Using the CSM-CROPGRO-Soybean model to estimate soybean sowing dates in the Cerrado of Piaui, Brazil
DOI:
https://doi.org/10.5902/2179460X85822Keywords:
Agricultural modeling, Sowing date, Climate riskAbstract
Soybean cultivation is one of the main agricultural activities in Piauí, particularly in the Cerrado biome region. It is a rainfed crop, so the soybean sowing date is crucial to its good yield performance. This study aimed to make an evaluation using the CSM-CROPGRO-Soybean model to simulate soybean grain yield for the Cerrado region of southwest Piauí according to the different sowing dates. The CSM-CROPGRO-Soybean model and historical climate data were used to simulate scenarios for rainfed soybean, sowing dates for eight municipalities in the southwest region of Piauí. Two soybean cultivars were considered: BRS 8980 IPRO (BRS 8980) and the BMX 84I86 cultivar (Dominio). The simulated yield results were analyzed regarding frequency distribution and yield breaks. Sowings made in the first ten days of November had longer cycles, while later, sowings resulted in shorter cycles. This difference in duration was 16.4% for the BRS 8980 cultivar and 13.1% for the Dominio cultivar. The process of assessing the consistency of soybean yield variability concerning simulated yields, was carried out by comparing simulated and measured yields on a commercial soybean production farm in the municipality of Bom Jesus. The best sowing dates were observed for the second and third ten-day period of November and the first 10-day period of December, while the worst date was the third 10-day period of January for all the municipalities evaluated. Choosing the best sowing date for the region can vary according to the risk level the producer is willing to assume. It was concluded that sowings made in the first 10-day period of November had longer cycles, while later sowings resulted in shorter cycles. The use of the DSSAT CSM-CROPGRO-Soybean simulation model proved to be a suitable tool to help make decisions regarding soybean cultivation in the Cerrado region of southwest Piauí.
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References
Alves, E. S., Rodrigues, L. N., Oliveira, R. A., & Lorena, D. R. (2021). Water deficit on the growth and yield of irrigated soybean in the Brazilian cerrado region. Revista Brasileira Engenharia Agrícola e Ambiental, 25(11):750-757. DOI: http://dx.doi.org/10.1590/1807-1929/agriambi.v25n11p750-757
Andrade Júnior, A. S., Bastos, E. A., Barros, A. H. C., Silva, C. O., & Gomes, A. A. N. (2005). Classificação climática e regionalização do semi-árido do Estado do Piauí sob cenários pluviométricos distintos. Revista Ciência Agronômica, 36(2):143-151.
Báez, M. S. A., Petry, M. T., Carlesso, R., Basso, L. J., Rocha, M. R., & Rodriguez, G. J. (2020). Balanço hídrico e produtividade da soja cultivada sob diferentes níveis de déficit hídrico no Sul do Brasil. Investig. Agrar, 22(1):03-12. http://dx.doi.org/10.18004/investig.agrar.2020.junio.03-12
Barbieri, J. D., Dallacort, R., Freitas, P. S. L., Tieppo, R. C., Silva Andrea, M. C., & seabra Junior, S. (2020). Simulação da produtividade e de épocas de semeadura para soja e milho em eventos de El niño Oscilação Sul no estado de Mato Grosso. Acta Iguazu, 9(1):45-66.
