Advanced biosensing technologies for monitoring of agriculture pests and diseases: A review

[13] V Rossi, S Giosuè, T Caffi. Modelling plant diseases for decision making in crop protection. Precision Crop Protection - the Challenge and Use of Heterogeneity. Dordrecht: Springer Netherlands, 241(2010).

[14] M Grünig, E Razavi, P Calanca et al. Applying deep neural networks to predict incidence and phenology of plant pests and diseases. Ecosphere, 12, e03791(2021).

[15] T Cordier, D Forster, Y Dufresne et al. Supervised machine learning outperforms taxonomy-based environmental DNA metabarcoding applied to biomonitoring. Mol Ecol Resour, 18, 1381(2018).

[16] R van Klink, T August, Y Bas et al. Emerging technologies revolutionise insect ecology and monitoring. Trends Ecol Evol, 37, 872(2022).

[17] A K Mahlein. Plant disease detection by imaging sensors - parallels and specific demands for precision agriculture and plant phenotyping. Plant Dis, 100, 241(2016).

[18] J C Zhang, Y B Huang, R L Pu et al. Monitoring plant diseases and pests through remote sensing technology: A review. Comput Electron Agric, 165, 104943(2019).

[19] K Ennouri, A Kallel. Remote sensing: An advanced technique for crop condition assessment. Math Probl Eng, 2019, 1(2019).

[20] A K Mahlein, M T Kuska, S Thomas et al. Plant disease detection by hyperspectral imaging: From the lab to the field. Adv Animal Biosci, 8, 238(2017).

[21] M O J Carlos, H C L María, B F Veronica. Detection of significant wavelengths for identifying and classifying Fusarium oxysporum during the incubation period and water stress in Solanum lycopersicum plants using reflectance spectroscopy. J Plant Prot Res, 59, 244(2019).

[22] L do Prado Ribeiro, A L S Klock, J A W Filho et al. Hyperspectral imaging to characterize plant-plant communication in response to insect herbivory. Plant Methods, 14, 54(2018).

[23] P A Eliopoulos, I Potamitis, D Ch Kontodimas et al. Detection of adult beetles inside the stored wheat mass based on their acoustic emissions. J Econ Entomol, 108, 2808(2015).

[24] G A Holguin, B L Lehman, L A Hull et al. Electronic traps for automated monitoring of insect populations. IFAC Proc Vol, 43, 49(2010).

[25] B Shaked, A Amore, C Ioannou et al. Electronic traps for detection and population monitoring of adult fruit flies (Diptera: Tephritidae). J Appl Entomol, 142, 43(2018).

[26] W G Ding, G Taylor. Automatic moth detection from trap images for pest management. Comput Electron Agric, 123, 17(2016).

[27] T J Welsh, D Bentall, C Kwon et al. Automated surveillance of lepidopteran pests with smart optoelectronic sensor traps. Sustainability, 14, 9577(2022).

[28] I Potamitis, I Rigakis, N Vidakis et al. Affordable bimodal optical sensors to spread the use of automated insect monitoring. J Sens, 2018, 1(2018).

[29] M E Maffei. Sites of synthesis, biochemistry and functional role of plant volatiles. S Afr N J Bot, 76, 612(2010).

[30] S Xu, Z Y Zhou, K L Li et al. Recognition of the duration and prediction of insect prevalence of stored rough rice infested by the red flour beetle (tribolium castaneum herbst) using an electronic nose. Sensors, 17, 688(2017).

[31] B Nouri, K Fotouhi, S S Mohtasebi et al. Detection of different densities ofEphestia kuehniella pest on white flour at different larvae instar by an electronic nose system. J Stored Prod Res, 84, 101522(2019).

[32] M F Rutolo, D Iliescu, J P Clarkson et al. Early identification of potato storage disease using an array of metal-oxide based gas sensors. Postharvest Biol Technol, 116, 50(2016).

[33] M Labanska, S Jenkins, S Van Amsterdam et al. Detection of the fungal infection in post-harvest Onions by an electronic nose. 2022 IEEE International Symposium on Olfaction and Electronic Nose, 1(2022).

[34] K P P Chang, A Zakaria, A S Abdul Nasir et al. Analysis and feasibility study of plant disease using e-nose. 2014 IEEE International Conference on Control System, Computing and Engineering, 58(2015).

[35] S Hazarika, R Choudhury, B Montazer et al. Detection of citrus tristeza virus in mandarin orange using a custom-developed electronic nose system. IEEE Trans Instrum Meas, 69, 9010(2020).

