New APSIM-Sugar features and parameters required to account for high sugarcane yields in tropical environments

Dias, Henrique Boriolo; Inman-Bamber, N. G.; Bermejo, Rodrigo; Sentelhas, Paulo César; Christodoulou, Diomedes

doi:10.1016/j.fcr.2019.02.002

Cited by 31 publications

(10 citation statements)

References 67 publications

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“…Then it simulates the key outputs (fresh cane yield, sugar yield, and sucrose contents) [2,7]. This process is controlled by environmental (soil and climate), plant or ratoon, and cultivar-specific parameters [7,25,26].…”

Section: Apsim Simulationmentioning

confidence: 99%

Sensitivity Analysis of Plant- and Cultivar-Specific Parameters of APSIM-Sugar Model: Variation between Climates and Management Conditions

et al. 2019

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With increasing demand for food and energy, there is a great need for improving sugarcane productivity. New cultivars and management strategies can be assessed using process-based crop models. Information on cultivars needs to be updated frequently, but it is still limited in most crop models. Therefore, it is important to identify possible candidates for varietal parameterization and calibration. Because sensitivity analysis is computationally expensive, we used a less expensive emulator-based approach to conduct a global sensitivity analysis using the apsimr package and GEM-SA software. We studied the sensitivity of four yield outputs of the APSIM-Sugar model to 13 parameters in rainfed and irrigated conditions in Japan and Sri Lanka. Unlike previous studies, our aim was to give comprehensive insights into the variation in sensitivity due to variation in climate. The results confirmed distinct variation of parameter influence between climates and between management conditions. We identify possible candidates for parameterization and calibration of new cultivars for APSIM-Sugar under different environments, and show the effect of variation in climate on variation in parameter influence under different management conditions. It was confirmed that both radiation use efficiency and transpiration efficiency were sensitive and have to be examined to use new cultivars, though these are not listed as cultivar parameters.

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Section: Apsim Simulationmentioning

confidence: 99%

Sensitivity Analysis of Plant- and Cultivar-Specific Parameters of APSIM-Sugar Model: Variation between Climates and Management Conditions

et al. 2019

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“…As APSIM underestimated the growth and yield, we modified the RUE like-minded (Gunarathna et al 2019) and (Sexton et al 2017). (Dias et al 2019) also suggested substantial changes to enable APSIM-Sugar to simulate canopy and yield of Brazilian genotypes. We increased the maximum RUE values up to 2.0, confining the findings of (Muchow et al 1997;De Silva and De Costa 2012).…”

Section: Apsim Simulationmentioning

confidence: 99%

Simulation of Sugarcane Growth and Yield Under Optimized Subsurface Irrigation System

Gunarathna

Kumari

2021

Preprint

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The optimized subsurface irrigation system (OPSIS) is a newly developed subsurface irrigation system to irrigate upland crops. Although it is already evaluated for few crops using field experiments, further evaluation is required. Since field experiments are tedious, expensive, we need an alternative approach to evaluate the OPSIS. A well-calibrated and validated crop model is a fast-alternative option for developing and evaluating agronomic practices. Therefore, this study aimed to develop the modeling capabilities of APSIM to simulate the OPSIS. We conducted field experiments for three growing seasons (main crop and two ratoons), two planting seasons (spring and summer planting), and two separate crops to collect necessary data for calibration and validation processes. We scripted a new module named "OPSIS" to couple OPSIS to the APSIM engine. We parameterized, calibrated, and validated the APSIM to simulate the growth and yield of sugarcane with OPSIS. After firm parameterization and calibration, APSIM-Sugar can successfully simulate the growth and yield of sugarcane with OPSIS. However, the simulation of soil moisture dynamics and irrigation water use were not up to the standards. Although it gives quite reasonable results for growth and yield simulations of sugarcane, further studies are suggested to develop the simulation accuracy of soil water dynamics and irrigation water use through the OPSIS.

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“…Changes to APSIM's standard release sugarcane model (Keating et al, 1999) include reductions in radiation use efficiency for the tropical environments of Tully and Mackay farms (Dias et al, 2019) and the effect of storms on crop lodging following Inman-Bamber et al ( 2004). Mill mud is applied in APSIM as surface organic matter with a chemical composition taken from Thorburn et al (2008) and set at 23.1 and 31.7 NH4 and NO3 ppm respectively.…”

Section: Sugarcane Farmsmentioning

confidence: 99%

Modelling to determine key drivers of water quality off sugarcane paddocks in the Great Barrier Reef catchment

2021

MODSIM2021, 24th International Congress on Modelling and Simulation.

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Reducing pollutants, such as nitrogen and sediment from sugarcane lands, in the Great Barrier Reef catchment is important for protecting the resilience of the World Heritage listed ecosystem. Modelling is used to predict the change in water quality in response to typical changes in sugarcane management. To accomplish this, workshops were conducted with groups of 15 to 20 industry experts in each of the major sugarcane growing regions and a range of typical agronomic management, appropriate for each region, was elicited. APSIM was used to simulate a farm in each of the three regions Burdekin Delta, Mackay, and Tully, to estimate the expected pollutant loads from each farm. Each in silico farm is represented by a combination of soil, climate and the range of management derived from the workshops. Simulated pollutants include erosion and dissolved inorganic nitrogen (DIN), from both leaching below the root zone and in runoff. To quantify and rank the effect of changes in management on pollutants exiting farms least squared regressions were estimated using model output. Results are presented for the key management of nutrient and irrigation rates, tillage, and fallow crop scenarios. We found the rate of applied mill mud had the greatest effect on DIN exiting sugarcane paddocks both via leaching and in runoff (Figure 1) and the amount of tillage had the greatest effect on erosion (Figure 2).

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New APSIM-Sugar features and parameters required to account for high sugarcane yields in tropical environments

Cited by 31 publications

References 67 publications

Sensitivity Analysis of Plant- and Cultivar-Specific Parameters of APSIM-Sugar Model: Variation between Climates and Management Conditions

Sensitivity Analysis of Plant- and Cultivar-Specific Parameters of APSIM-Sugar Model: Variation between Climates and Management Conditions

Simulation of Sugarcane Growth and Yield Under Optimized Subsurface Irrigation System

Modelling to determine key drivers of water quality off sugarcane paddocks in the Great Barrier Reef catchment

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