Using Path Analysis to Predict Wheat Plant Loss (Triticum aestivum L.) Knowing the Density of the Weed (Bromus Rigidus)
Article Sidebar
Main Article Content
Abstract
The research explores the use of path analysis to predict the effect of brome grass (Bromus rigidus Roth) density on wheat (Triticum aestivum L.) yield loss. It also studies the relationship between weed density and wheat productivity. The research was conducted during the fall 2020 and spring 2021 seasons. Data were collected from experiments conducted under different densities of weeds and wheat. The statistical analysis program SPSS was used to determine the effect of competition on the amount of loss in wheat and brome productivity, using the Cousins (1985) equation and to calculate the competition coefficient between species using the Steward (1969) equation. Then, path analysis was used to predict the effect of internal and external variables on plant traits, biomass, and productivity. The results showed that increasing grass density led to a decrease in wheat productivity. The study emphasizes the importance of taking physiological factors into account in crop productivity. Recommendations include implementing measures to control weed density, adjusting wheat planting density to compete effectively with weeds, using weed-resistant wheat varieties, adopting comprehensive farm management practices, and conducting further research to enhance understanding of the interaction between wheat and weeds.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format.
- Adapt — remix, transform, and build upon the material.
Under the following terms:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- NonCommercial — You may not use the material for commercial purposes.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
References
R. Cousens, "A simple model relating yield loss to weed density," Annals of Applied Biology, vol. 107, pp. 239-252, 1985.
M. Attarat, M. Subouh, and W. Elak, "Variation, correlation and path coefficient analysis of some yield qualities in a hybrid of durum wheat," *Damascus University Journal of Agricultural Sciences*, vol. 31, no. 1, pp. 73-87, 2015.
M. S. Al-Taweel, "Correlations, path coefficient analysis, and evaluation of selection evidence for genetic compositions in coarse wheat," *Al-Rafidain Agriculture Journal*, vol. 42, no. 4, p. 13, 2014.
S. Wright, "The distribution of self-fertilizing and cross-fertilizing varieties of plants," Genetics, vol. 19, no. 1, pp. 1-32, 1934.
L. D. Barton, C. D. T., and B. S., "Integrated wild oat *Avena fatua* management affects spring barley *Hordeum vulgare* yield and economics," *Weed Technology*, vol. 6, pp. 129-135, 1992.
S. A. Khalifa, A. N. Abboud, and D. S. Madab, "Estimating genetic parameters and analyzing the path coefficient of the traits of the fruit yield and its components for the structures of the sweet grain (*Foeniculum vulgare* Mill)," *Samarra Journal of Pure and Applied Sciences*, vol. 5, no. 1, pp. 33-46, 2023.
A. Muhammad, "Determining economic threshold of downy brome (*Bromus tectorum* L.) in wheat (*Triticum aestivum* L.)," doi: 10.28941/24-1 (2018) -3, 2018.
K. P., V. Singh, G. Sharma, M. P. Chauhan, T. Singh, R. D. S., and Yadav, "Correlation and path coefficient analysis in wheat (*Triticum aestivum* L. em. Thell)," *International Journal of Current Microbiology and Applied Sciences*, doi: 10.20546/IJCMAS.2020.911.186, 2020.
R. Singh and R. Rajput, "Path analysis and genetic parameters for grain yield in bread wheat (*Triticum aestivum* L.)," *Annual Research & Review in Biology*, doi: 10.9734/ARRB/2019/V31I330050, 2019.
R. Ojha, A. Sarkar, A. Aryal, K. C. Rahul, S. Tiwari, M. Poudel, K. R. Pant, and J. Shrestha, "Correlation and path coefficient analysis of wheat (*Triticum aestivum* L.) genotypes," *Journal Title*, 2018.
D. Bisht, N. S. Dhaka, N. Kumar, R. Malik, and S. Kumar, "Path analysis studies of EMS-mutagenized mutant population of hexaploid wheat (*Triticum aestivum* L.)," *International Journal of Chemical Studies*, doi: 10.22271/CHEMI.2020.V8I6F.10799, 2020.
M. Nemati, N. Zare, N. Hedayat-Evrigh, and R. Asghari, "Meta-analysis of common wheat physiological response to biotic stresses," *Zemdirbyste-agriculture*, doi: 10.13080/z-a.2022.109.031, 2022.
A. Selvakumari, T. Schwinghamer, P. Dutilleul, and D. L. Smith, "Heterogeneous causal relationships between plant growth variables for biofertilized field-grown hard red spring wheat (*Triticum aestivum* [L.])," *Field Crops Research*, doi: 10.1016/J.FCR.2019.06.003, 2019.
T. F. Hussein, "Rivalry of wild horseradish *Raphanus raphanistrum* L. on the qualities of growing and producing wheat *Triticum durum* in Jebel Akhdar - Libya," *Scientific Journal of the Faculty of Agriculture, Cairo University*, vol. 52, no. 2, pp. 221-237, 2005.
F. C. Steward, "Analysis of growth," *Plant Physiology*, Academic Press, New York, vol. 46, pp. 17-22, 1969.