Evaluation empirical models of competitiv ability of four wheat varieties (Triticum aestivum L.) to Japanese borom (Bromus japonicus L.)

Document Type : Research Paper

Abstract

Background and objectives
Weed management is one of the effective methods to maintain capacitance of production. weed density is a quantitative effective factor in competition with crop. nowadays in the management of weed communities, instead complete elimination weed of farm, work to recognition and quantitative assessment of the behavior and effects of weed in crop ecosystemse. This requires is knowledge of crop-weed properties during the growing season and their interaction and quantify of the competition. So far, several experimental models to express the relationship between crop yield loss in the presence of weed suggested. These models are used to understand concepts such as the intensity of competition and thresholds of weed control. Hence this study was done in order to assess the competation of various densities Japanese borom weed and four varieties of wheat (Hamun, Hirmand, Bolani and Kalak afghani) and prediction of yield loss using experimental models and compare its performance.
Materials and Methods
This study was carried out to evaluate empirical models of competition, as based on a factorial arrengment using arandomized complete blocks design (RCBD) with 4 replications at field experiment was conducted at the Chah Nimeh field experiment station University of Zabol, in 2014-2015 growing season. In this experiment Hamun, Hirmand, Bulani and Kalak afghani cultivar were planted with density of 400 plants m-2. Simultaneously with planted of wheat, Japanese borom (Boromus japonicus L.) with densities of 0, 100, 150, 200. 250 and 300 plants m-2 were planted. At the end of the growing season, the final harvest of the lower half of each plot was performed by observing the marginal effect and in the area a square meter. To estimate grain yield loss of wheat cultivars in different levels of weed density was used of density-yield loss model, one-parameter and two-parameter models of relative weed leaf area and one-parameter and two-parameter models of relative weed dry weight. In this reaserch was used to softwares SAS and Sigmaplot and Excel to analysis of variance and estimation of model parameterse and plot graphs.
Results
Our results based on yield loss models confirmed that biological yield decreased less than grain yield (Grain yield was more susceptible).Obtained relative damage coefficients (q parameter) of one and two-parameter models based on relative leaf area and relative dry matter were indicative of high competitive ability of japanese borom than wheat cultivars.Comparison of several empirical yield loss models showed that models based on relative leaf area and relative dry matter of Japanese borom with Minimum regression root mean square error, had more efficiency in predict of wheat grain yield loss in compared with yield loss-density model.
Conclusions
Overall our results of this study showed that Japanese borom weed is exist a strong competitor to wheat cultivars. Also addition of weed density reduced grain yield and biological yield wheat varieties investigated linearly. Wheat cultivars were different of sensitivity to weed interference. Compare the performance models was suggested excellence of weed relative leaf area and dry weight relative models to density-yield loss model. As a result of these models can be used to a good measure to predict of wheat yield loss in interference with the Japanese borom weed.

