Adaptability and phenotypic stability of sugarcane clones

Regis, Jiuli Ani Vilas Boas; Andrade, João Antônio da Costa; Santos, Adriano dos; Moraes, Aparecido de; Trindade, Rafael William Romo; Henriques, Hermano José Ribeiro; Polis, Bruno Henrique; Oliveira, Luiz Carlos

doi:10.1590/s0100-204x2018000100005

Cited by 13 publications

(5 citation statements)

References 15 publications

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“…The first and second principal component analyses accounted for 45.5% and 24.7% of the G × E, respectively, together explained 70.2% of the total variation (Table 3). This was in agreement with Mattos et al (2013); Regis et al (2018) suggested that G × E pattern is collected in the first two principal component analyses. Similarly, previous studies also suggested the importance of capturing most of the G × E sum squares in the first two principal component axis to attain accurate information (Crossa et al, 1990; Purchase et al, 2000).…”

Section: Resultssupporting

confidence: 92%

Genotype × environment interaction of lowland bread wheat varieties for irrigation in different areas of Oromia

Bayissa

Mengistu

Gerema

et al. 2023

Plant Enviro Interactions

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Ethiopia is the leading wheat producer in Sub‐Saharan Africa, and the productivity has increased in the last few years. There is also a potential for irrigated wheat production in the lowlands, even though its cultivation is at infant stage. The experiment was conducted in the Oromia region at nine locations in 2021 with irrigation. The study aimed to select high yielding and stable bread wheat variety/ies for lowland areas. Twelve released bread wheat varieties were tested using randomized complete block design with two replications. Environment had the largest effect, 76.5% of total variability, while genotypes 5.0% and GE interaction 18.5% explained total sum of squares. The average grain yield of varieties across locations ranged from the lowest 1.40 t ha−1 at Girja to the highest 6.55 t ha−1 at Daro Labu, with a grand mean of 3.14 t ha−1. The result showed that varieties released for irrigated areas, Fentale 1, Ardi, and Fentale 2, were ranked the top three based on overall environment mean grain yield. The first and second principal component account 45.5% and 24.7% of the genotype by environment interaction (G × E), respectively, explained 70.2% of the total variation. Daro Lebu and Bedeno were the most productive environment, while Girja was the least productive of irrigated bread wheat for lowlands of the Oromia region. Genotype Selection Index (GSI) showed that varieties Fentale 2, Fentale 1, Pavon 76, and ETBW9578 are stable and high yielding. Based on AMMI and GGE biplot analysis, Girja indicated the most discriminating area and Sewena as representative environment for selecting wide adaptable irrigated lowland varieties. The results of the present study indicated that Fentale 2 and Fentale 1 showed better yield stability across all test environments, therefore, these bread wheat varieties are recommended for wide cultivation in irrigated areas of the Oromia region.

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Section: Resultssupporting

confidence: 92%

Genotype × environment interaction of lowland bread wheat varieties for irrigation in different areas of Oromia

Bayissa

Mengistu

Gerema

et al. 2023

Plant Enviro Interactions

View full text Add to dashboard Cite

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“…Those genotypes G24 (Co 88025), G23 (CoV 94101), and G20 (Co 16001) with high mean yield and large PCA1 scores resulted in specific adaptation to the favorable environments. These were also detected by Meena et al 2017 andRegis et al 2018 in sugarcane.…”

Section: Resultsmentioning

confidence: 75%

“…, UshaRani et al (2017) andRegis et al (2018) who suggested that GEI pattern is collected in the first principal components of analysis. Average cane yield recorded 102.28 t/ha and 65.26 t/ha for II plant crop and ratoon, respectively (table 5).…”

mentioning

confidence: 99%

Evaluation of promising commercial sugarcane genotypes for stability by AMMI analysis

Karthigeyan

2021

EJPB

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The choice and recommendation of a variety for commercial cultivation are influenced by genotype x environment interaction (GEI)). The complication of genotype by environment interaction (GEI) is that usually involves layout of trials in various seasons, making it difficult to identify the genotype adapted to different environments. Twenty sugarcane clones and four standard checks were evaluated under three environments within the tropical climate. Additive Main Effects and Multiplicative Interaction (AMMI) model was applied to assess the extent of genotype x environment (GE) interaction and also the stability of sugarcane clones across the environments. The significant difference was observed by AMMI analysis among the tested clones and environments. The sum of the first two principal components conferred to 63.6 per cent of the total of G x E interaction. In the present study, the genotypes G24 (Co 88025), G23 (CoV 94101) and G20 (Co 16001) recorded in high mean yield and higher Principal Component Analysis (PCA) scores; hence, these materials specifically suited to the favorable locations. Since the genotypes Co 15021(G19), Co 0240 (G3), and Co 13001(G7) were near the center point of the axes and hence were influenced by the environment. These clones recorded higher cane yield and stability and suitable for cultivation in different environments. The utilization of the AMMI model made it easy for the visual comparison and identification of exceedingly superior genotypes for every set of environments.

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“…It is more difficult to determine experimental accuracy for the traits TPH and TCH. The coefficients of variation for these traits usually have medium magnitude [38]. In contrast, the coefficients of variation for the traits FIB (%), CP (%), PT (%), SSC (%), and TRS (Kg) have low magnitude [37].…”

Section: Plos Onementioning

confidence: 99%

Genetic divergence for adaptability and stability in sugarcane: Proposal for a more accurate evaluation

et al. 2021

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The best agro-industrial performance presented by a crop genotype in one environment may not be reproduced in another owing to complex edaphoclimatic variations. Therefore, breeding programs are constantly attempting to obtain, through artificial hybridization, novel genotypes with high adaptability and stability potential. The objective of this study was to analyze genetic divergence in sugarcane based on the genotypic values of adaptability and stability. A total of 11 sugarcane genotypes were analyzed for eight agro-industrial traits. The genotypic values of the traits were determined using mixed model methodology, and the genetic divergence based on phenotypic and genotypic values was measured using the Mahalanobis distance. The distance matrices were correlated using the Mantel test, and the genotypes were grouped using the Tocher method. Genetic divergence is more accurate when based on genotypic values free of genotype–environment interactions and will differ from genetic divergence based on phenotypic data, changing the genotype allocations in the groups. The above methodology can be applied to assess genetic divergence to obtain novel sugarcane genotypes with higher productivity that are adapted to intensive agricultural systems using diverse technologies. This methodology can also be tested in other crops to increase accuracy in selecting the parents to be crossed.

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Adaptability and phenotypic stability of sugarcane clones

Cited by 13 publications

References 15 publications

Genotype × environment interaction of lowland bread wheat varieties for irrigation in different areas of Oromia

Genotype × environment interaction of lowland bread wheat varieties for irrigation in different areas of Oromia

Evaluation of promising commercial sugarcane genotypes for stability by AMMI analysis

Genetic divergence for adaptability and stability in sugarcane: Proposal for a more accurate evaluation

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