https://doi.org/10.4081/jae.2024.1647
Application of MOS gas sensors for detecting mechanical damage of tea plants
Published: 2 December 2024
Abstract Views: 5
PDF: 5
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Authors
Mechanical damage of tea plant is a serious problem in tea production. This work employed metal oxide semiconductor (MOS) gas sensors and gas chromatography-mass spectrometer (GC-MS), as an auxiliary technique, to detect tea plants with different types of mechanical damage in different severities. Various algorithms were applied. The results showed the uniformity of the results of gas sensors and GC-MS. While, it was hard for gas sensors to discriminate among tea plants with different types of mechanical damage. However, the feasibility of gas sensors for predicting the damage severity in different damaged types based on gas sensors was proven, which was more meaningful. Finally, multi-layer perceptron neural networks (MLPNN) was employed and the results showed that the correct discrimination accuracy rate for damage severity was 99.07% for the training set and 95.83% for the testing set, which indicated that MLPNN was an excellent algorithm for damage severity determination. This study provided a new technique for mechanical damage of tea plant detection and was very meaningful for tea plant protection.
Abiri, B., Amini, S., Hejazi, M., Hosseinpanah, F., Zarghi, A., Abbaspour, F., Valizadeh, M. 2023. Tea's anti-obesity properties, cardiometabolic health-promoting potentials, bioactive compounds, and adverse effects: A review focusing on white and green teas. Food Sci. Nutr. 11:5818-5836.
DOI: https://doi.org/10.1002/fsn3.3595
Aghoutane, Y., Brebu, M., Moufd, M., Ionescu, R., Bouchikhi, B., Bari, N.E. 2023. Detection of counterfeit perfumes by using GC-MS technique and electronic nose system combined with chemometric tools. Micromachines 14:524.
DOI: https://doi.org/10.3390/mi14030524
Andrews, S.J., Hackenberg, S C., Carpenter, L.J. 2015. Technical note: a fully automated purge and trap GC-MS system for quantification of volatile organic compound (VOC) fluxes between the ocean and atmosphere. Ocean Sci. 11:13-321.
DOI: https://doi.org/10.5194/os-11-313-2015
Bezerra, R., Sousa-Souto, L., Santana, A., Ambrogi, B.G. 2021. Indirect plant defenses: volatile organic compounds and extrafloral nectar. Arthropod-Plant Inte. 15:467-489.
DOI: https://doi.org/10.1007/s11829-021-09837-1
Chacón-Fuentes, M., Bardehle, L., Seguel, I., Espinoza, J., Lizama, M., Quiroz, A. 2023. Herbivory damage increased VOCs in wild relatives of Murtilla plants compared to their first offspring. Metabolites 13:616.
DOI: https://doi.org/10.3390/metabo13050616
Ghooshkhaneh N. G., Mollazade K. 2023. Optical techniques for fungal disease detection in citrus fruit: a review. Food Bioprocess Tech. 16:1668-1689.
DOI: https://doi.org/10.1007/s11947-023-03005-4
He, W., Yuan, Z., Yin, B., Wu, W., Min, Z. 2023. Robust locally linear embedding and its application in analogue circuit fault diagnosis. Meas. Sci. Technol. 34:105005.
DOI: https://doi.org/10.1088/1361-6501/acdcb1
Holopainen, J. K., Gershenzon, J. 2010. Multiple stress factors and the emission of plant VOCs. Trends Plant Sci. 15:176-184.
DOI: https://doi.org/10.1016/j.tplants.2010.01.006
Jiang, S., Wang, J., Wang, Y., Cheng, S. 2017. A novel framework for analyzing MOS E-nose data based on voting theory: application to evaluate the internal quality of Chinese pecans. Sensors Actuat. B-Chem. 242:511-521.
DOI: https://doi.org/10.1016/j.snb.2016.11.074
Jiang, W., Su, B., Fan, S. 2023. Spatial disequilibrium and dynamic evolution of eco-efficiency in China’s tea industry. Sustainability (Basel) 15:9597.
