93 research outputs found

    Options for selecting dairy cattle for milk coagulation ability

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    v2008okDiss.: Helsinki : Helsingin yliopisto, 200

    Lypsylehmien maidon juoksettumiskyvyn jalostuskeinot

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    Lypsylehmien maidon juoksettumiskyvyn jalostuskeinot Väitöskirjassa tutkittiin lypsylehmien maidon juustonvalmistuslaadun parantamista jalostusvalinnan avulla. Tutkimusaihe on tärkeä, sillä yhä suurempi osa maidosta käytetään juustonvalmistukseen. Tutkimuksen kohteena oli maidon juoksettumiskyky, sillä se on yksi keskeisistä juustomäärään vaikuttavista tekijöistä. Maidon juoksettumiskyky vaihteli huomattavasti lehmien, sonnien, karjojen, rotujen ja lypsykauden vaiheiden välillä. Vaikka tankkimaidon juoksettumiskyvyssä olikin suuria eroja karjoittain, karja selitti vain pienen osan juoksettumiskyvyn kokonaisvaihtelusta. Todennäköisesti perinnölliset erot lehmien välillä selittävät suurimman osan karjojen tankkimaitojen juoksettumiskyvyssä havaituista eroista. Hyvä hoito ja ruokinta vähensivät kuitenkin jossain määrin huonosti juoksettuvien tankkimaitojen osuutta karjoissa. Holstein-friisiläiset lehmät olivat juoksettumiskyvyltään ayrshire-rotuisia lehmiä parempia. Huono juoksettuminen ja juoksettumattomuus oli vain vähäinen ongelma holstein-friisiläisillä (10 %), kun taas kolmannes ayrshire-lehmistä tuotti huonosti juoksettuvaa tai juoksettumatonta maitoa. Maitoa sanotaan huonosti juoksettuvaksi silloin, kun juustomassa ei ole riittävän kiinteää leikattavaksi puolen tunnin kuluttua juoksetteen lisäyksestä. Juoksettumattomaksi määriteltävä maito ei saostu lainkaan puolen tunnin aikana ja on siksi erittäin huonoa raaka-ainetta juustomeijereille. Noin 40 % lehmien välisistä eroista maidon juoksettumiskyvyssä selittyi perinnöllisillä tekijöillä. Juoksettumiskykyä voikin sanoa hyvin periytyväksi ominaisuudeksi. Kolme mittauskertaa lehmää kohti riittää varsin hyvin lehmän maidon keskimääräisen juoksettumiskyvyn arvioimiseen. Tällä hetkellä juoksettumiskyvyn suoran jalostamisen ongelmana on kuitenkin automatisoidun, laajamittaiseen käyttöön soveltuvan mittalaitteen puute. Tämän takia väitöskirjassa tutkittiin mahdollisuuksia jalostaa maidon juoksettumiskykyä epäsuorasti, jonkin toisen ominaisuuden kautta. Tällaisen ominaisuuden pitää olla kyllin voimakkaasti perinnöllisesti kytkeytynyt juoksettumiskykyyn, jotta jalostus olisi mahdollista sen avulla. Tutkittavat ominaisuudet olivat sonnien kokonaisjalostusarvossa jo mukana olevat maitotuotos ja utareterveyteen liittyvät ominaisuudet sekä kokonaisjalostusarvoon kuulumattomat maidon valkuais- ja kaseiinipitoisuus sekä maidon pH. Väitöskirjassa tutkittiin myös mahdollisuuksia ns. merkkiavusteiseen valintaan tutkimalla maidon juoksettumattomuuden perinnöllisyyttä ja kartoittamalla siihen liittyvät kromosomialueet. Tutkimuksen tulosten perusteella lehmien utareterveyden jalostaminen parantaa jonkin verran myös maidon juoksettumiskykyä sekä vähentää juoksettumattomuutta ayrshire-rotuisilla lehmillä. Lehmien maitotuotos ja maidon juoksettumiskyky sekä juoksettumattomuus ovat sen sijaan perinnöllisesti toisistaan riippumattomia ominaisuuksia. Myöskin maidon valkuais- ja kaseiinipitoisuuden perinnöllinen yhteys juoksettumiskykyyn oli likimain nolla. Maidon pH:n ja juoksettumiskyvyn välillä oli melko voimakas perinnöllinen yhteys, joten maidon pH:n jalostaminen parantaisi myös maidon juoksettumiskykyä. Todennäköisesti sen jalostaminen ei kuitenkaan vähentäisi juoksettumatonta maitoa tuottavien lehmien määrää. Koska maidon juoksettumattomuus on niin yleinen ongelma suomalaisilla ayrshire-lehmillä, väitöksessä selvitettiin tarkemmin ilmiön taustoja. Kaikissa kolmessa tutkimusaineistoissa noin 10 % ayrshire-lehmistä tuotti juoksettumatonta maitoa. Kahden vuoden kuukausittaisen seurannan aikana osa lehmistä tuotti juoksettumatonta maitoa lähes joka mittauskerralla. Maidon juoksettumattomuus oli yhteydessä lypsykauden vaiheeseen, mutta mikään ympäristötekijöistä ei pystynyt täysin selittämään sitä. Sen sijaan viitteet sen periytyvyydestä vahvistuivat tutkimusten edetessä. Lopuksi tutkimusryhmä onnistui kartoittamaan juoksettumattomuutta aiheuttavat kromosomialueet kromosomeihin 2 ja 18, lähelle DNA-merkkejä BMS1126 ja BMS1355. Tulosten perusteella maidon juoksettumattomuus ei ole yhteydessä maidon juoksettumistapahtumassa keskeisiin kaseiinigeeneihin. Sen sijaan on mahdollista, että juoksettumattomuusongelman aiheuttavat kaseiinigeenien syntetisoinnin jälkeisessä muokkauksessa tapahtuvat virheet. Asia vaatii kuitenkin perusteellista tutkimista. Väitöksen tulosten perusteella maidon juoksettumattomuusgeeniä kantavien eläinten karsiminen jalostuseläinten joukosta olisi tehokkain tapa jalostaa maidon juoksettumiskykyä suomalaisessa lypsykarjapopulaatiossa.The main objective of this thesis was to evaluate means of selecting dairy cattle for milk coagulation ability (MCA) to improve milk quality for cheese production. The possibilities for direct selection