Research on Quality Detection of Jujube (<i>Ziziphus jujuba</i> Mill.) Fruit Based on UAV Multi-Spectrum
To enhance the accuracy of multispectral detection using unmanned aerial vehicles (UAVs), multispectral data of jujube fruit with different soluble solids content (SSC) and moisture content (MC) were obtained under different relative azimuth angles. Prediction models for SSC and MC of jujube fruit w...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-03-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/14/7/2962 |
| _version_ | 1797212827961786368 |
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| author | Xueting Ma Congying Wang Huaping Luo Ganggang Guo |
| author_facet | Xueting Ma Congying Wang Huaping Luo Ganggang Guo |
| author_sort | Xueting Ma |
| collection | DOAJ |
| description | To enhance the accuracy of multispectral detection using unmanned aerial vehicles (UAVs), multispectral data of jujube fruit with different soluble solids content (SSC) and moisture content (MC) were obtained under different relative azimuth angles. Prediction models for SSC and MC of jujube fruit were established using partial least squares regression (PLSR) and support vector machines (SVM), respectively. The findings revealed that the MC of jujube fruit had the best prediction effect when the relative azimuth angle was 90°, while the SSC of the jujube fruit had the best prediction effect at an azimuth angle of 180°. Then, the spectral reflectance data corresponding to the eight relative azimuth angles were used as input variables to establish a jujube fruit quality detection model. The results showed that the prediction model for MC and SSC, established using the angle fusion method, had higher detection accuracy compared to the prediction model established at a single angle. This research provides a technical reference for improving the accuracy of outdoor jujube fruit quality detection using spectral technology. |
| first_indexed | 2024-04-24T10:48:35Z |
| format | Article |
| id | doaj.art-2685d40df1d646809f55dcc3fa5492e5 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-04-24T10:48:35Z |
| publishDate | 2024-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-2685d40df1d646809f55dcc3fa5492e52024-04-12T13:15:19ZengMDPI AGApplied Sciences2076-34172024-03-01147296210.3390/app14072962Research on Quality Detection of Jujube (<i>Ziziphus jujuba</i> Mill.) Fruit Based on UAV Multi-SpectrumXueting Ma0Congying Wang1Huaping Luo2Ganggang Guo3Xinjiang Production & Construction Corps Key Laboratory of Protection and Utilization of Biological Resources in Tarim Basin, Tarim University, Alar 843300, ChinaXinjiang Production & Construction Corps Key Laboratory of Protection and Utilization of Biological Resources in Tarim Basin, Tarim University, Alar 843300, ChinaXinjiang Production & Construction Corps Key Laboratory of Protection and Utilization of Biological Resources in Tarim Basin, Tarim University, Alar 843300, ChinaXinjiang Production & Construction Corps Key Laboratory of Protection and Utilization of Biological Resources in Tarim Basin, Tarim University, Alar 843300, ChinaTo enhance the accuracy of multispectral detection using unmanned aerial vehicles (UAVs), multispectral data of jujube fruit with different soluble solids content (SSC) and moisture content (MC) were obtained under different relative azimuth angles. Prediction models for SSC and MC of jujube fruit were established using partial least squares regression (PLSR) and support vector machines (SVM), respectively. The findings revealed that the MC of jujube fruit had the best prediction effect when the relative azimuth angle was 90°, while the SSC of the jujube fruit had the best prediction effect at an azimuth angle of 180°. Then, the spectral reflectance data corresponding to the eight relative azimuth angles were used as input variables to establish a jujube fruit quality detection model. The results showed that the prediction model for MC and SSC, established using the angle fusion method, had higher detection accuracy compared to the prediction model established at a single angle. This research provides a technical reference for improving the accuracy of outdoor jujube fruit quality detection using spectral technology.https://www.mdpi.com/2076-3417/14/7/2962UAV multispectraljujube fruitmoisture content detectionsoluble solids content detectionrelative azimuth angle |
| spellingShingle | Xueting Ma Congying Wang Huaping Luo Ganggang Guo Research on Quality Detection of Jujube (<i>Ziziphus jujuba</i> Mill.) Fruit Based on UAV Multi-Spectrum Applied Sciences UAV multispectral jujube fruit moisture content detection soluble solids content detection relative azimuth angle |
| title | Research on Quality Detection of Jujube (<i>Ziziphus jujuba</i> Mill.) Fruit Based on UAV Multi-Spectrum |
| title_full | Research on Quality Detection of Jujube (<i>Ziziphus jujuba</i> Mill.) Fruit Based on UAV Multi-Spectrum |
| title_fullStr | Research on Quality Detection of Jujube (<i>Ziziphus jujuba</i> Mill.) Fruit Based on UAV Multi-Spectrum |
| title_full_unstemmed | Research on Quality Detection of Jujube (<i>Ziziphus jujuba</i> Mill.) Fruit Based on UAV Multi-Spectrum |
| title_short | Research on Quality Detection of Jujube (<i>Ziziphus jujuba</i> Mill.) Fruit Based on UAV Multi-Spectrum |
| title_sort | research on quality detection of jujube i ziziphus jujuba i mill fruit based on uav multi spectrum |
| topic | UAV multispectral jujube fruit moisture content detection soluble solids content detection relative azimuth angle |
| url | https://www.mdpi.com/2076-3417/14/7/2962 |
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