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Climate Efficiency for Sugarcane Production in Brazil and its Application in Agricultural Zoning

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Abstract

Climate efficiency is an index that shows quantitative reduction related to production caused by the drought. Using climate efficiency in zoning agricolas sure is a vanguard in agrometeorology. Therefore, we aimed to simulate the climate efficiency for sugarcane production in Brazil and test its use in agricultural zoning. Mean annual air temperature, total annual precipitation, and climate efficiency were the climatic variables used to define suitable areas for sugarcane cultivation. Potential and actual yield was established using the agroecological zone method. Regions with mean annual temperatures between 28 and 38 °C, annual precipitations between 1000 and 1500 mm year−1, and climate efficiency higher than 0.65 were considered climatically suitable for cultivation. The interpolation and crossing of information allowed obtaining the climatic aptitude zoning of sugarcane production for Brazil. Kriging was used as an interpolation method, using the spherical model, one neighbor, and a 0.25° resolution (27.75 km). The Brazilian states were divided into three major groups, according to sugarcane climate efficiency. The most favorable states for sugarcane production had a mean climate efficiency of 0.92. On the other hand, the states with the lowest climate efficiencies presented values of 0.59. Climatic aptitude zoning shows that 24.45% of the Brazilian territory is climatically suitable for sugarcane cultivation. Mato Grosso do Sul State has favorable climatic aptitude in 98% of its territory. The aptitude of productive losses due to climate efficiency is the lowest from January to April in Brazil. The Midwest and Northeast regions have the lowest climate efficiencies from June to September, thus requiring other alternatives, such as irrigation systems for crop maintenance. The use of climate efficiency to elaborate agricultural zoning allows determining with a high accuracy suitable areas for sugarcane cultivation.

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References

  • Abreu, Magno Luiz de, Marcelo de Almeida Silva, Iêdo Teodoro, Lucas Almeida de Holanda, and Givaldo Dantas Sampaio Neto. 2013. Growth and productivity of sugarcane varieties as affected by water availability in the Coastal Tablelands of the Alagoas State, Brazil. Bragantia 72: 262–270. https://doi.org/10.1590/brag.2013.028.

    Article  Google Scholar 

  • Almeida, B.M., E.M. Araújo, E.G. Cavalcante Júnior, J.B. Oliveira, E.M. Araújo, and B.R.C. Nogueira. 2010. Methods comparison of eto estimation in monthly scale to Fortaleza-CE, Brazil. Revista Brasileira de Agricultura Irrigada 4: 93–98. https://doi.org/10.7127/rbai.v4n200610.

    Article  Google Scholar 

  • Alvares, Clayton Alcarde, José Luiz Stape, Paulo Cesar Sentelhas, and José Leonardo de Moraes Gonçalves. 2013a. Modeling monthly mean air temperature for Brazil. Theoretical and Applied Climatology 113: 407–427. https://doi.org/10.1007/s00704-012-0796-6.

    Article  Google Scholar 

  • Alvares, Clayton Alcarde, José Luiz Stape, Paulo Cesar Sentelhas, José Leonardo De Moraes Gonçalves, and Gerd Sparovek. 2013b. Köppen’s climate classification map for Brazil. Meteorologische Zeitschrift 22: 711–728. https://doi.org/10.1127/0941-2948/2013/0507.

    Article  Google Scholar 

  • Aparecido, Lucas Eduardo Rafael de Oliveira, Madureira Batista, José Reinaldo da Silva Cabral de Moraes, Cícero Teixeira Silva Costa, and Adriana Ferreira de Moraes-Oliveira. 2019. Agricultural zoning of climate risk for Physalis peruviana cultivation in Southeastern Brazil. Pesquisa Agropecuaria Brasileira 54: 1–8. https://doi.org/10.1590/S1678-3921.pab2019.v54.00057.

