Genetic parameters and multi-trait selection of white oats for forage

被引:0
|
作者
da Rosa, T. C. [1 ]
Carvalho, I. R. [2 ]
da Silva, J. A. G. [2 ]
Szareski, V. J. [1 ]
Segatto, T. A. [2 ]
Port, E. D. [2 ]
Loro, M., V [2 ]
Almeida, H. C. F. [3 ]
de Oliveira, A. C. [1 ]
da Maia, L. C. [1 ]
de Souza, V. Q. [4 ]
机构
[1] Univ Fed Pelotas, Capao Do Leao, RS, Brazil
[2] Univ Reg Noroeste Estado Rio Grande do Sul, Ijui, RS, Brazil
[3] Univ Fed Vicosa, Vicosa, MG, Brazil
[4] Univ Fed Pampa, Sao Gabriel, RS, Brazil
来源
GENETICS AND MOLECULAR RESEARCH | 2021年 / 20卷 / 03期
关键词
Avena sativa; Generation mean analysis; Effects of genes; Factor analysis; SOFTWARE; WHEAT;
D O I
10.4238/gmr18451
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Avena sativa is the sixth most produced cereal in the world. It is widely used for human consumption. Due to the bromatological quality of its forage, it is used for direct grazing, hay and silage. Due to the large number of interesting characteristics of forage white oats, the selection of unique characteristics becomes difficult and expensive for breeders. In this sense, the use of analysis with multiple characteristics can facilitate the process. Therefore, the objective of this work was to estimate genetic parameters of morphological characteristics, productivity, and quality of forages, as well as to define multiple characteristics that assist in the selection of promising white oat genotypes with forage profile through factor analysis. Field trials were carried out during the agricultural year of 2013 in the municipality of Capao do Leao, RS. The experimental design was in randomized blocks, with treatments arranged in four replications. The treatments corresponded to the genotypes CHIARASUL (G1), FAEM006 (G2), BARBARASUL (G3), BRISASUL, (G4) CGF03006 (G5), CGF07023-1 (G6), CGF07-74 027-1 (G7), CGF07033 (G8), CGF07033-1 (G9), CGF07041 (G10), CGF0705-7 (G11), CGF07060-2 (G12) and CGF07060-3 (G13). The characteristics analyzed were: plant height, leaf area, weight of fresh plants, weight of dry plants, number of tillers and levels of nitrogen, crude protein, phosphorus, potassium, calcium, magnesium, copper, zinc, manganese and iron. The data were submitted to the normality test and to various components of variance. Statistical analyses were performed using Selegen (R), SAS (R) and Genes (R) software. The white oat genotypes expressed high genetic variability and possibility of selection for leaf area, fresh forage mass, dry forage mass, number of tillers and calcium content. Simultaneously the magnesium content with multiple traits + zinc content, dry matter + fresh mass, nitrogen content + calcium content, crude protein + potassium content and number of tillers, showing potential to select genotypes of interest for genetic improvement.
引用
收藏
页数:13
相关论文
共 50 条
  • [1] Forage peanut genetic variability: Multi-trait selection for forage production and ornamental purposes
    Miqueloni, Daniela Popim
    de Assis, Giselle Mariano Lessa
    Beber, Paulo Marcio
    [J]. ACTA SCIENTIARUM-AGRONOMY, 2023, 45
  • [2] MULTI-TRAIT SELECTION FOR GENETIC IMPROVEMENT IN INDIAN BUFFALOES
    Kumar, Sunil
    Yadav, M. C.
    Prasad, R. B.
    [J]. BUFFALO BULLETIN, 2008, 27 (01): : 154 - 160
  • [3] Genetic parameters and selection of maize cultivars using Bayesian inference in a multi-trait linear model
    Bocianowski, Jan
    Nowosad, Kamila
    Szulc, Piotr
    Tratwal, Anna
    Bakinowska, Ewa
    Piesik, Dariusz
    [J]. ACTA AGRICULTURAE SCANDINAVICA SECTION B-SOIL AND PLANT SCIENCE, 2019, 69 (06): : 465 - 478
  • [4] Evaluation of multi-trait selection indices for improving egg production in White Leghorn
    Dhankhar, K
    Bais, RKS
    Prasad, RB
    Kumar, A
    [J]. INDIAN JOURNAL OF ANIMAL SCIENCES, 2004, 74 (09): : 959 - 964
  • [5] Multi-trait multi-environment models in the genetic selection of segregating soybean progeny
    Volpato, Leonardo
    Alves, Rodrigo Silva
    Teodoro, Paulo Eduardo
    Vilela de Resende, Marcos Deon
    Nascimento, Moyses
    Campana Nascimento, Ana Carolina
    Ludke, Willian Hytalo
    da Silva, Felipe Lopes
    Borem, Aluizio
    [J]. PLOS ONE, 2019, 14 (04):
  • [6] Multi-trait selection indices for improving overall genetic value of Murrah buffaloes
    Kumar, D
    Singh, H
    Kumar, D
    Singh, CV
    [J]. INDIAN JOURNAL OF ANIMAL SCIENCES, 2002, 72 (04): : 324 - 327
  • [7] MULTI-TRAIT SELECTION USING RELATIVES RECORDS
    HENDERSON, CR
    QUAAS, RL
    [J]. JOURNAL OF ANIMAL SCIENCE, 1976, 43 (01) : 218 - 218
  • [8] CONSTRUCTION OF MULTI-TRAIT SELECTION INDEXES IN SHEEP
    SINGH, G
    KUSHWAHA, BP
    [J]. INDIAN JOURNAL OF ANIMAL SCIENCES, 1995, 65 (03): : 341 - 343
  • [9] Genetic parameters and multi-trait genomic prediction for hemoparasites infection levels in cattle
    Romero, Andrea Renata da Silva
    do Nascimento, Andre Vieira
    Oliveira, Marcia Cristina de Sena
    Okino, Cintia Hiromi
    Braz, Camila Urbano
    Scalez, Daiane Cristina Becker
    Cardoso, Diercles Francisco
    Cardoso, Fernando Flores
    Gomes, Claudia Cristina Gulias
    Caetano, Alexandre Rodrigues
    Tonhati, Humberto
    Gondro, Cedric
    de Oliveria, Henrique Nunes
    [J]. LIVESTOCK SCIENCE, 2023, 273
  • [10] Estimation of genetic parameters for litter size in pigs using multi-trait analyses
    Barbosa, Leandro
    Lopes, Paulo Savio
    Regazzi, Adair Jose
    Torres, Robledo de Almeida
    Santana, Mario Luiz, Jr.
    Veroneze, Renata
    [J]. REVISTA BRASILEIRA DE ZOOTECNIA-BRAZILIAN JOURNAL OF ANIMAL SCIENCE, 2008, 37 (11): : 1947 - 1952