Skip to main content

Advertisement

Log in

Application of CSM-CANEGRO Model for Climate Change Impact Assessment and Adaptation for Sugarcane in Semi-arid Environment of Southern Punjab, Pakistan

  • Research
  • Published:
International Journal of Plant Production Aims and scope Submit manuscript

Abstract

Climate change is a severe threat for productivity of sugarcane crop. Crop models have potential to quantify the climate change impacts, and management practices effects on development and productivity of sugarcane crop. These models provide simulations as a result of interaction between genotype, management, and environment. The current study was conducted with the objectives to (1) calibration, evaluation and application of CSM-CANEGRO-Sugarcane model (2) climate change assessment and make adaptation strategies for industrial (spring and autumn crops) and non-industrial (summer crop) sugarcane. Two field experiments regarding industrial sugarcane were carried out at Multan during 2013–2014 and 2014–2015 and two field experiments regarding ponda chewing sugarcane (non-industrial, thick, soft and juicier sugarcane) at Vehari during 2017 and 2018. Calibration and evaluation of CSM-CANEGRO-Sugarcane model showed that all model statistical parameters were obtained under acceptable range. Model sensitivity was also evaluated against Carbon, Temperature and Water analysis for both sites. Results revealed that average temperature is increased almost 0.94 °C during baseline weather data (1980–2018), while according to different climate projections by Global Climate Models (GCMs), average temperature 3–5 °C can be increase during mid-century. So, without adaptation strategies, fresh cane yield will be decreased ranging from 15.31 to 22.57% at different GCMs during mid-century (2039–2069). Adaptation strategies; like 18–25 days earlier planting, increasing 15% N application quantity and increasing frequency of irrigation and growing heat tolerant and more growing degree days requiring varieties can compensate the negative impact of climate change in future scenario.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Source: Modified and adopted from Dias et al., 2021)

Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

References

  • Ahmed, M., Ahmad, S. (2019). Carbon dioxide enrichment and crop productivity. In M. Hasanuzzaman, (Eds.), Agronomic Crops (pp. 31–46); Volume 2 Springer Nature Singapore Pte Ltd. https://link.springer.com/chapter/10.1007/978-981-32-9783-8_3.

  • Ahmed, M., Ahmad, S. (2020). Systems Modeling. In M. Ahmed, (Ed.), Systems Modeling, Springer Nature Singapore Pte Ltd. https://doi.org/10.1007/978-981-15-4728-7_1.

  • Ahmad, S., Nadeem, M., Abbas, G., Fatima, Z., Khan, R. J., Ahmed, M. et al. (2017). Quantification of the effects of climate warming and crop management on sugarcane phenology. Climate Research, 71(1), 47–61.

    Article  Google Scholar 

  • Ahmed, M., Ahmad, S., Raza, M. A., Kumar, U., Ansar, M., Shah, G. A. et al. (2020). Models calibration and evaluation. In M, Ahmed, (Ed.), Systems Modeling (pp. 151–178); Springer Nature Singapore Pte Ltd. https://doi.org/10.1007/978-981-15-4728-7_5.

  • Ahmad, I., Ahmad, B., Boote, K. J., & Hoogenboom, G. (2020). Adaptation strategies for maize production under climate change for semiarid environments. European Journal of Agronomy, 115, 126040.

    Article  CAS  Google Scholar 

  • Ahmed, M., Ahmad, S., Fahad, S., Fayyaz-Ul-Hassan. (2021). Potential applications of DSSAT, AquaCrop, APSIM models for crop water productivity and irrigation scheduling. In M. R. Goyal, & L. I. P. Ray (eds.) Fertigation Technologies For Micro Irrigated Crops. CRC Press, Taylor & Franis Group.

  • Allen, L. H., Jones, P. & Jones, J. W. (1985). Rising atmospheric CO2 and evapotranspiration. Proc. Natl. Conf. on Advances in Evapotranspiration, Chicago, IL, 16–17 December 1985. ASAE, St Joseph, MI, pp. 13–27.