DOI: https://doi.org/10.3390/su15129597
Lautner, S., Grams, T.E.E., Matyssek, R., Fromm, J. 2005. Characteristics of electrical signals in poplar and responses in photosynthesis. Plant Physiol. 138:2200-2209.
DOI: https://doi.org/10.1104/pp.105.064196
Lee, J.P., Lee, S.W., Kim, C.S., Ji, H.S., Song, J.H., Lee, K.Y., et al. 2006. Evaluation of formulations of bacillus licheniformis for the biological control of tomato gray mold caused by Botrytis cinerea. Biol. Control 37:329-337.
DOI: https://doi.org/10.1016/j.biocontrol.2006.01.001
Lin, W., Gao, Q., Du, M., Chen, W., Tong, T. 2021. Multiclass diagnosis of stages of Alzheimer's disease using linear discriminant analysis scoring for multimodal data. Comput. Biol. Med. 134:104478.
DOI: https://doi.org/10.1016/j.compbiomed.2021.104478
Lu, C., Feng, J., Chen, Y., Liu, W., Lin, Z., Ya,n S. 2020. Tensor robust principal component analysis with a new tensor nuclear norm. IEEE T. Pattern Anal. 42:925-938.
DOI: https://doi.org/10.1109/TPAMI.2019.2891760
Ma, M., Yang, X., Ying, X., Shi, C., Jia, Z., Jia, B. 2023. Applications of gas sensing in food quality detection: a review. Foods (Basel) 12:3966.
DOI: https://doi.org/10.3390/foods12213966
Miller, A.R. 1992. Physiology, biochemistry and detection of bruising (mechanical stress) in fruits and vegetables. Postharvest News Inform. 3:53-58.
Nykänen, H., Koricheva, J. 2004. Damage-induced changes in woody plants and their effects on insect herbivore performance: a meta-analysis. Oikos 104:247-268.
DOI: https://doi.org/10.1111/j.0030-1299.2004.12768.x
Piłat-Rożek, M., Dziadosz, M., Majerek, D., Jaromin-Gleń, K., Szeląg, B., Guz, Ł., et al. 2023. Rapid method of wastewater classification by electronic nose for performance evaluation of bioreactors with activated sludge. Sensors (Basel) 23:8578.
DOI: https://doi.org/10.3390/s23208578
Seo, M., Min, S. 2023. Graph neural networks and implicit neural representation for near-optimal topology prediction over irregular design domains. Eng. Appl. Artif. Intell. 123:106284.
DOI: https://doi.org/10.1016/j.engappai.2023.106284
Sheikhhosseini, Z., Mirzaei, N., Heidari, R., Monkaresi, H. 2021. Delineation of potential seismic sources using weighted k-means cluster analysis and particle swarm optimization (PSO). Acta Geophys. 69:2161-2172.
DOI: https://doi.org/10.1007/s11600-021-00683-6
Sibi, S.P.L., Rajkumar, M., Manoharan, M., Mobika, J., Priya, V.N., Kumar, R.T.R. 2024. Humidity activated ultra-selective room temperature gas sensor based on W doped MoS2/RGO composites for trace level ammonia detection. Anal. Chim. Acta 1287:342075.
DOI: https://doi.org/10.1016/j.aca.2023.342075
Tang, Z., Zhu, J., Song, Q., Daly, P., Kong, L., et al. 2024. Identification and pathogenicity of Fusarium spp. associated with tea wilt in Zhejiang Province, China. BMC Microbiol. 24:38.
DOI: https://doi.org/10.1186/s12866-023-03174-4
Tonin, F., Tao, Q., Patrinos, P., Suykens, J.A.K. 2024. Deep Kernel principal component analysis for multi-level feature learning. Neural Networks 170:578-595.
DOI: https://doi.org/10.1016/j.neunet.2023.11.045
Wang, J. 2012. Geometric structure of high-dimensional data and dimensionality reduction. Berlin, Springer.
DOI: https://doi.org/10.1007/978-3-642-27497-8
Yang, R., Lin, W., Liu, J., Liu, H., Fu, X., Liu, H., et al. 2023. Formation mechanism and solution of Pu-erh tea cream based on non-targeted metabonomics. LTW 173:114331.
