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Interference of junglerice (Echinochloa colona) in mung bean

Published online by Cambridge University Press:  13 May 2022

Gulshan Mahajan*
Affiliation:
Adjunct Associate Professor, Centre for Crop Science, Queensland Alliance for Agriculture and Food Innovation (QAAFI), University of Queensland, Gatton, QLD, Australia; 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; Adjunct Professor, Department of Agronomy, Chaudhary Charan Singh Haryana Agricultural University, Hisar, Haryana, India
*
Author for correspondence: Gulshan Mahajan, Centre for Crop Science, Queensland Alliance for Agriculture and Food Innovation (QAAFI), University of Queensland, Gatton, QLD 4343, Australia. (Email: g.mahajan@uq.edu.au)
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Abstract

Junglerice [Echinochloa colona (L.) Link] is increasing its prevalence in eastern Australia by adapting to Australia’s changing climatic conditions and conservation agricultural systems and by evolving resistance to glyphosate. Information is limited on the growth and seed production dynamics of E. colona when it interferes with mung bean [Vigna radiata (L). R. Wilczek], a major potential export crop for eastern Australia. This field study examined the interference of E. colona in mung bean for two summer seasons (2020 and 2021) at Gatton, QLD. Different infestation levels (0, 2, 4, 8, 16, and 32 plants m−2) of E. colona were assessed for their potential to cause yield reductions in mung bean. Seed yield of mung bean was highest in the weed-free plots (2,767 kg ha−1) and declined by 20%, 27%, 34%, and 43% at weed infestation levels of 4, 8, 16, and 32 plants m−2, respectively. Echinochloa colona biomass in mung bean varied from 11 to 137 g m−2 as weed density increased from 2 to 32 plants m−2. Based on a three-parameter hyperbolic rectangular decay model, crop yield loss was 52% and 57%, respectively, when weed density and weed biomass approached maximum. Echinochloa colona at the highest density (32 plants m−2) produced a maximum of 15,140 seeds m−2, and this seed production was reduced by 50% at a weed density of 10 plants m−2. Echinochloa colona plants retained 63% to 68% seeds at mung bean maturity, indicating a great opportunity for harvest weed seed control. This study suggests that a high infestation of E. colona in mung bean fields could cause a substantial yield loss and increase the weed seedbank.

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), 2022. Published by Cambridge University Press on behalf of the Weed Science Society of America
Figure 0

Figure 1. Weather conditions in Gatton, QLD, Australia, during crop seasons of mung bean.

Figure 1

Table 1. Effect of Echinochloa colona density on weed parameters and seed yield in mung bean.

Figure 2

Figure 2. Effect of Echinochloa colona density on mung bean seed yield as a percent of weed-free control. Symbols indicate means from a total of six replications in 2020 and 2021, and the response was fit using a three-parameter hyperbolic decay model (Equation 2).

Figure 3

Figure 3. Effect of Echinochloa colona biomass on mung bean seed yield as a percent of weed-free control. Symbols indicate means from a total of six replications in 2020 and 2021, and the response was fit using a three-parameter hyperbolic decay model (Equation 2).

Figure 4

Figure 4. Effect of Echinochloa colona density on weed seed production. Symbols indicate means from a total of six replications in 2020 and 2021, and the response was fit using a three-parameter logistic model (Equation 3).

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