Multi-Trait Selection Index for Superior Agronomic and Tuber Quality Traits in Bush Yam (Dioscorea praehensilis Benth.)

Adewumi, Adeyinka S.; Asare, Paul A.; Adejumobi, Idris I.; Adu, Michael O.; Taah, Kingsley J.; Adewale, Samuel; Mondo, Jean M.; Agre, Paterne A.

doi:10.3390/agronomy13030682

Cited by 11 publications

(8 citation statements)

References 37 publications

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“…The analysis of variance showed significant variations among the genotypes across all eight traits indicating a high level of diversity among the genotypes. A similar genetic differentiation among yam genotypes showing high coefficients of variation (CVs > 20) for agronomic and quality traits was reported by Cao et al [45], Adejumobi et al [46], and Adewumi et al [24].…”

Section: Discussionsupporting

confidence: 80%

“…Olivoto and Nardino [18] compared several multi-trait selection indices and proposed the novel multi-trait genotype-ideotype distance index (MGIDI) to select genotypes with desirable mean performances across multiple traits while overcoming the limitations of traditional linear indices. The use of multiple traits in the selection of superior yam genotypes has been reported for D. rotundata wherein FAI-BLUP (multi-trait index-based factor analysis and ideotype design) [22] and MGIDI method [23] were used, while the MGIDI method was used for D. praehensilis [24] species, but none for D. alata species. In this context, an attempt was made in this study to assess a panel of D. alata mapping population progenies as well as their parents for selection of desirable genotypes/ideotypes based on their agronomic and quality characteristics.…”

Section: Introductionmentioning

confidence: 99%

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Multi-Trait Selection Index for Simultaneous Selection of Water Yam (Dioscorea alata L.) Genotypes

Ouattara,

Agre,

Adejumobi

et al. 2024

Agronomy

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Water yam (Dioscorea alata L.) is the most widely cultivated yam species with good agronomic attributes. However, several biotic and abiotic constraints and its lower food quality such as poor pound ability limit its production and use. Therefore, the identification of superior genotypes with suitable characteristics is needed for water yam improvement. This study aims to assess a panel of half-sib (progenies with one parent in common) and full-sib (progenies with the same male and female parents) progenies as well as their parents for selection of desirable ideotypes based on their agronomic and quality characteristics. A total of 280 progenies from bi-parental populations as well as five parents were evaluated, and a significant variation was observed (p < 0.01) in their performances for the eight traits used in the study. A moderate to high broad-sense heritability (30% < H2–H2 ≥ 60%) was observed for all traits except for tuber pound ability (H2 < 30%). Positive correlations were displayed between the traits, while the hierarchical clustering grouped genotypes into three clusters indicating the potential for selection of diverse genotypes for multiple traits from the four families under study. Plant vigor and number of tubers per plant contributed (p < 0.01) positively to the yield per plant in the path coefficient analysis. Using the multi-trait genotype–ideotype distance index (MGIDI), a total of 39 most promising genotypes were identified. These promising genotypes could be further used as progenitors in D. alata improvement programs targeting good agronomic and quality traits targeted for farmers and end users.

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Section: Discussionsupporting

confidence: 80%

Section: Introductionmentioning

confidence: 99%

Multi-Trait Selection Index for Simultaneous Selection of Water Yam (Dioscorea alata L.) Genotypes

Ouattara,

Agre,

Adejumobi

et al. 2024

Agronomy

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“…The MGIDI index efficiently selected accessions SM227, NLR33892, MTU3626, 239(3), SMB3, and 405C3 as promising candidates for direct-seeded rice improvement programs. The versatility of the MGIDI model is underscored by its successful application in assessing ideal yield and yield-related traits in various crops such as Bush Yam (Adewumi et al, 2023), Maize (Palaniyappan et al, 2023), Wheat (Meier et al, 2021), Eggplant (Uddin et al, 2021), Guar (Cymopsis tetragonoloba) (Benakanahalli et al, 2021), soybean (Woyann et al, 2019, Volpato et al, 2019. These diverse studies collectively highlight the efficiency of multivariate selection indices for simultaneous trait selection.…”

Section: Resultsmentioning

confidence: 99%

Multi trait genotype- ideotype distance index (MGIDI) for early seedling vigour and yield related traits to identify elite lines in rice (Oryza sativa L.)

