Advertisement

European Journal of Plant Pathology

, Volume 147, Issue 3, pp 579–590 | Cite as

Spatio-temporal dynamics on a plot scale of cocoa black pod rot caused by Phytophthora megakarya in Cameroon

  • Michel Ndoumbe Nkeng
  • Ives Bruno Efombagn Mousseni
  • Lucien Bidzanga Nomo
  • Ivan Sache
  • Christian CilasEmail author
Article

Abstract

Black pod disease is caused by several species of Phytophthora. In Cameroon, the disease is mainly due to Phytophtora megakarya. The pathogen attacks cocoa pods and can lead to almost total production losses in a plot if no control measures are applied. To control the disease, several research programmes are being conducted: breeding for increased resistance, development of several biocontrol or agronomic methods. However, for better use of a specific method it is useful to have a good understanding of several epidemiological processes and more effectively know how the disease is distributed in the field. The purpose of this study was to describe the spatial development of the disease in several cocoa fields in Cameroon. In particular, we determined the spatial relation of the disease using several tools, including geostatistics models and Moran indices. The results indicated that the disease was not randomly distributed, while correlations between neighbouring cocoa trees existed. The relationships were detected up to a distance of between 7 and 9 m, revealing the wide dispersal pattern of the pathogen over short distances. No spatial structure was found in the spread of the disease in the oldest cocoa plantations and the inoculum was dispersed throughout the plot. Disease dispersal over short distances should make it possible to adapt control methods by attempting to confine the first disease foci in young plots. Research should also be undertaken to limit inoculum dispersal.

Keywords

Black pod disease Epidemiological processes Phytophthora megakarya Primary inoculum Spatial dynamics 

Notes

Acknowledgments

The authors acknowledge Peter Biggins for translation in English.