    Article  Google Scholar 

  • Aparecido, Lucas Eduardo de Oliveira, Victor Brunini Moreto, Glauco de Souza Rolim, José Reinaldo da Silva Cabral de Moraes, Taynara Tuany Borges Valeriano, and Paulo Sergio de Souza. 2018a. Climatic potential for summer and winter wine production. Journal of the Science of Food and Agriculture 98: 1280–1290. https://doi.org/10.1002/jsfa.8575.

    Article  CAS  Google Scholar 

  • Aparecido, Lucas Eduardo de Oliveira, Glauco de Souza Rolim, José Reinaldo da Silva Cabral de Moraes, Hélio Gallo Rocha, Guilherme Henrique Expedito Lense, and Paulo Sergio Souza. 2018b. Agroclimatic zoning for urucum crops in the state of Minas Gerais, Brazil. Bragantia 77: 193–200. https://doi.org/10.1590/1678-4499.2016527.

    Article  Google Scholar 

  • Aparecido, Lucas Eduardo de Oliveira, Guilherme Botega Torsoni, Daniel Zimmerman Mesquita, Kamila Cunha de Meneses, and Jose Reinaldo da Silva Cabral de Moraes. 2020. Modeling safrinha corn productivity according to climatic conditions in Mato Grosso do Sul. Revista Brasileira de Climatologia 26: 113–132. https://doi.org/10.5380/abclima.v26i0.69183.

    Article  Google Scholar 

  • Arlanch, Adolfo Bergamo, Glauber José Gava, Kölln de Castro, Oriel Tiago, William José Dellabiglia, Fabio Vale Scarpare, Regina Celia Pires, and De. Matos. 2018. Physiological indices and the yield of genotypes of sugarcane in the handling of drought and drip irrigation. Irriga 1: 112–124. https://doi.org/10.15809/irriga.2018v1n1p112-124.

    Article  Google Scholar 

  • Atampugre, Gerald, Melissa Nursey-Bray, and Richard Adade. 2019. Using geospatial techniques to assess climate risks in savannah agroecological systems. Remote Sensing Applications: Society and Environment 14: 100–107. https://doi.org/10.1016/j.rsase.2019.01.006.

    Article  Google Scholar 

  • Bacchi, O.O.S. 1983. Ecophysiology of Sugarcane. In Sugarcane nutrition and fertilization in Brazil (In Portuguese) (In Portuguese), ed. J. Orlando Filho, 24–37. Piracicaba: IAA/Planalsucar.

    Google Scholar 

  • Barbieri, V., and N.A. Villa Nova. 1977. Climatology and sugarcane. Araras: Planalsucar.

    Google Scholar 

  • Battisti, Rafael, Paulo Cesar Sentelhas, Felipe Gustavo Pilau, and Cássio Arthur. Wollmann. 2013. Climatic efficiency for soybean and wheat crops in the state of Rio Grande do Sul, Brazil, in different sowing date. Ciencia Rural 43: 390–396. https://doi.org/10.1590/S0103-84782013000300003.

    Article  Google Scholar 

  • Bentz, Barbara J., Jacques Régnière, Christopher J. Fettig, E. Matthew Hansen, Jane L. Hayes, Jeffrey A. Hicke, Rick G. Kelsey, Jose F. Negrón, and Steven J. Seybold. 2010. Climate change and bark beetles of the Western United States and Canada: direct and indirect effects. BioScience 60: 602–613. https://doi.org/10.1525/bio.2010.60.8.6.

    Article  Google Scholar 

  • Bracho-Mujica, Gennady, Peter T. Hayman, and Bertram Ostendorf. 2019. Modelling long-term risk profiles of wheat grain yield with limited climate data. Agricultural Systems 173: 393–402. https://doi.org/10.1016/j.agsy.2019.03.010.

    Article  Google Scholar 

  • Brazil. 1992. Climatologic Normals: 1961–1990. Brasília: Ministry o.

    Google Scholar 

  • Brazil. 2003. Ministry of Agriculture, Livestock and Supply. Agricultural risk zoning. http://www.mda.gov.br/sitemda/sites/sitemda/files/user_arquivos_64/INSTRU%C3%87%C3%83O_NORMATIVA_N%C2%BA_2,_DE_9_DE_OUTUBRO_DE_2008.pdf. Accessed 25 June 2020.

