloss of Bromus diandrus Roth. Weed Research. 51, 581-590.
Derakhshan, A., Gherekhloo, J., Vidal, R.B., De Prado, R., 2013. Quantitative description of the germination of littleseed canarygrass (Phalaris minor) in response to temperature. Weed Science. 62, 250-257.
Dumur, D., Pilbeam, C.J., Craigon, J., 1990. Use of the Weibull Function to Calculate Cardinal Temperatures in Faba Bean. Journal of ExperimentalBotany. 41, 1423–1430.
Fischer, R.A., Turner, N.C., 1978. Plant productivity in the arid and semiarid zones. Annual Review of Plant Physiology. 29, 277–317
Forcella, F., Benech-Arnold, R.L., Sanchez, R., Ghersa, C.M., 2000. Modelingseedling emergence. Field Crops Research. 67, 123-139.
Ghaderi-Far, F., Soltani, A., Sadeghipour, H.R., 2009. Evaluation of nonlinear regeression models in quantifying germination rate of medicinal pumpkin (Cucurbita pepo L. subsp. pepo. Convar. pepo var. styriaca Greb), borago (Borago officinalis L.) and black cumin (Nigella sativa L.) to temperature. Journal of Plant Production. 16(4), 1-9. [In Persian with English Summary].
Grundy, A.C., 2003. Predicting weed emergence: a review of approaches and future challenges. Weed Research. 43, 1–11.
Grundy, A.C., Phelps, K., Reader, R.J., Burston, S., 2000. Modelling the germination of Stellaria media using the concept of hydrothermal time. New Phytology. 148, 433–444.
Guerke, W.R., Gutormson, T., Meyer, D., McDonald, M., Mesa, D., Robinson, J.C., TeKrony, D., 2004. Application of hydrotime analysis in seed testing. Seed Technology. 26 (1), 75- 85.
Gummerson, R.J., 1986. The effect of constant temperature and osmotic potentials on the germination of sugar beet. Journal of Experimental of Botany. 37, 729-741.
Huarte, R., 2006. Hydrotime analysis of the effect of fluctuating temperatures on seed germination in several non-cultivated species. Seed Science and Technology. 34, 533-547.
Kebreab, E., Murdoch, A.J., 2000. The effect of water stress on the temperature germination rate of Orobanche aegyptiaca seeds. Journal of Experimental Botany. 50, 655-664.
Leblanc, M. L., Cloutier, D.C., Stewart, K.A., Hamel, C., 2004. Calibration and validation of a common lambsquarters (Chenopodium album) seedling emergence model. Weed Science. 52, 61–66.
Michel, B.E., Kaufmann, M.R., 1973. The osmotic potential of polyethyleneglycol 6000. Plant Physiology. 51, 914-916.
Myers, M.W., Curran, W.S., VanGessel, M.J., Calvin, D.D., Mortensen, D.A., Majek, B.A., Karsten, H. D., Roth, G.W., 2004. Predicting weed emergence for eight annual species in the northeastern United States. Weed Science. 52, 913–919
Ni, B.R., Bradford, K.J., 1992. Quantities models characterizing seed germinationresponse to abscisic acid and osmoticum. Plant Physiology. 98, 1057-1068
Probert, R.J., 2000. The role of temperature in the regulation of seed dormancy andgermination. In: Fenner M., (Ed.), Seeds: the ecology of regeneration in plantcommunities. CABI Pub., Oxon, UK, New York, pp. 261-292.
Roman, E.S., Murphy, S.D., Swanton, C.J., 2000. Simulation of Chenopodium album seedling emergence. Weed Science. 48, 217–224.
Schellenberg, M.P. Biligetu, B. Wei, Y. Predicting seed germination of slender wheatgrass [Elymus trachycaulus (Link) Gould subsp.trachycaulus] using thermal and hydro time models. Canadian Journal of Plant Science. 93, 793-798.
Sester, M., Dürr, C., Darmency, H., Colbach, N., 2007. Modeling the effects of cropping systems on the seed bank dynamics and the emergence of weed beet. Ecology Modeling. 204, 47–58.
Sohrabi, S., Gherekhloo, J., 2015. Investigating status of the invasive weeds of Iran. Proceeding of 6th Iranian Weed Science Congress. 1-3 September, Birjand, Iran. [In Persian with English Summary].
Tabaraki, R., Yousefi, Z., Ali, H., Gharneh, 2011. Chemical Composition and Antioxidant Properties of Medicinal Plant Malva sylvestris L. Journal of Research in Agricultural Science. 8(1): 59-68. [In Persian with English Summary].
Van Assche, J.A., Vandelook, F.E.A., 2006. Germination ecology of eleven species of Geraniaceae and Malvaceae, with special reference to the effects of drying seeds. Seed Science Research. 16(4), 283-290.
Windauer, L., Altuna, A., Benech-Arnold, R., 2007. Hydrotime analysis ofLesquerella fendleri seed germination responses to priming treatments. Industrial Crops Products. 25, 70-74.