Skip to main content
SpringerLink
Log in

Geostatistical analysis of fruit yield and detachment force in coffee

  • Published:
Precision Agriculture Aims and scope Submit manuscript

Abstract

The aim of this study was to use geostatistical analysis to evaluate the spatial variation in the detachment force of coffee fruit and coffee yield by variograms and kriging for precision agriculture. This study was conducted at Brejão farm, Três Pontas, Minas Gerais, Brazil. The detachment force of green and mature coffee fruit was measured with a prototype dynamometer and georeferenced. The yield data were obtained from manual harvesting and were georeferenced. The data were evaluated by variograms estimated by residual maximum likelihood (REML), which provided a satisfactory approach for modeling all the variables with a small sample size. Spherical and exponential models were fitted, the first provided the better fit to mature fruit detachment force and the latter provided the better fit to coffee yield and green fruit detachment force. They were used to describe the structure and magnitude of spatial variation in the variables studied. Kriged estimates were obtained with the best fitting variogram models and mapped. The statistical and geostatistical analyses enabled us to characterize the spatial variation of the detachment force of green and mature coffee fruit and coffee yield and to visualize the spatial relations among these variables. The precision agriculture techniques used in this paper to collect, map and analyze the variables studied will help coffee farmers to manage their fields. Maps of coffee yield will enable farmers to apply nutrients site-specifically and manage harvesting either manually or mechanically. In addition, maps of detachment force of coffee fruit can enable farmers to harvest coffee selectively by choosing the appropriate places and the right time to start. This will improve the quality of the final product and also increase profits.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Alves, M. C., Silva, F. M., Moraes, J. C., Pozza, E. A., Oliveira, M. S., Souza, J. C. S., et al. (2011). Geostatistical analysis of the spatial variation of the berry borer and leaf miner in a coffee agroecosystem. Precision Agriculture, 12, 18–31.

    Article  Google Scholar 

  • Alves, M. C., Silva, F. M., Pozza, E. A., & Oliveira, M. S. (2008). Modeling spatial variability and pattern of rust and brown eye spot in coffee agroecosystem. Journal of Pest Science, 82, 137–148.

    Article  Google Scholar 

  • Amaral, J. A. T., Rena, A. B., & Amaral, J. F. T. (2006). Crescimento vegetativo sazonal do cafeeiro e sua relação com fotoperíodo, frutificação, resistência estomática e fotossíntese. Pesquisa Agropecuária Brasileira, 41, 377–384.

    Article  Google Scholar 

  • Andriotti, J. L. S. (2003). Fundamentos de Estatística e Geoestatística. São Leopoldo, RS: Universidade do Vale do Rio dos Sinos.

    Google Scholar 

  • Borén, F. M. (2008). A água nos frutos e nos grãos de café. In F. M. Borén (Ed.), Pós-colheita do café (pp. 127–158). Lavras: Universidade Federal de Lavras.

    Google Scholar 

  • Burrough, P. A., & McDonnell, R. A. (1998). Principles of geographical information systems. New York: Oxford University Press.

    Google Scholar 

  • Cambardella, C. A., Moorman, T. B., Novak, J. M., Parkin, T. B., Karlen, D. L., Turco, R. F., et al. (1994). Field scale variability of soil properties in Central Iowa soils. Soil Science Society of America Journal, 58, 1501–1511.

    Article  Google Scholar 

  • Campanha, M. M., Santos, R. H. S., Freitas, G. B., Martinez, H. E. P., García, S. L. R., & Finger, F. L. (2004). Growth and yield of coffee plants in agroforestry and monoculture systems in Minas Gerais, Brazil. Agroforestry Systems, 63, 75–82.

    Article  Google Scholar 

  • Cannell, M. G. R. (1970). Contribution of carbohydrates from vegetative laterals of the growth of fruits on the bearing branches of Coffea arabica. Turrialba, 20, 15–19.

    Google Scholar 

  • Cannell, M. G. R., & Huxley, P. A. (1970). Seasonal patterns of growing and development of Arabica coffee in Kenya. Kenya Coffee, 35, 139–143.

    Google Scholar 

  • Carvalho, G. R., Mendes, A. N. G., Bartholo, G. F., Nogueira, Â. M., & Amaral, M. A. (2006). Avaliação de produtividade de progênies de cafeeiro em dois sistemas de plantio. Ciência e Agrotecnologia, 30, 838–843.

