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Sugarcane: Contribution of Process-Based Models for Understanding and Mitigating Impacts of Climate Variability and Change on Production

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Abstract

Sugarcane is cultivated on about 26 M ha across tropics and subtropics worldwide as a source of many industrial products, especially sugar and also bioenergy purposes (biofuel as ethanol and electricity). As the crop is grown in a wide range of climates, soils, and countries, different cropping systems are adopted across producing areas, resulting in large genotype × environment × management interactions, consequently large variations in yield levels are found. Climate and its variability and change play an important role in plant processes. In this chapter, a climate characterization of the main producing countries is presented along with the influence of main weather variables on sugarcane growth, development, and yields. The key variables of climate change are also explored. The effect of weather conditions on key sugarcane yield-building processes are well captured by process-based models. Two are embedded in the well-known and readily available agricultural systems modeling platforms; DSSAT/CANEGRO and APSIM-Sugar. These two models and a third (WaterSense) are described briefly with highlights of recent improvements and weaknesses. Finally, this chapter lists a series of application papers found so far in literature that included, at least to some extent, the intrinsic effect of climate and its variability mostly based on long-term weather data series. Special focus is then given to irrigation and nitrogen management, yield analysis (gaps, benchmarking, and forecasting), climate change issues, drought adaptation, and breeding studies. Even though sugarcane models have some weaknesses, they are considered as powerful tools for understanding and proposing management and adaptive actions to mitigate or increase yields in risky climates, in the present or future.

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Acknowledgments

This contribution was not funded by any institution. However, the first author (HBD) is truly grateful to the São Paulo Research Foundation (FAPESP), which facilitated his studies in sugarcane agrometeorology, physiology, and modeling in the past few years through the grants #2014/05173-3, #2016/11170-2, and #2017/24424-5.

Climate data used in Fig. 8.2 were obtained from the NASA Langley Research Center (LaRC) POWER Project funded through the NASA Earth Science/Applied Science Program.

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  1. Biosystems Engineering Department, “Luiz de Queiroz” College of Agriculture, University of São Paulo, Piracicaba, SP, Brazil

    Henrique Boriolo Dias

  2. College of Science, Technology and Engineering, James Cook University, Townsville, QLD, Australia

    Geoff Inman-Bamber

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Correspondence to Henrique Boriolo Dias .

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  1. Department of Agricultural Research for Northern Sweden, Swedish University of Agricultural Sciences, Umeå, Sweden, Department of Agronomy, Pir Mehr Ali Shah Arid Agriculture University, Rawalpindi, Pakistan

    Mukhtar Ahmed

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Dias, H.B., Inman-Bamber, G. (2020). Sugarcane: Contribution of Process-Based Models for Understanding and Mitigating Impacts of Climate Variability and Change on Production. In: Ahmed, M. (eds) Systems Modeling. Springer, Singapore. https://doi.org/10.1007/978-981-15-4728-7_8

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