  • Camargo, A.P. 1971. Water balance in the state of São Paulo, vol. 116, 9–29. Campinas: IAC Boletim.

    Google Scholar 

  • Cardozo, Nilceu Piffer, Ricardo de Oliveira Bordonal, and Newton La Scala. 2018. Sustainable intensification of sugarcane production under irrigation systems, considering climate interactions and agricultural efficiency. Journal of Cleaner Production 204: 861–871. https://doi.org/10.1016/j.jclepro.2018.09.004.

    Article  Google Scholar 

  • Cavalcanti R.Q., Mario M. Rolim, Renato P. de Lima, Uilka E. Tavares, Elvira M.R. Pedrosa, and Igor F. Gomes. 2019. Soil physical and mechanical attributes in response to successive harvests under sugarcane cultivation in Northeastern Brazil. Soil and Tillage Research 189: 140–147.

    Article  Google Scholar 

  • Cesconetto Laisi Bellon, F. F. Falco Pruski, R. del G. Rodriguez, and G. E. Marcatti. (2018) Potentiality of sugarcane expansion under irrigation conditions considering natural and potential water availability. Agricultural Water Management 203: 162–171.

    Article  Google Scholar 

  • Dias, Henrique Boriolo, and Paulo Cesar Sentelhas. 2019. Dimensioning the impact of irrigation on sugarcane yield in Brazil. Sugar Tech 21: 29–37. https://doi.org/10.1007/s12355-018-0619-x.

    Article  CAS  Google Scholar 

  • Diola, V., and F. Santos. 2012. Physiology. In Sugarcane: Bioenergy, sugar and ethanol—Technologies and perspectives, ed. F. Santos, A. Borém, and C. Caldas, 25–49. Viçosa: In Portuguese.

    Google Scholar 

  • Djaman, Koffi, Michael O’Neill, Curtis K. Owen, Daniel Smeal, Komlan Koudahe, Margaret West, Samuel Allen, Kevin Lombard, and Suat Irmak. 2018. Crop evapotranspiration, irrigation water requirement and water productivity of maize from meteorological data under semiarid climate. Water 10: 1–17. https://doi.org/10.3390/w10040405.

    Article  Google Scholar 

  • Doorenbos, Jan, and Amir Kassam. 1979. Yield response to water. Irrigation and Drainage Paper 33: 257.

    Google Scholar 

  • Doorenbos, Jan, and Amir Kassam. 1994. Effect of water on crop yield (in Portuguese). Campina Grande: UFPB 33: 220–226.

    Google Scholar 

  • Farooq, Nageen, and Shabbir H. Gheewala. 2020. Assessing the impact of climate change on sugarcane and adaptation actions in Pakistan. Acta Geophysica 68: 1489–1503. https://doi.org/10.1007/s11600-020-00463-8.

    Article  Google Scholar 

  • Hair, Joseph, William Black, Barry Babin, Rolph Anderson, and Ronald Tatham. 2009. Multivariate data analysis (in Portuguese). São Paulo: Bookman Editora.

    Google Scholar 

  • Hernandes, Thayse Aparecida Dourado, Fabio Vale Scarpare, and Joaquim Eugênio Abel Seabra. 2018. Assessment of the recent land use change dynamics related to sugarcane expansion and the associated effects on water resources availability. Journal of Cleaner Production 197: 1328–1341. https://doi.org/10.1016/j.jclepro.2018.06.297.

    Article  Google Scholar 

  • Inman-Bamber, N.G., and D.M. Smith. 2005. Water relations in sugarcane and response to water deficits. Field Crops Research 92: 185–202. https://doi.org/10.1016/j.fcr.2005.01.023.

    Article  Google Scholar 

  • Köppen, W. das. 1936. Das geographische system der klimat. Gebruder Borntraeger: Handbuch der klimatologie.

    Google Scholar 

  • Krige, Daniel G. 1951. A statistical approach to some basic mine valuation problems on the Witwatersrand. Journal of the Southern African Institute of Mining and Metallurgy 52: 119–139.