References

  1. Babacauh, K. D. (1983). Facteurs déterminant la localisation des lésions de pourriture brune des cabosses du cacaoyer (Theobroma cacao L.). I. Age de la cabosse et localisation de la lésion. Café Cacao Thé, 27(1) :195–208.Google Scholar
  2. Berry, D., & Cilas, C. (1994). Etude génétique de la réaction à la pourriture brune des cabosses chez des cacaoyers (Theobroma cacao L) issus d’un plan de croisements diallèle. Agronomie, 14, 599–609.CrossRefGoogle Scholar
  3. Bivan, R. S., Pebesma, E. J., & Gomez-Rubio, V. (2008). Applied spatial data analysis with R (373 p). Springer.Google Scholar
  4. Chadoeuf, J., Nandris, D., Geiger, J. P., Nicole, M., & Pierrat, J. C. (1992). Modélisation spatio-temporelle d’une épidémie par un processus de Gibbs : Estimation et tests. Biometrics, 48, 1165–1175.CrossRefGoogle Scholar
  5. Cilas, C., & Despréaux, D. (Eds.). (2004). Improvement of cocoa tree resistance to Phytophthora diseases. Editions Quae.Google Scholar
  6. Cliff, A. D., & Ord, J. K. (1981). Spatial processes : Models and applications (266 p). London: Pion.Google Scholar
  7. Cressie, N. A. C. (1985). When are variograms useful in geostatistics ? Journal of the International Association for Mathematical Geology, 17, 693–702.CrossRefGoogle Scholar
  8. Cressie, N. A. C. (1991). Statistics for spatial data (900 p). New York: John Wiley & Sons.Google Scholar
  9. Drenth, A., Sendall, B., & Guest, D. I. (2004). Economic impact of phytophthora diseases in Southeast Asia (pp. In 10–28). Australian Centre for: International Agricultural Research (ACIAR).Google Scholar
  10. FAO (2009) CountryStat pour l’Afrique Sub-Saharienne. Projet GCP/GLO/208/BMG. Rapport Panorama 1 sur les statistiques agroalimentaires. FAO, Rome, 2009, 78 p.Google Scholar
  11. Gregory, P. H. (1974). Phytophthora diseases of cocoa. London: Longman Group Limited.Google Scholar
  12. ICCO (2015) Quarterly Bulletin of Cocoa Statistics, Vol. XLI, No. 3, Cocoa year 2014/15.Google Scholar
  13. Isaaks, H., & Srivastava, R. H. (1989). An Introduction to Applied Geostatistics (561 p). New York: Oxford University Press.Google Scholar
  14. Jackson, G. V., & Newhook, F. J. (1978). Sources of Phytophtorapalmivorainoculum in Salomon Islands cocoa plantations. Transactions of the British Mycological Society, 71(2), 239–249.CrossRefGoogle Scholar
  15. Jones, G.D. (1998). The epidemioloy of plant diseases. Kluwer Academic Publishers (Dordrecht/Boston/London), 460 p.Google Scholar
  16. Lannou, C., & Savary, S. (1991). The spatial structure of spontaneous epidemics of different diseases in a groudnut plot. Netherlands Journal of Plant Pathology, 97, 355–367.CrossRefGoogle Scholar
  17. Larkin, R. P., Gumpertz, M. L., & Ristaino, J. B. (1995). Geostatistical analysis of Phytophthora epidemic development in commercial bell pepper fields. Phytopathology, 85(2), 191–202.CrossRefGoogle Scholar
  18. Lecoustre, R., & de Reffye, P. (1986). La théorie des variables régionalisées, ses applications possibles dans le domaine épidémiologiques aux recherches agronomiques en particulier sur le palmier à huile et le cocotier. Oléagineux, 41(12), 541–548.Google Scholar
  19. Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58, 1246–1266.CrossRefGoogle Scholar
  20. Matheron, G. (1970). La théorie des variables régionalisées et ses applications. In Les cahiers du centre de morphologie mathématique de Fontainebleau (5). Paris: Ecole des Mines de.Google Scholar
  21. Medeiros, A.G. (1976). Sporulation of Phytophtora palmivora (Butl.)Butl.In relation to epidemiology and control of cocoa black pod disease.Ph.D. Thesis, University of California, Riverside, 220 p.Google Scholar
  22. Minogue, K. P., & Fry, W. E. (1983). Models for the spread of disease: model description. Phytopathology, 73(8), 1168–1173.CrossRefGoogle Scholar
  23. Mouen Bedimo, J. A., Bieysse, D., Cilas, C., & Nottéghem, J. L. (2007). Spatio-temporal Dynamics of Arabica Coffee Berry Disease due to Colletotrichum kahawae on a Plot Scale. Plant Disease, 91, 1229–1236.CrossRefGoogle Scholar
  24. Musoli, P., Pinard, F., Charrier, A., Kangire, A., ten Hoopen, G. M., Kabole, C., Ogwang, J., Bieysse, D., & Cilas, C. (2008). Spatial and temporal analysis of coffee wilt disease caused by Fusariumxylarioidse in a Coffeacanephora. European Journal of Plant Pathology, 122, 51–617.CrossRefGoogle Scholar
  25. Ndoumbé Nkeng, M., Efombagn, M. I. B., Nyassé, S., Nyemb, E., Sache, I., & Cilas, C. (2009). Relationships between cocoa Phytophthora pod rot disease and climatic variables in Cameroon. Canadian Journal of Plant Pathology, 31(3), 309–320.CrossRefGoogle Scholar
  26. Ndoumbé-Nkeng, M., Cilas, C., Nyemb, E., Nyassé, S., Bieysse, D., Flori, A., & Sache, I. (2004). Impact of removing diseased pods on cocoa black pod caused by Phytophthora megakarya and on cocoa production in Cameroon. Crop Protection, 23, 415–424.CrossRefGoogle Scholar
