Microclimate-Based Pest and Disease Management through a Forewarning System for Sustainable Cotton Production

Bhuvaneswari Madasamy, Paramasivan Balasubramaniam and Ritaban Dutta
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Bhuvaneswari Madasamy: Natioanal Engineering College, Kovilpatti, Tamilnadu 628503, India
Paramasivan Balasubramaniam: Natioanal Engineering College, Kovilpatti, Tamilnadu 628503, India
Ritaban Dutta: Data61, Commonwealth Scientific and Industrial Research Organisation, Hobart 7001, Australia

Agriculture, 2020, vol. 10, issue 12, 1-12

Abstract: Cotton is an essential commercial crop. Unfortunately, this crop is affected by many pests and diseases, which can cause considerable loss in yield. Climate has a strong correlation with the occurrence of pests and diseases in crops. Currently, weather forecasting services are available to the farmers, which help with weather-based planning of farm operations. Still, weather-based pest and disease forewarning services are not available to all the farmers. Unfortunately, cotton cultivation consumes about one-third of total pesticide consumption, which increases the cost of production apart from polluting the environment. An information and communication technology (ICT) based intelligent pest and disease forewarning system for cotton is an innovative system for providing forewarning on pests and diseases. It aims at improving farm productivity through better crop management. In this paper, the proposed method aims to predict the occurrence of pests and diseases based on microclimatic parameters. This pest and disease forewarning information and appropriate crop management practices will be disseminated to the farmers using electronic media through short message service (SMS), the Internet, etc. In this way, both livelihood security and environmental security are achieved. The proposed model shows a higher optimal performance then the two related works in terms of the average root mean square error rate, average accuracy rate, average percentage error rate, and prediction accuracy.

Keywords: pest and disease management; climate change impact; time-series algorithms; sensor networks; information and communication technology (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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