  • Baez-Gonzalez, A. D., Kiniry, J. R., Meki, M. N., Williams, J. R., Cilva, M. A., Gonzalez, J. L. R., et al. (2018). Potential impact of future climate change on sugarcane under dryland conditions in Mexico. Journal of Agronomy and Crop Science, 204(5), 515–528.

    Article  Google Scholar 

  • Bhengra, A. H., Yadav, M. K., Patel, C., Singh, P. K., Singhand, K. K., & Singh, R. S. (2016). Calibration and validation study of sugarcane (DSSAT-CANEGRO V4. 6.1) model over North Indian region. Journal of Agrometeorology, 18(2), 234.

    Article  Google Scholar 

  • Biggs, J. S., Thorburn, P. J., Crimp, S., Masters, B., & Attard, S. J. (2013). Interactions between climate change and sugarcane management systems for improving water quality leaving farms in the Mackay Whitsunday region, Australia. Agriculture, Ecosystems and Environment, 180, 79–89.

    Article  CAS  Google Scholar 

  • Bonnett, G. D. (2014). Developmental stages (phenology). In P. H. Moore & F. C. Botha (Eds.), Sugarcane: Physiology, biochemistry, and functional biology (pp. 35–53). Wiley.

    Google Scholar 

  • Bonnett, G. D., Hewitt, M. L., & Glassop, D. (2006). Effects of high temperature on the growth and composition of sugarcane internodes. Australian Journal of Agricultural Research, 57(10), 1087–1095.

    Article  Google Scholar 

  • Boote, K. J., Adam, M., Ahmad, I., Ahmad, S., Cammarano, D., Chattha, A. A. et al. (2021). Understanding differences in climate sensitivity simulations of APSIM and DSSAT crop models. In C. Rosenzweig, C. Z. Mutter, & E. M. Contreras, (Eds.), Handbook of Climate Change and Agroecosystems; Climate Change and Farming System Planning in Africa and South Asia: AgMIP Stakeholder-driven Research (Part-1), (pp. 15–46). https://doi.org/10.1142/9781786348791_0002.

  • Christina, M., Jones, M. R., Versini, A., Mézino, M., Le Mezo, L., Auzoux, S., Soulie, J. C., Poser, C., & Gérardeaux, E. (2021). Impact of climate variability and extreme rainfall events on sugarcane yield gap in a tropical Island. Field Crops Research, 274, 108326.

    Article  Google Scholar 

  • de Medeiros Silva, W. K., de Freitas, G. P., Junior, L. M. C., de Almeida Pinto, P. A. L., & Abrahão, R. (2019). Effects of climate change on sugarcane production in the state of Paraíba (Brazil): A panel data approach (1990–2015). Climatic Change, 154, 195–209.

    Article  Google Scholar 

  • Deressa, T., Hassan, R., & Poonyth, D. (2005). Measuring the impact of climate change on South African agriculture: The case of sugarcane growing regions. Agrekon, 44(4), 524–542.

    Article  Google Scholar 

  • 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 M. Ahmed (Ed.), Systems modeling (pp. 217–260). Springer.

    Chapter  Google Scholar 

  • Dias, H. B., Sentelhas, P. C., Inman-Bamber, G., & Everingham, Y. (2021). Sugarcane yield future scenarios in Brazil as projected by the APSIM-Sugar model. Industrial Crops and Products, 171, 113918.

    Article  Google Scholar 

  • Dunne, J. P., John, J. G., Adcroft, A. J., Griffies, S. M., Hallberg, R. W., Shevliakova, E., et al. (2012). GFDL’s ESM2 global coupled climate–carbon earth system models. Part I: Physical formulation and baseline simulation characteristics. Journal of Climate, 25, 6646–6665.

