Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 3 de 3
Filter
Add filters








Language
Year range
1.
Biosci. j. (Online) ; 37: e37007, Jan.-Dec. 2021. ilus, tab, graf
Article in English | LILACS | ID: biblio-1358471

ABSTRACT

The objective of this work was to analyze the genetic diversity using conventional methods and artificial neural networks among 12 colored fiber cotton genotypes, using technological characteristics of the fiber and productivity in terms of cottonseed and cotton fiber yield. The experiment was conducted in an experimental area located at Fazenda Capim Branco, belonging to the Federal University of Uberlândia, in the city of Uberlândia, Minas Gerais. Twelve genotypes of colored fiber cotton were evaluated, 10 from the Cotton Genetic Improvement Program (PROMALG): UFUJP - 01, UFUJP - 02, UFUJP - 05, UFUJP - 08, UFUJP - 09, UFUJP - 10, UFUJP - 11, UFUJP - 13, UFUJP - 16, UFUJP - 17 and two commercial cultivars: BRS Rubi (RC) and BRS Topázio (TC). The experimental design used was complete randomized block (CRB) with three replications. The following evaluations were carried out at full maturation: yield of cottonseed (kg ha-1) and the technological characteristics, which include, fiber length, micronaire, maturation, length uniformity, short fiber index, elongation and strength, using the HVI (High volume instrument) device. Genetic dissimilarity was measured using the generalized Mahalanobis distance and after obtaining the dissimilarity matrix, the genotypes were grouped using a hierarchical clustering method (UPGMA). A discriminant analysis and the Kohonen Self-Organizing Map (SOM) by Artificial Neural Networks (ANN's) were performed through computational intelligence. SOM was able to detect differences and organize the similarities between accesses in a more coherent way, forming a larger number of groups, when compared to the method that uses the Mahalanobis matrix. It was also more accurate than the discriminant analysis, since it made it possible to differentiate groups more coherently when comparing their phenotypic behavior. The methods that use computational intelligence proved to be more efficient in detecting similarity, with Kohonen's Self-Organizing Map being the most adequate to classify and group cotton genotypes.


Subject(s)
Genetic Variation , Artificial Intelligence , Neural Networks, Computer , Gossypium , Cotton Fiber/analysis
2.
Biosci. j. (Online) ; 36(6): 2068-2077, 01-11-2020. tab
Article in English | LILACS | ID: biblio-1148244

ABSTRACT

Cotton is one of the main agricultural products produced in Brazil. With such a high demand in the market, it is necessary that the cotton cultivars present high productivity and fiber quality. In order to favor the expression of the potential of the genotypes, the cultivation must occur in climatic conditions that provide good development of the plants, being the sowing time a primordial factor for the good performance of the cotton plant. In order to establish an ideal sowing season for different cotton genotypes, the present study aimed to evaluate the best sowing season of cotton genotypes for the environment of Uberlândia (Minas Gerais State), aiming at productivity and fiber quality. The experiment was carried out in field conditions, in the 2016/2017 harvest in the experimental area located at Fazenda Capim Branco, in the city of Uberlândia, Minas Gerais State. A randomized complete block design (DBC) with four replications in a 4x7 factorial scheme was used: 4/12 sowing dates: 05/12, 19/12, 30/12, 13/01 and 7 genotypes. 5 strains of the breeding program of the Federal University of Uberlândia (UFU) and 2 commercial cultivars. The evaluated characteristics were: seed cotton yield, feather yield, micronaire index, maturity index, fiber length, uniformity of length, short fibers, resistance and elongation. It was concluded that the best sowing season for a high productivity was the one performed on 12/05/16, with emphasis on the UFUJP-Z genotype. For fiber quality, UFUJP-C showed the best results at the 12/19/16 sowing season.


O algodão é um dos principais produtos agrícolas produzidos no Brasil. Com tamanha exigência do mercado, é necessário que as cultivares de algodoeiro apresentem alta produtividade e qualidade de fibras. Para favorecer a expressão do potencial dos genótipos, a semeadura deve ocorrer na época em que as condições climáticas proporcionem bom desenvolvimento das plantas, sendo a temperatura, precipitação e luminosidade fatores primordiais para o bom desempenho. Com o intuito de estabelecer uma época de semeadura ideal para diferentes genótipos de algodoeiro, o presente estudo teve como objetivo avaliar a melhor época de semeadura, para o ambiente de Uberlândia (MG), visando produtividade e qualidade da fibra. O experimento foi desenvolvido em condições de campo, na safra 2016/2017 na área experimental localizada na Fazenda Capim Branco, no município de Uberlândia, Minas Gerais. Utilizou-se delineamento experimental de blocos completos casualizados (DBC) com quatro repetições em esquema fatorial 4x7, constituíram-se de 4 épocas de semeadura: 05/12, 19/12, 30/12, 13/01 e 7 genótipos, sendo 5 linhagens do Programa de melhoramento do algodoeiro da Universidade Federal de Uberlândia (UFU) e 2 cultivares comerciais. As características avaliadas foram: produtividade do algodão em caroço, rendimento de pluma, índice micronaire, índice de maturação, comprimento de fibra, uniformidade de comprimento, fibras curtas, resistência e alongamento. Concluiu-se que a semeadura em 05/12/16 obteve melhores resultados quando visa alta produtividade, com destaque para o genótipo UFUJP-Z. Visando qualidade de fibra a semeadura em 19/12/16 foi mais favorável, com destaque para o UFUJP-C.