Battisti, R. & Sentelhas, P. C. (2015). Drought tolerance of brazilian soybean cultivars simulated by a simple agrometeorological yield model. Experimental Agriculture, 51(2): 285–298. doi:10.1017/S0014479714000283
Battisti, R. & Sentelhas, P. C. (2019). Characterizing Brazilian soybean-growing regions by water deficit patterns. Field Crops Research, 240:95–105. https://doi.org/10.1016/j.fcr.2019.06.007
Battisti, R., Sentelhas, P. C., Parker, P. S., Nendel, C., Câmara, G. M. S., Farias, J. R. B., & Basso, C. J. (2018b). Assessment of crop-management strategies to improve soybean resilience to climate change in Southern Brazil. Crop and Pasture Science, 69:154-162. https://doi.org/10.1071/CP17293
Battisti, R., Sentelhas, P. C., Pascoalino, J. A. L., Sako, H., Dantas, J. P. S., & Moraes, M. F. (2018a). Soybean yield gap in the areas of yield contest in Brazil. International Journal of Plant Production, 12:159-168. https://doi.org/10.1007/s42106-018-0016-0
Bohn, N. P., Lustosa Filho, J. F., Nóbrega, J. C. A., Campos. A. R., Nóbrega, R. S. A., & Pacheco, L. P. (2016). Indentificação de cultivares de soja para a região sudoeste do cerrado piauiense. Revista Agro@mbiente On-line, 10(1):10:1. DOI:10.18227/1982-8470ragro.v10i1.2911
Brasil. Ministério da Agricultura, Pecuária e Abastecimento. (2023). Programa Nacional de Zoneamento Agrícola de Risco Climático - Zarc. Available in: https://www.gov.br/agricultura/pt-br/assuntos/noticias-2022/publicado-zoneamento-agricola-da-soja-safra-2022-2023.
Cuadra, S.V., Rocha, R. P., Llopart, M. P., Victoria, D. C., Almeida, I. R., & Farias, J. R. B. (2018). Impactos da correção de viés sobre projeções de mudanças climáticas aplicadas a simulações de rendimento de culturas. Agrometeoros, 26(2):287-298. DOI: http://dx.doi.org/10.31062/agrom.v26i2.26399
Embrapa - Empresa Brasileira de Pesquisa Agropecuária. (2021). Soja: Tipo de Crescimento. Available in: Tipo de Crescimento - Portal Embrapa. https://www.embrapa.br/agencia-de-informacao-tecnologica/cultivos/soja/pre-producao/caracteristicas-da-especie-e-relacoes-com-o-ambiente/estadios-de-desenvolvimento/tipo-de-crescimento
Ergo, V. V., Lascano, R., Veja, C. R. C., Parola, R., & Carrera, C. S. (2018). Heat and water stressed field-grown soybean: A multivariate study on the relationship between physiological-biochemical traits and yield. Environmental and Experimental Botany, 148:1-11. https://doi.org/10.1016/j.envexpbot.2017.12.023
Eulenstein, F., Lana, M., Schlindwein, S., Sheudzhen, A., Tauschk, M., Behrend, A., Guevara, E., & Meira, S. (2017). Trends of Soybean Yields under Climate Change Scenarios. Horticulturae, 3(10). doi:10.3390/horticulturae3010010
Google Earth. (2023). Plataforma Google Earth. https://earth.google.com/web/@-0.33447651,42.86296857,13462.10686798a,25695504.53098297d,35y,0h,0t,0r/data=CgRCAggBQgIIAEoNCP___________wEQAA
Hoogenboom, G. (2019). The DSSAT crop modeling ecosystem. In K. J. Boote (Ed7), Advances in Crop Modeling for a Sustainable Agriculture (1a ed.). Cambridge, GB: Burleigh Dodds Science Publishing. (pp. 173-216).
Instituto Brasileiro de Geografia e Estatística - IBGE. (2023). Levantamento sistemático da produção agrícola. https://sidra.ibge.gov.br/home/lspa/piaui.
Jones, J. W., Hoogenboom, G., Boote, K. J., & Porter, C. H. (2010.). Decision Support System for Agrotechnology Transfer Version 4.0. Volume 4. DSSAT v4.5: Crop Model Documentation. University of Hawaii, Honolulu, HI,
Melo, A. C. A., Nobre Júnior, A. A., Silva, F. A. M., & Abreu, L. M. (2020). Zoneamento de risco climático para cultivo da soja no cerrado. Pesquisas Agrárias e Ambientais, 8(1):26-36. DOI: http://dx.doi.org/10.31413/nativa.v8i1.8249
Ministério da Agricultura, Pecuária e Abastecimento/Secretaria de Política Agrícola - MAPA. (2021). Portaria nº 116/2021. Published on 05/12/2021. Available in: https://www.in.gov.br/web/dou/-/portaria-n-116-de-11-de-2021-319515885.
