Applications of quantitative genetics and statistical analyses in sugarcane breeding

Hoarau Jean-Yves, Dumont Thomas, Wei Xianming, Jackson Phil A., D'Hont Angélique. 2022. Applications of quantitative genetics and statistical analyses in sugarcane breeding. Sugar Tech, 24 : 320-340.

https://doi.org/10.1007/s12355-021-01012-3

Article de revue ; Article de revue à facteur d'impact

Prévisualisation

Version Online first - Anglais
Sous licence

.
Hoarau 2021.pdf
Télécharger (847kB) | Prévisualisation

Prévisualisation

Version publiée - Anglais
Sous licence

.
598937.pdf
Télécharger (835kB) | Prévisualisation

Résumé : Sugarcane breeding programs aim to deliver new high-yielding varieties, resistant to diseases and pests, which contribute to profitability and sustainability of cane industries. These programs generally mobilize significant experimental, technological and human resources on long-term basis. Their efficiency in terms of genetic gains per unit of cost and time and their ability to release new varieties rely on the development of many breeding applications based on quantitative genetics theory and on statistical analyses of numerous experimental data from selection schemes including DNA marker data developed for some genomic breeding applications. New methodological approaches and new technologies that might better guide and support breeding research in cultivars development programs are continually sought. This paper presents an overview of the main applications developed in statistical methodology in support of the efficiency of sugarcane breeding programs. For each type of application, its conceptual and methodological framework is presented. Implementation issues are reviewed as well as the main scientific and practical achievements so far obtained.

Mots-clés Agrovoc : amélioration génétique, canne à sucre, Saccharum, génétique quantitative, amélioration des plantes, gain génétique, méthode statistique, modèle linéaire

Mots-clés complémentaires : Urochloa brizantha

Mots-clés libres : Sugarcane breeding, Linear mixed models, Quantitative genetics, Genetic gain, Genomics applications

Classification Agris : F30 - Génétique et amélioration des plantes
U10 - Informatique, mathématiques et statistiques

Champ stratégique Cirad : CTS 2 (2019-) - Transitions agroécologiques

Auteurs et affiliations

Hoarau Jean-Yves, CIRAD-BIOS-UMR AGAP (REU) ORCID: 0000-0001-9734-4165 - auteur correspondant
Dumont Thomas, eRcane (REU)
Wei Xianming, SRA (AUS)
Jackson Phil A., CSIRO (AUS)
D'Hont Angélique, CIRAD-BIOS-UMR AGAP (FRA)