were examined by obtaining sufficiently reliable heritability and repeatability estimates for milk coagulation traits; estimates obtained in earlier studies have been based on fairly small data sets. In addition, possibilities for indirect selection and marker assisted selection for MCA were considered by obtaining sufficiently reliable estimates of genetic correlations between milk coagulation and production and quality traits, and by studying the non-coagulation of milk and associated factors. The effect of non-genetic factors on MCA and the breed differences between Finnish Ayrshire and Holstein-Friesian cows in MCA were assessed as well. To estimate the genetic parameters for MCA and to study the effects of non-genetic and breed factors on MCA, three separate data sets were collected: a longitudinal Finnish Ayrshire data set, a data set of Finnish Ayrshire and Holstein-Friesian cows and a data set of 91 Finnish Ayrshire sires with large daughter groups. The last data set was also used as source data for gene mapping of the genomic regions associated with the non-coagulation of milk. The traits used to describe MCA were milk renneting time, curd firming time and curd firmness. The results revealed significant variation in MCA among cows, sires, herds, breeds and lactation stage. Despite the large differences in herd bulk milks, herd explained only a minor part of the variation in MCA. There was some indication that good management and feeding decrease the proportion of poorly coagulating milks. However, breed differences and genetic differences within breeds are probably a greater cause for large variation in herd bulk milks than herd management and feeding. Holstein-Friesian cows were superior to Finnish Ayrshire cows in MCA. Poor coagulation or non-coagulation of milk was only a minor problem (10%) in Holstein-Friesian cows, whereas one-third of Finnish Ayrshire cows produced poorly or non-coagulating milk. Almost 40% of the variation among animals was additive genetic. Selection is thus the most effective way to improve MCA. Direct selection is the most effective selection method. Based on the high repeatability estimates, only three measurements are needed to reliably estimate cows’ average MCA. However, the current measuring devices are not suitable for the large-scale measurement required to include the trait in routine milk recording. Options for selecting MCA indirectly or via marker-assisted selection were evaluated by studying the following means: selection based on production and udder health traits in the total merit index, selection based on protein or casein content or on the pH of milk and selection based on reduction of the prevalence of non-coagulating milk. The findings indicate that the udder health index both improves MCA genetically and decreases the prevalence of non-coagulating milk through somatic cell count. Under the present weighting scheme, however, hardly any response to MCA is expected. No genetic correlation between test-day milk yield and milk coagulation traits or non-coagulation of milk was observed. Neither the protein or casein content of milk nor the pH of milk was found to be a viable option for indirect selection. The results for casein content were identical to those for protein content, which is already included in routine milk recording. The genetic correlation between MCA and protein and casein content of milk was, however, almost zero. Further investigation of the relationship between predicted breeding values for curd firmness and protein and casein contents suggested that selection based on the latter would maintain NC-carriers in the Finnish Ayrshire population. The pH of milk was moderately genetically correlated with milk coagulation traits, but was not clearly genetically associated with the non-coagulation of milk. Therefore, its inclusion in the index would likely not decrease the frequency of non-coagulating milk. About 10% of Finnish Ayrshire cows produced non-coagulating milk in all data sets analysed; some of the cows produced non-coagulating milk at almost every sampling. The non-coagulation of milk is thus a worryingly common problem in the Finnish Ayrshire population. None of the environmental factors studied could fully explain it. However, several indications of a genetic cause emerged and two associated loci were mapped to chromosome 2 (BMS1126) and chromosome 18 (BMS1355). No association between casein genes themselves and non-coagulation of milk was observed. Instead, two candidate genes, LOC538897 in chromosome 2 and SIAT4B in chromosome 18, were found, both of them involved in the post-translational modification of amino acids. LOC538897 functions as a non-specific serine/threonine kinase and SIAT4B, or sialyltransferase, catalyses the last step of glycosylation of κ-casein. The potential role of the candidate genes in the non-coagulation of milk warrants further investigations. Currently, the elimination of the carrier bulls of non-coagulation genes would be the most effective way of genetically improving MCA in Finland

