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Remote Sensing Dynamics for Analyzing Nitrogen Impact on Rice Yield in Limited Environments

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Remote Sensing Dynamics for Analyzing Nitrogen Impact on Rice Yield in Limited Environments

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dc.contributor.author Fita-Silvestre, David es_ES
dc.contributor.author San Bautista Primo, Alberto es_ES
dc.contributor.author Castiñeira-Ibáñez, Sergio es_ES
dc.contributor.author Franch, Belén es_ES
dc.contributor.author Domingo Carrasco, Concha es_ES
dc.contributor.author Rubio Michavila, Constanza es_ES
dc.date.accessioned 2024-10-16T11:09:45Z
dc.date.available 2024-10-16T11:09:45Z
dc.date.issued 2024-10-04 es_ES
dc.identifier.uri http://hdl.handle.net/10251/210294
dc.description.abstract [EN] Rice production remains highly dependent on nitrogen (N). There is no positive linear correlation between N concentration and yield in rice cultivation because an excess of N can unbalance the distribution of photo-assimilates in the plant and consequently produce a lower yield. We intended to study these imbalances. Remote sensing is a useful tool for monitoring rice crops. The purpose of this study was to evaluate the effectiveness of using remote sensing to assess the impact of N applications on rice crop behavior. An experiment with three different doses (120, 170 and 220 kg N·ha¿1) was carried out over two years (2021 and 2022) in Valencia, Spain. Biomass, Leaf Area Index (LAI), plants per m2, yield, N concentration and N uptake were determined. Moreover, reflectance values in the green, red, and NIR bands of the Sentinel-2 satellite were acquired. The two data matrices were merged in a correlation study and the resulting interpretation ended in a protocol for the evaluation of the N effect during the main phenological stages. The positive effect of N on the measured parameters was observed in both years; however, in the second year, the correlations with the yield were low, being attributed to a complex interaction with climatic conditions. Yield dependence on N was optimally evaluated and monitored with Sentinel-2 data. Two separate relationships between NIR¿red and NDVI¿NIR were identified, suggesting that using remote sensing data can help enhance rice crop management by adjusting nitrogen input based on plant nitrogen concentration and yield estimates. This method has the potential to decrease nitrogen use and environmental pollution, promoting more sustainable rice cultivation practices. es_ES
dc.description.sponsorship This research has been funded by the PREDIC-PRO project SCPP2100C008733XVD, of the State Research Agency of the Ministry of Science, Innovation and Universities, and ACIF Generalitat Valenciana, European Union (European Social Fund. Investing in Your Future) (CIACIF/2021/143) and DETECTORYZA project INNEST/2022/227, INNEST/2022/319 and INNEST/2022/361 Regional Operational Programme, FEDER Comunitat Valenciana de la Innovació, Generalitat Valenciana. es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation.ispartof Agriculture es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Rice es_ES
dc.subject Nitrogen es_ES
dc.subject Remote sensing es_ES
dc.subject Yield es_ES
dc.subject Modelling es_ES
dc.subject Sentinel-2 es_ES
dc.subject.classification PRODUCCION VEGETAL es_ES
dc.subject.classification FISICA APLICADA es_ES
dc.title Remote Sensing Dynamics for Analyzing Nitrogen Impact on Rice Yield in Limited Environments es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/agriculture14101753 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI//CPP2021-008733//Sensores remotos para la obtención de información predictiva de la producción de cultivos cereales (PREDIC-PRO)/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AGENCIA VALENCIANA DE LA INNOVACION//INNEST%2F2022%2F361//AGRICULTURA DE PRECISIÓN EN EL CULTIVO DEL ARROZ: DETECCIÓN PRECOZ DE SÍNTOMAS DE PYRICULARIA ORYZAE Y DETERMINACIÓN DE LA DOSIS (DETECTORYZA)/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GENERALITAT VALENCIANA//CIACIF%2F2021%2F143//APLICACIÓN Y USO DE SENSORES REMOTOS PARA LA MODELIZACIÓN Y ANÁLISIS DE LA RESPUESTA PRODUCTIVA EN EL CULTIVO DEL ARROZ/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AVI//INNEST%2F2022%2F319/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AVI//INNEST%2F2022%2F227/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI//SCPP2100C008733XVD/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros de Telecomunicación - Escola Tècnica Superior d'Enginyers de Telecomunicació es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingeniería Agronómica y del Medio Natural - Escola Tècnica Superior d'Enginyeria Agronòmica i del Medi Natural es_ES
dc.description.bibliographicCitation Fita-Silvestre, D.; San Bautista Primo, A.; Castiñeira-Ibáñez, S.; Franch, B.; Domingo Carrasco, C.; Rubio Michavila, C. (2024). Remote Sensing Dynamics for Analyzing Nitrogen Impact on Rice Yield in Limited Environments. Agriculture. 14(10). https://doi.org/10.3390/agriculture14101753 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/agriculture14101753 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 14 es_ES
dc.description.issue 10 es_ES
dc.identifier.eissn 2077-0472 es_ES
dc.relation.pasarela S\527692 es_ES
dc.contributor.funder European Social Fund es_ES
dc.contributor.funder GENERALITAT VALENCIANA es_ES
dc.contributor.funder AGENCIA ESTATAL DE INVESTIGACION es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
dc.contributor.funder European Regional Development Fund es_ES
dc.contributor.funder AGENCIA VALENCIANA DE LA INNOVACION es_ES
dc.contributor.funder Agència Valenciana de la Innovació es_ES
dc.subject.ods 02.- Poner fin al hambre, conseguir la seguridad alimentaria y una mejor nutrición, y promover la agricultura sostenible es_ES
dc.subject.ods 12.- Garantizar las pautas de consumo y de producción sostenibles es_ES


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