Ministério da Agricultura, Pecuária e Abastecimento/Secretaria de Política Agrícola - MAPA. (2022). Instrução Normativa SPA/MAPA Nº 1, de 21 de junho de 2022. Available in: https://www.gov.br/agricultura/pt-br/assuntos/riscos-seguro/programa-nacional-de-zoneamento-agricola-de-risco-climatico/documentos/InstruoNormativa_n_1_de_21_de_junho_de2022_V2.pdf.
Nóia Júnior, R. S. & Sentelhas, P. C. (2019). Soybean-maize succession in Brazil: Impacts of sowing dates on climate variability, yields and economic profitability. European Journal of Agronomy, 103:140-151. https://doi.org/10.1016/j.eja.2018.12.008
Pham, Q. V., Nguyen, T. T. N., Vo, T. T. X., Le, P. H., Nguyen, X. T. T., Duong, N. V., & Le, C. T. S. (2023). Applying the SIMPLE Crop Model to Assess Soybean (Glicine max. (L.) Merr.) Biomass and Yield in Tropical Climate Variation. Agronomy, 13:1180. https://doi.org/10.3390/agronomy13041180
Pragana, R. B., Souza Junior, V. S., Moura, R. S., & Soares, J. M. (2016). Characterization of yellow latosols (oxisols) of Serra do Quilombo, in Piauí state savanna woodlands – Brazil. Revista Caatinga, 29(4):832 – 840. https://doi.org/10.1590/1983-21252016v29n407rc
Reis, L., Silva, C. M. S., Bezerra, B., Mutti, P., Spyrides, M. H., Silva, P., Magalhães, T. R. F., Rodrigues, D., & Andrade, L. (2020). Influence of Climate Variability on Soybean Yield in MATOPIBA, Brazil. Atmosphere, 11(1).
Santos, T. G., Battisti, R., Casaroli, D., Alves Jr, J., & Evangelista, A. W. P. (2021). Assessment of agricultural efficiency and yield gap for soybean in the Brazilian Central Cerrado biome. Bragantia, 80(1821):1-11. https://doi.org/10.1590/1678-4499.20200352
Sena, C. C. R., Silva, G. C., Evangelista, Z. R., Nunes, M. E., & Pego, A. W. E. (2021). Atributos físico-hídricos de solos do cerrado. Revista Agrotecnologia, 12(1):80-91.
Souza, P. J. O. P., Santos, C. D. M., Souza, E. B., Oliveira, E. C., & Santos, J. T. S. (2018). Impactos das mudanças climáticas na cultura da soja no Nordeste do estado do Pará. Revista Brasileira de Agricultura Irrigada, 12(2):2454-2467. DOI: 10.7127/rbai.v12n200744
Teixeira, W. G., Victoria, D. C., Barros, A. H. C., Lumbreras, J. F., Araújo filho, J. C., Silva, F. A. M., Lima, E. P., Bueno Filho, J. S. S., & Monteiro, J. E. B. A. (2021). Predição da água disponível no solo em função da granulometria para uso nas análises de risco no Zoneamento Agrícola de Risco Climático. Boletim de pesquisa e desenvolvimento, 272. Rio de Janeiro: Embrapa Solos. Available in: https://www.embrapa.br/busca-de-publicacoes/-/publicacao/1131095/predicao-da-agua-disponivel-no-solo-em-funcao-da-granulometria-para-uso-nas-analises-de-risco-no-zoneamento-agricola-de-risco-climatico.
Xavier A. C., Scanlon, B. R., King, C. W., & Alves, A. I. (2022). New improved Brazilian daily weather gridded data (1961–2020). International Journal of Climatology, 42:8390–8404. https://doi.org/10.1002/joc.7731
Winck, J. E. M., Martin, T. N., Pinto, M. A. B., Bruning, L. A., & Arismendi, G. A. (2020). Spatial arrangement of plants on leaf growth and development and the yield potential of soybean. Australian Journal of Crop Science, 14(06):913-922. doi: 10.21475/ajcs.20.14.06.p1721
Wu, W., Yu, Q., You, L., Chen, K., Tang, H., & Liu, J. (2018). Global cropping intensity gaps: Increasing food production without cropland expansion. Land Use Policy, 76:515-525. https://doi.org/10.1016/j.landusepol.2018.02.032
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