    Estimation of inbreeding depression on female fertility in the Finnish Ayrshire population

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    Single nucleotide polymorphism (SNP) data enable the estimation of inbreeding at the genome level. In this study, we estimated inbreeding levels for 19,075 Finnish Ayrshire cows genotyped with a low-density SNP panel (8K). The genotypes were imputed to 50K density, and after quality control, 39,144 SNPs remained for the analysis. Inbreeding coefficients were estimated for each animal based on the percentage of homozygous SNPs (F-PH), runs of homozygosity (F-ROH) and pedigree (F-PED). Phenotypic records were available for 13,712 animals including non-return rate (NRR), number of inseminations (AIS) and interval from first to last insemination (IFL) for heifers and up to three parities for cows, as well as interval from calving to first insemination (ICF) for cows. Average F-PED was 0.02, F-ROH 0.06 and F-PH 0.63. A correlation of 0.71 was found between F-PED and F-ROH, 0.66 between F-PED and F-PH and 0.94 between F-ROH and F-PH. Pedigree-based inbreeding coefficients did not show inbreeding depression in any of the traits. However, when F-ROH or F-PH was used as a covariate, significant inbreeding depression was observed; a 10% increase in F-ROH was associated with 5days longer IFL0 and IFL1, 2weeks longer IFL3 and 3days longer ICF2 compared to non-inbred cows.Peer reviewe

    Principal component and factor analytic models in international sire evaluation

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    <p>Abstract</p> <p>Background</p> <p>Interbull is a non-profit organization that provides internationally comparable breeding values for globalized dairy cattle breeding programmes. Due to different trait definitions and models for genetic evaluation between countries, each biological trait is treated as a different trait in each of the participating countries. This yields a genetic covariance matrix of dimension equal to the number of countries which typically involves high genetic correlations between countries. This gives rise to several problems such as over-parameterized models and increased sampling variances, if genetic (co)variance matrices are considered to be unstructured.</p> <p>Methods</p> <p>Principal component (PC) and factor analytic (FA) models allow highly parsimonious representations of the (co)variance matrix compared to the standard multi-trait model and have, therefore, attracted considerable interest for their potential to ease the burden of the estimation process for multiple-trait across country evaluation (MACE). This study evaluated the utility of PC and FA models to estimate variance components and to predict breeding values for MACE for protein yield. This was tested using a dataset comprising Holstein bull evaluations obtained in 2007 from 25 countries.</p> <p>Results</p> <p>In total, 19 principal components or nine factors were needed to explain the genetic variation in the test dataset. Estimates of the genetic parameters under the optimal fit were almost identical for the two approaches. Furthermore, the results were in a good agreement with those obtained from the full rank model and with those provided by Interbull. The estimation time was shortest for models fitting the optimal number of parameters and prolonged when under- or over-parameterized models were applied. Correlations between estimated breeding values (EBV) from the PC19 and PC25 were unity. With few exceptions, correlations between EBV obtained using FA and PC approaches under the optimal fit were ≥ 0.99. For both approaches, EBV correlations decreased when the optimal model and models fitting too few parameters were compared.</p> <p>Conclusions</p> <p>Genetic parameters from the PC and FA approaches were very similar when the optimal number of principal components or factors was fitted. Over-fitting increased estimation time and standard errors of the estimates but did not affect the estimates of genetic correlations or the predictions of breeding values, whereas fitting too few parameters affected bull rankings in different countries.</p

