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Analysis of institutional authors

Rio SCorresponding AuthorIsidro Y Sánchez JAuthor

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September 20, 2022
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Genomic prediction and training set optimization in a structured Mediterranean oat population

Publicated to: THEORETICAL AND APPLIED GENETICS. 134 (11): 3595-3609 - 2021-11-01 134(11), DOI: 10.1007/s00122-021-03916-w

Authors:

Rio, S; Gallego-Sánchez, L; Montilla-Bascón, G; Canales, FJ; Sánchez, JIY; Prats, E
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Affiliations

Spanish Res Council CSIC, Inst Sustainable Agr, Cordoba, Spain - Author
Univ Politecn Madrid UPM, Inst Nacl Invest & Tecnol Agr & Alimentaria INIA, Ctr Biotecnol & Genom Plantas CBGP UPM INIA, Campus Montegancedo UPM, Madrid 28223, Spain - Author

Abstract

Key message: The strong genetic structure observed in Mediterranean oats affects the predictive ability of genomic prediction as well as the performance of training set optimization methods. Abstract: In this study, we investigated the efficiency of genomic prediction and training set optimization in a highly structured population of cultivars and landraces of cultivated oat (Avena sativa) from the Mediterranean basin, including white (subsp. sativa) and red (subsp. byzantina) oats, genotyped using genotype-by-sequencing markers and evaluated for agronomic traits in Southern Spain. For most traits, the predictive abilities were moderate to high with little differences between models, except for biomass for which Bayes-B showed a substantial gain compared to other models. The consistency between the structure of the training population and the population to be predicted was key to the predictive ability of genomic predictions. The predictive ability of inter-subspecies predictions was indeed much lower than that of intra-subspecies predictions for all traits. Regarding training set optimization, the linear mixed model optimization criteria (prediction error variance (PEVmean) and coefficient of determination (CDmean)) performed better than the heuristic approach “partitioning around medoids,” even under high population structure. The superiority of CDmean and PEVmean could be explained by their ability to adapt the representation of each genetic group according to those represented in the population to be predicted. These results represent an important step towards the implementation of genomic prediction in oat breeding programs and address important issues faced by the genomic prediction community regarding population structure and training set optimization.
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Keywords

accuracyassisted predictionavena sativacalibration setenvironmental adaptationgenetic structuregenetic valuegenomic predictionlinkage disequilibriumplantregressionselectiontraining set optimizationwide associationAvenaAvena sativaBayes theoremBeta-glucan concentrationEdible grainEnvironmental adaptationGenetic structureGenetics, populationGenome, plantGenomic predictionGenomicsGenotypeMediterranean regionModels, geneticOatPhenotypePlant breedingSpainTraining set optimization

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal THEORETICAL AND APPLIED GENETICS due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2021, it was in position 3/36, thus managing to position itself as a Q1 (Primer Cuartil), in the category Horticulture. Notably, the journal is positioned above the 90th percentile.

From a relative perspective, and based on the normalized impact indicator calculated from World Citations provided by WoS (ESI, Clarivate), it yields a value for the citation normalization relative to the expected citation rate of: 1.44. This indicates that, compared to works in the same discipline and in the same year of publication, it ranks as a work cited above average. (source consulted: ESI Nov 13, 2025)

This information is reinforced by other indicators of the same type, which, although dynamic over time and dependent on the set of average global citations at the time of their calculation, consistently position the work at some point among the top 50% most cited in its field:

  • Weighted Average of Normalized Impact by the Scopus agency: 1.36 (source consulted: FECYT Mar 2025)

Specifically, and according to different indexing agencies, this work has accumulated citations as of 2026-04-25, the following number of citations:

  • WoS: 16
  • Scopus: 17
  • Europe PMC: 10
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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2026-04-25:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 25.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 23 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 5.
  • The number of mentions on the social network X (formerly Twitter): 8 (Altmetric).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://oa.upm.es/86531/

As a result of the publication of the work in the institutional repository, statistical usage data has been obtained that reflects its impact. In terms of dissemination, we can state that, as of

  • Views: 108
  • Downloads: 37
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Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (RIO, SIMON) .

the author responsible for correspondence tasks has been RIO, SIMON.

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