DOI: https://doi.org/10.1016/j.lwt.2022.114331
Zangerl, A. 2002. Impact of folivory on photosynthesis is greater than the sum of its holes. Proc. Natl. Acad. Sci. USA 99:1088-1091.
DOI: https://doi.org/10.1073/pnas.022647099
Zhu, C., Guo, J., Yuan, J., Jin, X., Li, C. 2021. Refining altimeter-derived gravity anomaly model from shipborne gravity by multi-layer perceptron neural network: a case in the South China Sea. Remote Sens. (Basel) 13:607.
DOI: https://doi.org/10.3390/rs13040607
Supporting Agencies
Zhejiang Provincial Natural Science Foundation of ChinaHow to Cite
Sun, Y. and Zheng, Y. (2024) “Application of MOS gas sensors for detecting mechanical damage of tea plants”, Journal of Agricultural Engineering, 55(4). doi: 10.4081/jae.2024.1647.
Copyright (c) 2024 the Author(s)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
PAGEPress has chosen to apply the Creative Commons Attribution NonCommercial 4.0 International License (CC BY-NC 4.0) to all manuscripts to be published.
Similar Articles
- Roberto Beghi, Valentina Giovenzana, Raffaele Civelli, Enrico Cini, Riccardo Guidetti, Characterisation of olive fruit for the milling process by using visible/near infrared spectroscopy , Journal of Agricultural Engineering: Vol. 44 No. 2 (2013)
- Daniele Dell'Antonia, Rino Gubiani, Daniele Maroncelli, Gianfranco Pergher, GASEOUS EMISSIONS FROM FOSSIL FUELS AND BIOMASS COMBUSTION IN SMALL HEATING APPLIANCES , Journal of Agricultural Engineering: Vol. 41 No. 4 (2010)
- Yane Ansanay, Praveen Kolar, Ratna Sharma-Shivappa, Jay Cheng, Sunkyu Park, Consuelo Arellano, Pre-treatment of biomasses using magnetised sulfonic acid catalysts , Journal of Agricultural Engineering: Vol. 48 No. 2 (2017)
- Francesca Valenti, Simona M.C. Porto, Giovanni Cascone, Claudia Arcidiacono, Potential biogas production from agricultural by-products in Sicily. A case study of citrus pulp and olive pomace , Journal of Agricultural Engineering: Vol. 48 No. 4 (2017)
- Salvatore Benfratello, Costanza Di Stefano, Vito Ferro, Luigi Palizzolo, Testing mechanical characteristics of chestnut stakes used in bed sills for stream restoration , Journal of Agricultural Engineering: Vol. 48 No. 3 (2017)
- Emanuele Cerruto, Giuseppe Manetto, Giampaolo Schillaci, Vibration produced by hand-held olive electrical harvesters , Journal of Agricultural Engineering: Vol. 43 No. 2 (2012)
- Chiara Antinoro, Vincenzo Bagarello, Vito Ferro, Giuseppe Giordano, Massimo Iovino, Testing the shape-similarity hypothesis between particle-size distribution and water retention for Sicilian soils , Journal of Agricultural Engineering: Vol. 43 No. 3 (2012)
- Frank Agyen Dwomoh, Xingye Zhu, Alexander Fordjour, Junping Liu, Shouqi Yuan, Hong Li, Structural design and performance characteristics of the fluidic sprinkler application technology for saving irrigation water: a review , Journal of Agricultural Engineering: Vol. 54 No. 2 (2023)
- José F. Reyes, Elías Contreras, Christian Correa, Pedro Melin, Image analysis of real-time classification of cherry fruit from colour features , Journal of Agricultural Engineering: Vol. 52 No. 4 (2021)
- Sara Cucchiaro, Laura Carretta, Paolo Nasta, Federico Cazorzi, Roberta Masin, Nunzio Romano, Paolo Tarolli, Multi-temporal geomorphometric analysis to assess soil erosion under different tillage practices: A methodological case study , Journal of Agricultural Engineering: Vol. 53 No. 1 (2022)
<< < 18 19 20 21 22 23 24 25 26 27 > >>
You may also start an advanced similarity search for this article.