    Article  Google Scholar 

  • Farooq, O., Sarwar, N., Yasir, T. A., Iqbal, M. M., Naz, T. et al. (2019). Advanced production technology of sugar crops. In M. Hasanuzzaman, (Ed.), Agronomic Crops, Volume 1: Production Technologies (pp. 335–361). Springer Singapore.

  • Farooq, N., & Gheewala, S. H. (2020). Assessing the impact of climate change on sugarcane and adaptation actions in Pakistan. Acta Geophysica, 68, 1489–1503.

    Article  Google Scholar 

  • Fatima, Z., Naz, S., Iqbal, P., Khan, A., Ullah, H., Abbas, G. et al. (2022). Field crops and climate change. In W. N. Jatoi, M. Mubeen, A. Ahmad, M. A. Cheema, Z. Lin, & M. Z. Hashmi, (Eds.), Building Climate Resilience in Agriculture (pp. 83–94). Sringer Nature, Switzerland. https://doi.org/10.1007/978-3-030-79408-8_6.

  • Gordon, H. B., O’Farrell, S., Collier, M., Dix, M., Rotstayn, L., & Kowalczyk, E., et al. (2010). The CSIRO Mk3. 5 climate model. CSIRO and Bureau of Meteorology.

  • Hoogenboom, G., Porter, C. H., Shelia, V., Boote, K. J., Singh, U., & White, J. W., et al. (2019a). Decision Support System for Agrotechnology Transfer (DSSAT) Version 4.7.5 (https://DSSAT.net). DSSAT Foundation.

  • Hoogenboom, G., Porter, C. H., Boote, K. J., Shelia, V., Wilkens, P. W., Singh, U. et al. (2019b). The DSSAT crop modeling ecosystem. In K. J. Boote, (Ed.), Advances in Crop Modeling for a Sustainable Agriculture (pp. 173–216). Burleigh Dodds Science Publishing, Cambridge, United Kingdom. https://doi.org/10.19103/AS.2019.0061.10.

  • Inman-Bamber, N. G. (2014). Sugarcane yields and yield-limiting processes. In P. H. Moore & F. C. Botha (Eds.), Sugarcane: Physiology, biochemistry, and functional biology (pp. 579–600). Wiley.

    Google Scholar 

  • Inman-Bamber, N. G., Bonnett, G. D., Spillman, M. F., Hewitt, M. H., & Glassop, D. (2010). Sucrose accumulation in sugarcane is influenced by temperature and genotype through the carbon source–sink balance. Crop and Pasture Science, 61(2), 111–121.

    Article  Google Scholar 

  • IPCC. (2014). Climate change 2014: Synthesis report. In R. K. Pachauri, L. A., Meyer (Eds.) Contribution of working groups I, II and III to the fifth assessment report of the intergovernmental panel on climate change (IPCC, p. 151).

  • Jones, J.W., G. Hoogenboom, C.H. Porter, K.J. Boote, W.D. Batchelor, L.A. Hunt, et al. (2003). DSSAT cropping system model. European Journal of Agronomy, 18, 235–265.

    Article  Google Scholar 

  • Jones, C. D., Hughes, J. K., Bellouin, N., Hardiman, S. C., Jones, G. S., Knight, J., et al. (2011). The HadGEM2-ES implementation of CMIP5 centennial simulations. Geoscientific Model Development, 4, 543–570.

    Article  Google Scholar 

  • Jones, M. R., & Singels, A. (2018). Refining the Canegro model for improved simulation of climate change impacts on sugarcane. European Journal of Agronomy, 100, 76–86.

    Article  Google Scholar 

  • Khan, M. N., Hussain, M., Abbas, G., Fatima, Z., Iqbal, P., Khan, A. et al. (2020). Improving resource use efficiencies of sugarcane at farmer field under arid environment. International Journal of Agriculture & Biology, 24(5), 1279–1285.

