Values Of Different Traits Research Articles

Assessment of growth and early maturation traits in various genotypes of muskmelon (Cucumis melo L.)

The success of any breeding programs depends on the parents chosen. Breeders select parents with high mean values as an added benefit for crossing programmes. The present investigation was carried out to evaluate the performance of muskmelon genotypes for growth and earliness attributes. Muskmelon (Cucumis melo L.) is one of the most well-known desert vegetables, belong to the Cucurbitaceae family. Thirty-three germplasm lines were collected from different regions of India. The experiment was conducted at Puthur village, Salem district, and evaluated under Randomised Block Design with three replications during February to May 2022. The findings indicate that the genotypes CM 2, CM 16, CM 11, CM 19, CM 7, CM 13 and CM 22 reported as elite genotypes were exhibited higher values for different traits like days to first female flower opening, first female flowering node, number of vines per plant, vine length (cm), sex ratio and days to first fruit harvest. As a result, the above mentioned seven genotypes are used in the hybridization programme, could be exploited to develop elite cultivars with maximum growth and earlier in flowering and harvest.

Implementation of Feed Efficiency in Iranian Holstein Breeding Program.

This study aimed to evaluate the economic impact of improving feed efficiency on breeding objectives for Iranian Holsteins. Production and economic data from seven dairy herds were used to estimate the economic values of different traits, and a meta-analysis was conducted to analyze the genetic relationships between feed efficiency and other traits. Economic weights were calculated for various traits, with mean values per cow and per year across herds estimated at USD 0.34/kg for milk yield, USD 6.93/kg for fat yield, USD 5.53/kg for protein yield, USD -1.68/kg for dry matter intake, USD -1.70/kg for residual feed intake, USD 0.47/month for productive life, and USD -2.71/day for days open. The Iranian selection index was revised to improve feed efficiency, and the feed efficiency sub-index (FE$) introduced by the Holstein Association of the United States of America was adopted to reflect Iran's economic and production systems. However, there were discrepancies between Iranian and US genetic coefficients in the sub-index, which could be attributed to differences in genetic and phenotypic parameters, as well as the economic value of each trait. More accurate estimates of economic values for each trait in FE$ could be obtained by collecting dry matter intake from Iranian herds and conducting genetic evaluations for residual feed intake.

Assessment of Genetic Diversity in Sesame (Sesamum indicum L.) for Yield and its Components

A field experiment was conducted to assess the diversity among sesame genotypes for yield and yield component traits during late kharif, 2017 (August-November) at Seed Research and Technology Centre, Rajendranagar, Hyderabad, Telangana State, India. Genetic diversity among the genotypes were estimated based on the data recorded for eight yield and yield attributing characters in 51 genotypes using Mahalanobis’s D2 statistics. The percent contribution of characters towards divergence showed that the character days to 50% flowering contributed maximum followed by seed yield plant-1, capsule length and number of seeds capsule-1. Selection of parents based on these traits would be useful to achieve a wide range of genetic variability in crop improvement programmes. The 51 genotypes were grouped into ten clusters and out of them, cluster I was the largest comprising of eighteen genotypes followed by cluster III with fifteen genotypes, cluster IV with seven genotypes, cluster II with five genotypes. The clusters viz., V, VI, VII, VIII, IX and X represented by single genotype indicating high degree of diversity among the genotypes. The maximum inter cluster distance was observed between cluster IX and cluster X (219.39) followed by cluster VII and cluster VIII (190.41). Among the ten clusters, the cluster X had highest mean value for capsule length, number of capsules plant-1, number of seeds capsule-1 and seed yield plant-1. The genotypes from these divergent clusters with favourable mean values for different traits could be used as parents in hybridization programme to get superior transgressive segregants.

Determination of Genetic Divergence in Okra Genotypes [Abelmoschus esculentus (L.) Moench

