Economic Weights Research Articles

Identification of Disease Resistance Parents and Genome-Wide Association Mapping of Resistance in Spring Wheat.

The likelihood of success in developing modern cultivars depend on multiple factors, including the identification of suitable parents to initiate new crosses, and characterizations of genomic regions associated with target traits. The objectives of the present study were to (a) determine the best economic weights of four major wheat diseases (leaf spot, common bunt, leaf rust, and stripe rust) and grain yield for multi-trait restrictive linear phenotypic selection index (RLPSI), (b) select the top 10% cultivars and lines (hereafter referred as genotypes) with better resistance to combinations of the four diseases and acceptable grain yield as potential parents, and (c) map genomic regions associated with resistance to each disease using genome-wide association study (GWAS). A diversity panel of 196 spring wheat genotypes was evaluated for their reaction to stripe rust at eight environments, leaf rust at four environments, leaf spot at three environments, common bunt at two environments, and grain yield at five environments. The panel was genotyped with the Wheat 90K SNP array and a few KASP SNPs of which we used 23,342 markers for statistical analyses. The RLPSI analysis performed by restricting the expected genetic gain for yield displayed significant (p < 0.05) differences among the 3125 economic weights. Using the best four economic weights, a subset of 22 of the 196 genotypes were selected as potential parents with resistance to the four diseases and acceptable grain yield. GWAS identified 37 genomic regions, which included 12 for common bunt, 13 for leaf rust, 5 for stripe rust, and 7 for leaf spot. Each genomic region explained from 6.6 to 16.9% and together accounted for 39.4% of the stripe rust, 49.1% of the leaf spot, 94.0% of the leaf rust, and 97.9% of the common bunt phenotypic variance combined across all environments. Results from this study provide valuable information for wheat breeders selecting parental combinations for new crosses to develop improved germplasm with enhanced resistance to the four diseases as well as the physical positions of genomic regions that confer resistance, which facilitates direct comparisons for independent mapping studies in the future.

Selection of dam breeds under stable and declined conditions

Reproductive selection index of two dam pig breeds was established five years ago to enhance the reproductive ability of sows. Since then, positive genetic progress in the population and some economic disorders (e.g. the input and output prices disproportion) appeared in the swine sector. The study aimed to revise index according to the current circumstances and further ensure the desired gain. In three index variants, the current, optimal, and adjusted trait proportion was assessed. Economic weights (EWs) of the breeding objective traits were applied in two alternatives to evaluate the index for future stable and deteriorated conditions. Under the current index construction and stable EWs, the favourable selection gain in piglets born alive (NBA) and slight extension of farrowing interval (FI) is indicated. The optimal index construction would result in a favourable gain of both traits in one breed. The adjusted index maintained the increasing litter size equal to the current index and achieved favourable gain in FI in both breeds. The same was true for deteriorated economic conditions except for the optimised index variant, where expected higher genetic progress in one breed. Nevertheless, this genetic gain was insufficient to compensate the declined EW of traits, and the overall financial benefit was almost half of those in stable conditions. For both alternatives of evaluated economic conditions, the current index should be revised in terms of a slightly higher proportion of FI to reach favourable genetic gain in both breeding goals.

​Construction of Selection Indices by using Different Economic Coefficients in Indian Bean [Lablab purpureus (L.) Sweet

Background: Most of the plant characters are governed by polygenes and greatly influenced by environmental conditions. The progress of breeding is conditioned by the magnitude, nature and interrelationship of genotypic and non-genotypic variation. In most of the crop improvement programs, the improvement of one trait may cause advancement or deterioration in associated traits serves to emphasize the need for simultaneous consideration of all traits which determine the economic value of a genotype. Methods: The present investigation was undertaken for Indian bean [Lablab purpureus (L.) Sweet] to construct efficient selection indices for selecting best progenies. The experiment was conducted with 55 progenies with checks GNIB-21 and GNIB-22 in randomized block design (RBD) with 3 replications. An attempt was made to build a selection index by taking 3 different type of economic weights viz. equal weight [W1], genotypic correlation coefficients [W2] and genotypic path coefficients (Direct effect) [W3]. Result: It has been seen that genetic gain of Indian bean of selected progenies observed higher with equal weight method as compared to weight assigned method with genotypic correlation coefficients and genotypic path coefficients (Direct effect). It has been concluded that the selection of progeny based on seed yield per plant, plant height, pod width and days to maturity provide higher genetic gain in Indian bean.