Keywords

Main Subjects

References

1. Adim, H. 2009. Advanced weed survey and mapping of weeds in Baloochestan using
Geographic Information System (GIS). Final Report. Agriculture and Natural Resources
Center of Baloochestan (Iranshahr). (in Persian)
2. Ahmadi, M., Kamkar, B., Soltani, A., and Zeinali, E. 2010. Evaluation of non-Linear
regression models to predict stem elongation rate of wheat (Tajan cultivar) in response to
temperature and Photoperiod. EJCP. 2: 4. 39-54.
3. Baghestani meybodi, M.A., and Zand, E. 2004. Evaluation of competitive ability of some
winter wheat (Triticum aestivum L.) genotypes against weeds with attention to Goldbachia
laevigata DC. And Avena ludoviciana Dur. In Karaj. J. Plant Pests and Disease. 72: 91-111.
(In Persian)
4. Blackshaw, R.E. 1994. Differential competitive ability of winter wheat cultivar against
downy borom. Agron. J. 86: 649-654.
5. Cousense, R. 1985a. A simple model relating yield loss to weed density. Ann. Appl. Biol.
107: 239-252.
6. Cousense, R. 1985b. An empirical model relating crop yield to weed and crop density and a
statistical comparison with other models. J. Agric. Sci. 105: 513-521.
7. Cousense, R., Brain, P., O., Donovan, I., and Sullivan, P.A. 1987. The use of biologically
realistic equations to describe the effects of weed density and relative time of emergence on
crop yield. Weed Sci. 35: 720-725.
8. Dianat, M., Rahimian Mashhadi, H., Baghestani, M.A., Alizadeh, H.M., and Zand, E. 2007.
Evaluation of Iranian cultivars of bread Wheat (Triticum aestivum L.) for competitive ability
against Rye (Secale cereale). J. Agric Sci. Natur. Resour. 23: 267-280. (In Persian)
9. Eslami, S.V., Gill, G.S., Bellotti, B., and McDonald, G. 2006. Wild radish (Raphanus
raphanistrum) interference in wheat. Weed Sci. 54: 749-756.
10. Kafi, M., Jafar-Nezhad, A., and Jami Al-ahmadi, M. 2005. Wheat- Ecology, Physiology and
Yield Determination.Ferdowsi University of Mashhad Press. (In Persian)
11. Klein, R.N., Wicks, G.A., and Lyon, D.J. 2002. Downy brom control. Description and
control of downy brome in wheat, alfalfa, and rangeland. Cooperative extension, Institute of
Agriculture and Natural resources, University of Nebraska– Lincoln.
12. Knezevic, S.Z., Weise, S.F., and Swanton, C.J. 1995. Comparison of empirical models
depicting density of Amaranthus retroflexus L., and relative leaf area as predictors of yield
loss in maize (Zea mays L.). Weed Res. 35: 207-214.
13. Kroppf, M.J., and Spitters, C.J.T. 1991. A simple model of crop loss by weed competition
from early observation of relative leaf area of weeds. Weed Res. 31: 97-105.
14. Kroppf, M.J., and Lotz, L.A.P. 1992. System approach to quantify crop-weed interactions
and their application to weed management. Agric Sys. 40: 256-282.
15. Li, YH. 1998. Weeds of China. 1st edn, Volume 2. Weeds of Seed Plants. China Agriculture
Press. Pp: 1180–1181.
16. Lotz, L.A.P., Christenzen, S., and lotier, C. 1996. Prediction of weed competitive effects of
weed on crop yields based on the relative leaf area of weeds. Weed Res. 36: 93-101.
17. Lutman, P.J.W., Bowerman, P., Palmer, G.M., and Whytock, G.P. 2000. Prediction of
competition between oilseed rape and Stellaria media. Weed Res. 40: 255-269.
18. Makarian, H., Banaian, M., Rahimian, H., and Isadi Darbandi, E. 2003. Planting date and
population density influence on competitiveness of corn (Zea mays L.) with redroot pigweed
(Amaranthus retroflexus L.). Iran. J. Crop Res. 2: 271-279.
19. Massinga, R.A., Currie, R.S., Horak, M., and Boyer Jr, J. 2001. Interference of Palmer
amaranth in corn. Weed Sci. 49: 202-208.
20. Mennan, H., and Zandstra, B.H. 2005. Effect of wheat (Triticum aestivum) cultivars and
seeding rate on yield loss from Galium aparine (cleavers). Short communication. Crop Prot.
24: 1061-1067.
21. Ngouajio, M., Lemieux, C., and Leroux, G.D. 1999. Prediction of corn (Zea mays) yield loss
from ealy observation of the relative leaf area and the relative leaf cover of weeds. Weed Sci.
47: 297-304.
22. Ngouajio, M., Mcgiffen, M.E., and Hembree, J.J. 2001. Tolerance of tomato cultivars to
velvetleaf interference. Weed Sci. 49: 91-98.
23. Niknam Haghighi, A., Kazemeini, S.A.R., and Ghadiri, H. 2014. Effects of Nitrogen,
Seeding rate and weed interference on growth and yield of Wheat (Shiraz Cultivar). J. Weed.
Sci. 9: 159-174. (in Persian)
24. Olofsdotter, M., Navarez, D., and Rebulanan, M. 1999. Weed suppressing rice cultivars-does
allelopathy play a role. Weed Res. 39: 441-454.
25. Park, S.E., Benjamin, L.R., and Watkinson, A.R. 2003. The theory and application of plant
competition models: an agronomic perspective. Ann. Bot. 92: 741-748.
26. Paynter, B.H., and Hills, A.L. 2009. Barley and rigid ryegrass (Lolium rigidum) competition
is influenced by crop cultivar and density. Weed Technol. 23: 40-48.
27. Paynter, B.H. 2010. Wide row spacing and rigid ryegrass (Lolium rigidum) competition can
decrease barley yield. Weed Technol. 24: 310-318.
28. Rahimian, H., and Shariati, S.H. 1999. Modeling Crop-Weed Interactions. Agriculture
Research and Education Organazation press. 294p. (Translated in Persian)
29. Roberts, J., Peeper, T.F., and Solie, J.B. 2001. Wheat (Triticum aestivum) row spacing,
seeding rate and cultivar affect interference from rye (Secale cereale). Weed Technol. 15:
19-25.
30. Saadatian, B., Ahmadvand, G., and Soleymani, F. 2011. Study of canopy structure and
growth characters role of two wheat cultivars in competition, on economic threshold and
yield of rye and wild mustard. Iran. J. Field Crops Res. 9(3): 494-504. (In Persian)
31. Saadatian, B., Ahmadvand, G., and Soleymani, F. 2012. Evaluation of empirical models of
feral rye and wild mustard to predict yield loss of two winter wheat cultivars. EJCP. 4(4):
157-175. (In Persian)
32. Saadatian, B., Kafi, M., Soleymani, F., and Ahmadvand, G. 2013. Evaluating empirical
models to predict yield loss of winter wheat (Triticum aestivum L.) cultivars in interference
with feral rye (Secale cereale). Cereal Res. 3: 1. 69-82. (In Persian)
33. Safahani Langrodi, A.S., Kamkar, B., Zand, E., and Baghestani, M.A. 2008. Evaluation of
ability tolerance competition of canola cultivars to wild mustard (Sinapis arvensis) using
some empirical models in Golestan province. J. Agric. Sci. Nat. Resour. 15: 101-111. (In
Persian)
34. Sahraeyan, M., and Bakhshoodeh, M. 2007. Integration of domestic and foreign markets for
wheat in Iran. Iran. J. Agric. Eco. 59: 97-118. (In Persian)
35. Sarani, M., Rezvani Moghadam, P., Nasiri Mahallati, M., and Zand, E. 2011. Evaluation of
some morphological characteristics effective in increasing the competitiveness of wheat
(Trticum aestivum) in competition with japanes borom (Bromus japonicus). J. Plant Prot. 25:
127-133. (in Persian)
36. Soleymani, F., Ahmadvand, G., and Saadatian, B. 2011. Investigation the effect of nitrogen
on competitive ability of canola (Brassica napus) against wild mustard (Sinapis arvensis)
using empirical models. J. Plant Prot. 25(2): 158-167. (In Persian)
37. Yenish, J.P., Durdan, B.R., Miller, D.W., and Wyse, D.L. 1992. Wheat (Triticum aestivum)
yield reduction from common milkweed (Asclepias syriaca) competition. Weed Sci. 45: 127-
131.
Journal of Crop Production
Volume 10, Issue 2
November 2017
Pages 29-43

Files

Share

How to cite

Statistics