The investigation was executed at Main Experimental Station, Department of Vegetable Science, Acharya Narendra Deva University of Agriculture and Technology, Kumarganj, Ayodhya during Kharif, 2019 in Randomized Block Design with three replications comprising thirty -six genotypes of okra collected from various sources to study the existence of genetic divergence among the germplasm by Mahalanobis D2 statistics. The germplasm was grouped into six clusters. Out of six clusters, cluster 1 contained maximum number of genotypes (22) followed by cluster VI (5), cluster II (3) and cluster III (2) Cluster IV (2) cluster V (2). The minimum intra cluster diversity was found for cluster III (8.39) and maximum intra-cluster distance was exhibited for cluster I (16.95). The highest inter-cluster distance was recorded between cluster I and III (30.83) preceded by cluster III and VI (30.15) and cluster 1 and V (24.89), it suggested that the genotypes of these two (cluster I and III) clusters are genetically very dissimilar to each other. The minimum inter-cluster distance was found between cluster IV and V (13.08) followed by cluster III and IV (14.24) and cluster II and IV (14.62). Highest per cent contribution in favour of total genetic diversity was showed by total fruit yields per plant (75.08%) followed by average fruit weight (12.38). Each clusters have higher mean values for different traits and the genotypes of cluster I followed by II and VI have more mean value for traits studies and deserve to be mentioned as important clusters of genotypes which could be use for further yield improvement plan of okra.

Detection and Estimation of Genetic and Environmental Parameters through Model Fitting of Ten Bulb Yield Contributing Traits in Onion

Two onion varieties P2 and P3 and their products F1 and F2 were evaluated in summer and winter seasons for this investigation. Estimated mean values of different traits showed variations from generation to generation in each season. Values of six-parameters viz., m ̂, [d], [h], e1, gd1, gh1 for all the characters were significant except gd1 for a number of leaves, leaf length and bulb volume and also [d] for leaf length and neck length. Overall means ‘m ̂’ had the highest magnitude than [d], [h], e1, gd1 and gh1 for all the characters. Environmental parameter ‘e1’ also exhibited higher magnitude than [d], gd1 and gh1. As the values of [d] and gd1 were found to be non-significant, 4-parameter model was considered for leaf length only. Five-parameter model was considered for neck length, number of leaves and bulb volume and for rest of the traits 6-parameter model was considered. The goodness of fit test showed that 4, 5 and 6-parameter models were not adequate except bulb length and neck length. Therefore, for the development of these two traits in consideration of genotype × environment (G × E) interaction proper design and analysis needs to be done. Due to significant 2 values for other characters the situations becoming more complex as G × E interaction model is inadequate, so for their exact genetic explanation G × E model needs to be extended to include linkage and non-allelic parameters.

EVALUATION OF VARIABILITY FOR SOME COMPONENTS OF PLANT YIELD IN WINTER WHEAT

Breeders are permanently looking for effective methods for developing cultivars with improved yield. For that goal, they should include different genotypes in many cross combination to obtain the recombination of desirable genes. The biological material was composed of 11 winter wheat varieties with different origin: Alex, Boema, Ciprian, Izvor, Glosa (Romania); Laurentio, Renan (France); Josef, Galio (Austria); Akteor, Exotic Germany). The wheat varieties were evaluated regarding the following traits: plant height; spike length; spikelet number/spike; spike weight; grain number/spike and grain weight/spike. This study evaluated the diversity of 11 winter wheat varieties with different origins for some plant yield traits, and the possibilities of using these varieties in breeding programs. Higher plant stature of Josef, Galio and Laurentio varieties was associated with the highest values of spike weight, number and weight of grains/spike, and values above the mean for spike length and spikelets number/spike, respectively. The results of this research show that some varieties achieved high values for different traits of plant yield. Therefore, these varieties are successively used for further breeding programs based on diallel-crossing methods, to develop new wheat varieties. For these varieties, the spike weight has the highest and significant contribution (64,83%) to the achievement of plant yield, followed by the plant height, which contributes with 10,26 % to the variability of this trait. The spike length and grain’s number/spike had the lowest influence on plant yield. According to the high diversity between some varieties like the following Glosa-Akteor; Izvor-Josef; Izvor-Akteor; Josef-Exotic, these pairs are suitable for crossing to obtain hybrids with useful gene combinations for different yield components. Considering the highest variance for plant height and spike length, we appreciate that it is possible to identify valuable gene combinations for these traits in segregating generations.

Principal components for morphometric traits in Campolina horses.

Principal component analysis (PCA) was applied to evaluate the genetic variability and relationship between 15 morphometric traits in 91,483 Campolina horses, as well as to propose an index based on an aggregate genotype that promotes a particular selection objective. PCA was applied to the genetic (co)variance matrix among variables. After calculation of the principal components, the breeding values were estimated to obtain an index related to the component that explained most of the variation. The first principal component (PC1) accounted for 97.8% of the total additive genetic variance of the traits. PC1 contrasted animals in terms of body size (wither, back and croup heights, body length, and thoracic girth). PC1 traits showed higher heritabilities and positive and high genetic correlations. An index was obtained (HPC1) with the combination of the breeding values of different traits from PC1 which permitted the use of this index as an aggregate genotype to identify the best animals for selection. The second principal component (PC2) was much smaller and grouped traits related to head and neck morphometry, among others. These traits are commonly used for breed qualification, a fact explaining the small variation in this component. An evaluation of the effect of HPC1 on withers height in two-trait analysis was also made which provided positive genetic correlations of moderate to high magnitude (0.73-0.86), indicating that selection for this trait (important in Campolina horses) is accounted for in the index. The use of HCP1 could be considered as an important alternative to selection since it does not consider a single trait but rather a set of variables that capture body proportions.

