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Your search keyword '"Teodoro, Larissa Pereira Ribeiro"' showing total 15 results
Start Over Author "Teodoro, Larissa Pereira Ribeiro" Journal scientific reports
15 results on '"Teodoro, Larissa Pereira Ribeiro"'

10. Assessing soil CO2 emission on eucalyptus species using UAV-based reflectance and vegetation indices.

Author

Rossi, Fernando Saragosa, Della-Silva, João Lucas, Teodoro, Larissa Pereira Ribeiro, Teodoro, Paulo Eduardo, Santana, Dthenifer Cordeiro, Baio, Fábio Henrique Rojo, Morinigo, Wendel Bueno, Crusiol, Luís Guilherme Teixeira, La Scala Jr., Newton, and da Silva Jr., Carlos Antonio

Subjects
EUCALYPTUS, CARBON cycle, MULTIVARIATE analysis, FOREST soils, GREENHOUSE effect, REFLECTANCE
Abstract

Eucalyptus species play an important role in the global carbon cycle, especially in reducing the greenhouse effect as well as storing atmospheric CO₂. Thus, assessing the amount of CO₂ released by the soil in forest areas can generate important information for environmental monitoring. This study aims to verify the relation between soil carbon dioxide (CO₂) flux (FCO₂), spectral bands, and vegetation indices (VIs) derived from a UAV-based multispectral camera over an area of eucalyptus species. Multispectral imageries (green, red-edge, and near-infrared) from the Parrot Sequoia sensor, derived vegetation indices, and the FCO₂ data from a LI-COR 8100 analyzer, combined with soil moisture and temperature data, were collected and related. The vegetation indices ATSAVI (Adjusted Transformed Soil-Adjusted VI), GSAVI (Green Soil Adjusted Vegetation Index), and SAVI (Soil-Adjusted Vegetation Index), which use soil correction factors, exhibited a strong negative correlation with FCO₂ for the species E. camaldulensis, E. saligna, and E. urophylla species. A Multivariate Analysis of Variance showed significance (p < 0.01) for the species factor, which indicates that there are differences when considering all variables simultaneously. The results achieved in this study show a specific correlation between the data of soil CO₂ emission and the eucalypt species, providing a distinction of values between the species in the statistical data. [ABSTRACT FROM AUTHOR]

Published
2024
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14. Persistent fire foci in all biomes undermine the Paris Agreement in Brazil

Author

da Silva Junior, Carlos Antonio, Teodoro, Paulo Eduardo, Delgado, Rafael Coll, Teodoro, Larissa Pereira Ribeiro, Lima, Mendelson, de Andréa Pantaleão, Ariane, Baio, Fabio Henrique Rojo, de Azevedo, Gileno Brito, de Oliveira Sousa Azevedo, Glauce Taís, Capristo-Silva, Guilherme Fernando, Arvor, Damien, and Facco, Cassiele Uliana

Published
2020
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15. Understanding the combining ability of nutritional, agronomic and industrial traits in soybean F2 progenies.

Author

das Chagas, Paulo Henrique Menezes, Teodoro, Larissa Pereira Ribeiro, Santana, Dthenifer Cordeiro, Filho, Marcelo Carvalho Minhoto Teixeira, Coradi, Paulo Carteri, Torres, Francisco Eduardo, Bhering, Leonardo Lopes, and Teodoro, Paulo Eduardo

Subjects
*GROWING season, *COPPER, *GRAIN yields, *NUTRIENT uptake, *IRON, *SOYBEAN farming, *SOYBEAN
Abstract

Obtaining soybean genotypes that combine better nutrient uptake, higher oil and protein levels in the grains, and high grain yield is one of the major challenges for current breeding programs. To avoid the development of unpromising populations, selecting parents for crossbreeding is a crucial step in the breeding pipeline. Therefore, our objective was to estimate the combining ability of soybean cultivars based on the F2 generation, aiming to identify superior segregating parents and populations for agronomic, nutritional and industrial traits. Field experiments were carried out in two locations in the 2020/2021 crop season. Leaf contents of the following nutrients were evaluated: phosphorus, potassium, calcium, magnesium, sulfur, copper, iron, manganese, and zinc. Agronomic traits assessed were days to maturity (DM) and grain yield (GY), while the industrial traits protein, oil, fiber and ash contents were also measured in the populations studied. There was a significant genotype × environment (G × A) interaction for all nutritional traits, except for P content, DM and all industrial traits. The parent G3 and the segregating populations P20 and P27 can be used aiming to obtain higher nutritional efficiency in new soybean cultivars. The segregating populations P11 and P26 show higher potential for selecting soybean genotypes that combine earliness and higher grain yield. The parent G5 and segregant population P6 are promising for selection seeking improvement of industrial traits in soybean. [ABSTRACT FROM AUTHOR]

Published
2023
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