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Interference of Brassicaceae weeds (Brassica tournefortii, Rapistrum rugosum, and Sisymbrium thellungii) in chickpea

Published online by Cambridge University Press:  09 August 2023

Gulshan Mahajan*
Affiliation:
Adjunct Faculty, Centre for Crop Science, Queensland Alliance for Agriculture and Food Innovation (QAAFI), University of Queensland, Gatton, QLD, Australia; and Principal Agronomist, Punjab Agricultural University, Ludhiana, Punjab, India
Bhagirath Singh Chauhan
Affiliation:
Professor, Centre for Crop Science, Queensland Alliance for Agriculture and Food Innovation (QAAFI) and School of Agriculture and Food Sciences (SAFS), University of Queensland, Gatton, QLD, Australia; and Adjunct Professor, Department of Agronomy, Chaudhary Charan Singh Haryana Agricultural University, Hisar, Haryana, India
*
Corresponding author: Gulshan Mahajan; Email: g.mahajan@uq.edu.au
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Abstract

African mustard (Brassica tournefortii Gouan), turnipweed [Rapistrum rugosum (L.) All.], and African turnipweed (Sisymbrium thellungii O.E. Schulz) are common broadleaf weeds in chickpea (Cicer arietinum L.) crops, particularly under dryland region conditions in eastern Australia. Information on crop yield losses and the seed production potential for these weeds in chickpea are limited. Field studies were conducted in the winter seasons of 2020 and 2021 in eastern Australia with different densities of the three weeds (B. tournefortii, R. rugosum, and S. thellungii) in chickpea. Based on the sigmoidal model, chickpea yield was reduced by 50% at 11 plants m−2 of B. tournefortii. Based on hyperbolic models, a 50% yield reduction of chickpea occurred at 5 and 25 plants m−2 of R. rugosum and S. thellungii, respectively. Based on the linear model, B. tournefortii, R. rugosum, and S. thellungii produced a maximum of 448,000, 206,700, and 869,400, seeds m−2, respectively. At chickpea harvest, the low seed retention (<55%) of B. tournefortii and S. thellungii suggests limited opportunities for harvest weed seed control, and the seed rain of these weeds may enrich the weed seedbank in the soil. At crop harvest, the seed retention of R. rugosum was found to be greater than 90%, suggesting that it is a suitable candidate for harvest weed seed control. This study demonstrated that R. rugosum could cause a greater reduction in chickpea yield compared with B. tournefortii and S. thellungii. Furthermore, restricting seed rain of B. tournefortii and S. thellungii by not allowing the plants to produce seeds is recommended to reduce their weed seedbanks in the soil. The information generated from this study could aid in strengthening integrated weed management in chickpea.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of the Weed Science Society of America
Figure 0

Figure 1. Air temperature and rainfall during the crop seasons (May–October) of chickpea for 2020 and 2021 at the University of Queensland, Gatton, Australia.

Figure 1

Table 1. Effect of Brassica tournefortii density on weed parameters and chickpea yield attributes and seed yield.a

Figure 2

Figure 2. Chickpea yield reduction as a percent of weed-free control in response to weed densities of (A) Brassica tournefortii, (B) Rapistrum rugosum, and (C) Sisymbrium thellungii. Relationships are described with a sigmoidal model for B. tournefortii and with modified rectangular hyperbolic models for R. rugosum and S. thellungii.

Figure 3

Table 2. Effect of Rapistrum rugosum density on weed parameters, and chickpea yield attributes and seed yield.a

Figure 4

Table 3. Effect of Sisymbrium thellungii density on weed parameters and chickpea yield attributes, and seed yield.a

Figure 5

Figure 3. Weed seed production in response to weed densities of (A) Brassica tournefortii, (B) Rapistrum rugosum, and (C) Sisymbrium thellungii. The lines represent a linear model fit to the data.