Ad hoc breeding of a genetically depauperate landrace of noble fir (Abies procera Rehder) using SNP genotyping via high-throughput targeted sequencing

Pedigree reconstruction via DNA markers and subsequent quantitative genetic analyses in production stands of trees is an alternative to traditional forest tree breeding. The method requires variable DNA markers; preferably cost-efficient to genotype. We tested the approach in breeding for Christmas tree traits in a Danish landrace of Abies procera. Initial analysis with simple sequence repeats (SSRs) revealed a substantial reduction in genetic diversity of Danish A. procera compared with direct imports from the USA, indicating a genetic bottleneck. Due to the reduced genetic variation, the SSRs were not variable enough for pedigree reconstruction, and 145 single nucleotide polymorphisms (SNPs) were therefore identified and genotyped via high-throughput targeted sequencing. In the field, we phenotypically selected 674 superior trees, based on criteria for good Christmas trees, among 21,000 trees in three Christmas tree plantations originating from an A. procera clonal seed orchard. By SNP-genotyping and parentage analysis, pedigree was reconstructed for the selected individuals, and genetic predictions for the Christmas tree traits were estimated. A final selection of 45 trees out of the 674 genotyped, based on an index of predicted values for different traits, foresees a gain in the Christmas tree score and branch angle score of 16% and 10%, respectively. The study clearly demonstrated the benefits of pedigree reconstruction, even though mass selection seemed to give similar gain. Primarily, the possibilities to control the level of inbreeding, and to check whether the production stands, from where we select trees, actually originate from the declared and desired parent pool.

Quantifying the Relationship between Adaptive Traits and Agro-climatic Conditions

Background & Aim: Durum wheat is an economically important and regularly eaten food for billions of people in the world. In the International Center for Agriculture Research in the Dry Areas (ICARDA), genbanks are using Focused Identification of the Germplasm Strategy (FIGS) to find out and quantify relationships between agro-climatic conditions and the presence of specific traits. Hence, the study is aimed to investigate the predictive value of various types of long-term agro-climatic variables on the future values of different traits. Method: Ordinary multiple linear regression with stepwise variable selection method on the complete data set, and multiple linear regression models with predictors selected by penalized methods with mean square error cross-validation as a model selection criterion, are used to analyze 238 durum wheat landraces. Each of the models are fitted on Days to Heading and Days to Maturity response variables with 57 predictor variables, independently. Ordinary least square and weighted least square estimation methods were used. Result: Findings implied that there is high multicollinearity among the predictor variables. It is found that there are some predictors which affect positively and some others affect negatively for both Days to Heading and Days to Maturity using both ordinary and shrinkage based models. It is revealed that the prediction from the lasso based model is not that much reasonable. Furthermore, for the Days to Heading showed that there seems better prediction as their predicted value increase continuously as a function of the actual values though there is considerable variability. Conclusion: In conclusion, inferences and predictions by the ordinary MLR models are not trusted due to the presence of multicollinearity, and violation of some model assumptions. However, predictions using the models with predictors selected by the shrinkage methods may be better as the effects of the variability on these methods are minimal. Moreover, the WLS methods might give more sensible predictions than the OLS estimation methods. Better predictions were found on the Days to Heading.

