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Title: Developing a Multi-Species Weed-Control Threshold Model for High-Yielding Irrigated Cotton
Contributor(s): Charles, Graham William  (author); Sindel, Brian  (supervisor)orcid ; Cowie, Annette  (supervisor); Knox, Oliver  (supervisor)orcid 
Conferred Date: 2021-02-23
Copyright Date: 2020
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Related DOI: 10.1017/wet.2019.35
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Glyphosate tolerant and resistant weeds are becoming increasingly problematic in cotton fields in Australia, necessitating a return to a more integrated weed management (IWM) system. Ideally, an IWM system will combine the judicious use of herbicides with mechanical and cultural approaches to weed control, to optimise production, and minimise selection for herbicide resistance and negative off-target impacts. The development of an IWM system for cotton can be facilitated by identifying the critical period for weed control (CPWC), a concept that enables cotton growers to optimize the timing of their weed control inputs. CPWC models are commonly developed for specific weed and crop combinations, but the results from these studies are generally specific to the site, season and species tested. No CPWC model, applicable to multiple weed species, has been developed thus far. In order to explore the potential to create a multi-species CPWC model, applicable to a range of weeds in high yielding, fully irrigated Australian cotton, we developed CPWC models using mimic weeds with widely differing morphological and physiological traits. We then combined the information from our individual mimic weeds and from this data, developed, and tested, a multi-species weed control model. Thus, we achieved the aim of this research, to test the hypothesis that a statistically valid multi-species weed-control threshold model for weeds of irrigated cotton could be developed, integrating aspects of weed size and density, and that such a model could be applied across seasons.

Crop plants have been used as mimic weeds to substitute for real weeds in many competition studies. These mimic weeds have the advantages of availability of seed, uniform germination and growth, and potentially conferring better experimental controllability and repeatability. However, the underlying assumption that the competitive effects of mimic weeds are similar to real weeds had not been tested. We compared a range of morphological traits (plant height, node and leaf number, leaf area, leaf size and dry weight) between the mimic weeds and real weeds: Japanese millet vs. awnless barnyard grass; mungbean vs. bladder ketmia; and sunflower vs. fierce thornapple. The impact of these mimic and real weeds on cotton plant height, node and leaf number, leaf area, leaf size, dry weight, lint yield and ginning percentage was also assessed. There were similarities and differences between the mimic and real weeds, but their impact on cotton lint yield was most closely associated with weed height and dry weight at mid-season. We concluded from this research that mimic weeds could be satisfactorily substituted for real weeds in competition experiments where seasonal and environmental conditions are not limiting, such as with fully irrigated cotton, provided the plants have similar dry weight and height at mid-season, or one can account for the differences in dry weight and height. A more generalised relationship estimating the yield loss of high yielding, irrigated cotton from weed competition over a range of weed dry weights and heights was defined, allowing the competitive effects of a range of weeds to be extrapolated from the results of mimic weeds.

Based on our findings that mimic weeds could be satisfactorily substituted for real weeds in competition experiments, field studies were conducted over six seasons to determine the critical period for weed control (CPWC) in high-yielding, irrigated cotton, using sunflower, Japanese millet, and mungbean as mimic weeds. Mimic weeds were planted with or after cotton emergence at densities of: 1, 2, 5, 10, 20 and 50 plants m−2 (sunflower); 10, 20, 50, 100 and 200 plants m−2 (Japanese millet); and 1, 3, 6, 15, 30 and 60 plants m−2 (mungbean). Weeds were added and removed at approximately 0, 150, 300, 450, 600, 750 and 900 growing degree days (GDD) after planting.

High levels of intraspecific and interspecific competition occurred at the highest weed densities, with increases in weed biomass and reductions in crop yield not proportional to the changes in weed density. The data were fitted to extended Gompertz and logistic curves including weed density as a covariate, allowing a dynamic CPWC to be estimated for the observed weed densities. Using a 1% yield-loss threshold, the CPWC extended from before crop emergence through to 836 GDD, and full-season, from before crop emergence through to crop harvest for one and 35 or more sunflower plants m−2, respectively. Japanese millet also competed strongly with cotton, with season-long competition resulting in an 84% reduction in cotton yield with 200 Japanese millet plants m−2. Using a 1% yield-loss threshold, the CPWC commenced at 65 GDD, corresponding to 0 to 7 days after crop emergence (DAE), and ended at 803 GDD, 76 to 98 DAE with 10 Japanese millet plants m−2 , and 975 GDD, 90 to 115 DAE with 200 Japanese millet plants m−2 . Similarly, mungbean competed strongly with cotton, with season-long interference at densities of 60 mungbean plants m−2 resulting in an 84% reduction in cotton yield. Using a 1% yield-loss threshold, the CPWC extended for the full growing season of the crop at all weed densities. The minimum yield loss from a single weed control input was 35% at the highest weed density of 60 mungbean plants m−2 . The relationship for the critical time of weed removal was further improved by substituting weed biomass for weed density in the relationship.

Using data from these field studies, a multi-species CPWC model was developed from the combined data sets for sunflower, Japanese millet and mungbean competing in cotton, using weed height and weed biomass as additional descriptors in the models. Comparison of observed and predicted relative cotton lint yields from the multi-species CPWC model demonstrated that the single model reasonably described the competition from these three very different mimic weeds, opening the possibility for cotton growers to use a multi-species CPWC model to determine the timing of weed control inputs in cotton fields.

Application of our multi-species weed threshold model in Australian cotton will facilitate the optimisation of the timing of weed control inputs and the prioritisation of fields for weed control. This will lead to further improved crop yields and improved economic returns to cotton growers, with benefits flowing through to other crops in the cropping system. Further, our approach should be applicable to other intensively farmed, fully irrigated crops, where crop yields are not highly influenced by environmental variability, such as many of the horticultural crops.

Publication Type: Thesis Doctoral
Fields of Research (FoR) 2020: 300403 Agronomy
300407 Crop and pasture nutrition
300409 Crop and pasture protection (incl. pests, diseases and weeds)
Socio-Economic Objective (SEO) 2020: 260602 Cotton
Rights Statement: Awarded the Chancellor's Doctoral Research Medal on 23rd February, 2021.
HERDC Category Description: T2 Thesis - Doctorate by Research
Description: Please contact if you require access to this thesis for the purpose of research or study.
Appears in Collections:School of Environmental and Rural Science
Thesis Doctoral

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