Brazil is one of the world’s biggest emitters of greenhouse gases (GHGs). Fire foci across the country contributes to these emissions and compromises emission reduction targets pledged by Brazil under the Paris Agreement. In this paper, we quantify fire foci, burned areas, and carbon emissions in all Brazilian biomes (i.e., Amazon, Cerrado, Caatinga, Atlantic Forest, Pantanal and Pampa). We analyzed these variables using cluster analysis and non-parametric statistics to predict carbon and CO2 emissions for the next decade. Our results showed no increase in the number of fire foci and carbon emissions for the evaluated time series, whereby the highest emissions occur and will persist in the Amazon and Cerrado biomes. The Atlantic Forest, Pantanal, Caatinga and Pampa biomes had low emissions compared to the Amazon and Cerrado. Based on 2030 projections, the sum of emissions from fire foci in the six Brazilian biomes will exceed 5.7 Gt CO2, compromising the national GHG reduction targets. To reduce GHG emissions, Brazil will need to control deforestation induced by the expansion of the agricultural frontier in the Amazon and Cerrado biomes. This can only be achieved through significant political effort involving the government, entrepreneurs and society as a collective.
Low base saturation (V) is one of the major abiotic stresses in the Brazilian Cerrado. Given this scenario, it is important to evaluate different physiological responses of genotypes in environments with and without liming aiming at select both liming responsive and low‐saturation tolerant genotypes. The hypothesis of this study is that contrasting V conditions provide changes in physiological performance of soybean genotypes. Thus, our objective was to select soybean genotypes in environments with recommended and low V. Two field experiments were carried in randomized block design with three replicates and 10 F3 soybean genotypes (P1, P2, P3, P4, P5, P6, P7, P8, P9 and P10). In the first experiment, genotypes were evaluated without V correction (V = 30%), while in the second experiment, a liming was performed three months before to raise V to 60%. The traits evaluated were as follows: calcium and magnesium contents, days for maturation, transpiration, net photosynthesis, stomatal conductance and internal CO2 concentration. Our findings indicate that the physiological performance of soybean genotypes depends on the saturation condition. The P9 genotype obtained the best physiological performance under recommended V and can be used to obtain F3:4 lines physiologically responsive to soil correction. The P5 genotype obtained the best physiological performance at low V and can be used to obtain F3:4 lines aiming at a higher tolerance to low saturation. Considering that the Brazilian soils, especially in the Cerrado, are mostly poorly fertile, our study provide crucial information for soybean breeding programmes aiming at selecting genotypes tolerant to limiting environmental conditions.
This study aimed to evaluate the adaptability and phenotypic stability of cowpea genotypes using a nonlinear regression analysis and multivariate analysis. Experiments were performed at four sites in Brazil using a randomized blocks design with 20 treatments and four replications. The adaptability and stability of genotypes were evaluated by Toler nonlinear regression and genotype plus genotype × environment (GGE) biplot methodologies. Most of the genotypes revealed linear response patterns, with no differences regarding the favorable and unfavorable environments. Regarding the genotype classification for stability and adaptability, the Toler and GGE biplot methodologies are congruent. Genotypes MNC99-537F-4, MNC00-561G-6, MNC99542F-5, and Patativa have high overall adaptability and adequate yield. Therefore, they should be recommended for cultivation in the tested environments. Genotypes closer to the ideotype by the GGE biplot method are considered doubly desirable by the nonlinear method.
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