Combining pedigree and genomic information to improve prediction quality: an example in sorghum

Key messageThe use of a kinship matrix integrating pedigree- and marker-based relationships optimized the performance of genomic prediction in sorghum, especially for traits of lower heritability.Selection based on genome-wide markers has become an active breeding strategy in crops. Genomic prediction models can make use of pedigree information to account for the residual polygenic effects not captured by markers. Our aim was to evaluate the impact of using pedigree and genomic information on prediction quality of breeding values for different traits in sorghum. We explored BLUP models that use weighted combinations of pedigree and genomic relationship matrices. The optimal weighting factor was empirically determined in order to maximize predictive ability after evaluating a range of candidate weights. The phenotypic data consisted of testcross evaluations of sorghum parental lines across multiple environments. All lines were genotyped, and full pedigree information was available. The performance of the best predictive combined matrix was compared to that of models fitting the component matrices independently. Model performance was assessed using cross-validation technique. Fitting a combined pedigree–genomic matrix with the optimal weight always yielded the largest increases in predictive ability and the largest reductions in prediction bias relative to the simple G-BLUP. However, the weight that optimized prediction varied across traits. The benefits of including pedigree information in the genomic model were more relevant for traits with lower heritability, such as grain yield and stay-green. Our results suggest that the combination of pedigree and genomic relatedness can be used to optimize predictions of complex traits in crops when the additive variation is not fully explained by markers.

Morphological characterization of newly introduced lettuce (Lactuca sativa L.) germplasm through principal component and regression analyses

Twenty seven newly introduced genotypes of lettuce collected from different indigenous and exotic sources were characterized with respect to economically important traits by using principle component and regression analyses. Significant differences were observed among the genotypes for all the characters under study. CGN-10944 performed best among all the genotypes for most of the traits under study. Principal component analysis indicated that the first five factors had variances of 3.88, 2.78, 1.47, 1.42 and 1.24 with 25.87%, 18.57%, 9.81%, 9.49% and 8.26% of total variation, respectively and aggregating to 72.01% of total variation. The highest positive values of different traits in different components indicated that main emphasis should be given on the gross head weight (X 2 ), polar (X 6 ) & equatorial diameter (X 7 ) and seed vigour index-I (X 12 ) & II (X 13 ) to have higher yields in lettuce. To quantify the importance of each variable in predicting yield, multiple linear regression model was developed. The coefficient of determination (R 2 ) in linear regression model revealed that 94% of total variation in yield per plot (X 15 ) was influenced by days to marketable maturity (X 1 ), gross head weight (X 2 ), heading percentage (X 4 ), seed germination (X 11 ), seed vigour index-II (X 13 ) and severity of bacterial soft rot (X 14 ). Therefore, main emphasis should be given on days to marketable maturity, gross head weight, polar & equatorial diameter, heading percentage, seed germination, seed vigour index-I & II and severity of bacterial soft rot during selection and hybridization programmes for yield improvement in lettuce.

Genetic Divergence Analysis in Rice under Irrigated Conditions

The nature and magnitude of genetic divergence were estimated in 134 rice germplasm accessions during kharif 2013 using Mahalanobis D2 statistics. The genotypes were grouped into five clusters based on Euclidean cluster analysis. The pattern of distribution of genotypes into various clusters was random and independent of geographical origin or region of adoption indicating geographical diversity and genetic diversity were not related. Cluster means indicated considerable differences in the mean values of different traits. The genotypes of cluster II and cluster III exhibited high seed yield. The highest intra-cluster distance was observed among the genotypes, in cluster IV (12.19) followed by cluster III (11.03) and cluster V (10.90) indicating existence of wide genetic divergence among genotypes. Number of filled grains/panicle contributed highest towards divergence. The relative divergence of each cluster from other clusters displaced higher order of divergence between cluster IV and V followed by clusters II and V. The hybridization involving genotypes belong to these clusters is expected to give desirable segregants in rice breeding programmes.

Combining Ability Analysis and Estimates of Heterosis for Grain Yield and Nutritional traits in Finger millet (Eleusine coracana (L.) Geartn)Combining Ability Analysis and Estimates of Heterosis for Grain Yield and Nutritional traits in Finger millet (Eleusine coracana (L.) Geartn)

Finger millet (Eleusine coracana (L.) Gaertn.) is an important subsistence cereal in parts of Africa and South Asia. Finger millet is commonly called as “nutritious millet” as the grains are superior to many cereals providing fair amount of protein, minerals and vitamins in abundance to the people. The parental values of different traits in different crosses depend on their potential and their combining ability in different combinations. The concept of general and specific combining abilities is useful to characterize the hybrids in the breeding programme and also elucidate the nature and magnitude of gene actions involved in the trait of interest. Two hybrids namely CO (Ra) 14 x PR 202 and GPU 28 x K 7 were found to be superior for grain yield and other major yield components along with the protein content based on per se performance, sca effect and standard heterosis.

