Micronutrient malnutrition is a global health problem. An improved understanding of the genetic variation of important micronutrient traits within a potato breeding population will help devise breeding strategies for the biofortification of this important food staple. The dataset consisted of 556 individuals from 17 full‐sib diploid families grown in 2006 in Huanuco, Peru, and 1329 individuals from 32 full‐sib families grown in 2009 in Ayacucho, Peru. Genetic parameters were estimated using univariate and multivariate individual Bayesian models for micronutrient tuber content including Fe and Zn. Genetic variance was additive and heritability estimates were moderate (0.36 to 0.57) and inflated if the common environment of full‐sibs was not taken into account. Posterior modes of genetic correlation estimates between minerals, when analyzed on a dry‐weight basis, were all positive (0.04 to 0.72) and between minerals and tuber dry matter were negative (−0.14 to −0.38). On a fresh‐weight basis, genetic correlations between minerals and tuber dry matter were small but positive (0.05 to 0.18). The implications and challenges for selective breeding to enhance micronutrient content in potato tubers are discussed.

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Genetic evaluation aims to identify genotypes with high empirical breeding values (EBVs) for selection as parents. In this study, 2157 potato genotypes were evaluated for tuber yield using 8 years of early‐stage trial data collected from a potato breeding programme. Using linear mixed models, spatial parameters to target greater control of localised spatial heterogeneity within trials were estimated and variance models to account for across‐trial genetic heterogeneity were tested. When spatial components improved model fit, correlations of errors were mostly small and negative for marketable tuber yield (MTY) and total tuber yield (TTY), suggesting the presence of interplot competition in some years. For the analysis of multi‐environment trials, a variance model with a simple correlation structure (with heterogeneous variances) was the most favourable variance structure fitted for TTY and PTY (per cent marketable yield). There was very little difference in model fit when comparing a factor analytic structure of order 2 (FA2) with either FA1 or simple correlation structures for MTY, indicating that simple variance models may be preferable for early‐stage genetic evaluation of potato yield.

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Traditional tree improvement is cumbersome and costly. Our main objective was to assess the extent to which genomic data can currently accelerate and improve decision making in this field. We used diameter at breast height (DBH) and wood density (WD) data for 4430 tree genotypes and single-nucleotide polymorphism (SNP) data for 2446 tree genotypes. Pedigree reconstruction was performed using a combination of maximum likelihood parentage assignment and matching based on identity-by-state (IBS) similarity. In addition, we used best linear unbiased prediction (BLUP) methods to predict phenotypes using SNP markers (GBLUP), recorded pedigree information (ABLUP), and single-step “blended” BLUP (HBLUP) combining SNP and pedigree information. We substantially improved the accuracy of pedigree records, resolving the inconsistent parental information of 506 tree genotypes. This led to substantially increased predictive ability (i.e., by up to 87%) in HBLUP analyses compared to a baseline from ABLUP. Genomic prediction was possible across populations and within previously untested families with moderately large training populations (N = 800–1200 tree genotypes) and using as few as 2000–5000 SNP markers. HBLUP was generally more effective than traditional ABLUP approaches, particularly after dealing appropriately with pedigree uncertainties. Our study provides evidence that genome-wide marker data can significantly enhance tree improvement. The operational implementation of genomic selection has started in radiata pine breeding in New Zealand, but further reductions in DNA extraction and genotyping costs may be required to realise the full potential of this approach.