Characterizing multiple linkages between individual diseases, crop health syndromes, germplasm deployment, and rice production situations in India uri icon

abstract

  • Five groups of crop health syndromes, four production situations, and three patterns of germplasm deployment were identified and characterized from a data set consisting of information from 129 Indian districts, which were surveyed in 2005 as part of the Production-Oriented Surveys conducted by the Directorate of Rice Research of the Indian Council of Agricultural Research. ANOVAs and MANOVAs indicated that these groupings from hierarchical cluster analyses correspond to clearly different levels of disease and animal pest injuries (crop health syndromes): of crop rotation, crop management, agricultural resources, and inputs (production situations): and of deployment of traditional, high yielding, or hybrid plant material (patterns of germplasm deployment). Correspondence analysis and discriminant analyses further indicated that crop health syndromes, and their change, are strongly associated with production situations, and patterns of germplasm deployment. A few specific hypotheses were tested, indicating that false smut is statistically associated with the involvement of hybrid rice in patterns of germplasm deployment. This highlights the need for research on the biology and the epidemiology of this disease in order to develop suitable management tools. Importantly, this work shows that national surveys, such as the Production-Oriented Surveys conducted by the Directorate of Rice Research, generate extremely valuable information to guide research and development through the characterization of production environments, contexts, and crop health responses, in times of unprecedented agricultural change. This work concurs with earlier results obtained at the field level, and thus opens important methodological questions regarding the up- and down-scaling of information between different scales (e.g., field, district). We propose that our ability to predict emerging diseases and crop health syndromes in the face of global and climate change will necessarily entail our ability to link different scales, where a range of different processes, biological and socio-economic, take place. (C) 2010 Elsevier B.V. All rights reserved.

publication date

  • 2011
  • 2011
  • 2011