Defining smallholders' breeding objectives for common Tigray highland sheep in Northern Ethiopia.

A sound breeding objective is a basis for genetic improvement in the overall economic merit of farm animals. This study aimed to define smallholders' sheep breeding objectives using a conjoint-based choice experiment and bio-economic model. Multinomial logistic regression analysis showed differences (p < 0.001) among the derived weights allocated by farmers to body size, twining rate, mothering ability, libido, tail type, colour and lambing interval which formed the high priority traits. The likelihood values of farmer's top three preferred traits for ram were body size (0.659 ± 0.009), tail type (0.325 ± 0.016) and libido (0.247 ± 0.016) while body size (0.459 ± 0.010), twining rate (0.313 ± 0.010) and mothering ability (0.261 ± 0.010) were more preferred traits for selection of breeding ewes. Conjoint-based choice experiment and bio-economic model indicated that live body weight at 6 months of age, twining rate (litter size) and mothering ability (preweaning lamb survival) were the most economically important traits of the breeding ewes. A genetic improvement by one genetic standard deviation (σa ) in these traits resulted in a profit of Ethiopian Birr 36.03-60.47/ewe/year. A fair correlation (r=0.63) was observed between farmers' traits preference (conjoint-based choice card experiment) and the estimated economic value of traits indicating a good relationship between farmers' preferences for traits and economic values of the traits. This would indicate that weighting traits in selection indexes with farmers' trait selection using a conjoint-based choice experiment would direct genetic improvement towards desired profitability. Moreover, the fair correspondence between the two methods suggests that bio-economic modelling, if designed properly considering farmers' concerns, could be used to reflect farmers' breeding objectives. Therefore, for reasonable genetic progress and sheep flock profitability, more attention should be given to litter size, preweaning lamb survival and body weight at 6 months of age as they are preferred by farmers and their economic weights. Further, research on the modalities for complementary use of the two methods to define breeding objectives under smallholder conditions is warranted.

NATO defense demand, free riding, and the Russo-Ukrainian war in 2022

The article applies the economic theory of alliances to uncover military expenditure burden sharing in the North Atlantic Treaty Organization (NATO) during 1991–2020, prior to Russia’s invasion of Ukraine in February 2022. In so doing, our analysis accounts for the relative locations of NATO allies through various spatial or economic weights applied to the allies’ defense spending. Such weights include NATO membership status, contiguity, US power projection, inverse distance between members’ capitals, economic trade, and contiguity to Russia. In the post-Cold War era, we uncover allies’ free riding on the aggregate military expenditure of other allies. Free riding also included reliance on the defense spending of NATO allies in proximity to Russia. Surprisingly, NATO allies reduced their defense spending as Russia increased its defense spending. The pattern of free riding and lack of response to heightened Russian defense spending likely encouraged the Russian invasion as NATO appeared divided.

Identification of Spring Wheat with Superior Agronomic Performance under Contrasting Nitrogen Managements Using Linear Phenotypic Selection Indices.

