Development of Selection Indices for Improvement of Seed Yield and Lipid Composition in Bambara Groundnut (Vigna subterranea (L.) Verdc.)

The underutilised grain legume bambara groundnut (Vigna subterranea) has the potential to contribute significantly to nutritional security. However, the lack of commercial cultivars has hindered its wider adoption and utilisation as a food source. The development of competitive cultivars is impeded by (1) lack of systematic data describing variation in nutritional composition within the gene pool, and (2) a poor understanding of how concentrations of different nutritional components interact. In this study, we analysed seed lipid and protein concentration and lipid composition within a collection of 100 lines representing the global gene pool. Seed protein and lipid varied over twofold with a normal distribution, but no significant statistical correlation was detected between the two components. Seed lipid concentration (4.2–8.8 g/100 g) is primarily determined by the proportion of oleic acid (r2 = 0.45). Yield and composition data for a subset of 40 lines were then used to test selection parameters for high yielding, high lipid breeding lines. From five selection indices tested using 15 scenarios, an index based on the seed number, seed weight, and oleic acid yielded a > 50% expected increase in each of the mean values of seed number, pod dry weight, seed dry weight, and seed size, as well as an expected 7% increase in seed lipid concentration.

The structure of productivity elements of durum wheat varieties of Saratov selection

The objects of the study were plants of 14 varieties of durum wheat Triticum durum Desf., permitted for use at different times in the period from 1975 to 2014. An analysis of the elements of ear productivity in durum wheat plants of Saratov varieties under the conditions of 2020 was carried out. The varietal features of the development of the spike of the main shoot were revealed according to a number of characteristics: the number of spikelets in a spike, the number of grains in an ear, the weight of a grain, the number of ungrained and grained spikelets. The height of the plant and the length of the spike were measured. On the basis of the data obtained, the selection indices were calculated – the Canadian index, the Mexican index, the index of the linear density of the ear, the morphogenetic index of productivity. A cultivar with a balanced type of morphogenetic systems was revealed in terms of the elements of ear productivity – the number of spikelets, the number of caryopses and their weight – Luch 25. This cultivar is characterized by the most developed embryonic shoot among the studied cultivars, as well as the maximum length of the embryonic root system and a high growth rate root system of the seedling.

Genetic parameters and selection of biofortified lettuce genotypes based on selection indices

ABSTRACT Obtaining biofortified vegetables with an emphasis on lettuce is a tool to improve the nutritional status of the population. Selection indices can maximize the simultaneous selection of good agronomic traits and high carotenoid levels. The objective of this study was to estimate the genetic parameters and efficiency of different indices in selecting genotypes of biofortified lettuce with high concentrations of carotenoids and favorable agronomic traits. Statistical analyses were performed on 91 genotypes belonging to the vegetable germplasm bank of the Federal University of Uberlândia, Brazil. The variables analyzed were the chlorophyll index of the leaves, plant diameter, stem diameter, and number of leaves per plant. The values found for narrow sense heritability (h²) ranged from 89.63% (stem diameter) to 96.05% (chlorophyll), showing a high magnitude. The Smith-Hazel index, sum of ranks by the Mulamba & Mock index, direct and indirect selection, and Williams base index were used to predict the selection gains. A total of 17 individuals were selected using the selection methodologies. The Smith-Hazel, Williams, and Mulamba & Mock indices were efficient in showing good direct gains for the evaluated traits. Thirteen genotypes were selected for all indices presenting suitable agronomic traits, which show promise for advancing generations within the breeding program to obtain biofortified lettuce strains.