    Google Scholar 

  • Lecoeur, J., and T.R. Sinclair. 1996. Field pea transpiration and leaf growth in response to soil water deficits. Crop Science 36: 331–335. https://doi.org/10.2135/cropsci1996.0011183X003600020020x.

    Article  Google Scholar 

  • Lin, Hsiang Chun, Robert Coe, William Paul Quick, and Anindya Bandyopadhyay. 2019. Climate-Resilient Future Crop: Development of C4 Rice. In Sustainable solutions for food security, ed. Atanu Sarkar, p. 111–124. London: Springer.

  • Lyra, Gustavo Bastos, Evandro Lima da Silveira, Guilherme Bastos Lyra, Carlos Rodrigues Pereira, Leonardo Duarte Batista da Silva, and Givanildo Miguel da Silva 2012. Sugarcane crop coefficient at the initial stage of development in Campos dos Goytacazes, RJ (in Portuguese). Irriga 17: 102–113. https://doi.org/10.15809/irriga.2012v17n1p102.

    Article  Google Scholar 

  • Marcari, Marcos Antônio, Glauco de Souza Rolim, and Lucas Eduardo de Oliveira Aparecido. 2015. Agrometeorological models for forecasting yield and quality of sugarcane. Australian Journal of Crop Science 9: 1049–1056.

    Google Scholar 

  • Marin, Fábio Ricardo., Geoff Inman-Bamber, Thieres George Freire Silva, Murilo dos Santos, Daniel Silveira Vianna, Pinto Nassif, and Kassio dos Santos Carvalho. 2020. Sugarcane evapotranspiration and irrigation requirements in tropical climates. Theoretical and Applied Climatology 140: 1349–1357. https://doi.org/10.1007/s00704-020-03161-z.

    Article  Google Scholar 

  • Marin, Fábio Ricardo., Rafael Vasconcelos Ribeiro, and Paulo Euripedes Ribeiro. Marchiori. 2014. How can crop modeling and plant physiology help to understand the plant responses to climate change? A case study with sugarcane. Theoretical and Experimental Plant Physiology 26: 49–63. https://doi.org/10.1007/s40626-014-0006-2.

    Article  Google Scholar 

  • Monteiro, Leonardo A., and Paulo C. Sentelhas. 2014. Potential and actual sugarcane yields in southern Brazil as a function of climate conditions and crop management. Sugar Tech 16: 264–276. https://doi.org/10.1007/s12355-013-0275-0.

    Article  Google Scholar 

  • Montes-Belmont, Roberto, Ignacio Méndez-Ramírez, and Elizabet Flores-Moctezuma. 2002. Relationship between sorghum ergot, sowing dates, and climatic variables in Morelos, Mexico. Crop Protection 21: 899–905. https://doi.org/10.1016/S0261-2194(02)00056-X.

    Article  Google Scholar 

  • Parker, Louis, Clement Bourgoin, Armando Martinez-Valle, and Peter Läderach. 2019. Vulnerability of the agricultural sector to climate change: The development of a pan-tropical Climate Risk Vulnerability Assessment to inform sub-national decision making. PLoS ONE 14: 1–25. https://doi.org/10.1371/journal.pone.0213641.

    Article  CAS  Google Scholar 

  • Pereira, A R, L R Angelocci, P C Sentelhas, and others. 2002. Agrometeorology (in Portuguese). In Fundamentos e Aplicações Praticas. ed. Pereira, A R. Viçosa: Livraria e Editora Agropecuária.

  • de Silva, A.L.C., and W.A.J.M. de Costa. 2004. Varietal variation in growth, physiology and yield of sugarcane under two contrasting water regimes. Tropical Agricultural Research 16: 1–12.

    Google Scholar 

  • Silva, Marcelo De Almeida, John Lonfover Jifon, Claudiana Moura dos Santos, Cleber Junior Jadoski, and Jorge Alberto Gonçalves da Silva. 2013. Photosynthetic capacity and water use efficiency in sugarcane genotypes subject to water deficit during early growth phase. Brazilian Archives of Biology and Technology 56: 735–748. https://doi.org/10.1590/S1516-89132013000500004.