Subject(s)
Crop Production , Cotton Fiber
3.
Biosci. j. (Online) ; 34(5): 1287-1297, sept./oct. 2018.
Article in English | LILACS | ID: biblio-967318

ABSTRACT

The genetic breeding of soybean aims to obtain productive genotypes, so it is necessary that the genetic components, environment and the interaction between them be understood. The G x E interaction is the differential behavior of the genotypes against environmental. The objective was to study the G x E interaction and analyze the adaptability and stability of soybean genotypes under natural rust infection without fungicide. The experiment was conducted in the Genetic Breeding Program of the Federal University of Uberlândia. Fourteen soybean genotypes were evaluated, with 10 lines developed by the UFU Program (UFUS1117: 01, 02, 03, 05, 06, 07, 08, 09, 10 and 11) and 4 cultivars: UFUS 7415, UFUS Riqueza, TMG 801 and BRSGO 7560 in four seasons: 2013/14, 2014/15, 2015/16 and 2016/17, in a randomized complete block design. The G x E interaction was complex and the H2 was 85.97% indicating superiority of genetic variation in relation to the environment. The average grain yield was 2284.13kg ha-1. The genotype UFUS 1117-01 was identified by Eberhart and Russel, Wricke, AMMI 2 and Centroid as being a highly productive stability genotype. The UFUS 1117-07 showed high stability by Eberhart and Russel, Wricke, Lin and Binns modified by Carneiro methods and wide adaptability by Eberhart and Russel and Centroid. The genotype UFUS 1117-09 was identified as being adaptable to unfavorable environments by the Lin and Binns modified by Carneiro and Centroid methods, and UFUS 1117-10 presented favorable environmental adaptability by the Centroid method and high stability by Eberhart and Russel.


O melhoramento genético da soja visa à obtenção de genótipos produtivos, então é necessário que os componentes genéticos, ambientais e a interação entre eles sejam compreendidos. A interação G x A é o comportamento diferencial dos genótipos frente às variações ambientais. O objetivo foi estudar a interação G x A e analisar a adaptabilidade e estabilidade produtiva de genótipos de soja sob infecção natural por ferrugem, sem fungicida. O experimento foi conduzido no Programa de Melhoramento Genético da UFU. Quatorze genótipos de soja foram avaliados, sendo 10 linhagens desenvolvidas pelo Programa de Melhoramento Genético de Soja da UFU (UFUS 1117-01, UFUS 1117-02, UFUS 1117-03, UFUS 1117-05, UFUS 1117-06, UFUS 1117-07, UFUS 1117-08, UFUS 1117-09, UFUS 1117-10 e UFUS 1117-11) e 4 cultivares ( UFUS 7415, UFUS Riqueza, TMG 801 e BRSGO 7560), em quatro safras: 2013/14, 2014/15, 2015/16 e 2016/17, em delineamento de blocos casualizados. A interação G x A foi significativa e complexa e o H2 foi de 85,97% indicando superioridade da variação genética em relação a ambiental. A média de produtividade de grãos foi 2284,13kg ha-1. O genótipo UFUS 1117-01 foi identificado pelas metodologias de Eberhart e Russel, Wricke, AMMI 2 e Centroide como sendo um genótipo de alta estabilidade produtiva. A linhagem UFUS 1117-07 apresentou alta estabilidade por Eberhart e Russel, Wricke, Lin e Bins modificado por Carneiro e ampla adaptabilidade por Eberhart e Russel e Centroide. O genótipo UFUS 1117-09 foi identificado como sendo adaptável a ambientes desfavoráveis por Lin e Bins modificado por Carneiros e Centroide, e UFUS 1117-10 apresentou adaptabilidade a ambiente favoráveis pelo método Centroide e alta estabilidade por Eberhart e Russel.


Subject(s)
Glycine max , Crop Production , Efficiency , Plant Breeding , Genotype
SELECTION OF CITATIONS
SEARCH DETAIL