Optimum breeding strategies using genomic and phenotypic selection for the simultaneous improvement of two traits

Key message A breeding strategy combining genomic with one-stage phenotypic selection maximizes annual selection gain for net merit. Choice of the selection index strongly affects the selection gain expected in individual traits. Abstract Selection indices using genomic information have been proposed in crop-specific scenarios. Routine use of genomic selection (GS) for simultaneous improvement of multiple traits requires information about the impact of the available economic and logistic resources and genetic properties (variances, trait correlations, and prediction accuracies) of the breeding population on the expected selection gain. We extended the R package “selectiongain” from single trait to index selection to optimize and compare breeding strategies for simultaneous improvement of two traits. We focused on the expected annual selection gain (ΔGa) for traits differing in their genetic correlation, economic weights, variance components, and prediction accuracies of GS. For all scenarios considered, breeding strategy GSrapid (one-stage GS followed by one-stage phenotypic selection) achieved higher ΔGa than classical two-stage phenotypic selection, regardless of the index chosen to combine the two traits and the prediction accuracy of GS. The Smith–Hazel or base index delivered higher ΔGa for net merit and individual traits compared to selection by independent culling levels, whereas the restricted index led to lower ΔGa in net merit and divergent results for selection gain of individual traits. The differences among the indices depended strongly on the correlation of traits, their variance components, and economic weights, underpinning the importance of choosing the selection indices according to the goal of the breeding program. We demonstrate our theoretical derivations and extensions of the R package “selectiongain” with an example from hybrid wheat by designing indices to simultaneously improve grain yield and grain protein content or sedimentation volume.

The Environmental Impact of Changes in Cow Productivity and Its Component Traits in South Africa's Landrace Beef Breeds

Any reduction in the carbon footprint of beef production will contribute to future sustainability. This study investigates the environmental impact (carbon footprint) of the changes that occurred in cow productivity in the cowherds of four South African landrace breeds over a period of 25–30 years. Cow productivity, defined as kilogram calf weaned per large stock unit mated, increased by 18.3, 10.0, 14.2, and 10.4% in the Afrikaner, Bonsmara, Drakensberger, and Nguni, respectively. This resulted in a decrease in the carbon footprint, as defined by the enteric methane emissions factor, of between 6.6 and 12.0%. Changes in the cow productivity component traits, viz. weaning weight, cow weight, and fertility (as measured by inter-calving period) was also investigated. In all breeds, except the Nguni, the change in the environmental trends were less than that of the direct genetic or phenotypic trends. The genetic trends for direct weaning weight in the Afrikaner, Bonsmara, and Drakensberger were +6.7, +11.7, and +6.2 kg, respectively. In the case of the Bonsmara and Drakensberger breeds, the genetic trends were larger than the phenotypic trends, which may indicate that the environment cannot support the higher “genetic” weaning weights. The genetic trends for mature cow weight in Bonsmara and Drakensberger were +15.9 and +15.1 kg, respectively, whereas in the Afrikaner and Nguni it was not significantly different from zero (R2 ≤ 0.24). The trends in the phenotypic mature cow weights were −8.3, +17.5, +8.5, and −17.2 kg for in the Afrikaner, Bonsmara, Drakensberger, and Nguni, respectively. Although the observed inter-calving period of all breeds declined, there was no genetic change in inter-calving period for any of the breeds. It is proposed that selection indices are developed for cow productivity, which can be extended to a carbon footprint selection index. It is recommended that similar studies be done on all the major beef breeds in South Africa, especially those that rely on regular importation of genetic material.

Incorporating Molecular Markers and Causal Structure among Traits Using a Smith-Hazel Index and Structural Equation Models

The goal in breeding programs is to choose candidates that produce offspring with the best phenotypes. In conventional selection, the best candidate is selected with high genotypic values (unobserved), in the assumption that this is related to the observed phenotypic values for several traits. Multi-trait selection indices are used to identify superior genotypes when a number of traits are to be considered simultaneously. Often, the causal relationship among the traits is well known. Structural equation models (SEM) have been used to describe the causal relationships among variables in many biological systems. We present a method for multi-trait genomic selection that incorporates causal relationships among traits by coupling SEM with a Smith–Hazel index that incorporates markers. The method was applied to field data from a Nebraska winter wheat breeding program. We found that the correlation and the relative efficiency increased for the proposed Smith–Hazel indices when the total causal information among traits was accounted for by the vector of weights (b), which includes the causal path coefficients in the causal matrix (Λ). On the other hand, when selection was based on a primary trait, for example yield, the proposed SI increased the mean yield of the best 28 (Top 10%) genotypes to 7%.