Improving water productivity in moisture-limited rice-based cropping systems through incorporation of maize and mungbean: A modelling approach

Amarasingha, R.P.R.K.; Suriyagoda, L. D. B.; Marambe, B.; Rathnayake, W. M. U. K.; Gaydon, Donald S.; Galagedara, Lakshman; Punyawardena, Ranjith; Silva, G.L.L.P.; Nidumolu, Uday; Howden, Mark

doi:10.1016/j.agwat.2017.05.002

Cited by 34 publications

(13 citation statements)

References 33 publications

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“…The APSIM phenology model is simple compared to more complex rate-based models [30,35]. However, the prediction of flowering and maturity times using the phenology model embedded in the APSIM model was found to be reasonably accurate [10,37]. In Chauhan and Rachaputi [37], the mungbean cultivar 'Crystal' required a total of 1200 • C d from sowing to maturity and this was similar to the older cultivar 'Emerald' already parametrised in APSIM.…”

Section: Crop Phenologymentioning

confidence: 92%

“…Notwithstanding a several-fold increase in mungbean production, the average yield of mungbean on Australian farms is still less than one t/ha, despite the yield potential for mungbean being around three t/ha [9]. Similar yields have also been harvested in Sri Lanka [10]. Even in trials conducted under relatively well-managed conditions, yield is low.…”

Section: Introductionmentioning

confidence: 99%

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Physiological and Agronomic Strategies to Increase Mungbean Yield in Climatically Variable Environments of Northern Australia

Chauhan¹,

Williams²

2018

Agronomy

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Mungbean (Vigna radiata (L.) Wilczek) in Australia has been transformed from a niche opportunistic crop into a major summer cropping option for dryland growers in the summer-dominant rainfall regions of Queensland and New South Wales. This transformation followed stepwise genetic improvements in both grain yields and disease resistance. For example, more recent cultivars such as 'Crystal', 'Satin II', and 'Jade-AU' have provided up to a 20% yield advantage over initial introductions. Improved agronomic management to enable mechanised management and cultivation in narrow (<50 cm) rows has further promised to increase yields. Nevertheless, average yields achieved by growers for their mungbean crops remain less than 1 t/ha, and are much more variable than other broad acre crops. Further increases in yield and crop resilience in mungbean are vital. In this review, opportunities to improve mungbean productivity have been analysed at four key levels including phenology, leaf area development, dry matter accumulation, and its partitioning into grain yield. Improving the prediction of phenology in mungbean may provide further scope for genetic improvements that better match crop duration to the characteristics of target environments. There is also scope to improve grain yields by increasing dry matter production through the development of more efficient leaf canopies. This may introduce additional production risks as dry matter production depends on the amount of available water, which varies considerably within and across growing regions in Australia. Improving crop yields by exploiting G × E × M interactions related to cultivar photo-thermal sensitivities and make better use of available water in these variable environments is likely to be a less risky strategy. Improved characterisation of growing environments using modelling approaches could also better define and identify the risks of major abiotic constraints. This would assist in optimising breeding and management strategies to increase grain yield and crop resilience in mungbean for the benefit of growers and the industry.

show abstract

Section: Crop Phenologymentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Physiological and Agronomic Strategies to Increase Mungbean Yield in Climatically Variable Environments of Northern Australia

Chauhan¹,

Williams²

2018

Agronomy

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“…Although Nelson et al (1998a,b) used APSIM to simulate a maize and Desmanthus virgatus intercrop system, the two crops were grown as monocultures and did use the CANOPY module. It was not clear whether Amarasingha et al (2017) used the CANOPY module when maize and mung bean intercrop systems were simulated in APSIM. In contrast, Knörzer et al (2011) found that APSIM was unable to simulate wheat-pea and maize-pea intercropping systems in Germany because it strongly underestimates the competitive ability of the species that was planted the first relative to the one that was planted last.…”

Section: Apsim Maize -Bambara Groundnut Intercrop Modelmentioning

confidence: 99%

Optimizing Traditional Cropping Systems Under Climate Change: A Case of Maize Landraces and Bambara Groundnut

Chimonyo

Wimalasiri²,

Kunz

et al. 2020

Front. Sustain. Food Syst.

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“…The APSIM phenology model is simple compared to more complex rate-based models (Summerfield and Lawn, 1987;Imrie and Lawn, 1990). However, the prediction of flowering and maturity times using the phenology model embedded in the APSIM model was found to be reasonably accurate (Chauhan and Rachaputi, 2014;Amarasingha et al, 2017). In Chauhan and Rachaputi (2014), the mungbean cultivar 'Crystal' required a total of 1200 °C d from sowing to maturity and this was similar to the older cultivar 'Emerald' already parametrised in APSIM.…”

mentioning

confidence: 92%

“…Notwithstanding a several-fold increase in mungbean production, the average yield of mungbean on Australian farms is still less than one t/ha, despite the yield potential for mungbean being around three t/ha (Thomas et al, 2004). Similar yields have also been harvested in Sri Lanka (Amarasingha et al, 2017). Even in trials conducted under relatively well-managed conditions, yield is low.…”

Section: Introductionmentioning

confidence: 99%

Physiological and Agronomic Strategies to Increase Mungbean Yield in Climatically Variable Environments of Northern Australia

Chauhan¹,

Williams²

2018

Preprint

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Mungbean [Vigna radiata (L.) Wilczek] in Australia has been transformed from a niche opportunistic crop into a major summer cropping option for dryland growers in the summer-dominant rainfall regions of Queensland and New South Wales. This transformation followed stepwise genetic improvements in both grain yields and disease resistance. For example, more recent cultivars such as 'Crystal', 'Satin II' and 'Jade-AU' have provided up to a 20% yield advantage over initial introductions. Improved agronomic management to enable mechanised management and cultivation in narrow (<50 cm) rows has further promised to increase yields.Nevertheless, average yields achieved by growers for their mungbean crops remain less than 1 t/ha, and are much more variable than other broad acre crops. Further increases in yield and crop resilience in mungbean are vital. In this review, opportunities to improve mungbean have been analysed at four key levels including phenology, leaf area development, dry matter accumulation and its partitioning into grain yield. Improving the prediction of phenology in mungbean may provide further scope for genetic improvements that better match crop duration to the characteristics of target environments. There is also scope to improve grain yields by increasing dry matter production through the development of more efficient leaf canopies. This may introduce additional production risks as dry matter production depends on the amount of available water, which varies considerably within and across growing regions in Australia. Improving crop yields by exploiting photo-thermal sensitivities to increase dry matter is likely a less risky strategy for these variable environments. Improved characterisation of growing environments using modelling approaches could also better define and identify the risks of major abiotic constraints. This would assist in optimising breeding and management strategies to increase grain yield and crop resilience in mungbean for the benefit of growers and industry.

show abstract

Improving water productivity in moisture-limited rice-based cropping systems through incorporation of maize and mungbean: A modelling approach

Cited by 34 publications

References 33 publications

Physiological and Agronomic Strategies to Increase Mungbean Yield in Climatically Variable Environments of Northern Australia

Physiological and Agronomic Strategies to Increase Mungbean Yield in Climatically Variable Environments of Northern Australia

Optimizing Traditional Cropping Systems Under Climate Change: A Case of Maize Landraces and Bambara Groundnut

Physiological and Agronomic Strategies to Increase Mungbean Yield in Climatically Variable Environments of Northern Australia

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