TY - JOUR
T1 - Highly sensitive graphene oxide leaf wetness sensor for disease supervision on medicinal plants
AU - Patle, Kamlesh S.
AU - Dehingia, Biswajit
AU - Kalita, Hemen
AU - Palaparthy, Vinay S.
N1 - KAUST Repository Item: Exported on 2022-09-14
Acknowledgements: The authors are thankful the Department of Science and Technology - Science and Engineering Research Board (DST-SERB) for financial assistance received through a start-up research grant (SRG) FILE NO. SRG/2019/000895. We would like to extend our thanks to the staff of Nanofabrication Core Lab, King Abdullah University of Science and Technology (KAUST), Saudi Arabia for providing his assistance in the project. Author HK would like to thank DST-SERB for funding project under ‘Early career research award’ (SERB/F/77662018-2019). HK would like to thank UGC-BSR for the research start-up grant [F.30-386/2017 (BSR)]. Authors are thankful to the IIT Bombay Nanofabrication facility (IITBNF) for performing XRF.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.
PY - 2022/7/21
Y1 - 2022/7/21
N2 - Plant disease prediction plays a pivotal role to abate the crop loss. For this purpose, early disease prediction models have been explored, where information about leaf wetness duration (LWD) is one of the important factors. The leaf wetness duration is measured with the help of leaf wetness sensors (LWS). Here, the LWS is fabricated on the polyamide flexible substrate where graphene oxide (GO) is used as the sensing film to detect the water molecules on the leaf canopy. Fabricated GO LWS has been tested under laboratory conditions, we exposed the entire sensing film with water molecule and we observed that it offers response of about 45000 % with respect to the air. Subsequently, observed response time of the fabricated sensor is around 400 s with recovery time of about 100 s. Further, the fabricated sensor shows only 2 % change in the response when exposed to the temperature ranging from 20 0C to 65 0C. Under field conditions, to explore the efficacy of the fabricated LWS, we benchmarked the LWD measured using the GO LWS with commercial LWS (Phytos 31). We have deployed the fabricated GO LWS along with Phytos 31 on the Tulsi (Ocimum tenuiflorum) medical plant. The on-field testing of the GO LWS indicates that maximum difference in LWD value using fabricated GO LWS and Phytos 31 is around ± 30 min.
AB - Plant disease prediction plays a pivotal role to abate the crop loss. For this purpose, early disease prediction models have been explored, where information about leaf wetness duration (LWD) is one of the important factors. The leaf wetness duration is measured with the help of leaf wetness sensors (LWS). Here, the LWS is fabricated on the polyamide flexible substrate where graphene oxide (GO) is used as the sensing film to detect the water molecules on the leaf canopy. Fabricated GO LWS has been tested under laboratory conditions, we exposed the entire sensing film with water molecule and we observed that it offers response of about 45000 % with respect to the air. Subsequently, observed response time of the fabricated sensor is around 400 s with recovery time of about 100 s. Further, the fabricated sensor shows only 2 % change in the response when exposed to the temperature ranging from 20 0C to 65 0C. Under field conditions, to explore the efficacy of the fabricated LWS, we benchmarked the LWD measured using the GO LWS with commercial LWS (Phytos 31). We have deployed the fabricated GO LWS along with Phytos 31 on the Tulsi (Ocimum tenuiflorum) medical plant. The on-field testing of the GO LWS indicates that maximum difference in LWD value using fabricated GO LWS and Phytos 31 is around ± 30 min.
UR - http://hdl.handle.net/10754/680008
UR - https://linkinghub.elsevier.com/retrieve/pii/S0168169922005397
UR - http://www.scopus.com/inward/record.url?scp=85134647060&partnerID=8YFLogxK
U2 - 10.1016/j.compag.2022.107225
DO - 10.1016/j.compag.2022.107225
M3 - Article
SN - 0168-1699
VL - 200
SP - 107225
JO - Computers and Electronics in Agriculture
JF - Computers and Electronics in Agriculture
ER -