Both the Linear Phenotypic Selection Index (LPSI) and the Restrictive Linear Phenotypic Selection Index (RLPSI) have been widely used to select parents and progenies, but the effect of economic weights on the selection parameters (the expected genetic gain, response to selection, and the correlation between the indices and genetic merits) have not been investigated in detail. Here, we (i) assessed combinations of 2304 economic weights using four traits (maturity, plant height, grain yield and grain protein content) recorded under four organically (low nitrogen) and five conventionally (high nitrogen) managed environments, (ii) compared single-trait and multi-trait selection indices (LPSI vs. RLPSI by imposing restrictions to the expected genetic gain of either yield or grain protein content), and (iii) selected a subset of about 10% spring wheat cultivars that performed very well under organic and/or conventional management systems. The multi-trait selection indices, with and without imposing restrictions, were superior to single trait selection. However, the selection parameters differed quite a lot depending on the economic weights, which suggests the need for optimizing the weights. Twenty-two of the 196 cultivars that showed superior performance under organic and/or conventional management systems were consistently selected using all five of the selected economic weights, and at least two of the selection scenarios. The selected cultivars belonged to the Canada Western Red Spring (16 cultivars), the Canada Northern Hard Red (3), and the Canada Prairie Spring Red (3), and required 83–93 days to maturity, were 72–100 cm tall, and produced from 4.0 to 6.2 t ha−1 grain yield with 14.6–17.7% GPC. The selected cultivars would be highly useful, not only as potential trait donors for breeding under an organic management system, but also for other studies, including nitrogen use efficiency.

Spatiotemporal characteristics and influencing factor analysis of universities' technology transfer level in China: The perspective of innovation ecosystems.

Universities are important parts of innovation ecosystems, and university technology transfer (UTT), which aims for the sustainable commercialization of sci-tech achievements, is closely related to other actors in the ecosystem. Based on the panel data of 31 provinces in mainland China, this paper empirically analyzes the spatiotemporal distribution characteristics of UTT levels from 2011 to 2019 and estimates the influencing factors using the spatial Durbin model (SDM) with an economic spatial weighting matrix from the perspective of innovation ecosystems. The results are presented as follows: (1) Although the overall level of UTT in China is low, it shows an upward trend in most provinces. In addition, the interprovincial gap is obvious, forming a ladder distribution of UTT levels increasing from west to east. (2) There is a significant spatial autocorrelation between UTT levels in the provinces. (3) Industry, economy, and informatization play significant roles in promoting UTT, while financial institutes and openness have significant inhibitory effects. The economy has a significant spatial spillover effect on UTT, while government, industry and informatization have a significant inhibitory effect on UTT in neighboring regions. (4) The direct and indirect effects of influencing factors in the Eastern Region and other regions show significant spatial heterogeneity.

An Exploratory Study of Crime: Examining Lived Experiences of Crime through Socioeconomic, Demographic, and Physical Characteristics

Debates in urban social research indicate that one of the most significant problems facing cities of the global south is the dilemma of crime. This study explores the research question: what is the level of influence of economic deprivation and residential mobility weights on criminal activities within vulnerable neighborhoods in urban centres? This research focuses on the urban social structural theory of social disorganization, to investigate how socioeconomic, demographic, and physical characteristics affect criminal behaviour. The study adopted a qualitative research approach that is cross-sectional. With the use of volunteer self-selection sampling techniques, in-depth interviews were conducted with heads of households via a semi-structured interview guide. The data were analyzed using thematic analysis. The study found that sociological factors such as economic deprivation and socioeconomic inequality lead to the gradual integration of delinquency in cities. The findings of this research build on the existing theory of social disorganization. To ensure safety, residents’ economic status must be standardized by supporting the provision of more regulated informal sector opportunities and activities for active engagement in supervising and controlling youth behaviour.

