Refining the Canegro model for improved simulation of climate change impacts on sugarcane

Abstract

Crop models can be used for predicting climate change impacts and exploring adaptation strategies, but their suitability for such tasks needs to be assessed. Although the DSSAT-Canegro model has been used widely for climate impact studies, some shortcomings have been revealed. The objectives were to improve and evaluate the capability of DSSAT-Canegro to predict crop responses to climate change. Model changes included improved simulation of elevated temperature and atmospheric CO 2 concentration ([CO2]) impacts, and revised algorithms for tillering, respiration and crop water relations. After calibration, the refined model was tested against an independent set of experimental data, demonstrating acceptable simulation accuracy for aerial dry mass, stalk dry mass and stalk sucrose mass (RMSE = 8.4, 5.2 and 3.3 t/ha respectively). A multiple-site sensitivity analysis revealed that simulated responses by the refined model, of canopy formation, crop water use, crop water status and stalk dry mass to changes in rainfall, temperature and [CO2], were more realistic than those of the old model. Highest average simulated stalk mass was achieved at a temperature regime that was 3 °C warmer than current climate, with yield increases ranging from 0.7% (irrigated Ligne Paradis, Reunion Island) to 7% (rainfed Piracicaba, Brazil). Elevated [CO2] increased yields for rainfed production only (7% for La Mercy, South Africa and 6% for Piracicaba, [CO2] = 750 ppm), through reduced transpiration and improved crop water status. The study highlighted the need for improvements in simulating reduced growth of older crops, and [CO2] effects on transpiration. This study has delivered an improved Canegro model that represents plant processes and their interactions with climatic drivers more Highlights  The refined DSSAT-Canegro predicts stalk dry mass to within 6 t/ha  The refined DSSAT-Canegro has improved capability for simulating climate change impacts.  Model changes address temperature responses, water relations, respiration, tillering.  Multi-site sensitivity analysis shows plausible responses to climate change factors.

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

“…While Tb can be changed in APSIM-Sugar software, such changes will affect all expansive growth processes. Tb for sprouting and tillering is clearly higher than for leaf appearance and elongation (Inman-Bamber, 1994;Singels and Smit, 2009) and this needs to be captured in future revisions of APSIM-Sugar for yield projections, especially under climate change (Jones and Singels, 2018;Wang et al, 2017).…”

“…Smit (2010) showed that for South African varieties grown in a glasshouse, the Tb for shoot emergence ranged between 16.8 and 18.1°C, much higher than the Tb adopted in APSIM-Sugar (9°C) and CANEGRO (10°C). The new version of CANEGRO now considers 16°C as Tb for this process (Jones and Singels, 2018). Tb cannot be varied for different processes of expansive growth in APSIM-Sugar.…”

“…These crop models are useful tools for several applications in research and decision T making in different sectors, such as consulting, agroindustry, government and policy makers (Lisson et al, 2005;Singels, 2014). There are several crop models dedicated to sugarcane, but those used most worldwide are DSSAT/CANEGRO (Inman-Bamber, 1991;Jones et al, 2003;Jones and Singels, 2018;Singels et al, 2008) and APSIM-Sugar (Holzworth et al, 2014;Inman-Bamber et al, 2016;Keating et al, 1999;McCown et al, 1996;Thorburn et al, 2005). The use of APSIM-Sugar has increased in Brazil recently.…”

“…Currently, the challenges in sugarcane modelling community are to simulate variety differences (Hoffman et al, 2018;Sexton et al, 2016;Singels, 2014), sucrose dynamics (O'Leary, 2000;Singels, 2014;Singels and Inman-Bamber, 2011), crop responses to carbon dioxide (Jones and Singels, 2018;Stokes et al, 2016) and genetic links (Singels, 2014). Another challenge for sugarcane modelling is the reduced growth phenomenon (RGP) (Park et al, 2005).…”

Condição hidráulica determinante à ocorrência de estresse hídrico na cultura da cana-de-açúcar

“…A utilização de modelos de simulação de culturas possibilita a individualização da influência de fatores ambientais e a determinação de parâmetros que governam a simulação de processos físicos e fisiológicos que compõem o crescimento e o desenvolvimento das plantas. No tocante à pesquisa científica, os modelos de simulação têm sido amplamente empregados para a comparação de manejos nutricionais, análise dos efeitos do déficit hídrico no rendimento das culturas, planejamento do uso da água, avaliação do efeito de alterações climáticas na produtividade das culturas, entre outras aplicações, tanto no Brasil, como no exterior (SCARPARE, 2011;SINGELS, 2018;RUAN et al;HU et al, 2019). Portanto, os modelos constituem uma ferramenta útil e indispensável, na medida em que o desempenho das culturas depende de interações complexas entre aspectos edáficos e condições meteorológicas, bem como de decisões sobre o seu manejo.…”