Glyphosate Pattern Recognition Using Microwave-Interdigitated Sensors and Principal Component Analysis
Glyphosate is an herbicide used worldwide with harmful health effects, and efforts are currently being made to develop sensors capable of detecting its presence. In this work, an array of four interdigitated microwave sensors was used together with the multivariate statistical technique of principal...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-02-01
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| Series: | AgriEngineering |
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| Online Access: | https://www.mdpi.com/2624-7402/6/1/32 |
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| author | Carlos R. Santillán-Rodríguez Renee Joselin Sáenz-Hernández Cristina Grijalva-Castillo Eutiquio Barrientos-Juarez José Trinidad Elizalde-Galindo José Matutes-Aquino |
| author_facet | Carlos R. Santillán-Rodríguez Renee Joselin Sáenz-Hernández Cristina Grijalva-Castillo Eutiquio Barrientos-Juarez José Trinidad Elizalde-Galindo José Matutes-Aquino |
| author_sort | Carlos R. Santillán-Rodríguez |
| collection | DOAJ |
| description | Glyphosate is an herbicide used worldwide with harmful health effects, and efforts are currently being made to develop sensors capable of detecting its presence. In this work, an array of four interdigitated microwave sensors was used together with the multivariate statistical technique of principal component analysis, which allowed a well-defined pattern to be found that characterized waters for agricultural use extracted from the Bustillos lagoon. The variability due to differences between the samples was explained by the first principal component, amounting to 86.3% of the total variance, while the variability attributed to the measurements and sensors was explained through the second principal component, amounting to 13.2% of the total variance. The time evolution of measurements showed a clustering of data points as time passed, which was related to microwave–sample interaction, varied with the fluctuating dynamical structure of each sample, and tended to have a stable mean value. |
| first_indexed | 2024-04-24T18:39:18Z |
| format | Article |
| id | doaj.art-dcb830e88388406482dc31f1e2495d7f |
| institution | Directory Open Access Journal |
| issn | 2624-7402 |
| language | English |
| last_indexed | 2024-04-24T18:39:18Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | AgriEngineering |
| spelling | doaj.art-dcb830e88388406482dc31f1e2495d7f2024-03-27T13:16:20ZengMDPI AGAgriEngineering2624-74022024-02-016152653810.3390/agriengineering6010032Glyphosate Pattern Recognition Using Microwave-Interdigitated Sensors and Principal Component AnalysisCarlos R. Santillán-Rodríguez0Renee Joselin Sáenz-Hernández1Cristina Grijalva-Castillo2Eutiquio Barrientos-Juarez3José Trinidad Elizalde-Galindo4José Matutes-Aquino5Centro de Investigación en Materiales Avanzados, S.C. (CIMAV), Av. Miguel de Cervantes #120, Complejo Industrial Chihuahua, Chihuahua 31136, MexicoCentro de Investigación en Materiales Avanzados, S.C. (CIMAV), Av. Miguel de Cervantes #120, Complejo Industrial Chihuahua, Chihuahua 31136, MexicoCONAHCYT—Centro de Investigación en Materiales Avanzados, S.C. (CIMAV), Av. Miguel de Cervantes #120, Complejo Industrial Chihuahua, Chihuahua 31136, MexicoInstituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias, Chihuahua 32910, MexicoInstituto de Ingeniería y Tecnología, Universidad Autónoma de Ciudad Juárez, Av. Del Charro 450 Norte, Ciudad Juárez 32310, MexicoCentro de Investigación en Materiales Avanzados, S.C. (CIMAV), Av. Miguel de Cervantes #120, Complejo Industrial Chihuahua, Chihuahua 31136, MexicoGlyphosate is an herbicide used worldwide with harmful health effects, and efforts are currently being made to develop sensors capable of detecting its presence. In this work, an array of four interdigitated microwave sensors was used together with the multivariate statistical technique of principal component analysis, which allowed a well-defined pattern to be found that characterized waters for agricultural use extracted from the Bustillos lagoon. The variability due to differences between the samples was explained by the first principal component, amounting to 86.3% of the total variance, while the variability attributed to the measurements and sensors was explained through the second principal component, amounting to 13.2% of the total variance. The time evolution of measurements showed a clustering of data points as time passed, which was related to microwave–sample interaction, varied with the fluctuating dynamical structure of each sample, and tended to have a stable mean value.https://www.mdpi.com/2624-7402/6/1/32glyphosateinterdigitated sensorspattern recognitionprincipal component analysis |
| spellingShingle | Carlos R. Santillán-Rodríguez Renee Joselin Sáenz-Hernández Cristina Grijalva-Castillo Eutiquio Barrientos-Juarez José Trinidad Elizalde-Galindo José Matutes-Aquino Glyphosate Pattern Recognition Using Microwave-Interdigitated Sensors and Principal Component Analysis AgriEngineering glyphosate interdigitated sensors pattern recognition principal component analysis |
| title | Glyphosate Pattern Recognition Using Microwave-Interdigitated Sensors and Principal Component Analysis |
| title_full | Glyphosate Pattern Recognition Using Microwave-Interdigitated Sensors and Principal Component Analysis |
| title_fullStr | Glyphosate Pattern Recognition Using Microwave-Interdigitated Sensors and Principal Component Analysis |
| title_full_unstemmed | Glyphosate Pattern Recognition Using Microwave-Interdigitated Sensors and Principal Component Analysis |
| title_short | Glyphosate Pattern Recognition Using Microwave-Interdigitated Sensors and Principal Component Analysis |
| title_sort | glyphosate pattern recognition using microwave interdigitated sensors and principal component analysis |
| topic | glyphosate interdigitated sensors pattern recognition principal component analysis |
| url | https://www.mdpi.com/2624-7402/6/1/32 |
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