Rapid Prediction of Nutrient Concentration in Citrus Leaves Using Vis-NIR Spectroscopy
The nutritional diagnosis of crops is carried out through costly foliar ionomic analysis in laboratories. However, spectroscopy is a sensing technique that could replace these destructive analyses for monitoring nutritional status. This work aimed to develop a calibration model to predict the foliar...
| Autores principales: | , , , , |
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| Formato: | article |
| Lenguaje: | Inglés |
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MDPI
2023
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| Acceso en línea: | https://hdl.handle.net/20.500.11939/8736 https://www.mdpi.com/1424-8220/23/14/6530 |
| _version_ | 1855032845112705024 |
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| author | Acosta, Maylin Quinones, Ana Munera, Sandra De-Paz, José M. Blasco, José |
| author_browse | Acosta, Maylin Blasco, José De-Paz, José M. Munera, Sandra Quinones, Ana |
| author_facet | Acosta, Maylin Quinones, Ana Munera, Sandra De-Paz, José M. Blasco, José |
| author_sort | Acosta, Maylin |
| collection | ReDivia |
| description | The nutritional diagnosis of crops is carried out through costly foliar ionomic analysis in laboratories. However, spectroscopy is a sensing technique that could replace these destructive analyses for monitoring nutritional status. This work aimed to develop a calibration model to predict the foliar concentrations of macro and micronutrients in citrus plantations based on rapid non-destructive spectral measurements. To this end, 592 ‘Clementina de Nules’ citrus leaves were collected during several months of growth. In these foliar samples, the spectral absorbance (430–1040 nm) was measured using a portable spectrometer, and the foliar ionomics was determined by emission spectrometry (ICP-OES) for macro and micronutrients, and the Kjeldahl method to quantify N. Models based on partial least squares regression (PLS-R) were calibrated to predict the content of macro and micronutrients in the leaves. The determination coefficients obtained in the model test were between 0.31 and 0.69, the highest values being found for P, K, and B (0.60, 0.63, and 0.69, respectively). Furthermore, the important P, K, and B wavelengths were evaluated using the weighted regression coefficients (BW) obtained from the PLS-R model. The results showed that the selected wavelengths were all in the visible region (430–750 nm) related to foliage pigments. The results indicate that this technique is promising for rapid and non-destructive foliar macro and micronutrient prediction. |
| format | article |
| id | ReDivia8736 |
| institution | Instituto Valenciano de Investigaciones Agrarias (IVIA) |
| language | Inglés |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | MDPI |
| publisherStr | MDPI |
| record_format | dspace |
| spelling | ReDivia87362025-04-25T14:49:24Z Rapid Prediction of Nutrient Concentration in Citrus Leaves Using Vis-NIR Spectroscopy Acosta, Maylin Quinones, Ana Munera, Sandra De-Paz, José M. Blasco, José Citrus nutrition Agricultural sensors Ionomics Chemometrics Citrus leaves F04 Fertilizing N20 Agricultural machinery and equipment Citrus Fertilization Vis-NIR Spectroscopy Nutrients Spectroscopy Plant analysis The nutritional diagnosis of crops is carried out through costly foliar ionomic analysis in laboratories. However, spectroscopy is a sensing technique that could replace these destructive analyses for monitoring nutritional status. This work aimed to develop a calibration model to predict the foliar concentrations of macro and micronutrients in citrus plantations based on rapid non-destructive spectral measurements. To this end, 592 ‘Clementina de Nules’ citrus leaves were collected during several months of growth. In these foliar samples, the spectral absorbance (430–1040 nm) was measured using a portable spectrometer, and the foliar ionomics was determined by emission spectrometry (ICP-OES) for macro and micronutrients, and the Kjeldahl method to quantify N. Models based on partial least squares regression (PLS-R) were calibrated to predict the content of macro and micronutrients in the leaves. The determination coefficients obtained in the model test were between 0.31 and 0.69, the highest values being found for P, K, and B (0.60, 0.63, and 0.69, respectively). Furthermore, the important P, K, and B wavelengths were evaluated using the weighted regression coefficients (BW) obtained from the PLS-R model. The results showed that the selected wavelengths were all in the visible region (430–750 nm) related to foliage pigments. The results indicate that this technique is promising for rapid and non-destructive foliar macro and micronutrient prediction. 2023-11-15T07:37:35Z 2023-11-15T07:37:35Z 2023 article publishedVersion Acosta, M., Quiñones, A., Munera, S., de-Paz, J. M. & Blasco, J. (2023). Rapid Prediction of Nutrient Concentration in Citrus Leaves Using Vis-NIR Spectroscopy. Sensors, 23(14), 6530. 1424-8220 https://hdl.handle.net/20.500.11939/8736 10.3390/s23146530 https://www.mdpi.com/1424-8220/23/14/6530 en This work is co-financed by the PNDR and GVA-IVIA (projects 52203, 52204 and by the EU through the ERDF of GVA 2021–2027). info:eu-repo/grantAgreement/ERDF/PCV 2021-2027/52203/ES/Sostenibilidad y economía circular como ejes de desarrollo del sector agrario valenciano: suelo, agua y biodiversidad/SostE-SABio info:eu-repo/grantAgreement/ERDF/PCV 2021-2027/52204/ES/Tecnología inteligente para una agricultura digital, sostenible y precisa en la comunitat valenciana/AgrIntel·ligència-CV Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ openAccess MDPI electronico |
| spellingShingle | Citrus nutrition Agricultural sensors Ionomics Chemometrics Citrus leaves F04 Fertilizing N20 Agricultural machinery and equipment Citrus Fertilization Vis-NIR Spectroscopy Nutrients Spectroscopy Plant analysis Acosta, Maylin Quinones, Ana Munera, Sandra De-Paz, José M. Blasco, José Rapid Prediction of Nutrient Concentration in Citrus Leaves Using Vis-NIR Spectroscopy |
| title | Rapid Prediction of Nutrient Concentration in Citrus Leaves Using Vis-NIR Spectroscopy |
| title_full | Rapid Prediction of Nutrient Concentration in Citrus Leaves Using Vis-NIR Spectroscopy |
| title_fullStr | Rapid Prediction of Nutrient Concentration in Citrus Leaves Using Vis-NIR Spectroscopy |
| title_full_unstemmed | Rapid Prediction of Nutrient Concentration in Citrus Leaves Using Vis-NIR Spectroscopy |
| title_short | Rapid Prediction of Nutrient Concentration in Citrus Leaves Using Vis-NIR Spectroscopy |
| title_sort | rapid prediction of nutrient concentration in citrus leaves using vis nir spectroscopy |
| topic | Citrus nutrition Agricultural sensors Ionomics Chemometrics Citrus leaves F04 Fertilizing N20 Agricultural machinery and equipment Citrus Fertilization Vis-NIR Spectroscopy Nutrients Spectroscopy Plant analysis |
| url | https://hdl.handle.net/20.500.11939/8736 https://www.mdpi.com/1424-8220/23/14/6530 |
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