Bio-economic models for deriving economic values for cattle: a review

Abstract. Bio-economic models for deriving economic weights in livestock have a significant development in recent years providing integrated assessment of biological and economic parameters of production systems and possibilities for achieving economic sustainability through inclusion in the selection index. Economic weights (EW) of traits have been calculated for different species of farm animals in the years. However, this review focuses on large ruminant aiming to summarize studies on calculation of economic values for dairy, beef and dual-purpose cattle. A method of research selection was used according to the productive direction (for milk, meat and dual-purpose), as well as according to the studied traits. In conclusion, it could be summarized that with regard to breeding objectives, economic weights of breeding traits need to be recalculated at certain time-periods and redefined in order to be relevant to the current market situations. Recently, there has been a tendency for functional traits to have an increasing economic influence and some of them should be included in the breeding goal. Moreover, the increased interest among customers in animal welfare and quality of dairy farm products will probably lead to the incorporation of health traits as clinical mastitis incidence and somatic cells score in the breeding objective. It is possible as well the relative importance of feed efficiency traits to increase in the future due to increasing requirements to mitigate the environmental impact of production systems.

Selection indexes and economic weights applied to runner-peanut breeding

ABSTRACT Runner peanuts are known for their high pod yields, but are late to flowering and pod maturation, and the optimal combination of these traits with pod yield is widely desired for peanut improvement. Selection indexes are useful tools for crop breeding. In this study, seven selection indexes combined with economic weights were used in a peanut population to estimate the superior and balanced genetic gains. Eleven runner genotypes were grown in three environments in the Northeast region of Brazil under a randomized block design with five replicates. The following indices were used: Smith and Hazel, Pesek and Baker, Williams, Elston, Subandi, Cruz, and Mulamba &amp; Mock, in combination with the following economic weights: weight 1 for all evaluated traits, primary and secondary traits, genetic variation coefficient, genetic standard deviation, and b coefficient, obtained via multivariate regression. Although the population is genetically uniform, statistical differences were found, indicating sufficient genetic variability to generate selection progress. The combinations involving earliness traits were not satisfactory for production gains. The index based on the Mulamba &amp; Mock rankings combined with weight 1 for all traits proved the optimal combination, as indicated by the most balanced gains. The cultivars Florunner, Cavalo, LGoPE-06, and LViPE-06 are promising germplasm for ensuring satisfactory selection gains based on production means and high heritability of the most evaluated traits.

Breeding objectives for dairy cattle under low, medium and high production systems in the tropics

A deterministic bio-economic model was developed to estimate economic weights for genetic improvement of lactation milk yield, fat yield, age at first calving, calving interval, mature weight and survival under low, medium and high production systems in the Tropics. Input parameters were obtained from dairy production systems in Kenya which has a tropical environment. The highest proportion of revenue is from the sale of milk followed by sale of heifers, cull cows and sale of male calves under all production systems. On the other hand, feed cost is the most important production cost followed by labour, marketing, reproduction and health costs, respectively. Economic values for the six traits were derived from a profit equation using revenue and production costs per cow per year. The economic values were then discounted using diffusion coefficients which account for differences between traits in the time when the improvement is expressed. Economic weights were robust to changes in input and output prices, changes in feeding strategies, and changes in milk and surplus heifer marketing strategies. Genetic standard deviations were multiplied by economic values to standardise the economic value of traits and to compare their potential for economic response. When expressed as proportion of their sum, these relative economic weights under the low, medium and high production systems for lactation milk yield were 51.36, 59.79 and 63.98%; for fat yield 4.50, 10.69 and 9.05%; for age at first calving 3.16, 2.66 and 0.55%; for calving interval 33.59, 19.88 and 20.05%; for mature weight 1.55, 1.34 and 1.19% and for survival rate 5.84, 5.64 and 5.18%, respectively. The predicted responses followed the same pattern as the relative economic weights. This shows that milk yield and calving interval were most important in all production systems but the value of response for traits differed between production systems with more emphasis on milk yield and less on calving interval in the high production systems. Moderate correlations were estimated between the breeding objective for the low, medium and high production systems. To maximise response in the overall breeding objective, different selection criteria are required for the three production systems.

