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dc.contributor.author | Acosta, Maylin | es_ES |
dc.contributor.author | Quiñones, Ana | es_ES |
dc.contributor.author | Munera, Sandra | es_ES |
dc.contributor.author | de Paz, Jose Miguel | es_ES |
dc.contributor.author | Blasco, José | es_ES |
dc.date.accessioned | 2024-01-12T19:02:23Z | |
dc.date.available | 2024-01-12T19:02:23Z | |
dc.date.issued | 2023-07 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/201900 | |
dc.description.abstract | [EN] 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. | es_ES |
dc.description.sponsorship | 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). Maylin Acosta thanks IFARHU-SENACYT for the Professional Excellence Scholarships, contract No. 270-2021-020. Sandra Munera thanks the Juan de la Cierva-Formación contract (FJC2021-047786-I) co-funded by MCIN/AEI/10.13039/501100011033 and European Union NextGenerationEU/PRTR. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | MDPI AG | es_ES |
dc.relation.ispartof | Sensors | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject | Citrus nutrition | es_ES |
dc.subject | Agricultural sensors | es_ES |
dc.subject | Fertilisation | es_ES |
dc.subject | Ionomics | es_ES |
dc.subject | Chemometrics | es_ES |
dc.title | Rapid Prediction of Nutrient Concentration in Citrus Leaves Using Vis-NIR Spectroscopy | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.3390/s23146530 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/SENACYT//270-2021-020//IFARHU/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/GVA//52203//IVIA/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/GVA//52204//IVIA/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MICINN//FJC2021-047786-I//Juan de la Cierva-Formación/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Ingeniería Gráfica - Departament d'Enginyeria Gràfica | es_ES |
dc.description.bibliographicCitation | Acosta, M.; Quiñones, A.; Munera, S.; De Paz, JM.; Blasco, J. (2023). Rapid Prediction of Nutrient Concentration in Citrus Leaves Using Vis-NIR Spectroscopy. Sensors. 23(14):1-11. https://doi.org/10.3390/s23146530 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.3390/s23146530 | es_ES |
dc.description.upvformatpinicio | 1 | es_ES |
dc.description.upvformatpfin | 11 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 23 | es_ES |
dc.description.issue | 14 | es_ES |
dc.identifier.eissn | 1424-8220 | es_ES |
dc.identifier.pmid | 37514824 | es_ES |
dc.identifier.pmcid | PMC10386652 | es_ES |
dc.relation.pasarela | S\498036 | es_ES |
dc.contributor.funder | European Commission | es_ES |
dc.contributor.funder | Generalitat Valenciana | es_ES |
dc.contributor.funder | European Regional Development Fund | es_ES |
dc.contributor.funder | Ministerio de Ciencia e Innovación | es_ES |
dc.contributor.funder | Secretaría Nacional de Ciencia, Tecnología e Innovación, Panamá | es_ES |