Estimation and comparison of heritability and parent–offspring resemblance in dispersal probability from capture–recapture data using different methods: the Collared Flycatcher as a case study

Understanding the evolution of a trait requires analysing its genetic basis. Many studies have therefore estimated heritability values of different traits in wild populations using quantitative genetic approaches on capture–recapture data of individuals with known parentage. However, these models assume perfect individual detection probability, a hidden hypothesis that is rarely met in natural populations. To what extent ignoring imperfect detection may bias heritability estimates in wild populations needs specific investigation. We give a first insight into this question using dispersal probability in a patchy population of Collared Flycatchers Ficedula albicollis as an example. We estimate and compare heritability and parent–offspring resemblance in dispersal obtained from (1) quantitative genetic approaches (“classical” parent–offspring regressions and more recent animal models) and (2) multi-state capture–recapture models accounting for individual detection probability. Unfortunately, current capture–recapture models do not provide heritability estimates, preventing a full comparison of results between models at this stage. However, in the study population, detection probability may be expected to be lower for dispersing compared to philopatric individuals because of lower mating/breeding success and/or higher temporary emigration, making the use of capture–recapture models particularly relevant. We show significant parent–offspring resemblance and heritable component of between-patch dispersal probability in this population. Accounting for imperfect detection does however not seem to influence the observed pattern of parent–offspring resemblance in dispersal probability, although detection probability is both sensibly lower than 1 and heterogeneous among individuals according to dispersal status. We discuss the problems encountered, the information that can be derived from, and the constraints linked to, each method. To obtain unbiased heritability estimates, combining quantitative genetic and capture–recapture models is needed, which should be one of the main developments of capture–recapture models in the near future.

Evaluation of Silkworm Lines against Variations in Temperature and RH for Various Parameters of Commercial Cocoon Production

Eleven inbred silkworm lines (M-101, M-103, M-104, M-107, Pak-1, Pak-3, Pak-2, Pak-4, PFI-1, PFI-2, and S-1) were evaluated for various parameters of cocoon production under different temperature and relative humidity conditions (25±1,30±1, and35±1 °Cin combination with 55, 65, and 75% RH for three hrs during 4th and 5th instar. The experiment was laid out in factorial design with three replications. Significant variations in the performance of silkworm lines were noticed due to influence of temperature and RH treatment on 4th and 5th instar larvae. The silkworm lines performed significantly better when the larvae were reared at25±1 °Cwith 70–80% RH while almost all the silkworm lines showed poor performance at higher temperature exposures for 3 hrs. Exposures to lower humidity (55%) during larval rearing in 4th and 5th instar at different temperatures (25±1,30±1, and35±1 °C) resulted in lowering the cocoon production. The cumulative evaluation index values for different traits showed that Pak-4 (61.42) was the best line followed by M-101 (59.15), Pak-2 (56.37), Pak-3 (52.83) PFI-I (52.62), and M-107(50.03). The study clearly underlines the importance of optimization of environmental conditions during larval rearing in relation to commercial cocoon production. The investigations strongly recommend that temperature and relative humidity in the range of 25-26 °Cand 70–80%, respectively, are mandatory for excellent results of cocoon production and Pak-4, M-101, Pak-2, Pak-3, PFI-I, and M-107 were suitable for commercial rearing.

Estimates of economic values for traits of Arabic sheep in village system

A deterministic bio-economic model was used to estimate the economic values of different traits in Arabic sheep native to the Khuzestan province of Iran. In the studied system, variable costs accounted for about 98.5% of the total costs and among variable costs, feed costs had the highest proportion with 70.7%. Revenue sources included meat, wool, and manure, where meat was the most important one and formed 95.5% of total revenues. Economic value for a trait was estimated as the amount of change in the profit of system as its mean increased by one unit, while the means of other traits were constant. The most important trait in this system was litter size, followed by ewe survival, dressing percentage, and wool weight, respectively. Birth weight had a negative economic value but weight at older ages especially weaning weight and 12-month weight had positive economic values. The sensitivity of economic values of traits was investigated by changing feed and non-feed costs, meat and wool prices by ±10%. Results showed that economic values for dressing percentage and wool weight are not sensitive to change in costs. In addition, changes in marketing and management costs had no effect on the economic value for traits related to body weight in different ages. In general, the economic value for traits which showed sensitivity to the changes of costs, except ewe survival, decreased due to an increase in costs. The economic value for all traits, except birth and wool weight, changed because of a change in meat price. Increasing meat price meant a higher economic importance. Among different factors, meat price fluctuations had the most effect on the economic value of traits.