Impact of financial development and renewable energy consumption on environmental sustainability: a spatial analysis in CEMAC countries

This research aims to examine the impact of financial development and renewable energy consumption on CO2 emissions in CEMAC for the period 1990-2018. The study employs spatial analysis approach. As previous investigations have overlooked the effects of the spatial interactions in demonstrating environmental sustainability across nations, this paper gives the first comprehensive spatial analysis of CO2 emissions among countries. To eliminate possible bias and inefficiency in estimated coefficients, the spatial autoregressive model is used to account for both geographical dependency and individual heterogeneity. The results revealed that under economic distance weights, the values of the spatial lag coefficients of financial development (FD), foreign direct investment (FDI), gross domestic product (GDP), and renewable energy consumption depict negative and statistical significance effects regarding spatial fixed effects in the SDM model, while trade openness (TO) shows a negative and insignificant impact. Other decomposition effects results show that FD had both direct and indirect significantly negative effects on environmental sustainability in CEMAC. This indicates that FD has a significant negative effect on CO2 emissions in both the local country and its adjoining countries. On average, a unit change in FD in each country and its neighboring countries would reduce dioxide carbon by 0.071 and 0.066, respectively, and that of the whole region would be 0.137 units, meaning that environmental sustainability will improve. However, GDP recorded significantly positive direct and indirect effects on environmental sustainability. The direct and indirect effects of FDI on CO2 in both the local and neighboring countries were negative but statistically insignificant. On the other hand, the direct and indirect effects of TO on environmental sustainability were positive and statistically significant. Along with significant and statistical effects of financial development, GDP, FDI, renewable energy consumption, and TO, the findings reveal the presence of a positive spatial dependency of CO2 emissions in CEMAC. This implies that policymakers in CEMAC countries lean to rely on their environmental sustainability decisions to assign financial and investments to that of neighboring nations. Furthermore, the findings indicate that adjacent countries' FD and REC have a considerable impact on a country's CO2 emissions. Our findings offer significant political implications, implying that financial development and renewable energy consumption should be strengthened to meet environmental sustainability goals.

Selection strategies for identifying fast cooking, mineral-biofortified bean cultivars with high agronomic performance

Simultaneous selection for various agronomic traits, cooking time and mineral concentration are major challenges for common-bean (Phaseolus vulgaris L.) breeding programs. The authors of this study proposed to analyze genetic gain estimates obtained by direct and indirect selection using selection indices and economic weights for 13 traits, and to determine the most efficient selection strategy for the simultaneous selection of fast cooking, mineral-biofortified common bean cultivars with high agronomic performance. For this purpose, three experiments were carried out in different growing seasons to evaluate 49 common bean cultivars of different grain types. Agronomic performance was evaluated based on six traits; cooking time was determined using a Mattson cooker; and the concentration of six minerals was analyzed in samples of raw grains. Significant genotype × environment interaction or genotype effects were observed for all traits, indicating the existence of genetic variability. Direct selection resulted in high genetic gain estimates for individual traits, but caused undesirable changes in one or more of the traits under selection. The classic, base, desired-gains and rank-sum selection indices tested with six economic weights do not provide genetic gain estimates favorable to the selection of all traits. The multiplicative index is the best selection strategy for use in the breeding program when aiming at the simultaneous selection of fast cooking, mineral-biofortified common bean cultivars with high agronomic performance.

Breeding goals for conservation and active Polish dairy cattle breeds derived with a bio-economic model

The aim of the study was to calculate economic values (EV) of breeding traits (production, reproduction, direct health, calving and survival traits) for the Polish dairy cattle breeds Polish Holstein (PH) and Polish Red (PR). EV are key elements in setting up economically based breeding goals for dairy cattle and they are crucial for optimizing breeding schemes. For deriving EV, a stochastic bio-economic model was used, which estimates EVs based on population-specific biological and economic characteristics. Because the bio-economic model considers correlations between different traits, a multiple regression approach was used to correct for any double counting of effects. The results showed that EVs for direct health traits and fertility differed between breeds. The biggest difference was observed for lameness (PH -1.44 €, PR -1.09 € per cow-year), ketosis (PH -0.94 €, PR -0.58 € per cow-year) and for cow conception rate (PH 1.94 €, PR 0.84 € per cow-year). The relative economic weights for production traits were estimated as 37.00 % (PH) and 34.30 % for (PR) and for fertility traits 15.10 % (PH and for 16.10 % (PR). Major economic differences between the relative weights were observed for cow mortality (22.70 % PH, 16.90 % PR). The results of our study showed that breeding the PH brings higher economic profit than breeding the PR. Total income per PR cow was equal to 1,623 € and for PH 2,970 €.