2024

EJPB

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Rice (Oryza sativa L.) stands as a important cereal sustaining over half of the world's population. This study delves into the challenges confronting breeders in the realm of crop improvement, specifically focusing on the intricate task of designing an ideotype-a genotype amalgamating diverse attributes for optimal performance. Traditional methodologies, exemplified by the Smith-Hazel (SH) index, grapple with issues such as multicollinearity and the complexities of economic weighting decisions. In response to these challenges, the Multi-Trait Genotype-Ideotype Distance Index (MGIDI), conceptualized by Olivoto and Nardino (2021), emerges as a ground breaking approach. Principal Component Analysis (PCA) aids in the reduction of trait dimensionality, revealing four key factors that collectively contribute to 79.444% of total variability. The Scree plot guides factor selection, ensuring a targeted analysis. The MGIDI index computation yields a total genetic gain of 273.025%, with specific traits like spikelet fertility and seedling dry weight exhibiting significant gains. Six high-performing rice accessions-SM227, NLR33892, MTU3626, 239(3), SMB3, and 405C3 were identified through MGIDI. These identified genotypes serve as valuable resources for developing recombinant populations, aligning with sustainable and effective crop improvement strategies. Additionally, these promising varieties exhibit strengths across various traits, offering potential for simultaneous trait improvement in future breeding programmes. The efficiency of MGIDI is highlighted through its innovative application in simultaneous trait selection, underscoring its significance across a wide range of crops.

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“…However, these statistical tools are insufficient to detect the weaknesses and strengths of genotypes and to select individuals with desired average performance and stability [58]. The MGIDI is a sophisticated quantitative genetic technique used to exploit desired accessions in all crop species [59] and is free from multi-collinearity problems [60]. In the current study, the MGIDI was computed for the best treatment combination (cut × space) and for the selection of suitable genotypes by grouping the studied traits into the same factor.…”

Section: Treatment Combination and Genotypes Selection Using The Mgidimentioning

confidence: 99%

Multi-Trait Selection of Quinoa Ideotypes at Different Levels of Cutting and Spacing

et al. 2023

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Climate change has affected the food supply chain and raised serious food concerns for humans and animals worldwide. The present investigation aimed to assess the effect of environmental factors along with three different levels of cutting (i.e., cutting 1, 2, and 3 at the vegetative, budding, and flowering stages, respectively) and spacing (i.e., 21, 23, and 26 cm) on quinoa biomass and quality to select the most suitable accessions. This experiment was repeated for two years using a split–split plot experimental design. The cutting × genotype × year and cutting × space × genotype interactions were significant for most quinoa morphological traits (except for leaf area and intermodal distance), where the maximum growth in number of leaves/plant (NoL), plant height (PH), fresh weight (FW), number of branches/plant (Br), and dry weight (DW) were observed during the second growing season. Cutting and spacing levels also showed significant effects on morphological and quality traits of quinoa. Among the different levels of cutting and spacing, cutting level 3 and spacing level 2 were more effective across both years at gaining maximum biomass and quality traits such as crude fat (CF) and crude protein (CP). According to the MGIDI, only two accessions (R3 and R9) fared better in both growing seasons, and selected accessions had positive morphological and quality traits. There were moderately significant negative correlations between PH, NoL, LA, FW, and DW and anti-quality traits such as neutral detergent fiber (NDF) and acid detergent fiber (ADF), indicating that an increase in biomass decreased the concentrations of ADF and NDF in both stem and leaves. A comparison with oat accessions (G3 and G7) revealed that quinoa has higher CP and CF and lower NDF than oats in both stems and leaves (except for ADF). In conclusion, the combination of cutting level 3 and spacing level 2 (23 cm) is more suitable to obtain high-quality quinoa forage with maximum biomass production. Furthermore, the MGIDI is a useful tool for breeders to select genotypes based on their mean performance, stability, and desired traits.

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Multi-Trait Selection Index for Superior Agronomic and Tuber Quality Traits in Bush Yam (Dioscorea praehensilis Benth.)

Cited by 11 publications

References 37 publications

Multi-Trait Selection Index for Simultaneous Selection of Water Yam (Dioscorea alata L.) Genotypes

Multi-Trait Selection Index for Simultaneous Selection of Water Yam (Dioscorea alata L.) Genotypes

Multi trait genotype- ideotype distance index (MGIDI) for early seedling vigour and yield related traits to identify elite lines in rice (Oryza sativa L.)

Multi-Trait Selection of Quinoa Ideotypes at Different Levels of Cutting and Spacing

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