Resumo
Climate change impacts are stressing many economic sectors worldwide, including agriculture, increasingly hindering efforts to meet human needs. Dioxide carbon is one of the main greenhouse gases and it affects directly the crop production. The objective of this study was to evaluate if established remote sensing indices could detect the effects of elevated atmospheric CO2 on the leaves of coffee (Coffea arabica L.) plantation growing under field conditions. Plots of coffee plants were exposed to ambient air (~390 µmol CO2 mol-1) and elevated CO2 (~550 µmol CO2 mol-1) at the free air CO2 enrichment (FACE) experiment. The statistical design was the completely randomized blocks with six replicates per treatment (ambient CO2 and elevated CO2), with 10m-diameter plots. Coffee leaves were spectrally characterized by reflectance spectra on their adaxial surfaces and seven vegetation indices were calculated from reflectance data: chlorophyll normalized difference index (Chl NDI), normalized difference nitrogen index (NDNI), normalized difference vegetation index (NDVI), photochemical reflectance index (PRI), pigment specific simple ration indices for chlorophyll a (PSSRa) and chlorophyll b (PSSRb), and structural independent pigment index (SIPI). NDNI was a sensitive indicator of the atmospheric CO2 effects on coffee leaves. NDVI, PSSRa and PSSRb were sensitive to estimate the effect of elevated CO2 only under drought conditions. These indices identify the effect of CO2 when a long period with high precipitation deficit stressing the leaves occurred. Chl NDI, PRI and SIPI were not sensitive to atmospheric CO2.
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