Evidence map›Paper›PMID 39521894›Full record

ArticleScientific reports2024

Evaluation of yield and stability of sugar beet (beta vulgaris L.) genotypes using GGE biplot and AMMI analysis.

Vali-Allah Yousefabadi, Parviz Mehdikhani, Fathollah Nadali, Mastaneh Sharifi, Heydar Azizi, Masoud Ahmadi, Parviz Fasahat

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Vali-Allah YousefabadiSugar Beet Seed Institute (SBSI), Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran. v_yosef@yahoo.com.
Parviz MehdikhaniSugar Beet Research Department, West Azarbaijan Agricultural and Natural Resources Research Center, Agricultural Research, Education and Extension Organization (AREEO), Urmia, Iran.
Fathollah NadaliAgricultural and Natural Resources Research and Education Centre of Semnan province, Agricultural Research, Education and Extension Organization (AREEO), Shahrud, Iran.
Mastaneh SharifiAgricultural and Natural Resources Research Center of Fars, Agricultural Research, Education and Extension Organization (AREEO), Shiraz, Iran.
Heydar AziziSugar Beet Research Department, West Azarbaijan Agricultural and Natural Resources Research Center, Agricultural Research, Education and Extension Organization (AREEO), Urmia, Iran.
Masoud AhmadiAgricultural and Natural Resources Research Center of Khorasan Razavi, , Agricultural Research, Education and Extension Organization (AREEO), Mashhad, Iran.
Parviz FasahatSugar Beet Seed Institute (SBSI), Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rhizomania is the most destructive sugar beet disease in the world, and in recent years, it has widespread in most of the sugar beet growing areas in Iran. Since the control of this soil-borne disease is a difficult task, the use of resistant genotypes is known as the best measure against the disease. The ultimate goal of sugar beet breeders is to produce genotypes that can be used in both infected and non-infected fields without any reduction in terms of yield and quality. Twenty-one sugar beet genotypes along with four controls were evaluated in randomized complete block design with four replications in fields with natural infection to rhizomania in five research stations. Important sugar beet traits including root yield, sugar yield, sugar content, and white sugar yield were evaluated for two years (2021 and 2022). For all traits, location was the main source of variation that spanned 33 to 55% of the total sum of the square followed by the location×year×genotype accounted for 3-40% of the variation. Based on the results of analysis of variance, multivariate stability parameters were computed to evaluate the genotypes' stability. The first two principal components (IPCA1 and IPCA2) generated by GGE biplot contributed for 31.3 and 17.5% difference in genotype×environment interaction for root yield, respectively. According to the GGE biplot, genotypes RM-11 and RM-12 were identified as the winning genotypes across environments for both root yield and white sugar yield traits whereas AMMI model identified RM-14 and RM-9 (for root yield) and RM-1 (for white sugar yield) as best genotypes. Based on the ideal genotype ranking, RM-11 and RM-10 were the best performer with a high mean yield as well as stability in the studied environments. The biplot rendered using the weighted average of absolute scores (WAASB) and root yield and white sugar yield identified RM-11 and RM-9 as superior genotypes in terms of yield and stability. The selected genotypes can be used in breeding programs to transfer the disease resistance and cultivar development.

Indexed as

Beta vulgarisGenotypeIranPlant BreedingPlant DiseasesPlant RootsSugarsSugarsGenotype × environment interactionRhizomaniaStabilitySugar beet

Identifiers

PMID39521894
PMCPMC11550840

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