    Article  CAS  Google Scholar 

  • Silva, Vicente De P R, Roberta A Silva, Girlene F Maciel, Enio P De Souza, Célia C Braga, and Romildo M De Holanda. 2020. Soybean yield in the Matopiba region under climate changes. Revista Brasileira de Engenharia Agrícola e Ambiental 14: 8–14. https://doi.org/10.1590/1807-1929/agriambi.v24n1p8-14.

    Article  Google Scholar 

  • Sneath, Peter H A, Robert R Sokal, et al. 1973. Numerical taxonomy. The principles and practice of numerical classification. New York: W H Freeman & Co.

  • Souza, José Leonaldo., and de, Gilson Moura Filho, Roberto Fernando da Fonseca Lyra, Iedo Teodoro, Erikson Amorim Dos Santos, Joaquim Louro da Silva, Paulo Ricardo Teixeira da Silva, Adriana de Holanda Cardim, and E Cavalcante Amorim. 2004. An assessment of the rainfall and air temperature in the region of Tabuleiro Costeiro of Maceió, AL, Brazil, during the 1972–2001 period. Revista Brasileira de Agrometeorologia 11: 131–141.

    Google Scholar 

  • Taiz, L., E. Zeiger, I.M. Moller, and A. Murphy. 2017. Physiology and plant development, 858. Porto Alegre: Artmed.

    Google Scholar 

  • Teodoro, Iêdo, José Dantas Neto, José L. de Souza, Lucas A. de Sampaio Neto, Givaldo D. Holanda, Geraldo V. de S. Barbosa, and Guilherme B. Lyra. 2016. Weather variables, water balance, growth, and agro industrial yield of sugarcane. Engenharia Agrícola 35: 76–88. https://doi.org/10.1590/1809-4430-eng.agric.v35n1p76-88/2015.

    Article  Google Scholar 

  • Thornthwaite, Charles Warren, and John R Mather. 1955. The Water Budget Ami Its Use in Irrigation. https://naldc.nal.usda.gov/download/IND43894582/PDF. Accessed 26 June 2020.

  • Thornthwaite, Charles Warren. 1948. An approach toward a rational classification of climate. Geographical review 38: 55–94.

    Article  Google Scholar 

  • Vianna, Murilo dos Santos, and Paulo Cesar Sentelhas. 2014. Simulation of the water deficit risk in sugarcane—Crop expansion regions in Brazil. Pesquisa Agropecuaria Brasileira 49: 237–246. https://doi.org/10.1590/S0100-204X2014000400001.

    Article  Google Scholar 

  • Yang, Daqing, Douglas Kane, Zhongping Zhang, David Legates, and Barry Goodison. 2005. Bias corrections of long-term (1973–2004) daily precipitation data over the northern regions. Geophysical Research Letters 32: 1–5. https://doi.org/10.1029/2005GL024057.

    Article  Google Scholar 

  • Yang, Yanmin, De Li. Liu, Muhuddin Rajin Anwar, Garry O’Leary, Ian Macadam, and Yonghui Yang. 2016. Water use efficiency and crop water balance of rainfed wheat in a semi-arid environment: sensitivity of future changes to projected climate changes and soil type. Theoretical and Applied Climatology 123: 565–579. https://doi.org/10.1007/s00704-015-1376-3.

    Article  Google Scholar 

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Funding

We are thankful to the Science and Technology of Mato Grosso do Sul—Campus of Naviraí, IFMS—Federal Institute of Education, Naviraí, Brazil, for the financial support of this study.

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Correspondence to Lucas Eduardo de Oliveira Aparecido.

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Aparecido, L.E.O., de Moraes, J.R.S.C., de Meneses, K.C. et al. Climate Efficiency for Sugarcane Production in Brazil and its Application in Agricultural Zoning. Sugar Tech 23, 776–793 (2021). https://doi.org/10.1007/s12355-020-00949-1

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