[36] S Srivastava, G Mishra, H N Mishra. Fuzzy controller based E-nose classification ofSitophilus oryzae infestation in stored rice grain. Food Chem, 283, 604(2019).

[37] A Cellini, S Blasioli, E Biondi et al. Potential applications and limitations of electronic nose devices for plant disease diagnosis. Sensors, 17, 2596(2017).

[38] Z C Zheng, C Zhang. Electronic noses based on metal oxide semiconductor sensors for detecting crop diseases and insect pests. Comput Electron Agric, 197, 106988(2022).

[39] T Wen, L Z Zheng, S Dong et al. Rapid detection and classification of citrus fruits infestation byBactrocera dorsalis (Hendel) based on electronic nose. Postharvest Biol Technol, 147, 156(2019).

[40] B D Lampson, Y J Han, A Khalilian et al. Development of a portable electronic nose for detection of pests and plant damage. Comput Electron Agric, 108, 87(2014).

[41] E Biondi, S Blasioli, A Galeone et al. Detection of potato brown rot and ring rot by electronic nose: From laboratory to real scale. Talanta, 129, 422(2014).

[42] V Schroeder, S Savagatrup, M He et al. Carbon nanotube chemical sensors. Chem Rev, 119, 599(2019).

[43] R M Cardoso, T S Pereira, M H M Facure et al. Current progress in plant pathogen detection enabled by nanomaterials-based (bio)sensors. Sens Actuat Rep, 4, 100068(2022).

[44] A Rabti, N Raouafi, A Merkoçi. Bio(Sensing) devices based on ferrocene-functionalized graphene and carbon nanotubes. Carbon, 108, 481(2016).

[45] H Onthath, M R Maurya, S Bykkam et al. Development and fabrication of carbon nanotube (CNT)/CuO nanocomposite for volatile organic compounds (VOCs) gas sensor application. Macromol Symp, 402, 2270202(2022).

[46] M W C C Greenshields, M A Mamo, N J Coville et al. Tristimulus mathematical treatment application for monitoring fungi infestation evolution in melon using the electrical response of carbon nanostructure-polymer composite based sensors. Sens Actuat B, 188, 378(2013).

[47] M W C C Greenshields, B B Cunha, N J Coville et al. Fungi active microbial metabolism detection of rhizopus sp. and aspergillus sp. section nigri on strawberry using a set of chemical sensors based on carbon nanostructures. Chemosensors, 4, 19(2016).

[48] D Zhao, B Y Zhao, D Koltsov et al. Detection of VOCs and nitrogen containing gaseous molecules by utilizing carbon nanotubes (CNTs) as sensing materials. Meet Abstr, 2629(2022).

[49] M S Verma, S C Wei, J L Rogowski et al. Interactions between bacterial surface and nanoparticles govern the performance of “chemical nose” biosensors. Biosens Bioelectron, 83, 115(2016).

[50] J S Kim, H W Yoo, H O Choi et al. Tunable volatile organic compounds sensor by using thiolated ligand conjugation on MoS2. Nano Lett, 14, 5941(2014).

[51] P Moitra, D Bhagat, V B Kamble et al. First example of engineered β-cyclodextrinylated MEMS devices for volatile pheromone sensing of olive fruit pests. Biosens Bioelectron, 173, 112728(2021).

[52] Y Q Zheng, Y W Wang, Z X Li et al. MXene quantum dots/perovskite heterostructure enabling highly specific ultraviolet detection for skin prevention. Matter, 6, 506(2023).

[53] Y F Chai, C Y Chen, X Luo et al. Cohabiting plant-wearable sensorin situ monitors water transport in plant. Adv Sci, 8, 2003642(2021).

[54] J P Giraldo, H H Wu, G M Newkirk et al. Nanobiotechnology approaches for engineering smart plant sensors. Nat Nanotechnol, 14, 541(2019).

[55] J Liu. Smart-agriculture: wearable devices for plant protection. In: Wearable Physical, Chemical and Biological Sensors. Amsterdam: Elsevier(2022).

[56] A S Nezhad. Future of portable devices for plant pathogen diagnosis. Lab Chip, 14, 2887(2014).

[57] K R Dong, Y C Wang, R P Zhang et al. Flexible and shape-morphing plant sensors designed for microenvironment temperature monitoring of irregular surfaces. Adv Mater Technol, 2201204(2022).

[58] Y Y Lu, G Yang, Y J Shen et al. Multifunctional flexible humidity sensor systems towards noncontact wearable electronics. Nanomicro Lett, 14, 150(2022).

