Appraisal of Test Location and Variety Performance for the Selection of Tuber Yield in a Potato Breeding Program

Abstract

1957ReseaRch W hen testing selection candidates over multiple environments, uncertainty in the estimates of genotype values increases with the magnitude of G E. This increases the difficulty of identifying superior genotypes and compromises genetic progress from selection (e.g., Annicchiarico, 2002;Bos and Caligari, 2008; DeLacy et al., 1996a,b). A better understanding of GE effects within a MET testing regime allows a reevaluation of resource allocation and selection strategy in a breeding program. The type and extent of G  E is of particular interest to plant breeders as the characterization of environments will help, in part, to define selection strategies. For example, measures of quantitative G E (heterogeneity of variance or the scale ABSTRACT Differences in trait responses of genotypes across environments, or genotype  environment interactions (G E), hinder the progress of genetic improvement. Characterization of these effects helps to determine breeding strategies and improve resource allocation in a cultivar development program. This study used historical multienvironment trial (MET) data (34 trials in five locations) for the analysis of marketable yield of advanced selections in a New Zealand potato (Solanum tuberosum L.) breeding program. A factor analytic (FA) model was used for the analysis of these MET data. Contrasts based on the environmental loadings were observed between the program's main trial locations in the North Island (pukekohe) and the South Island (Lincoln), indicating that these locations optimized differentiation between genotypes in terms of G E effects. Genetic correlation estimates between trial environments were mostly moderately high (>0.5) to high (>0.8) and ranged from zero to positive with a maximum coefficient of 0.97, suggesting that quantitative (rescaling) rather than qualitative (crossover) G E effects were of greater importance. A number of newly developed varieties were shown to have higher genetic yield potential than older and established commercial cultivars but did not necessarily show better yield stability over the locations tested.

Genetic Covariance of Environments in the Potato National Chip Processing Trial

“…The analysis used linear mixed models with factor-analytic (FA) covariance structures to parsimoniously model the genetic correlation between many environments (Piepho, 1998;Smith et al, 2001). Factor-analytic models have been used before to analyze multienvironment trials of potato, including Paget et al (2015) for yield in New Zealand and Wang et al (2017) for specific gravity of russet potatoes in the United States. Both studies used the "uniplot" technique of Cullis et al (2010) to visualize genetic correlation with a second-order FA model.…”

Tuber Yield, Water Productivity and Post-harvest Quality of Sprinkler-irrigated Chip Potato (solanum tuberosum L.) Under a Semiarid Climate

“…The stability of potato chip color during a long cold storage period is commercially preferred by processors. Paget et al reported genotypes and environment interaction and concluded that newly developed potato varieties showed higher yield stability compared to the commercially established varieties in New Zealand [17]. From the evaluation of 18 potato cultivars in São Manuel (Brazil), Feltran et al concluded that potato technological characteristics were influenced by cultivars [18].…”

Reliability of Measurement and Genotype × Environment Interaction for Potato Specific Gravity

“…Since the study of Wang et al (2015) was unreplicated within environment, there was limited opportunity to investigate the geographic pattern of genotype × location interactions. Regional patterns have been investigated for potato yield and quality in other countries (Affleck et al, 2008; Paget et al, 2015), but our understanding of this topic on a national scale in the United States is largely anecdotal. Therefore, the main goals of this study were (i) to determine the reliability of methods for measuring the mean and SD of the SpGr distribution, (ii) to assess the SpGr stability of new elite processing genotypes across environments, and (iii) to determine whether there is a consistent contribution of genotype × environment to mean SpGr across the major potato production regions in the United States.…”