  • Knox, J. W., Díaz, J. A. R., Nixon, D. J., & Mkhwanazi, M. (2010). A preliminary assessment of climate change impacts on sugarcane in Swaziland. Agricultural Systems, 103(2), 63–72.

    Article  Google Scholar 

  • Kohila, S., & Gomathi, R. (2018). Adaptive physiological and biochemical response of sugarcane genotypes to high-temperature stress. Indian Journal of Plant Physiology, 23(2), 245–260.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Lakshmanan, P., & Robinson, N. (2014). (2014). Stress physiology: Abiotic stresses. In P. H. Moore & F. C. Botha (Eds.), Sugarcane: Physiology, biochemistry, and functional biology (pp. 411–434). Wiley.

    Google Scholar 

  • Linnenluecke, M. K., Zhou, C., Smith, T., Thompson, N., & Nucifora, N. (2020). The impact of climate change on the Australian sugarcane industry. Journal of Cleaner Production, 246, 118974.

    Article  Google Scholar 

  • Long, S. P., Ainsworth, E. A., Rogers, A., & Ort, D. R. (2004). Rising atmospheric carbon dioxide: Plants FACE the future. Annual Review of Plant Biology, 55, 591–628.

    Article  CAS  PubMed  Google Scholar 

  • Marin, F. R., Jones, J. W., Royce, F., Suguitani, C., Donzeli, J. L., Filho, W. J. P., et al. (2011). Parameterization and evaluation of predictions of DSSAT/CANEGRO for Brazilian sugarcane. Agronomy Journal, 103(2), 304–314.

    Article  Google Scholar 

  • Marin, F. R., Jones, J. W., Singels, A., Royce, F., Assad, E. D., Pellegrino, G. Q., et al. (2013). Climate change impacts on sugarcane attainable yield in southern Brazil. Climatic Change, 117(1–2), 227–239.

    Article  Google Scholar 

  • Mhlanga-Ndlovu, B. F. N., & Nhamo, G. (2017). An assessment of Swaziland sugarcane farmer associations’ vulnerability to climate change. Journal of Integrative Environmental Sciences, 14(1), 39–57.

    Article  Google Scholar 

  • Naz, S., Fatima, Z., Iqbal, P., Khan, A., Zakir, I., Ullah, H. et al. (2022). An introduction to climate change phenomenon. In W.N. Jatoi, M. Mubeen, A. Ahmad, M. A. Cheema, Z. Lin, & M. Z. Hashmi, (Eds.), Building Climate Resilience in Agriculture (pp. 3–16). Sringer Nature, Switzerland. https://doi.org/10.1007/978-3-030-79408-8_1.

  • Pagani, V., Stella, T., Guarneri, T., Finotto, G., Van den Berg, M., Marin, F. R., et al. (2017). Forecasting sugarcane yields using agro-climatic indicators and Canegro model: A case study in the main production region in Brazil. Agricultural Systems, 154, 45–52.

    Article  Google Scholar 

  • Parmar, P. K., Mali, S. C., Arvadiya, L. K., Patel, D. P., Viyol, S. V., & Pandey, V. (2019). Calibration and validation of CANEGRO model for sugarcane in south Gujarat region. Journal of Agrometeorology, 21(3), 388–391.

    Article  Google Scholar 

  • Pipitpukdee, S., Attavanich, W., & Bejranonda, S. (2020). Climate change impacts on sugarcane production in Thailand. Atmosphere, 11(4), 408–415.

    Article  Google Scholar 

  • Rehman, A., Qamar, R., Safdar, M. E., Atique-ur-Rehman, Ahmad, S., Nadeem, M. A. et al. (2021). Role of plant growth promoters on sugarcane production propagated through budchips in semiarid region of Pakistan. Journal of Plant and Environment, 03(02), 137–146.

  • Rodríguez, M., Canales, E., & Borrás-Hidalgo, O. (2005). Molecular aspects of abiotic stress in plants. Biotecnología Aplicada, 22(1), 1–10.

