Banca de DEFESA: MIRIAN DA SILVA ALMICI

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
DISCENTE : MIRIAN DA SILVA ALMICI
DATA : 25/02/2022
HORA: 14:00
LOCAL: Cáceres
TÍTULO:

Genetic diversity of Carthamus tinctorius L. via Gower's algorithm.

PALAVRAS-CHAVES:

Safflower; Joint analysis; Genetic improvement

 

PÁGINAS: 73
GRANDE ÁREA: Ciências Agrárias
ÁREA: Agronomia
SUBÁREA: Fitotecnia
ESPECIALIDADE: Melhoramento Vegetal
RESUMO:

Due to the great demand for bioenergetic species on a world scale, the safflower crop has been highlighted as an important alternative for energy production. Safflower is an oilseed with several applications, in addition to its bioenergetic potential, it has high value for human consumption, in the food, industrial, ornamental, medicinal and animal consumption sectors. In addition, it has aroused interest in national agriculture, as it presents itself as an option for second crop cultivation, not competing for area with crops used for human consumption. However, the lack of technical knowledge regarding its cultivation and the lack of improved cultivars adapted to our environment is one of the reasons that prevent the expansion of this culture in the country. Considering that safflower genetic improvement is essential to increase its acceptability and utility as a global oilseed, the objective was to estimate the genetic divergence between safflower accessions in terms of morphological, agronomic, chemical and molecular characters using the Gower algorithm. A total of 116 genotypes from the LRG&B - UNEMAT Germplasm Collection were evaluated. The information regarding the morphoagronomic, chemical and molecular characterization was obtained through field and laboratory experiments carried out at the State University of Mato Grosso (UNEMAT), Mato-Grossense Company for Research, Assistance and Rural Extension (EMPAER) and Instituto Federal of Mato Grosso (IFMT). For data analysis, a joint analysis of the data was performed, in which the Gower Algorithm was used to create the dissimilarity matrix. The resulting matrix was submitted to different clusters, such as the Tocher Optimization, Hierarchical UPGMA and Ward-MLM clustering methods. The clustering methods applied were efficient in distinguishing the accessions and the results indicate the existence of genetic divergence between the safflower genotypes. Pi 193473, pi 195895, pi 237539, pi 262443, pi 279344, pi 401474, pi 401475, pi 401475, pi 406006, pi 537658, pi 544028, pi 532639, pi 568787, pi 568787, pi 613382, pi 613382, pi 613503, pi 638543 were the most divergent genetically, being indicated for possible crosses.

MEMBROS DA BANCA:
Presidente - 101376004 - MARCO ANTONIO APARECIDO BARELLI
Interno - 132048001 - LEONARDA GRILLO NEVES
Interno - 285519001 - THIAGO ALEXANDRE SANTANA GILIO
Externo à Instituição - RAFHAEL FELIPIN AZEVEDO - UNIVAG