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resumen

Resumen
Identification of areas with similar restrictions to crop productivity could improve the efficiency to manage agricultural systems, guarantee stable yields, and reduce the effect of droughts in rainfed systems. The ability of any vegetation index to discriminate N and moisture-related changes in leaf reflectance would present an important advantage over the present diagnostic system which involves soil-testing for moisture and available N. The purpose of [ver mas...]
dc.contributor.authorFarrell, Mauricio Aníbal
dc.contributor.authorGili, Adriana Anahí
dc.contributor.authorNoellemeyer, Elke
dc.date.accessioned2018-10-30T18:19:46Z
dc.date.available2018-10-30T18:19:46Z
dc.date.issued2018-03
dc.identifier.issn1385-2256
dc.identifier.issn1573-1618 (Online)
dc.identifier.otherhttps://doi.org/10.1007/s11119-018-9570-9
dc.identifier.urihttp://hdl.handle.net/20.500.12123/3748
dc.identifier.urihttps://link.springer.com/article/10.1007%2Fs11119-018-9570-9#citeas
dc.description.abstractIdentification of areas with similar restrictions to crop productivity could improve the efficiency to manage agricultural systems, guarantee stable yields, and reduce the effect of droughts in rainfed systems. The ability of any vegetation index to discriminate N and moisture-related changes in leaf reflectance would present an important advantage over the present diagnostic system which involves soil-testing for moisture and available N. The purpose of the study was to calibrate different vegetation indices regarding their capacity to identify water and nitrogen availability for rainfed corn crops in the semiarid Pampas of Argentina. A field experiment with corn with a control without fertilization (N0), and fertilized with 120 kg ha−1 of nitrogen (N120) was used. Two sites, Low (L) and High (H), were identified within the field, according to their altimetry, a multi-spectral aerial photography was taken from a manned airplane during flowering stage of the corn crop, and four spectral indices were calculated (NDVI, green NDVI, NGRDI, (NIR/GREEN)-1). At six georeferenced points at each site soil texture, organic matter, available phosphorus, nitrogen and moisture contents as well as corn aerial biomass and grain yield were determined. The two sites differed in most of the evaluated soil properties, crop biomass and grain yield. The spectral information obtained at crop flowering showed clear differences between sites H and L for all four indices, indicating that any of these would be able to detect the differences in soil moisture and fertility among these environments. Both (NIR/GREEN)-1 and green NDVI had the best correlation with crop yield determined in the field, and therefore could be considered most appropriate for estimating corn yields from images taken at flowering. For estimation of N requirements, green NDVI differentiated best between fertilized and non-fertilized crop in the moisture limited environment (H), while (NIR/GREEN)-1 performed better in the site where soil moisture was non-limiting (L).es_AR
dc.formatapplication/pdfes_AR
dc.language.isoenges_AR
dc.publisherSpringeres_AR
dc.rightsinfo:eu-repo/semantics/restrictedAccesses_AR
dc.sourcePrecision agriculture : 1–11. (28 March 2018)es_AR
dc.subjectMaízes_AR
dc.subjectMaizees_AR
dc.subjectZea Mayses_AR
dc.subjectVegetation Indexes_AR
dc.subjectIndice de Vegetaciónes_AR
dc.subjectRendimientoes_AR
dc.subjectYieldses_AR
dc.subjectMultispectral Imageryes_AR
dc.subjectImágenes Multiespectraleses_AR
dc.subjectNitrogen Fertilizerses_AR
dc.subjectAbonos Nitrogenadoses_AR
dc.titleSpectral indices from aerial images and their relationship with properties of a corn cropes_AR
dc.typeinfo:ar-repo/semantics/artículoes_AR
dc.typeinfo:eu-repo/semantics/articleeng
dc.typeinfo:eu-repo/semantics/publishedVersioneng
dc.description.origenEEA Anguiles_AR
dc.description.filFil: Farrell, Mauricio Aníbal. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Anguil; Argentinaes_AR
dc.description.filFil: Gili, Adriana Anahí. Universidad Nacional de La Pampa. Facultad de Agronomía; Argentinaes_AR
dc.description.filFil: Noellemeyer, Elke. Universidad Nacional de La Pampa. Facultad de Agronomía; Argentinaes_AR
dc.subtypecientifico


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