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dc.contributor.authorBRANDAO, Z. N.pt_BR
dc.contributor.authorSOFIATTI, V.pt_BR
dc.contributor.authorBEZERRA, J. R. C.pt_BR
dc.contributor.authorFERREIRA, G. B.pt_BR
dc.contributor.authorMEDEIROS, J. C.pt_BR
dc.date.accessioned2016-03-22T11:11:11Zpt_BR
dc.date.available2016-03-22T11:11:11Zpt_BR
dc.date.created2016-03-22pt_BR
dc.date.issued2015pt_BR
dc.identifier.citationAustralian Journal of Crop Science, v. 9, n. 1, p. 75-84, jan. 2015.pt_BR
dc.identifier.issn1835-2693pt_BR
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1041649pt_BR
dc.descriptionThe canopy reflectance using ground-based sensors has the potential to provide information on crop nitrogen content. The objective of this study was to determine relationships between canopy spectral reflectance and leaf N content, leaf area index (LAI), aboveground biomass (Biom) and yield of irrigated cotton under four nitrogen rates (0, 90, 180 and 270kg ha-1). Measurements of canopy reflectance were made throughout the growing seasons (2009-2010) using a hand-held spectroradiometer. Samples for LAI and Biom were obtained three times from squaring until fruiting. The normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), modified soil adjusted vegetation index (MSAVI) and the modified transformed vegetation index (MTVI2) were calculated from the hyperspectral reflectance data. All vegetation indexes (VIs) and also SPAD-502 readings allowed to figure out mathematical models for N content prediction in cotton leaves with great precision (r > 0.74). It also showed good correlations (r from 0.55 to 0.96) with the LAI since the first flowering. The vegetation indexes obtained through the canopy reflectance, explained more than 64% of the variation in cotton biomass. The MTVI2 was the index that provided the best LAI prediction in advanced stages. The peak flowering stage was the best time to estimate the cotton biomass, where the MSAVI and MTVI2 showed to be excellent predictors. The results indicate that the cotton yield can be estimated through the hyperspectral reflectance since the squaring until fruiting in irrigated conditions.pt_BR
dc.language.isoporpt_BR
dc.rightsopenAccesspt_BR
dc.subjectIrrigated cottonpt_BR
dc.subjectNitrogen fertilizationpt_BR
dc.titleSpectral reflectance for growth and yield assessment of irrigated cotton.pt_BR
dc.typeArtigo de periódicopt_BR
dc.date.updated2016-03-22T11:11:11Zpt_BR
dc.subject.thesagroGossypium hirsutumpt_BR
dc.subject.thesagroAlgodãopt_BR
dc.subject.thesagroÁrea foliarpt_BR
dc.subject.nalthesaurusleaf area indexpt_BR
dc.subject.nalthesaurusremote sensingpt_BR
riaa.ainfo.id1041649pt_BR
riaa.ainfo.lastupdate2016-03-22pt_BR
dc.contributor.institutionZIANY NEIVA BRANDAO, CNPA; VALDINEI SOFIATTI, CNPA; JOSE RENATO CORTEZ BEZERRA, CNPA; GILVAN BARBOSA FERREIRA, CNPA; JOSÉ C. MEDEIROS, CNPA.pt_BR
Aparece en las colecciones:Artigo em periódico indexado (CNPA)

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