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http://dx.doi.org/10.5423/PPJ.2003.19.3.129

Use of Quantitative Models to Describe the Efficacy of Inundative Biological Control of Fusarium Wilt of Cucumber  

Singh, Pushpinder P. (Department of Microbiology(BK21) and Research Institute of Natural Science, Gyeongsang National University)
Benbi, Dinesh K. (Department of Plant Pathology, Punjab Agricultural University)
Young, Ryun-Chung (Department of Soils, Punjab Agricultural University)
Publication Information
The Plant Pathology Journal / v.19, no.3, 2003 , pp. 129-132 More about this Journal
Abstract
Fusarium wilt of cucumber caused by Fusarium oxy-sporum f. sp. cucumerinum is a serious vascular disease worldwide. Biological control of Fusarium wilt in several crops has been accomplished by introducing non-pathogenic Fusarium sup. and other biocontrol agents in soil or in infection courts. In this study, quantitative models were used to determine the biocontrol efficacy of inundatively applied antagonist formulations and the length of their effectiveness in controlling Fusarium wilt of cucumber. Quantitative model of the form [Y=L (1${-exp}^{-kx}$)] best described the relationship between disease incidence (Y, %) and inoculum density (X) of isolates F51 and F55. Isolate F51 was selected as a more virulent isolate based on the extent of its effectiveness in causing the wilt disease. The degree of disease control (Xi/X) obtained with the density of the biocontrol agent (Z), was described by the model [Xi/X=A (1${-exp}^{-cz}$)]. The zeolite-based antagonist formulation amended with chitosan (ZAC) was better at lower rates of application and peaked at around 5 g/ kg of the potting medium, whereas the peat-based antagonist formulation (PA) peaked at around 10 g/kg of the potting medium. ZAC formulation provided significantly better suppression of Fusarium wilt as described by the curvilinear relationship of the type Y= a+bX+c$X^2$, where Y represents percent disease incidence and X represents sustaining effect of the biocontrol agent.
Keywords
Biocontrol; Fusarium oxysporum; quantitative models;
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