Document Type : Research Paper - Weed Sciences


1 Assistant Professor, Department of Plant Production and Genetics, Faculty of Agriculture, Agricultural Sciences and Natural Resources University of Khuzestan, Mollasani, Iran

2 Associate Professor, Department of Agrotechnology, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran

3 Professor, Department of Agrotechnology, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran

4 Professor, Department of Weed Research, Iranian Research Institute of Plant Protection, Tehran, Iran

5 Assistant Professor, Department of Biotechnology and Plant Breeding, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran


Chlorophyll fluorescence induction is a rapid and noninvasive technique for measuring photosynthetic electron transport in plants. Recognition of fluorescence curves such as Kautsky curves is a useful tool for quantifying herbicide effects. In general, since one of the goals of measuring chlorophyll fluorescence is the early detection of the effects of herbicide before its apparent effects on weed. PSII inhibiting herbicides resistance results from a mutation in the chloroplast genome, reducing the rate of electron transport between QA and QB in PS II.
Materials and Methods
The seeds pre-germinated in Petri dishes at 28±2 0C in 16/8 hr (light/dark) photoperiod for 72 hr. The pre-germinated seeds were sown in pots (with 10 cm diameter) containing loam: sand 2:1 mixture (v/v). Pots were transferred to a greenhouse and grown at 30 0C and 20 0C day and night temperatures, respectively, with artificial light to provide a 16-h photoperiod. Pots were irrigated regularly to avoid any moisture stress. Ten days after planting (DAP), they were thinned to two seedlings per pot. Twenty days after weed emergence, seedlings of the pots were subjected to the post emergence application of ametryn. Different ranges of ametryn rates were used for the resistant (0, 10, 30, 100, 300, 1000, 3000, 10000 and 30000 g ai ha-1) and susceptible (0, 1, 10, 30, 100, 300, 1000 g ai ha-1) populations because of the difference in dose-response among populations. Nonionic surfactant 0.25% (v/v) was applied with the herbicide at the time of spraying. The sprayer was calibrated to deliver 220 L ha-1 at pressure of 2 atm. The aboveground biomass was harvested 28 days after treatment (DAT) and weighed. In order to analyze the data and draw the shapes, Gompertz function and SigmaPlot11 and R soft wares were used. PEA Plus software, also, was used to output the chlorophyll fluorescence data recorded during the experiment.
Results and Discussion
The results showed that Fvj was more sensitivity to the application of ametryn in the tested populations. So that four hours after the application of ametryn, Fvj, in some populations, especially susceptible population (24.47 g ai ha-1), decreased significantly. Regarding ED50 values based on fresh weight of populations, the highest amount of ED50 belonged to R4 (10289 g ai ha-1), R1 (6844.6 g ai ha-1), R3 (4770 g ai ha-1) and R2 (3041.0 g ai ha-1), respectively. Estimated ED50 values for Fvj susceptible and resistant populations were, in some cases, far lower than estimated ED50 values for fresh weight of populations at 28 days after treatment with herbicides. In general, the linear relationship between the above parameter and the fresh weight of the populations indicates a strong correlation between these parameters. There were differences among the resistant and susceptible populations in the application of herbicide in terms of the slope of the curve of fvj. So that the curve slope in R1 and R2 biotypes was faster than other populations. In susceptible population response, more correlation was observed between the above parameters. The purpose of this parameter was to show that chlorophyll fluorescence parameters, such as fresh weight assay or weed dry weight, can predict the effect of herbicides. Thus, the researchers are able to evaluate the herbicide's impact on the plants by spending less time and cost.
Since the main effect of photosystem II inhibiting herbicides is in the J stage (Fvj). Therefore, it is possible to use the Fvj parameter, which most likely shows the changes in electron transfer in the electron transfer chain in photosystem II. The most resistant populations (R1 and R4) based on the measurement of fresh weight, in the analysis based on the Fvj parameter, like other resistant populations, showed the significant difference with the susceptible population. Also, the sensitivity of the susceptible population response to herbicide application based on the Fvj parameter was much higher than that of fresh weight. So that it enables the researcher to quickly distinguish among the susceptible and resistant populations to the mentioned herbicides.