  27. Nelson, M. R., Orum, T. V., Jaime-Garcia, R., & Nadeem, A. (1999). Applications of geographic information systems and geostatistics in plant disease epidemiology and management. Plant Disease, 83, 308–319.CrossRefGoogle Scholar
  28. Nyassé, S., Cilas, C., Herail, C., & Blaha, G. (1995). Leaf inoculation as an early screening test for cocoa (Theobroma cacao L.) resistance to Phytophthora black pod disease. Crop Protection, 14(8), 657–663.CrossRefGoogle Scholar
  29. Nyassé, S., Grivet, L., Risterucci, A. M., Blaha, G., Berry, D., Lanaud, C., & Despreaux, D. (1999). Diversity of Phytophthora megakarya in Central and West Africa revealed by isozyme and RAPD markers. Mycological Research, 103(10), 1225–1234.CrossRefGoogle Scholar
  30. Onesirosan, P. T. (1971). The survival of Phytophthora palmivora in a cacao plantation during the dry season. Phytopathology, 61, 975–977.CrossRefGoogle Scholar
  31. Opeke, L. K., & Gorentz, A. M. (1974). Phytophthora pod rot: symptoms and economic importance. In P. H. Gregory (Ed.), Phytophthora Disease of Cocoa (pp. 117–125). Londres, Royaume-Uni: Longman.Google Scholar
  32. Ortiz-Garcia, C., Herail, C., & Blaha, G. (1994). Utilisation des Isozymes en Tant que Marqueurs pour l’Identification Spécifique des Phytophthora Responsables de la Pourriture Brune des Cabosses dans les Pays Producteurs de Cacao. In Proceedings 11ème Conférence Internationale Sur la Recherche Cacoyère, 1993, Yamoussoukro, Côte d’Ivoire (pp. 135–43).Google Scholar
  33. Rémond, F., Cilas, C., Vega-Rosales, M. I., & Gonzalez, M. O. (1993). Méthodologie d'échantillonnage pour estimer les attaques des baies du caféier par les scolytes (Hypothenemus hampei Ferr.). Café, Cacao, Thé, 37(1), 35–52.Google Scholar
  34. Reynolds, K. M., & Madden, L. V. (1988). Analysis of epidemics using spatio-temporal autocorrelation. Phytopathology, 78, 240–246.CrossRefGoogle Scholar
  35. Ristaino, J. B., & Gumpertz, M. L. (2000). New frontiers in the study of dispersal and spatial analysis of epidemics caused by species in the genus Phytophthora. Annual Review of Phytopathology, 38, 541–576.CrossRefPubMedGoogle Scholar
  36. Ristaino, J. B., & Johnston, S. A. (1999). Ecologically based approaches to management of Phytophthora Blight on bell pepper. Plant Disease, 83(12), 1080–1089.CrossRefGoogle Scholar
  37. SAS Institute Inc. (2001). SAS User’s Guide : Statistics. Institute Inc. Release 8.2, Cary, NC, USA.Google Scholar
  38. Savary, S., Castilla, N. P., & Willocquet, L. (2001). Analysis of the spatiotemporal structure of rice sheath blight epidemics in a farmer’s field. Plant Pathology, 50, 53–68.CrossRefGoogle Scholar
  39. Shaw, M. W. (1994). Modeling stochastic processes in plant pathology. Annual Review of Phytopathology, 32(1), 523–544.CrossRefPubMedGoogle Scholar
  40. Shigesada, N., Kawasaki, K., & Takeda, Y. (1995). Modeling stratified diffusion in biological invasions. American Naturalist, 146, 229–251.CrossRefGoogle Scholar
  41. Stein, A., Kocks, C. G., Zadoks, J. C., Frinking, H. D., Ruissen, M. A., & Myers, D. E. (1994). A geostatistical analysis of the spatio-temporal development of downy mildew epidemics in cabbage. Phytopathology, 84(10), 1227–1238.Google Scholar
  42. Thorold, C. A. (1975). Black Pod Disease. In: Diseases of cocoa. Oxford University Press, Oxford, UK.Google Scholar
  43. Trangmar, B. B., Yost, R. S., & Uehara, G. (1985). Application of geostatistics to spatial studies of soil properties. Advances in Agronomy, 38, 45–74.CrossRefGoogle Scholar
  44. Van de Lande, H. L. (1993). Spatio-temporal analysis of spear rot and ‘marchitezsorpresiva’ in African oil palm in Surinam. Netherlands Journal of Plant Pathology, 99(3), 129–138.CrossRefGoogle Scholar
  45. Van de Lande, H. L., & Zadoks, J. C. (1999). Spatial pattern of spear rot in oil palm plantations in Surinam. Plant Pathology, 48, 189–201.CrossRefGoogle Scholar
  46. Van Maanen, A., & Xu, X. M. (2003). Modelling plant disease epidemics. European Journal of Plant Pathology, 109(7), 669–682.CrossRefGoogle Scholar
  47. Wu, B. M., Van Bruggen, A. H. C., Subbarao, K. V., & Pennings, G. G. H. (2001). Spatial analysis of lettuce downy mildew using geostatistics and geographic information systems. Phytopathology, 91(2), 134–142.CrossRefPubMedGoogle Scholar
  48. Zadoks, J. C., & Van den Bosch, F. (1994). On the spread of plant disease: a theory on foci. Annual Review of Phytopathology, 32(1), 503–521.Google Scholar

Copyright information

© Koninklijke Nederlandse Planteziektenkundige Vereniging 2016

Authors and Affiliations

  • Michel Ndoumbe Nkeng
    • 1
  • Ives Bruno Efombagn Mousseni
    • 2
  • Lucien Bidzanga Nomo
    • 2
  • Ivan Sache
    • 3
  • Christian Cilas
    • 4
    Email author
  1. 1.CARBAP BP 832 DoualaDoualaCameroon
  2. 2.IRADYaoundéCameroon
  3. 3.INRALaboratoire de Pathologie Végétale et EpidémiologieThiverval GrignonFrance
  4. 4.CIRADUR Bioagresseurs, Campus de BaillarguetMontpellier Cedex 5France

Personalised recommendations