[59] L Y Lan, X H Le, H Y Dong et al. One-step and large-scale fabrication of flexible and wearable humidity sensor based on laser-induced graphene for real-time tracking of plant transpiration at bio-interface. Biosens Bioelectron, 165, 112360(2020).

[60] S Oren, H Ceylan, P S Schnable et al. Wearable electronics: High-resolution patterning and transferring of graphene-based nanomaterials onto tape toward roll-to-roll production of tape-based wearable sensors. Adv Mater Technol, 2, 1770055(2017).

[61] L L Li, S F Zhao, W H Ran et al. Dual sensing signal decoupling based on tellurium anisotropy for VR interaction and neuro-reflex system application. Nat Commun, 13, 5975(2022).

[62] Y Y Lu, K C Xu, L S Zhang et al. Multimodal plant healthcare flexible sensor system. ACS Nano, 14, 10966(2020).

[63] S M Khan, S F Shaikh, N Qaiser et al. Flexible lightweight CMOS-enabled multisensory platform for plant microclimate monitoring. IEEE Trans Electron Devices, 65, 5038(2018).

[64] J M Nassar, S M Khan, D R Villalva et al. Compliant plant wearables for localized microclimate and plant growth monitoring. Npj Flex Electron, 2, 24(2018).

[65] K Lee, J Park, M S Lee et al. In-situ synthesis of carbon nanotube-graphite electronic devices and their integrations onto surfaces of live plants and insects. Nano Lett, 14, 2647(2014).

[66] Z Li, Y X Liu, O Hossain et al. Real-time monitoring of plant stresses via chemiresistive profiling of leaf volatiles by a wearable sensor. Matter, 4, 2553(2021).

[67] Y M Zhang, J M Cao, Z Y Yuan et al. TiVCTx MXene/chalcogenide heterostructure-based high-performance magnesium-ion battery as flexible integrated units. Small, 18, 2202313(2022).

[68] T T Høye, J Ärje, K Bjerge et al. Deep learning and computer vision will transform entomology. Proc Natl Acad Sci USA, 118, e2002545117(2021).

[69] A Galieni, N D'Ascenzo, F Stagnari et al. Past and future of plant stress detection: An overview from remote sensing to positron emission tomography. Front Plant Sci, 11, 609155(2021).

[70] J Barbedo. A review on the use of unmanned aerial vehicles and imaging sensors for monitoring and assessing plant stresses. Drones, 3, 40(2019).

[71] P P Roosjen, B Kellenberger, L Kooistra et al. Deep learning for automated detection of Drosophila suzukii: Potential for UAV-based monitoring. Pest Manag Sci, 76, 2994(2020).

[72] P Shanmugapriya, S Rathika, T Ramesh et al. Applications of remote sensing in agriculture - A review. Int J Curr Microbiol App Sci, 8, 2270(2019).

[73] M Bietresato, G Carabin, D D'Auria et al. A tracked mobile robotic lab for monitoring the plants volume and health. 2016 12th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications, 1(2016).

[74] Z H Hu, B Y Liu, Y C Zhao. Agricultural robot for intelligent detection of Pyralidae insects. Agricultural Robots - Fundamentals and Applications. London: IntechOpen(2019).

[75] S F Zhao, W H Ran, Z Lou et al. Neuromorphic-computing-based adaptive learning using ion dynamics in flexible energy storage devices. Natl Sci Rev, 9, nwac158(2022).

[76] I Potamitis, P Eliopoulos, I Rigakis. Automated remote insect surveillance at a global scale and the Internet of Things. Robotics, 6, 19(2017).

[77] L Chettri, R Bera. A comprehensive survey on Internet of Things (IoT) toward 5G wireless systems. IEEE Internet Things J, 7, 16(2020).

Tools

Get Citation

Copy Citation Text

Jiayao He, Ke Chen, Xubin Pan, Junfeng Zhai, Xiangmei Lin. Advanced biosensing technologies for monitoring of agriculture pests and diseases: A review[J]. Journal of Semiconductors, 2023, 44(2): 023104

Download Citation

EndNote(RIS)BibTex Plain Text

Set citation alerts for article

Save article for my favorites

Paper Information

Category: Articles

Received: Nov. 25, 2022

Accepted: --

Published Online: Mar. 20, 2023

The Author Email: He Jiayao (zjf1208@163.com), Chen Ke (zjf1208@163.com), Pan Xubin (zjf1208@163.com), Zhai Junfeng (zjf1208@163.com), Lin Xiangmei (linxm@caiq.org.cn)

DOI:10.1088/1674-4926/44/2/023104

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology