Multi-Trait Selection Indices for Identifying New Cassava Varieties Adapted to the Caribbean Region of Colombia

León, Rommel; Rosero, Amparo; García, Jorge Luis; Morelo, Julio; Orozco, Alfonso; Silva, Gabriel; Ossa, Víctor De la; Correa, Ender; Cordero, Carina Cecilia Cordero; Villalba, Leonardo; Belalcázar, John; Ceballos, Hernán

doi:10.3390/agronomy11091694

Cited by 15 publications

(17 citation statements)

References 39 publications

(45 reference statements)

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“…Several selection tools are generally used by breeders to allow ranking of top varieties. 18 The use of the deviation of preferred variables from the optimum as well as the regression coefficients as weights in our study should give consistent results.…”

Section: Discussionsupporting

confidence: 58%

“…To screen and rank yam varieties, the selection index described by León et al 18 was modified as follows: on the scale of overall liking (OL), the deviation from the ideal/optimum (DIOL(obs→opt)) was determined for each variety and used as selection index. It was calculated using the regression coefficient (β) between consumers' overall liking and relating parameters.…”

Section: Discussionmentioning

confidence: 99%

“…Based on the score (optimal and acceptable) of sensory attributes determined, the optimal/ideal and acceptable levels of explicative biophysical parameters were assessed using predictive models from multiple regressions. To screen and rank yam varieties, the selection index described by León et al 18 was modified as follows: on the scale of overall liking (OL), the deviation from the ideal/optimum (DI OL (obs → opt)) was determined for each variety and used as selection index. It was calculated using the regression coefficient (⊎) between consumers' overall liking and relating parameters.…”

Section: Discussionmentioning

confidence: 99%

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Characterizing quality traits of boiled yam: texture and taste for enhanced breeding efficiency and impact

et al. 2023

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BACKGROUND: Boiled yam key quality attributes typical for West African consumers are: crumbly, easy to break, and sweet taste. New yam varieties are being developed but high or medium throughput tools to assess the required quality traits and their range of acceptance are limited. This study assessed the acceptance thresholds of these quality attributes and established the predictive models for screening yam varieties that meet the required consumers' preferences. RESULTS:Overall liking was associated with sweet taste, crumbly and easy to break (r values 0.502, 0.291 and -0.087, respectively). These parameters and selected biophysical parameters highly discriminated the boiled yam varieties. Crumbly texture and easy to break were wellpredicted by penetration force and dry matter, whereas sweet taste by dry matter and sugar intensity. A high crumbliness and sweet taste are preferred (sensory scores above 6.19 and 6.22 for crumbly and sweet taste, respectively, on a 10 cm unstructured line scale), while a too high easiness to break is disliked (sensory scores ranging from 4.72 to 7.62). Desirable biophysical targets were between 5.1 and 7.1 N for penetration force, dry matter around 39% and sugar intensity below 3.62 g/100g. Some improved varieties fulfilled the acceptable thresholds, and the screening was improved through the deviation from optimum. CONCLUSION:The acceptance thresholds and the deviation from optimum for boiled yam assessed through the instrumental measurements are promising tools for yam breeders.

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Section: Discussionsupporting

confidence: 58%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Characterizing quality traits of boiled yam: texture and taste for enhanced breeding efficiency and impact

et al. 2023

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“…Multivariate approaches are needed to provide strategic treatment ranking considering value on multiple traits. To overcome limitations, multi‐trait genotype‐ideotype distance index (MGIDI) has been proposed (Olivoto & Nardino, 2021) and has been successfully used to select superior genotypes (Aboughadareh et al., 2021; Caballero et al., 2022; Farhad et al., 2022; Leon et al., 2021; Olivoto & Nardino, 2021; Uddin et al., 2021).…”

Section: Introductionmentioning

confidence: 99%

Understanding of G × E interactions of yield attributes in soybean MAGIC population and characterization for charcoal rot resistance

Maranna,

Nataraj,

Kumawat

et al. 2024

Agronomy Journal

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Multi‐parent advanced generation inter‐cross (MAGIC) populations have been developed and utilized in crop improvement programs in several economically important crops. In the current study, soybean (Glycine max L.) MAGIC population was evaluated at four locations to identify stable and high‐yielding MAGIC RILs (recombinant inbred lines) and to understand the genotype and environmental interaction for grain yield and attributing traits. For different traits under study, pooled analysis of variance indicated the significant genotype × environmental interactions at p < 0.01. RILs such as G236, G455, G159, G493, and G488 found ideal for grain yield across the four environments. Through multi‐trait genotype‐ideotype distance index ideotype‐MAGIC RILs have been identified for each location. Significant positive correlation of grain yield with pods per plant, 100‐seed weight, plant height, number of nodes per plant, and branches per plant has been identified. Under field conditions, screening of F2:3 generation of MAGIC population revealed that only 59 progenies exhibited adult plant resistance for charcoal rot disease (caused by Macrophomina phaseolina). Although under controlled conditions parental genotypes EC 572136 and EC 572109 found to be partially resistant with least mean necrosis length, MAGIC RILs (F2:8) showed variable reaction. Thus, the study established diverse genetic resources useful for both mapping and varietal development program.

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“…To overcome this fragility, the multi-trait genotype-ideotype distance index (MGIDI) has been proposed [19]. The MGIDI was originally designed for selecting genotypes in plant breeding based on information on multiple traits and has been successfully used to select superior genotypes [19][20][21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

MGIDI: a powerful tool to analyze plant multivariate data

et al. 2022

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Background Commonly, several traits are assessed in agronomic experiments to better understand the factors under study. However, it is also common to see that even when several traits are available, researchers opt to follow the easiest way by applying univariate analyses and post-hoc tests for mean comparison for each trait, which arouses the hypothesis that the benefits of a multi-trait framework analysis may have not been fully exploited in this area. Results In this paper, we extended the theoretical foundations of the multi-trait genotype-ideotype distance index (MGIDI) to analyze multivariate data either in simple experiments (e.g., one-way layout with few treatments and traits) or complex experiments (e.g., with a factorial treatment structure). We proposed an optional weighting process that makes the ranking of treatments that stands out in traits with higher weights more likely. Its application is illustrated using (1) simulated data and (2) real data from a strawberry experiment that aims to select better factor combinations (namely, cultivar, transplant origin, and substrate mixture) based on the desired performance of 22 phenological, productive, physiological, and qualitative traits. Our results show that most of the strawberry traits are influenced by the cultivar, transplant origin, cultivation substrates, as well as by the interaction between cultivar and transplant origin. The MGIDI ranked the Albion cultivar originated from Imported transplants and the Camarosa cultivar originated from National transplants as the better factor combinations. The substrates with burned rice husk as the main component (70%) showed satisfactory physical proprieties, providing higher water use efficiency. The strengths and weakness view provided by the MGIDI revealed that looking for an ideal treatment should direct the efforts on increasing fruit production of Albion transplants from Imported origin. On the other hand, this treatment has strengths related to productive precocity, total soluble solids, and flesh firmness. Conclusions Overall, this study opens the door to the use of MGIDI beyond the plant breeding context, providing a unique, practical, robust, and easy-to-handle multi-trait-based framework to analyze multivariate data. There is an exciting possibility for this to open up new avenues of research, mainly because using the MGIDI in future studies will dramatically reduce the number of tables/figures needed, serving as a powerful tool to guide researchers toward better treatment recommendations.

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Multi-Trait Selection Indices for Identifying New Cassava Varieties Adapted to the Caribbean Region of Colombia

Cited by 15 publications

References 39 publications

Characterizing quality traits of boiled yam: texture and taste for enhanced breeding efficiency and impact

Characterizing quality traits of boiled yam: texture and taste for enhanced breeding efficiency and impact

Understanding of G × E interactions of yield attributes in soybean MAGIC population and characterization for charcoal rot resistance

MGIDI: a powerful tool to analyze plant multivariate data

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