Non-Destructive Detection of Silage pH Based on Colorimetric Sensor Array Using Extended Color Components and Novel Sensitive Dye Screening Method
Non-destructive detection of maize silage quality is essential. The aim is to propose a fast and non-destructive silage pH detection method based on a colorimetric sensor array (CSA). Extended color components, a novel sensitive dye screening method, and a feature screening method were integrated an...
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2025-01-01
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| Series: | Agronomy |
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| Online Access: | https://www.mdpi.com/2073-4395/15/1/184 |
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| author | Kai Zhao Haiqing Tian Jue Zhang Yang Yu Lina Guo Jianying Sun Haijun Li |
| author_facet | Kai Zhao Haiqing Tian Jue Zhang Yang Yu Lina Guo Jianying Sun Haijun Li |
| author_sort | Kai Zhao |
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| description | Non-destructive detection of maize silage quality is essential. The aim is to propose a fast and non-destructive silage pH detection method based on a colorimetric sensor array (CSA). Extended color components, a novel sensitive dye screening method, and a feature screening method were integrated and applied to enhance pH detection. Fifty color components were constructed from five color spaces and used to extract information about the response of CSA to silage. Forward and backward stepwise selection and support vector regression (SVR) were combined to create a sensitive dye screening method, which was used to determine the optimal sensitive dye. The variable combination population analysis–iteratively retains informative variables algorithm was iterated to optimize effective features. Consequently, six hundred variables were extracted from the twelve dyes, which were able to comprehensively and finely characterize the CSA response. Four sensitive dyes were screened out from the twelve dyes, which were sensitive to silage volatile compounds and accurately reflected the odor changes. Twenty-eight effective features were preferred, based on which the SVR model had <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mrow><mi>R</mi></mrow><mrow><mi>p</mi></mrow><mrow><mn>2</mn></mrow></msubsup></mrow></semantics></math></inline-formula>, <i>RMSEP</i> and <i>RPD</i> scores of 0.9533, 0.4186, and 4.4186, respectively; the pH prediction performance was substantially improved. This study provides technical support for the scientific evaluation of silage quality. |
| format | Article |
| id | doaj-art-0d002e8fd7154b2cbc4b00b8ca812a76 |
| institution | Kabale University |
| issn | 2073-4395 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
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| series | Agronomy |
| spelling | doaj-art-0d002e8fd7154b2cbc4b00b8ca812a762025-01-24T13:17:05ZengMDPI AGAgronomy2073-43952025-01-0115118410.3390/agronomy15010184Non-Destructive Detection of Silage pH Based on Colorimetric Sensor Array Using Extended Color Components and Novel Sensitive Dye Screening MethodKai Zhao0Haiqing Tian1Jue Zhang2Yang Yu3Lina Guo4Jianying Sun5Haijun Li6College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, ChinaCollege of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, ChinaCollege of Physics and Electronic Information, Inner Mongolia Normal University, Hohhot 010020, ChinaCollege of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, ChinaCollege of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, ChinaCollege of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, ChinaCollege of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, ChinaNon-destructive detection of maize silage quality is essential. The aim is to propose a fast and non-destructive silage pH detection method based on a colorimetric sensor array (CSA). Extended color components, a novel sensitive dye screening method, and a feature screening method were integrated and applied to enhance pH detection. Fifty color components were constructed from five color spaces and used to extract information about the response of CSA to silage. Forward and backward stepwise selection and support vector regression (SVR) were combined to create a sensitive dye screening method, which was used to determine the optimal sensitive dye. The variable combination population analysis–iteratively retains informative variables algorithm was iterated to optimize effective features. Consequently, six hundred variables were extracted from the twelve dyes, which were able to comprehensively and finely characterize the CSA response. Four sensitive dyes were screened out from the twelve dyes, which were sensitive to silage volatile compounds and accurately reflected the odor changes. Twenty-eight effective features were preferred, based on which the SVR model had <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mrow><mi>R</mi></mrow><mrow><mi>p</mi></mrow><mrow><mn>2</mn></mrow></msubsup></mrow></semantics></math></inline-formula>, <i>RMSEP</i> and <i>RPD</i> scores of 0.9533, 0.4186, and 4.4186, respectively; the pH prediction performance was substantially improved. This study provides technical support for the scientific evaluation of silage quality.https://www.mdpi.com/2073-4395/15/1/184colorimetric sensor arrayfeature selectionnon-destructive detectionsilagepH |
| spellingShingle | Kai Zhao Haiqing Tian Jue Zhang Yang Yu Lina Guo Jianying Sun Haijun Li Non-Destructive Detection of Silage pH Based on Colorimetric Sensor Array Using Extended Color Components and Novel Sensitive Dye Screening Method Agronomy colorimetric sensor array feature selection non-destructive detection silage pH |
| title | Non-Destructive Detection of Silage pH Based on Colorimetric Sensor Array Using Extended Color Components and Novel Sensitive Dye Screening Method |
| title_full | Non-Destructive Detection of Silage pH Based on Colorimetric Sensor Array Using Extended Color Components and Novel Sensitive Dye Screening Method |
| title_fullStr | Non-Destructive Detection of Silage pH Based on Colorimetric Sensor Array Using Extended Color Components and Novel Sensitive Dye Screening Method |
| title_full_unstemmed | Non-Destructive Detection of Silage pH Based on Colorimetric Sensor Array Using Extended Color Components and Novel Sensitive Dye Screening Method |
| title_short | Non-Destructive Detection of Silage pH Based on Colorimetric Sensor Array Using Extended Color Components and Novel Sensitive Dye Screening Method |
| title_sort | non destructive detection of silage ph based on colorimetric sensor array using extended color components and novel sensitive dye screening method |
| topic | colorimetric sensor array feature selection non-destructive detection silage pH |
| url | https://www.mdpi.com/2073-4395/15/1/184 |
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