Banca de DEFESA: JÉFYNE CAMPOS CARRÉRA

Uma banca de DEFESA de DOUTORADO foi cadastrada pelo programa.
DISCENTE: JÉFYNE CAMPOS CARRÉRA
DATA: 13/12/2024
HORA: 14:00
LOCAL: Online
TÍTULO:

Leaf structure traits and biochemistry of Coffea arabica cultivars field-grown in Cerrado Mineiro, Minas Gerais, Brazil

PALAVRAS-CHAVES:

Leaf anatomy, Ecometabolomics, Non-targeted metabolomics, Proteomics.

PÁGINAS: 100
GRANDE ÁREA: Ciências Biológicas
ÁREA: Botânica
SUBÁREA: Botânica Aplicada
RESUMO:

Brazil is the world's largest exporter of arabica coffee, with the state of Minas Gerais accounting for over 50% of the country’s coffee production. Within Minas Gerais, coffee is cultivated across three key sub-regions: Cerrado Mineiro, Sul de Minas, and Zona da Mata. Among these, the Cerrado Mineiro region has gained recognition for producing high-quality coffees with distinct characteristics. It was also the first area in Brazil to receive a designation of origin. Productivity and cup quality depend heavily on the suitability of the Coffea arabica cultivars grown in the region. Ideally, cultivars that are resilient to environmental changes and consistently produce high-quality coffee will be an excellent indication for producers. Therefore, regular assessments of these cultivar's performance in the field are essential. To assess the structural and biochemical behavior of several Coffea arabica cultivars, leaves were collected from five cultivars grown at two experimental sites in the Cerrado Mineiro region. The plant material underwent a comprehensive analysis, including anatomical, specific leaf area, water potential, spectral indices analyses, and the quantification of starch and total proteins. Additionally, non-targeted metabolomics, proteomics, and enzyme activity (particularly invertases) were assessed. Climate, soil conditions, altitude, and water regime at the experimental sites were also collected, along with the agronomic traits of the cultivars, such as quality and mean productivity. To analyze this complex dataset, a combination of statistical methods, including univariate analysis and machine learning algorithms, was applied to extract meaningful insights about cultivar development. The findings revealed significant phenotypic and metabolic diversity among the cultivars, indicating that some exhibited greater resilience. Moreover, the study highlighted specific metabolic pathways that could be further investigated in future research on stress tolerance and disease resistance in coffee plants.

MEMBROS DA BANCA:
Externo à Instituição - VÂNIA APARECIDA SILVA - EPAMIG (Membro)
Interno - VITOR DE LAIA NASCIMENTO (Membro)
Interno - ORIVALDO BENEDITO DA SILVA - UFLA (Suplente)
Interno - MARINES FERREIRA PIRES LIRA (Membro)
Externo à Instituição - MARGARETE MARIN LORDELO VOLPATO - EPAMIG (Suplente)
Externo à Instituição - LEONOR DE CASTRO ESTEVES GUERRA GUIMARÃES - ULISBOA (Membro)
Presidente - FABIO AKIRA MORI (Membro)