INROADS- An International Journal of Jaipur National University
  • Year: 2014
  • Volume: 3
  • Issue: 2

Study and Development of Instrument for Plant Protection Applications Associated with Apple and Picrorhiza kurroa (Kutki) Diseases

  • Author:
  • Vhatkar Dattatraya Shivling1,, Sudhir Kumar Sharma2, C. Ghanshyam3, Sanjay Kumar4, Rakesh Kumar4, Supankar Das5, Sujit Kumar Gupta6
  • Total Page Count: 5
  • Page Number: 456 to 460

1Principal Scientist, CSIR-CSIO, Chandigarh, Punjab, India

2Head of the Department, Department of Electronics and Communication, JNU, Jaipur, Rajasthan, India

3Scientist, Department of Agrionics, CSIR-CSIO, Chandigarh, Punjab, India

4Scientist, CSIR-IHBT, Palampur, Himachal Pradesh, India

5Technical Officer, CSIR-CSIO, Chandigarh, Punjab, India

6Senior Project Fellow, CSIR-CSIO, Chandigarh, Punjab, India

*Corresponding author Email id: vvdatta2007@yahoo.com; vvdatta2008@gmail.com

Online published on 8 October, 2015.

Abstract

In the present research paper, plant response to the environment and disease monitoring system is presented, which is based on the meteorological approach and digital information and communication technology (ICT). It predicts the growth of kutki or apple fruit diseases such as Apple scab, Marssonina blotch, Red mite pest, etc. This system provides solutions to the farmers to mitigate the disease risk. Growth of apple disease and pests are highly dependent on various environmental parameters such as temperature, relative humidity (RH), leaf wetness, etc., which are measured by developing sensor arrangements and using a prediction model by which the index of infection is calculated. It tells about the severity of risk in crop management. This information can be sent to the farmer's mobile phone and also to the server located at far away from the field using GSM-GPRS (General packet radio service) so that they can easily handle the risk of pest control management. This ICT application consists of both hardware and software tools developed by the author.

Keywords

Pest Management, ICT, Disease Forecasting, Prediction Model