Harnessing sensor-based solutions to combat fall armyworm in India
|cookielawinfo-checkbox-advertisement||1 year||Set by the GDPR Cookie Consent plugin, this cookie records the user consent for the cookies in the "Advertisement" category.|
|cookielawinfo-checkbox-analytics||11 months||This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Analytics".|
|cookielawinfo-checkbox-functional||11 months||The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional".|
|cookielawinfo-checkbox-necessary||11 months||This cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary".|
|cookielawinfo-checkbox-others||11 months||This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Other.|
|cookielawinfo-checkbox-performance||11 months||This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Performance".|
|CookieLawInfoConsent||1 year||CookieYes sets this cookie to record the default button state of the corresponding category and the status of CCPA. It works only in coordination with the primary cookie.|
|_GRECAPTCHA||5 months 27 days||Google Recaptcha service sets this cookie to identify bots to protect the website against malicious spam attacks.|
|ac_enable_tracking||1 month||This cookie is set by Active Campaign to denote that traffic is enabled for the website.|
|_fbp||3 months||Facebook sets this cookie to display advertisements when either on Facebook or on a digital platform powered by Facebook advertising after visiting the website.|
|_ga||1 year 1 month 4 days||Google Analytics sets this cookie to calculate visitor, session and campaign data and track site usage for the site's analytics report. The cookie stores information anonymously and assigns a randomly generated number to recognise unique visitors.|
|_gat_gtag_UA_*||1 minute||Google Analytics sets this cookie to store a unique user ID.|
|_ga_*||1 year 1 month 4 days||Google Analytics sets this cookie to store and count page views.|
|_gid||1 day||Google Analytics sets this cookie to store information on how visitors use a website while also creating an analytics report of the website's performance. Some of the collected data includes the number of visitors, their source, and the pages they visit anonymously.|
|prism_26259200||1 month||Description is currently not available.|
Harnessing sensor-based solutions to combat fall armyworm in India
Over the last two years, Crop Health and Protection (CHAP) has led a two-phased project alongside a multidisciplinary and international team, including Knowmatics, Ystumtec and CABI, and supported by consortium members, MSSRF, Tamil Nadu Agriculture University (TNAU) and Pushkaram College of Agriculture Sciences, to develop an innovative sensor-based pheromone trap to help effectively monitor fall armyworm (FAW) in India.
This game-changing feasibility project was kindly funded by the UK Foreign, Commonwealth and Development Office’s (FCDO) Science and Innovation Network in New Delhi, India.
Fall armyworm, scientifically known as Spodoptera frugiperda, poses a significant threat to crops globally. Having already devastated cornfields in sub-Saharan Africa, this invasive species made its way to India around 2018. Its presence was swiftly followed by a rapid spread across the subcontinent, affecting maize cultivation in approximately 20 states. Intensive monoculture practices coupled with the emergence of pesticide resistant FAW have since been threatening the livelihoods of smallholder farmers around the country.
To address this challenge, a coordinated sentinel network is urgently needed to predict pest presence accurately, supporting farmers and growers in anticipating risks. However, due to the lack of key datasets, the establishment of a reliable sentinel network could not be initiated. As such, implementing sustainable crop protection strategies that mitigate inputs and minimise risk will be crucial for its setup. Ultimately, bridging the data gap and equipping farmers with the tools required to face upcoming challenges posed by FAW infestations is pivotal.
The project was delivered in two phases, with the first phase (2021-2022) focused on:
Outputs of this first phase demonstrated that the initial iteration of the novel pest sensor was able to transmit data from a field site in Tamil Nadu, where there is a high risk of FAW attack, to a farmer’s mobile phone. This phase showed that the novel remote sensing device could save farmers time, improve yields, and provide valuable intelligence of the presence of pests on farms.
The aim of the second phase (2022-2023) of the project was to build on this earlier work by transforming the hardware design and quantify efficacy of the device, through collaboration with MSSRF and Pushkaram College of Agriculture Sciences, so that we could establish datasets that correlate sensor signals and pheromone trap morphology with known pest species presence.
The approach included:
Below we detail the methodology for delivering the aforementioned works.
First, the team conducted an extensive literature review to research wind tunnel designs and protocols. Executed at Pushkaram College of Agriculture Science in Tamil Nadu, the work produced a detailed computer-aided design (CAD) model and comprehensive bill of materials (BOM). The BOM informed local material procurement within Tamil Nadu, while Ystumtec and Knowmatics supported with the wind tunnel construction using “t-slot” extrusion, polycarbonate sheet (Lexan), and standard ventilation fans. This approach ensured both functionality and local material accessibility. Additionally, the wind tunnel was outfitted with a computer and camera system for efficient experimental recording.
For the establishment of an effective fabrication capability, the project partners selected a range of tools and equipment such as a 3D printer and a small format laser cutter. This allowed the team to update the trap morphology based on user feedback.
Next, Ystumtec redesigned, built and tested a completely new version of the moth trap and sourced, configured and tested LoRaWAN gateways to be used as relay stations for use with the new design. Testing showed that data can be reliably received at least 16km range which means that a single gateway installed at Pushkaram College of Agriculture Science could cover more than 800km2 of land around the college.
Concurrently, a field experiment with maize was established with crop growth and FAW infestation monitored, and 30% crop damage recorded. The Pushkaram College of Agriculture Sciences, alongside guidance from CABI, developed methodologies for FAW larval collection and rearing. The work facilitated wind tunnel flight behaviour testing and life cycle study. A FAW culturing cabinet was established to observe pupae, adult emergence, and egg laying under controlled conditions. Additionally, a Y-tube testing facility was set up for further investigation.
To mark the end of phase two, a multi-stakeholder ‘show and tell’ event was hosted to provide a platform for farmers, growers, researchers, agricultural stakeholders and the local community to exchange insights, strategies and solutions to combat the challenges posed by FAW in India. The event showcased the ongoing efforts of the sentinel network invasive monitoring project, offered an introduction to CHAP, and featured presentations by CABI discussing the Plantwise program and plant clinic activities in the region.
The project has been a resounding success with the team achieving a series of key deliverables. These include the delivery of the updated trap morphology, which was supported through the establishment of new facilities and capabilities, as well as knowledge exchange and development of protocols.
The project also developed a comprehensive risk model for factors influencing FAW growth and lifecycle, and the design of a farmer-centric user experience pathway along with a progressive web app featuring initial risk reporting for farmers and agronomy advisors.
Furthermore, the establishment of FAW culturing facilities has supported the advancement of the novel pest sensor. Notably, the project has yielded valuable insights into device installation and user training processes, informing subsequent phases of iteration and testing.
For more information about the pest, visit the fall armyworm research collaboration portal.
© 2019 CHAP - Crop Health and Protection Limited