1,721,068 research outputs found
Large litters and low losses - a successful breeding goal in piglet production?
No full textFor this analysis individual birth weights of 13'019 piglets of BHZP-line 01 and 13'794 piglets of line 03 were available within two years. Genetic parameters were estimated for individual birth weight with random effects of animal, sow and litter. Litter size, mean birth weight and standard deviation of birth weight were estimated as a trait of the sow. Estimated heritabilities of individual birth weight were h(2)=.098 for line 01 and h(2)=.147 for Line 03. Heritabilities for litter size, mean birth weight and standard deviation of birth weight were estimated with. 119,.354 und .104 in Line 01 and .114, .276 und .130 in Line 03. Genetic correlations in Line 01 und Line 03 between litter size and mean birth weight were -.254 und -.661, between litter size and standard deviation of birth weights .563 und .280. Selection only on litter size reduces mean birth weight and increases the standard deviation of birth weights. In a further step two different selection strategies in combination with three different breeding goals were compared in a selection index. It could be shown, that a combination of litter size and mean birth weight causes a high genetic gain in the trait number of piglets weaned by increasing the number of piglets born alive and low (or none) increase of lost piglets. A high economic gain per generation can be reached, without increasing the number of piglet died before weaning
Variance and covariance estimates for litter size of purebred and crossbred sows
No full textThe aim of this study was the estimation of additive genetic variances and heritabilities of purebred and crossbred sows for the trait number of piglets born alive as well as the estimation of the genetic correlation between the litter size of purebred and crossbred sows. Two data sets were available for the analysis, which were very different in their genetic and organisational structure. At the one hand there was a data set from an Australian 3-way-crossbreeding program with litter performances of 8334 Large White sows (LW), 3262 Landrace sows (LR), 10416 LW LR crossbred sows and 1733 LR LW crossbred sows. For the genetic analysis no differences were made between the two reciprocal crosses. The data sets were recorded from October 1991 until November 1994 and were produced on the same farm, which was seperated in different breeding compartments (modules). On the other hand there was a second data set from the German Bundeshybridzuchtprogramm (BHZP). Litter preformances from 211006 purebred sows (01-sows) and 26422 crossbred sows (31-sows) were available. After the pedigree was set up the data set was reduced to 57263 purebred sows and 7773 crossbred sows. The data sets were recorded from the second quarter 1991 until third quarter 1996. The litter performances of the purebred sows were recorded on 181 different farms, the litter performances of the crossbred sows on 61 different farms. The results for the Australian data set showed heritabilities for number of piglets born alive in first, second and third litters of .059, .082 and .072 for Large White, .117, .158 and .063 for Landrace and .078, .083 and .090 crossbred sows. The genetic correlations between the litter size in first and second, first and third and second and third litter were for Large White .61, .51 and .99, for Landrace .77, .88 and .88 and for crossbred sows .88, .62 and .81, respectively. The estimated heritabilities for the German data set in first, second and third litters were .070, .069 and .099 for purebred and .077, .041 and .083 for crossbred sows. The genetic correlations between the litter size in first and second, first and third and second and third litter were for purebred sows .808, .700 and .957 and for crossbred sows .665, .576 and .98, respectively. Estimated coefficients of genetic correlations between purebred and crossbred performance were in the Australian data set .99, .69 and .83 (litter 1-3) and in the German data set .80, .99 and .81 (litter 1-3), respectively. The estimated correlations of the two very different structured data sets are very high, but they are only different in the second litter and confirm each other
Large litters and low losses - a successful breeding goal in piglet production?
No full textFor this analysis individual birth weights of 13'019 piglets of BHZP-line 01 and 13'794 piglets of line 03 were available within two years. Genetic parameters were estimated for individual birth weight with random effects of animal, sow and litter. Litter size, mean birth weight and standard deviation of birth weight were estimated as a trait of the sow. Estimated heritabilities of individual birth weight were h(2)=.098 for line 01 and h(2)=.147 for Line 03. Heritabilities for litter size, mean birth weight and standard deviation of birth weight were estimated with. 119,.354 und .104 in Line 01 and .114, .276 und .130 in Line 03. Genetic correlations in Line 01 und Line 03 between litter size and mean birth weight were -.254 und -.661, between litter size and standard deviation of birth weights .563 und .280. Selection only on litter size reduces mean birth weight and increases the standard deviation of birth weights. In a further step two different selection strategies in combination with three different breeding goals were compared in a selection index. It could be shown, that a combination of litter size and mean birth weight causes a high genetic gain in the trait number of piglets weaned by increasing the number of piglets born alive and low (or none) increase of lost piglets. A high economic gain per generation can be reached, without increasing the number of piglet died before weaning
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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