    Article  Google Scholar 

  • Carvalho, L. G., Sediyama, G. C., Cecon, P. R., & Alves, H. M. R. (2004). A regression model to predict coffee productivity in Southern Minas Gerais, Brazil. Revista Brasileira de Engenharia Agrícola e Ambiental, 8, 204–211.

    Article  Google Scholar 

  • Chalfoun, S. M., Silva, C. M., Pereira, A. A., & Paiva, F. A. (1978). Relação entre diferentes níveis de infecção de ferrugem (Hemileia vastatrix Berk. & Br.) e produção dos cafeeiros (Coffea arabica L.) em algumas localidades de Minas Gerais. In J. B. Matiello (Ed.), Proceedings of the Congresso Brasileiro de Pesquisas Cafeeiras (pp. 392–394). Rio de Janeiro: IBC.

  • Cressie, N. (1993). Statistics for spatial data. New York: Wiley.

    Google Scholar 

  • Diggle, P. J., & Ribeiro, P. J., Jr. (2007). Model based geostatistics. New York: Springer.

    Google Scholar 

  • Faraco, M. A., Uribe-Opazo, M. A., Silva, A. A., Johann, J. A., & Borssoi, J. A. (2008). Seleção de modelos de variabilidade espacial para elaboração de mapas temáticos de atributos físicos do solo e produtividade da soja. Revista Brasileira de Ciências do Solo, 32, 463–476.

    Article  Google Scholar 

  • Goovaerts, P. (1997). Geostatistics for natural resources evaluation. New York: Oxford University Press.

    Google Scholar 

  • Kerry, R., & Oliver, M. A. (2007). Sampling requirements for variograms of soil properties computed by the method of moments and residual maximum likelihood. Geoderma, 140, 383–396.

    Article  Google Scholar 

  • Mapa, R. B., & Kumaragamage, D. (1996). Variability of soil properties in a tropical Alfisol used for shifting cultivation. Soil Technology, 9, 187–197.

    Article  Google Scholar 

  • Marchant, B. P., & Lark, R. M. (2007). Robust estimation of the variogram by residual maximum likelihood. Geoderma, 140, 62–72.

    Article  Google Scholar 

  • Matheron, G. (1965). Les variables regionalisées et leur estimation. Paris: Masson.

    Google Scholar 

  • McBratney, A. B., & Webster, R. (1986). Choosing functions for semi-variograms of soil properties and fitting them to sampling estimates. Journal Soil Science, 37, 617–639.

    Article  Google Scholar 

  • Ministério da Agricultura e Pecuária (MAPA). (2009). Brasil: Produção de Grãos. http://www.agricultura.gov.br/. Accessed 29 November 2009.

  • Patterson, H. D., & Thompson, R. (1971). Recovery of inter-block information when block sizes are unequal. Biometrika, 58, 545–554.

    Article  Google Scholar 

  • Pierce, F. J., Anderson, N. W., Colvin, T. S., Schueller, J. K., Humburg, D. S., & McLaughlin, N. B. (1997). Yield mapping. In F. J. Pierce & E. J. Sadler (Eds.), The state of site specific management for agriculture (pp. 211–243). Madison: ASA, CSSA, SSSA.

    Google Scholar 

  • R Development Core Team. (2006). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. www.r-project.org. Version 2.3.1.

  • Rena, A. B., Nacif, A. P., Gontijo, P. T., & Pereira, A. A. (1996). Fisiologia do cafeeiro em plantios adensados. In P. H. Caramori, A. Androcioli Filho, J. C. D. Chaves, & R. G. Carneiro (Eds.), Proceedings of the Simpósio Internacional sobre Café Adensado (pp. 73–85). Londrina: Instituto Agronômico do Paraná.

  • Ribeiro, P. J., Jr., & Diggle, P. J. (2001). geoR: A package for geostatistical analysis. R-NEWS, 1, ISSN 1609-3631.

  • Silva, F. M. (2004). Colheita mecanizada e seletiva do café, cafeicultura empresarial, produtividade e qualidade. Lavras: Universidade Federal de Lavras.

    Google Scholar 

  • Silva, F. M., Alves, M. C., Souza, J. C. S., & Oliveira, M. S. (2010a). Efeitos da colheita manual na bienalidade do cafeeiro. Ciência e Agrotecnologia, 34, 625–632.

    Article  Google Scholar 

  • Silva, F. M., Arré, T. G., San Ruan, R., & Tourino, E. S. (2002). Avaliação da colheita mecanizada do café com uso do maturador fisiológico Ethrel. In J. B. Matiello (Ed.), Proceedings of the Congresso Brasileiro de Pesquisas Cafeeira, 28 (pp. 148–150). Caxambu: SDR/PROCAFE/PNFC.