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.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.

Strategy of multiple selection indices for discrimination of potential genotypes and associated traits for yield improvement in pearl millet [Pennisetum glaucum (L.) R.Br.

A study was conducted with 31 genotypes of pearl millet to identify the potential through correlation, path analysis and discriminant function analysis for yield and yield attributing traits at the Department of Millets, Tamil Nadu Agricultural University, Coimbatore during Kharif 2019. The top ranking genotypes for single plant yield was Cumbu 2, Kizikuppam local, PT6706, PT6582 and PT6581. High PCV and GCV were recorded for harvest index, single plant yield, biological yield, thousand grain weight, the number of productive tillers and total grains per panicle. The path coefficient analysis revealed that harvest index, biological yield, panicle length and flag leaf length showed a positive high direct effect on grain yield per plant, which can be utilized for the formulation of selection indices. The discriminant function analysis revealed that the maximum genetic gain for grain yield per plant can be obtained by selecting the traits like leaf sheath length, leaf length, flag leaf length, flag leaf width, the number of nodes, panicle length, the number of productive tillers, thousand grain weight, biological yield, harvest index and single plant yield in combination when path direct effect was used as economic weights. Selection criterion score values showed that the genotypes such as Cumbu 2, Kizikuppam local, Nattu Cumbu, PT6705, PT6580, PT6706, Cumbu 1 and PT6067 have outperformed others and can be utilized for further breeding programmes. Key words: Genetic variability, Path correlation, Discriminant function, Selection index, Pearl millet

Equality and Equity in Emerging Multilateral Financial Institutions: The Case of the BRICS Institutions

AbstractThe New Development Bank (NDB) and the BRICS Contingent Reserve Arrangement (CRA) were built by Brazil, Russia, India, China, and South Africa (the BRICS countries) in response to the ‘disappointing’ Bretton Woods Institutions, including the World Bank and the International Monetary Fund (IMF). The main difference between the Bretton Woods Institutions and the BRICS institutions is that the latter adopts an equal‐weight system instead of a weighted voting system in the NDB (all five BRICS countries have equal shares and voting weights regardless of the major differences in their economic weights) and uses consensus instead of majority voting rules to make decisions regarding critical issues in the CRA. In fact, both the equal‐weight system and consensus rule are unprecedented in the history of multilateral financial institutions. The World Bank, the IMF, the Asian Development Bank and even the Asian Infrastructure Investment Bank (AIIB) all adopt weighted voting systems and majority voting rules. We explain why the BRICS countries adopt these unprecedented designs through precise power measurements and carefully designed experiments. First, we measure the voting power of each member of the BRICS’ NDB and CRA under the current decision‐making systems, using this information as a control group. Then, we remeasure the voting power of each member of the NDB under the assumption that their shares and voting weights are allocated according to their economic weights; additionally, we remeasure the voting power of each country of the CRA under the assumption that majority rules are adopted when decisions are being made on critical issues. Moreover, we establish evaluation indices of power equality and power equity based on classic and variant Gini coefficients and Lorenz curves and use them to assess and compare the power structures of the BRICS’ NDB and CRA in the contexts of different voting weight reallocations and different voting rules redesigns. We use these indices to precisely analyse whether the power structures of the BRICS institutions become more equable or equitable in the examined contexts and to investigate the relationship between equality and equity in this setting.

