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dc.contributor.authorSILVA, P. C. da
dc.contributor.authorRIBEIRO JUNIOR, W. Q.
dc.contributor.authorRAMOS, M. L. G.
dc.contributor.authorLOPES, M. F.
dc.contributor.authorSANTANA, C. C.
dc.contributor.authorCASARI, R. A. DAS C.
dc.contributor.authorBRASILEIRO, L. DE O.
dc.contributor.authorVEIGA, A. D.
dc.contributor.authorROCHA, O. C.
dc.contributor.authorMALAQUIAS, J. V.
dc.contributor.authorSOUZA, N. O. S.
dc.contributor.authorROIG, H. L.
dc.date.accessioned2024-12-05T12:59:18Z-
dc.date.available2024-12-05T12:59:18Z-
dc.date.created2024-12-03
dc.date.issued2024
dc.identifier.citationSensors, v. 24, 7271, 2024.
dc.identifier.issn1424-8220
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1169930-
dc.descriptionThe advancement of digital agriculture combined with computational tools and Unmanned Aerial Vehicles (UAVs) has opened the way to large-scale data collection for the calculation of vegetation indices (VIs). These vegetation indexes (VIs) are useful for agricultural monitoring, as they highlight the inherent characteristics of vegetation and optimize the spatial and temporal evaluation of different crops. The experiment tested three coffee genotypes (Catuaí 62, E237 and Iapar 59) under five water regimes: (1) FI 100 (year-round irrigation with 100% replacement of evapotranspiration loss), (2) FI 50 (year-round irrigation with 50% evapotranspiration replacement), (3) WD 100 (no irrigation from June to September (dry season) and, thereafter, 100% evapotranspiration replacement), (4) WD 50 (no irrigation from June to September (water stress) and, thereafter, 50% evapotranspiration replacement) and (5) rainfed (no irrigation during the year). The irrigated treatments were watered with irrigation and precipitation. Most indices were highest in response to full irrigation (FI 100). The values of the NDVI ranged from 0.87 to 0.58 and the SAVI from 0.65 to 0.38, and the values of these indices were lowest for genotype E237 in the rainfed areas. The indices NDVI, OSAVI, MCARI, NDRE and GDVI were positively correlated—very strongly with photosynthesis (A) and strongly with transpiration (E) of the coffee trees. On the other hand, temperature-based indices, such as canopy temperature and the TCARI index correlated negatively with A, E and stomatal conductance (gs). Under full irrigation, the tested genotypes did not differ between the years of evaluation. Overall, the index values of Iapar 59 exceeded those of the other genotypes. The use of VIs to evaluate coffee tree performance under different water managements proved efficient in discriminating the best genotypes and optimal water conditions for each genotype. Given the economic importance of coffee as a crop and its susceptibility to extreme events such as drought, this study provides insights that facilitate the optimization of productivity and resilience of plantations under variable climatic conditions.
dc.language.isoeng
dc.rightsopenAccess
dc.titleMultispectral Images for Drought Stress Evaluation of Arabica Coffee Genotypes Under Different Irrigation Regimes.
dc.typeArtigo de periódico
dc.subject.thesagroCerrado
dc.subject.thesagroCafé
dc.subject.thesagroAbastecimento de Água
dc.subject.nalthesaurusWater supply
dc.subject.nalthesaurusCoffea arabica var. arabica
riaa.ainfo.id1169930
riaa.ainfo.lastupdate2024-12-03
dc.identifier.doihttps://doi.org/10.3390/s24227271
dc.contributor.institutionPATRÍCIA CARVALHO DA SILVA, UNIVERSIDADE DE BRASILIA; WALTER QUADROS RIBEIRO JUNIOR, CPAC; MARIA LUCRECIA GEROSA RAMOS, UNIVERSIDADE DE BRASILIA; MAURÍCIO FERREIRA LOPES, UNIVERSIDADE DE BRASILIA; CHARLES CARDOSO SANTANA, EMPRESA DE PESQUISA AGROPECUÁRIA DE MINAS GERAIS; RAPHAEL AUGUSTO DAS CHAGAS NOQUELI CASARI, UNIVERSIDADE DE BRASILIA; LEMERSON DE OLIVEIRA BRASILEIRO, EMBRAPA CERRADOS; ADRIANO DELLY VEIGA, CPAC; OMAR CRUZ ROCHA, CNPCA; JUACI VITORIA MALAQUIAS, CPAC; NARA OLIVEIRA SILVA SOUZA, UNIVERSIDADE DE BRASILIA; HENRIQUE LLACER ROIG, UNIVERSIDADE DE BRASILIA.
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