análise de coeficiente de trilha para os componentes de produção em arroz path coefficient analysis of rice yield components

Clicks: 132
ID: 214165
2005
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Popular

Ranked #374 of 436 articles by views in Trials

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 436 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
Com o objetivo de avaliar a influência dos componentes de produção de arroz no rendimento de grãos através da análise de trilha, avaliaram-se 88 genótipos de arroz em quatro anos agrícolas. Em cada ano, os experimentos foram conduzidos no delineamento em blocos completos casualizados, com quatro repetições. As variáveis analisadas foram: estatura de plantas, rendimento de grãos, esterilidade de espiguetas, número de grãos por panícula, massa de mil grãos e rendimento de engenho. As análises de variância, correlação e de trilha (Path Analysis) foram realizadas para cada variável, utilizando-se o programa computacional GENES. Os genótipos avaliados apresentaram diferenças significativas para todas as variáveis analisadas, nos quatro anos de experimento. A seleção de variáveis deve ser realizada em grupos de cultivares semelhantes entre si e a utilização de um maior número de variáveis possibilita melhores inferências sobre os componentes da produção do arroz. A massa de grãos é o componente de produção que mais afeta o rendimento da cultura do arroz.
Eighty eight rice genotypes were evaluated during four years aiming to study the relationship among yield components. In each year, the experimental design was a completely randomized block design with four replications and the variables studied were: plant height, seed yield, spikelet sterility, number of seeds per panicle, 1000 seeds weight and head grains. The estimation of correlations and the path coefficient analysis were conducted with the GENES software. The genotypes showed significant variability for all the variables analyzed within each one of years. It was concluded that variable selection must be carried out among the cultivars that are more similar and using a greater number of variables allows better inferences about rice yield components. Grain weight was the yield of component that most affected seed yield rice plants.
Reference Key
marchezan2005cinciaanlise Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Enio Marchezan;Thomas Newton Martin;Fernando Machado dos Santos;Edinalvo Rabaioli Camargo
Journal Trials
Year 2005
DOI
10.1590/S0103-84782005000500007
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.