Multivariate analysis and clustering of Cuphea procumbens inbred lines

15 C. procumbens inbred lines of different eco-geographical origin maintained at National Botanical Research Institute, Lucknow, India were evaluated for seed yield and its 6 component traits to assess genetic divergence among them. The standardized mean values of different traits were subjected to principal component analysis and cluster analysis was performed based on two different clustering strategies i.e. UPGMA and Wards. Ward's method that showed relatively high cophenetic correlation coefficient and significant Wilk's Lambda was identified as the best clustering solution. The first four principal components (PC) with eigenvalues >1 contributed 91.56% of variability among the inbred. First PC was related with fruits/plant and branches/plant; second PC with yield/ plant, seeds/fruit and test weight third PC with plant height; and fourth PC with days to flowering. The genotypes were grouped into five clusters and cluster II was largest with 5 genotypes followed by clusters I, III and Clusters IV, V. Cluster IV exhibited highest mean for seed yield (14.77g) followed by cluster III (14.53g) and the former incorporated inbred lines, NBCP-53 and NBCP-58 that were highly divergent among themselves and from genotypes in other clusters. The inbred in cluster IV and cluster III with good amount of genetic divergence and superior agronomic traits were identified as promising inbred to develop superior recombinants with desirable agronomic traits.

Robustness of Selection Indices in Murrah Buffaloes

Data pertaining to first lactation records of 316 Murrah buffaloes, progeny of 47 sires, maintained at NDRI Farm for a period of 18 years were analysed to construct selection indices and to examine their robustness by changing the relative economic values of different economic traits. A total of 120 selection indices were constructed for three sets of relative economic values ( 40 for each set) considering different combinations of seven first lactation traits viz. age at first calving (AFC), first lactation 305 day or less milk yield (FLMY), first lactation length (FLL), first calving interval (FCI), milk yield per day of first lactation length (MY/FLL), milk yield per day of first calving interval (MY/FCI) and milk yield per day age at second calving (MY/ASC). The three sets of relative economic values were based on economic values of different traits, 1% standard deviation of different traits and regression of different traits on FLMY. The 'optimum' indices for the first two sets had five traits each namely AFC, FLMY, FLL, FCI and MY/ASC giving improvement in aggregate genotype of Rupees 269.11 and Rs. 174.88, respectively. The accuracy of selection from both indices was 70.79 and 69.39%, respectively. The 'best' selection from the third set of data again had five traits (AFC, FLMY, FLL, FCI and MY/FLL) giving genetic gain of Rs. 124.16 and accuracy of selection of 71.81%. The critcal levels or break-even points for FLMY for varying levels of AFC and FCI estimated from the optimum index suggested the need of enhancement of present production level of the herd or reduction of AFC or FCI. It was concluded that economic values of various first lactation traits were the most appropriate to construct selection indices as compared to other criteria of assigning relative economic weights in Murrah buffaloes.

Derivation of economic values for veal, beef and milk production traits using profit equations

In this study profit equations for milk, veal and beef bull production were developed to obtain economic values for different traits. Veal and beef production were described in terms of fat and protein daily gain. For categorical traits, dystocia and carcass quality traits, economic values were derived using an underlying continuous scale. Parameters in the profit equations were chosen to reflect the Dutch situation for Black and White cows, but they can be changed to fit other breeds and production circumstances. The consequences of altering beef production characteristics on growth and mature weight in dairy cows are discussed in the paper but not included in the economic weights. Without product output restrictions, economic values for milk carrier, fat and protein yield were Dfl −0.082, 5.70 and 12.85 per kg, respectively. Under a multiple restriction of milk yield and fat content on herd level, economic weighhs were Dfl −0.328, 1.04 and 12.60 per kg, respectively. The economic weight of calf mortality was Dfl −3.83 per % and the marginal costs of dystocia were Dfl 59.75 per cow per unit on the underlying liability scale. The economic value for birth weight was Dfl 5.40 per kg for dairy farmers, Dfl −4.59 per kg for veal producers and Dfl −6.91 per kg for beef producers. For veal calf producers, economic weights were Dfl 0.45 for daily gain (g/day ), 25.67 for dressing percentage (%), −14.22 for mortality (%), 26.48 for fleshiness, 0.06 for fat covering and 37.44 for meat colour in veal calves. For beef bull producers, economic values were: Dfl 0.59 for daily gain, 37.35 for dressing percentage, −18.20 for mortality, 81.07 for fleshiness and 7.39 for fat covering. Sensitivity analysis of economic weights to changes in price and production circumstances showed that future economic values might change dependent on level of output and prices.