EPIDEMIOLOGY OF BANANA FUSARIUM FRUIT ROT UNDER SOUTH GUJARAT CONDITION

T.T. BARIA¹*, K.B. RAKHOLIYA², A.K. CHAUDHARI^3
1Department of Plant Pathology, N.M. College of Agriculture, Navsari Agricultural University, Navsari, Gujarat, 396 450, India
²Department of Plant Pathology, N.M. College of Agriculture, Navsari Agricultural University, Navsari, Gujarat, 396 450, India
³Department of Plant Pathology, N.M. College of Agriculture, Navsari Agricultural University, Navsari, Gujarat, 396 450, India
* Corresponding Author : bariatushar4@gmail.com

Received : 01-03-2020     Accepted : 27-03-2020     Published : 30-03-2020
Volume : 12     Issue : 3       Pages : 1785 - 1788
Int J Microbiol Res 12.3 (2020):1785-1788

Keywords : Banana, Fusarium fruit rot, Fusarium musae, Epidemiology, Correlation, Regression
Academic Editor : Dr Ranjana Hawaldar, Takemi Otsuki
Conflict of Interest : None declared
Acknowledgements/Funding : Authors are thankful to Department of Plant Pathology, N. M. College of Agriculture, Navsari Agricultural University, Navsari, 396 450, Gujarat, India
Author Contribution : All authors equally contributed

Banana fusarium fruit rot is an important post-harvest disease. Environmental factor plays important role to disease development. The initiation of the disease was noted in the month of July and continuously progressed upto the harvest of the fruits. The disease was more progressive during 36th to 39th MSW which considered as the window period. Correlation coefficient study between weather parameters and disease incidence indicated that all the parameters jointly played an important role in the development of fusarium fruit rot. Moreover, maximum temperature, minimum temperature, average temperature and relative humidity were found to play important role in the disease development. The stepwise regression, it has been also observed that R2-value (0.67) indicating association between per cent disease index to average temperature and maximum temperature. The stepwise regression equation [?= -586.270 + 18.613 (X4) + (-38.456) (X2) whereas, Y= Predicted Disease Index, X2= Maximum Temperature and X4= Average temperature]. Thus, maximum temperature and average temperature found to play dominant role in the disease development.

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