    Laatu hoitotyössä ja hoitotyön koulutuksessa - kokoelma tiivistelmistä

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    Hoitotyön koulutus ammattikorkeakouluissa on muuttunut paljon viimeisten viiden vuoden aikana. Sairaanhoitajien valtakunnalliset osaamisvaatimukset luovat pohjan hoitotyön koulutukselle ja koulutuksen kehittämiselle. Uudet opetusmenetelmät, kuten simulaatio-opetus ja verkko-opetus asettavat hoitotyön opettajat uusien ammatillisten haasteiden eteen. Hoitotyön opettajuus ja hoitotyön opettajan työnkuva ei koostu enää pelkästään hoitotyön opetuksesta, vaan opettajan työnkuvaan kuuluu yhä enemmän tutkimus- ja kehittämistoimintaan liittyviä tehtäviä niin kotimaassa kuin kansainvälisestikin. Saimaan ammattikorkeakoulun hoitotyön opettajat ovat osallistuneet aktiivisesti terveysalan koulutuksen konferensseihin sekä Suomessa, että ulkomailla. Tähän julkaisuun on kerätty tiivistelmiä Saimaan ammattikorkeakoulun hoitotyön opettajien tutkimustöistä, joita he ovat esitelleet myös alan seminaareissa ja konferensseissa vuosina 2012 - 2015

    Principal component approach in variance component estimation for international sire evaluation

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    <p>Abstract</p> <p>Background</p> <p>The dairy cattle breeding industry is a highly globalized business, which needs internationally comparable and reliable breeding values of sires. The international Bull Evaluation Service, Interbull, was established in 1983 to respond to this need. Currently, Interbull performs multiple-trait across country evaluations (MACE) for several traits and breeds in dairy cattle and provides international breeding values to its member countries. Estimating parameters for MACE is challenging since the structure of datasets and conventional use of multiple-trait models easily result in over-parameterized genetic covariance matrices. The number of parameters to be estimated can be reduced by taking into account only the leading principal components of the traits considered. For MACE, this is readily implemented in a random regression model.</p> <p>Methods</p> <p>This article compares two principal component approaches to estimate variance components for MACE using real datasets. The methods tested were a REML approach that directly estimates the genetic principal components (direct PC) and the so-called bottom-up REML approach (bottom-up PC), in which traits are sequentially added to the analysis and the statistically significant genetic principal components are retained. Furthermore, this article evaluates the utility of the bottom-up PC approach to determine the appropriate rank of the (co)variance matrix.</p> <p>Results</p> <p>Our study demonstrates the usefulness of both approaches and shows that they can be applied to large multi-country models considering all concerned countries simultaneously. These strategies can thus replace the current practice of estimating the covariance components required through a series of analyses involving selected subsets of traits. Our results support the importance of using the appropriate rank in the genetic (co)variance matrix. Using too low a rank resulted in biased parameter estimates, whereas too high a rank did not result in bias, but increased standard errors of the estimates and notably the computing time.</p> <p>Conclusions</p> <p>In terms of estimation's accuracy, both principal component approaches performed equally well and permitted the use of more parsimonious models through random regression MACE. The advantage of the bottom-up PC approach is that it does not need any previous knowledge on the rank. However, with a predetermined rank, the direct PC approach needs less computing time than the bottom-up PC.</p
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