Abbaspoor, M., & Streibig, J. C. (2005). Clodinafop changes the cholorophyll fluorescence induction curve. Weed Science, 53(1), 1-9.
Abbaspoor, M., & Streibig, J. C. (2007). Monitoring the efficacy and metabolism of phenylcarbamates in sugar beet and black nightshade by chlorophyll fluorescence parameters. Pest Management Science, 63(6), 576-585.
Abbaspoor, M., Teicher, H. B., & Streibig, J. C. (2006). The effect of root-obsorbed PSII inhibitors on Kautsky curves parameters in sugar beet. Weed Research, 46(3), 226-235.
Avarseji, Z., & Mohammadvand, E. (2018). Studying the effect of mesosulfuron methyl+iodosulfuron methyl on chlorophyll fluorescence parameters of Phalaris minor. Plant Productions, 41(3), 63-72. [In Farsi]
Baker, N. R., & Rosenqvist, E. (2004). Applications of chlorophyll fluorescence can improve crop production strategies: an examination of future possibilities. Journal of. Experimental Botany, 55(403), 1607-1621.
Chauhan, B. S., & Johnson, D. E. (2009). Seed germination ecology of junglerice (Echinochloa colona): a major weed of rice. Weed Science, 57(3), 235-240.
Cheristensen, M. G., Teicher, H. B., & Streibig, J. C. (2003). Linking fluorescence induction curve and biomass in herbicide screening. Pest Management Science, 59(12), 1303-1310.
Chitband, A. A., Ghorbani, R., Rashed Mohassel, M. H., & Abbasi, R. (2016). The Effect of PSII Inhibitors on Kautsky Curve and Chlorophyll Fluorescence in Common Lambsquarters (Chenopodium album L.) and Common Purslane (Portulaca oleracea L.). Plant Protections, 29(4), 540-550. [In Farsi]
Cobb, A. H., & Reade, J. P. H. (2010). Herbicides and Plant Physiology. 2nd ed. Wiley-Blackwell, New York.
Devine, M. D., & Shukla, A. (2000). Altered target sites as a mechanism of herbicide resistance. Crop Protection, 19(8-10), 881-889.
Elahifard, E., Ghanbari A., Rashed Mohassel M. H., Zand E., Mirshamsi Khakhki A., & Mohkami A. (2013). Charachtrization of triazine resistant populations of junglerice (Echinochloa colona (L.) Link.) found in Iran. Australian Journal of Crop Science, 7(9), 1302-1308.
Elahifard, E., Mijani, S., Kheyrandish, S., Kazerooni Monfared, E., & Tokasi, S. (2013). Investigation of dormancy and the effect of some environmental factors on germination of junglerice (Echinochloa colona (L.) Link.) seeds. Plant Productions, 27(3), 342-350. [In Farsi]
Fischer, A. J., Granados, E., & Trujillo, D. (1993). Propanil resistance in populations of junglerice (Echinochloa colona) in Colombian rice fields. Weed Science, 41(2), 201-206.
Foes, M. J., Liu, L., Tranel, P. J., Wax, L. M., & Stoller, E. W. (1998). A biotype of common waterhemp (Amaranthus rudis) resistant to triazine and ALS herbicides. Weed Science, 46(5), 514-520.
Foes, M. J., Liu, L., Vigue, G., Stoller, E. W., Wax, L. M., & Tranel, P. J. (1999). A Kochia (Kochia scoparia) biotype resistant to triazine and ALS-inhibiting herbicides. Weed Science, 47(1), 20-27.
Gadamski, G., Ciarka, D., Gressel, J., & Gawronski, S. W. (2000). Negative cross- resistance in triazine-resistant biotypes of Echinochloa crus-galli and Conyza canadensis. Weed Science, 48(2), 176-180.
Hoagland, R. E., Norsworthy, J. K., Carey, F., & Talbert, R. E. (2004). Methabolically based resistance to the herbicide propanil in Echinochloa species. Weed Science, 52(3), 475-486.
Klem, K., Spundova, M., Hrabalova, H., Naus, J., Vanova, M., Masojidek, J., & Tomek P. (2002). Comparison of chlorophyll fluorescence and whole-plant bioassays of isoproturon. Weed Research, 42(5), 335-341.
Knezevich, I., Streibig, J. C., & Ritz, C. (2007). Utilizing R software Package for dose-response studies: the concept and data analysis. Weed Technology, 21(4), 840-848.
Miles, B. (2003). Photosystem I and II. (Accessed October 2012)
Monaco, T. J., Weller, S. C., & Ashton, F. M. (2002). Weed Science: principles and practices. 4nd ed. John Wiley & Sons, New York.
Mousavi, M. (2011). Weed control: Principles and methods. Tehran: Marze Danesh Press. [In Farsi]
Park, K. W. & Mallory-Smith, C. A. (2005). Multiple herbicide resistance in downy brome (Bromus tectorum) and its impact on fitness. Weed Science, 53(6), 780-786.
Preston, C. (2009). Herbicide resistance: target site mutations. In Stewart, Jr. C.N. (Ed), Weedy and invasive plant genomics (pp: 127-148). New York: Wiley- Blackwell.
Senseman, S. A. (2007). Herbicide handbook. Lawrence, USA: Weed Science Society of America.
Taiz, L., & Zeiger, E. (2010). Plant physiology. Sunderland, Massachusetts U.S.A.: Sinauer Associates Inc.
Tian, X., & Darmency, H. (2006). Rapid bidirectional allele-specific PCR identification for triazine resistance in higher plants. Pest Management Science, 62(6), 531-536.
Valverde, B. E. (2007). Status and management of grass-weed herbicide resistance in Latin America. Weed Technology, 21(2), 310-323.