Estimation of the economic efficiency of Lacaune sheep farms, based on theoretical bio-economic models

Abstract. The aim of the present study was to develop theoretical bio-economic models of Lacaune sheep farms and establish their economic efficiency. Based on three main criteria, 15 options were considered and analyzed. Data were processed using the program EWSH2 as a part of ECOWEIGHT Package for calculating economic weights in livestock. Revenues from sales, variable costs, gross margin and profitability before and after subsidies and per ewe were calculated. It was found that raising sheep of the high productive Lacaune breed could generate profit and provide profitability for the studied models of farms, regardless of the level of selection, type of production system, flock size and even the amount of subsidies. Nucleus farms reported the largest gross margin, followed by the basic and commercial farms. Profitability without subsidies showed the highest values for the nucleus flocks of 1000 ewes – 24.24% when adopting semi-intensive production system and 23.14% for the intensive one. With the addition of subsidies, nucleus and basic farms of 1000 ewes were considered the most profitable with 40% and 37.37%, as for both options the semi-intensive conditions were preferable. A tendency for the values of the studied indicators to grow with the increase in the number of ewes in the flocks was observed, as only for the variable costs it was reversed. Due to the lack of studies on economic efficiency of Lacaune sheep farms in Bulgaria, an additional detailed research, based on real data, is advisable to be conducted.

Converting multi-trait breeding objectives into operative selection indexes to ensure genetic gains in low-input sheep and goat breeding programmes

Small ruminant breeding programmes in low-input production systems are best organised at the community level. Participant farmers have to agree on goal traits and their relative importance. When BLUP breeding values of goal traits are not available in time, appropriate selection indexes can be used to aid visual selection. Taking Ethiopian Abergelle goat and Bonga sheep community-based breeding programmes (CBBPs) as an example, breeding objective functions were defined and selection indexes were constructed and evaluated. Breeding goals for Abergelle goats included early sale weight, survival and milk production. Breeding goals for Bonga included the number of offspring born, sale weight and survival. Economic weights of objective traits can be used in several ways depending on measured traits and the reliability of their genetic parameters. Selection indexes included combinations of objective traits measured on candidates and their dams and situations when Abergelle communities prefer to restrict genetic changes in number of offspring born or adult weight and when Bonga communities prefer to restrict changes in adult weight. Genetic and economic gains were evaluated as well as sensitivity to feed cost assumptions and to repeated dam records. After independent culling on preponderant traits such as coat colour and horn/tail type, sires in Abergelle goat community breeding programmes should be selected on indexes including at least own early live weight and their dams average milk production records. Sires for Bonga sheep programmes should be selected on own early live weight and desirably also on their dam’s number of offspring born. Sensitivity to feed cost assumptions was negligible but repeated measurements of dam records improved index accuracies considerably. Restricting genetic changes in number of offspring born or adult weight is not recommended.

Index selection can improve the selection efficiency in a rice recurrent selection population

To attain success with selection process, the breeders need to understand the genetic variability into each population developed by breeding program. In this purpose, breeders need to estimate the variance components and genetic and phenotypic parameters. Besides, they need to have the ability to select simultaneously genetically top progenies for multiple traits. This study used a field trial, with a panel of 198 S0:2 lowland rice progenies, evaluated in three environments during two years in order to: (i) estimate genetic parameters for different traits in a rice breeding population, (ii) evaluate the impact of direct selection and selection performed through three selection indices in a rice population developed by recurrent selection, and (iii) compare three selection indices using different economic weights with direct and indirect selection. Significant genetic variation was found among progenies for: grain yield, plant height, days to flowering, panicle blast, leaf scald and grain discoloration. The direct selection provided high gains for single trait selection, but this method may results in undesirable changes in related traits. Thus, between the evaluated indices and in comparison, to indirect selection the Mulamba and Mock index provided simultaneously greater gains for all the evaluated traits. Furthermore, we found that when the random weights and $$b$$ -variation index were used as economic weight, it was found lower gains or no gains, showing that the gains attained with Smith and Hazel and Tai indices were linked to economic weights used.