    Google Scholar 

  • Rosenzweig, C., Jones, J. W., Hatfield, J. L., Ruane, A. C., Boote, K. J., Thorburn, P., Antle, J. M., Nelson, G. C., Porter, C., Janssen, S., & Asseng, S. (2013). The agricultural model intercomparison and improvement project (AgMIP): Protocols and pilot studies. Agricultural and Forest Meteorology, 170, 166–182.

    Article  Google Scholar 

  • Rosenzweig, C., Mutter, C. Z., Ruane, A. C., Contreras, E. M., Boote, K. J., Valdivia, R. O., Houtkamp, J. M., MacCarthy, D. S., Claessens, L. F. G., Adhikari, R., & Durand, W. (2021). AgMIP Regional Integrated Assessments: High-level Findings, Methods, Tools, and Studies (2012–2017). In Handbook of climate change and agroecosystems: Climate change and farming system planning in Africa and South Asia: AgMIP Stakeholder-driven Research, Part 1 (pp. 123–142). World Scientific Publishing.

  • Ruan, H., Feng, P., Wang, B., Xing, H., O’Leary, G. J., Huang, Z., et al. (2018). Future climate change projects positive impacts on sugarcane productivity in southern China. European Journal of Agronomy, 96, 108–119.

    Article  Google Scholar 

  • Ruane, A. C., & McDermid, S. P. (2017). Selection of a representative subset of global climate models that captures the profile of regional changes for integrated climate impacts assessment. Earth Perspective, 4, 1–20. https://doi.org/10.1186/s40322-017-0036-4

    Article  Google Scholar 

  • Sage, R. F. (2014). Peixoto MM, Sage TL. 2014. Photosynthesis in sugarcane. In P. H. Moore & F. C. Botha (Eds.), Sugarcane: Physiology, biochemistry, and functional biology (pp. 121–154). Wiley.

    Google Scholar 

  • Singels, A. (2014). Crop models. In P. H. Moore & F. C. Botha (Eds.), Sugarcane: Physiology, biochemistry, and functional biology (1st ed., pp. 541–577). Wiley.

    Google Scholar 

  • Singels, A., Jones, M., Marin, F., Ruane, A., & Thorburn, P. (2014). Predicting climate change impacts on sugarcane production at sites in Australia, Brazil and South Africa using the Canegro model. Sugar Technology, 16(4), 347–355.

    Article  Google Scholar 

  • Singh, B., & El Maayar, M. (1998). Potential impacts of greenhouse gas climate change scenarios on sugarcane yields in Trinidad. Tropical Agriculture, 75, 348–353.

    Google Scholar 

  • Singh, J., Mishra, S. K., Kingra, P. K., Singh, K., Biswas, B., & Singh, V. (2018). Evaluation of DSSAT-CANEGRO model for phenology and yield attributes of sugarcane grown in different agroclimatic zones of Punjab, India. Journal of Agrometeorology, 20(4), 280–295.

    Article  Google Scholar 

  • Sonkar, G., Singh, N., Mall, R. K., Singh, K. K., & Gupta, A. (2019). Simulating the impacts of climate change on sugarcane in diverse agro-climatic zones of Northern India using CANEGRO-Sugarcane model. Sugar Technology, 22, 460–472.

    Article  CAS  Google Scholar 

  • Srivastava, S., Pathak, A. D., Gupta, P. S., Shrivastava, A. K., & Srivastava, A. K. (2012). Hydrogen peroxide-scavenging enzymes impart tolerance to high temperature induced oxidative stress in sugarcane. Journal of Environmental Biology, 33(3), 657–665.

    CAS  PubMed  Google Scholar 

  • Stella, T., Francone, C., Yamaç, S. S., Ceotto, E., Pagani, V., Pilu, R., et al. (2015). Reimplementation and reuse of the Canegro model: From sugarcane to giant reed. Computers and Electronics in Agriculture, 113, 193–202.

