Enviromicsin breeding: applications and perspectives on envirotypic-assisted selection

Abstract

Key message:We propose the application of Enviromics to breeding practice, by which the similarity 16 among sites assessed on an "omics" scale of environmental attributes drives the prediction of 17 unobserved genotypes. 18 Abstract. Genotype by Environment interaction (G × E) studies have focused mainly on estimating 19 genetic parameters over a limited number of experimental trials. However, recent Geographic 20 34 when coupled with next-generation genotyping/phenotyping and powerful statistical modeling of 35 genetic diversity. Environmental scenarios can also be improved using information from strategic plans 36 for biodiversity and genetic resources management, especially in the current perspective of dynamic 37 climate change.38

Adaptability and stability analysis of new popcorn simple hybrids evaluated using additive main effects and multiplicative interaction Bayesian approaches

“…The presence of genotype × environment interaction for GY and PE has been reported in several popcorn studies, corroborating with this study and indicating that differential behavior of genotypes is environment-dependent (Gerhardt et al 2019;Paula et al 2010;Pena et al 2012;Peterlini et al 2020). In addition, these results confirm that adaptability and stability evaluation are important to mitigate the effects of the genotype × environment interaction (Resende et al 2019).…”

“…Before release new cultivars in the market, plant breeders need to perform experiments and investigate cultivars performance under different environmental conditions. Field experiments allow adaptation, stability and performance analysis of genotypes in facing different environmental conditions (Resende et al 2019). Several statistical methods to study adaptability and stability have been developed and widely used in plant breeding programs (Annicchiarico 2002;Fasahat https://doi.org/10.1590Fasahat https://doi.org/10.…”

Extending the breeder’s equation to take aim at the Target Population of Environments

“…The second considers an empirical example based on a previously published MET-TPE data set for wheat in Australia (Cooper et al, 1995(Cooper et al, , 1997(Cooper et al, , 2001. The wheat example was previously used to investigate the implications of GxE interactions for grain yield in the TPE, and also the MET-TPE relationship for design of METs to accelerate genetic gain for yield from wheat breeding in a TPE where complex GxE interactions for grain yield are ubiquitous (Brennan et al, 1981;Cooper and DeLacy, 1994;Cooper et al, 1995Cooper et al, , 1997Cooper et al, , 2001Cooper, 1998, Chenu et al, 2011;Lobell et al, 2015;Bustos-Korts et al, 2021;Resende et al, 2021).…”

“…However, taking aim at the TPE as a mixture of environment-types (Podlich et al, 1999;Cooper et al, 2014a,b;Gaffney et al, 2015;Rogers et al, 2021;Smith et al, 2021a, b;Messina et al, 2022a,b) is much less common than taking aim at specific environment-types. Taking aim at the TPE requires detailed consideration of the mixture of target environment-types within the TPE (Chapman et al, 2000;Chenu et al, 2011;Kholová et al, 2013;Cooper et al, 2014a, b;Lobell et al, 2015;Hajjarpoor et al, 2021;Resende et al, 2021), the extent of GxE interactions between environment-types (Figure 2) and the details of the genetic variance-covariance structure among the environment-types, and appropriate attention to weighting the sources of G2P information for traits, that is available from the environment-types sampled in the MET training data sets, by their frequencies of occurrence and relative importance in the TPE (Podlich et al, 1999;Cooper et al, 2014a, b;Gaffney et al, 2015;Messina et al, 2018;Smith et al, 2021b).…”

Genetic Progress of Seed Yield and Nitrogen Use Efficiency of Brazilian carioca Common Bean Cultivars Using Bayesian Approaches

“…The development of genotypes with environment adaptive plasticity, good stability, and high SY mean is one way to mitigate G × E interaction effects (Resende et al, 2019). Statistical methods to study adaptability and stability have been developed and widely used by plant breeding programs (Nascimento et al, 2020).…”