  • Silva, F. C., Silva, F. M., Alves, M. C., Barros, M. M., & Sales, R. S. (2010b). Comportamento da força de desprendimento dos frutos do cafeeiro ao longo do período da colheita. Ciência e Agrotecnologia, 34, 468–474.

    Article  Google Scholar 

  • Silva, F. M., Souza, Z. M., Figueiredo, C. A. P., Marques, J. J., & Machado, R. V. (2007). Variabilidade espacial de atributos químicos e de produtividade na cultura do café. Ciência Rural, 37, 401–407.

    Article  Google Scholar 

  • Silva, F. M., Souza, Z. M., Figueiredo, C. A. P., Vieira, L. H. S., & Oliveira, E. (2008). Variabilidade espacial de atributos químicos e produtividade da cultura do café em duas safras agrícolas. Ciência e Agrotecnologia, 32, 231–241.

    Article  Google Scholar 

  • Soto-Pinto, L., Perfecto, I., Castillo-Hernandez, J., & Caballero-Nieto, J. (2000). Shade effect on coffee production at the northern Tzeltal zone of the state of Chiapas, México. Agriculture, Ecosystems & Environment, 80, 61–69.

    Article  Google Scholar 

  • Souza, Z. M., Junior, J. M., Pereira, G. J., & Moreira, L. F. (2004). Variabilidade espacial do pH, Ca, Mg e V% do solo em diferentes formas do relevo sob cultivo de cana-de-açúcar. Ciência Rural, 34, 1763–1771.

    Google Scholar 

  • Toledo, S. V., & Barros, I. (1999). Influência da densidade de plantio e sistema de podas na produção de café. Pesquisa Agropecuária Brasileira, 34, 1379–1384.

    Article  Google Scholar 

  • Valencia, L. I. O., Meirelles, M. S. P., & Bettini, C. (2004). Geoestatística aplicada à Agricultura de Precisão. In P. L. O. A. Machado, A. C. C. Bernardi, & C. A. Silva (Eds.), Agricultura de Precisão para o Manejo da Fertilidade do Solo em Sistema Plantio Direto (pp. 37–56). Rio de Janeiro: Embrapa Solos.

  • Vieira, S. R. (2000). Geoestatística em estudos de variabilidade espacial do solo. In R. F. Novais, V. H. Alvarez, & C. E. G. R. Schaefer (Eds.), Tópicos em Ciência do Solo (pp. 1–54). Viçosa: Sociedade Brasileira de Ciência do Solo.

    Google Scholar 

  • Webster, R., & Oliver, M. (2007a). Geostatistics for Environmental Scientists. Chichester: Wiley.

    Book  Google Scholar 

  • Webster, R., & Oliver, M. (2007b). Sample adequately to estimate variograms of soil properties. Journal of Soil Science, 43, 177–192.

    Article  Google Scholar 

  • Zambolim, L. (2002). O estado da arte de tecnologias na produção de café. Viçosa: Suprema Gráfica e Editora Ltda.

    Google Scholar 

Download references

Acknowledgments

This research was supported by grants from Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq). We would like to acknowledge, the two referees and Professor Margaret Oliver for the precious comments and suggestions.

Author information

Authors and Affiliations

  1. Department of Engineering, Federal University of Lavras (UFLA), PO Box 3037, Lavras, MG, 37200-000, Brazil

    Gabriel Araújo e Silva Ferraz, Fábio Moreira da Silva, Rafael de Lima Bueno & Pedro Augusto Negrini da Costa

  2. Department of Soil and Rural Engineering (DSER), Faculty of Agronomy and Veterinary Medicine (FAMEV), Federal University of Mato Grosso (UFMT), Av. Fernando Correa da Costa 2367, Boa Esperança, Cuiabá, MT, 78060-900, Brazil

    Marcelo de Carvalho Alves

Authors
  1. Gabriel Araújo e Silva Ferraz
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Fábio Moreira da Silva
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Marcelo de Carvalho Alves
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Rafael de Lima Bueno
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Pedro Augusto Negrini da Costa
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Marcelo de Carvalho Alves.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Araújo e Silva Ferraz, G., da Silva, F.M., de Carvalho Alves, M. et al. Geostatistical analysis of fruit yield and detachment force in coffee. Precision Agric 13, 76–89 (2012). https://doi.org/10.1007/s11119-011-9223-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11119-011-9223-8

Keywords

Search

Navigation