    Article  Google Scholar 

  • Su, F., Duan, X., Chen, D., Hao, Z., & Cuo, L. (2013). Evaluation of the global climate models in the CMIP5 over the Tibetan Plateau. Journal of Climate, 26, 3187–3208.

    Article  Google Scholar 

  • Tariq, M., Ahmed, M., Iqbal, P., Fatima, Z., Ahmad, S. (2020). Crop phenotyping. In M. Ahmed, (Ed.), Systems Modeling (pp. 45–60); Springer Nature Singapore Pte Ltd. https://doi.org/10.1007/978-981-15-4728-7_2.

  • Taylor, K. E., Stouffer, R. J., & Meehl, G. A. (2012). An overview of CMIP5 and the experiment design. Bulletin of the American Meteorological Society, 93, 485–498.

    Article  Google Scholar 

  • Verma, R. R., Srivastava, T. K., & Singh, P. (2019). Climate change impacts on rainfall and temperature in sugarcane growing Upper Gangetic Plains of India. Theoretical and Applied Climatology, 135, 279–292.

    Article  Google Scholar 

  • Vu, J. C., & Allen, L. H., Jr. (2009). Stem juice production of the C4 sugarcane (Saccharum officinarum) is enhanced by growth at double-ambient CO2 and high temperature. Journal of Plant Physiology, 166(11), 1141–1151.

    Article  CAS  PubMed  Google Scholar 

  • Walker, N. J., & Schulze, R. E. (2010). Simulations of rainfed and irrigated sugarcane yields at the scale of mill supply areas in South Africa with the APSIM Model: A verification analysis and study of sensitivities of yields to scenarios of climate change. In R.E. Schulze (Ed.) Climate Change and the South African Sugarcane Sector: A 2010 Perspective, ACRUcons Report (Vol. 61, pp. 83–104). University of KwaZulu-Natal, School of Bioresources Engineering and Environmental Hydrology.

  • Waqas, M. M., Shah, S. H. H., Awan, U. K., Arshad, M. G., & Ahmad, R. (2019). Impact of climate change on groundwater fluctuation, root zone salinity and water productivity of sugarcane: A case study in lower Chenab Canal system of Pakistan. Pakistan Journal of Agricultural Sciences, 56(2), 443–450.

    Google Scholar 

  • Wilby, R. L., & Dawson, C. W. (2013). The statistical downscaling model: Insights from one decade of application. International Journal of Climatology, 33, 1707–1719.

    Article  Google Scholar 

  • Wild, M., Folini, D., Henschel, F., Fischer, N., & Müller, B. (2015). Projections of long-term changes in solar radiation based on CMIP5 climate models and their influence on energy yields of photovoltaic systems. Solar Energy, 116, 12–24.

    Article  Google Scholar 

  • Yang, J. M., Yang, J. Y., Liu, S., & Hoogenboom, G. (2014). An evaluation of the statistical methods for testing the performance of crop models with observed data. Agricultural Systems, 127, 81–89.

    Article  Google Scholar 

  • Zhao, D., & Li, Y. R. (2015). Climate change and sugarcane production: Potential impact and mitigation strategies. International Journal of Agronomy, 2015, 1–10.

    Article  CAS  Google Scholar 

Download references

Funding

This article was funded by Higher Education Commission, Pakistan, 17084, Shakeel Ahmad.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Shakeel Ahmad.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 104 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nadeem, M., Nazer Khan, M., Abbas, G. et al. Application of CSM-CANEGRO Model for Climate Change Impact Assessment and Adaptation for Sugarcane in Semi-arid Environment of Southern Punjab, Pakistan. Int. J. Plant Prod. 16, 443–466 (2022). https://doi.org/10.1007/s42106-022-00192-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s42106-022-00192-6

Keywords

Navigation