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Research Detail

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MS Monjil
Department of Plant Pathology, Bangladesh Agricultural University, Mymensingh 2202, Bangladesh.

T Ulfat
Department of Plant Pathology, Bangladesh Agricultural University, Mymensingh 2202, Bangladesh.

An experiment has been conducted to observed the disease severity of late blight of potato in the different weather parameters viz., air temperature, soil temperature, dew points, percent relative humidity and period of sunshine. The experiment was conducted in the Net-house, Department of Plant Pathology, Bangladesh Agricultural University (BAU), Mymensingh during July 2016 to November 2017. Weather data were collected on daily basis from BAU weather station during the experimental period. A significant role of weather parameters was detected in disease development and disease progress. Temperature was strongly linked with the late blight infection in potato. From 15 December, 2016 to 12 January, 2017 air temperature was ranged from 21.00-23.50°C and soil temperature was ranged from 19.00-22.00°C, and this range late blight incidence was not detected in the potato plant. From 13-14 January air and soil temperature suddenly decreased 2°C and from next day again increased the temperature as well as starting late blight disease symptoms. It was observed that dew point and percent relative humidity have a big role on late blight disease severity of potato. In 13-14 January, 2017 dew point decreased from 14°C to 8°C and Percent RH decreased from 80% to 51%. From 14 January, 2017, disease symptoms were observed in potato leaves and rapidly increased. Thus, late blight of potato disease may respond to the variation of temperature, dew point and relative humidity.

 

  Weather; Temperature; Disease severity; Late blight; Potato
  Department of Plant Pathology, Bangladesh Agricultural University (BAU), Mymensingh.
  00-07-2016
  00-11-2017
  Pest Management
  Diseases, Potato

To know the relationship between different weather parameters and the severity of late blight disease of potato.

The experiment was conducted in the Net-house and Microbiology and Bio-control Laboratory, Department of Plant Pathology, Bangladesh Agricultural University (BAU), Mymensingh. The experiment was carried out during the period July 2016 to November 2017 following Completely Randomized Design (CRD). Potato Variety, Diamont was selected for the experiment. Apparently good looking, healthy and large potato tubers were collected from market for planting in pot soil. The soil of the experiment was collected and then sun dried for two days. After that the soil was grounded and large particles and plant debris were removed. Soil was mixed with formalin solution @ 200 ml/cft soil. Then the formaldehyde added soil was covered with polyethylene sheets and kept for 2-3 days. After two days the soil was uncovered to release the gas of formalin. The soil was prepared and poured into perforated plastic pot (22 cm height and 18 cm diameter) at the rate of 3 kg soil per pot. Disease severity was determined by observing disease symptoms on leaf of potato. The mean values of rating (blight %) were determined to get rating score of the material with some modification of Henfling (1987). Disease severity was calculated by the following formula (Yaganza et al., 2004): Disease severity (%) = Sum of no.of total rating/Sum of total ratings × maximum grade × 100. Disease severity data ware recorded from 15 December, 2016 to 15 February, 2017. Data were collected daily basis, but data were placed in graph for alternate days. Five parameters of weather were considered for this experiment, such as Air Temperature, Soil Temperature, Dew Point, Relative Humidity and Sunshine. Weather data of all parameters were collected from Bangladesh Meteorological Department, Mymensingh Centre.

  Progressive Agriculture 31 (2): 74-80, 2020
  DOI: https://doi.org/10.3329/pa.v31i2.50711
Funding Source:
1.   Budget:  
  

It can be conclude that temperature, relative humidity and sunshine have combined effect for successful infection and existing temperature prediction might significantly improve their prediction capabilities.

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