The two native Croatian donkey breeds (Littoral-Dinaric donkey and Istrian donkey) were marginalized in the second half of the 20th century and were on the verge of biological extinction. The aim of ...this study was to analyze the demographic and genetic status of two donkey breeds, two decades after the start of protection by analyzing their pedigrees and genetic structure. The average generation interval was higher for the Istrian donkey (7.73) than for the Littoral-Dinaric donkey (7.27). The rate of the effective number of founders compared with the effective number of ancestors in the Littoral-Dinaric donkey (1.03; 325/316) and in the Istrian donkey (1.08; 70/65) revealed no evidence of a genetic bottleneck. The inbreeding coefficient (F) and the average relatedness coefficient (AR) was lower in the Littoral-Dinaric donkey population (0.99%; 0.13%) than in the Istrian donkey population (1.77%; 1.10%). Genetic microsatellite analysis showed relatively high genetic diversity in Littoral-Dinaric donkey and Istrian donkey breeds, expressed by mean allele number (5.92; 5.85) and expected heterozygosity (0.650; 0.653). Genetic differentiation between the Littoral-Dinaric donkey and the Istrian donkey has not significantly increased in the last two decades (FST = 0.028). Genetic analysis also showed no evidence of high inbreeding or genetic bottleneck in both breeds. A total of 11 haplotypes including 28 polymorphic sites were found in 30 samples. Analysis of mtDNA has shown that the Littoral-Dinaric donkey and Istrian donkey breeds belong to the Equus asinus africanus group. The study confirms the need to use different analytical approaches to get a regular and complete insight into the situation and trends within and between breeds, so that the existing diversity can be fully preserved.
The implementation of genomic selection (GS) together with the changes caused by globalization and trade liberalization of breeding material often raise the question of sustainability of breeding ...programs in small cattle populations/countries. The objective of this study was to describe the steps in the implementation of GS in small populations of Croatian Simmental (SIM) and Holstein (HOL) breeds; to show the results of its implementation; and to present the perspectives of GS for these populations. In order to improve the selection of SIM bulls, Croatia joined the German-Austrian genomic evaluation system in July 2013. The main goal of the GS in HOL population was selection of bull’s dams at a young age which started in 2016 through the inclusion in German HOL genomic evaluation system. In total, 268 SIM and 96 HOL calves were selected, genotyped, and genomically tested until the end of 2017. The criterion for the entry of SIM bulls in the artificial insemination (AI) centres is the total merit index over 130 and candidates should not be carriers of specific monogenic defects or be recessive for them. Based on these criteria, seven young bulls were selected as for AI. The criteria for the selection of HOL females are the total merit index of 150, without monogenic defects and so far none of them reached these standards. The future perspective for HOL breed is international IgHol project for small HOL populations representing the possibility for cost-efficient solutions of GS. The implementation of GS brought opportunity to Croatian breeders to use semen of bulls from the national breeding program. Genomics for females becomes an attractive option to capitalise the benefits of using this technology.
Svojstvo protoka mlijeka (PM) ima sve veću važnost sa stajališta upravljanja proizvodnjom mlijeka. Kod krava sa sporim PM potrebno je više rada, dok krave s brzim PM mogu biti u većoj opasnosti od ...pojave bolesti vimena. Iako se PM smatra svojstvom od značaja, malo je pozornosti dano procjeni genetskih parametara za PM i njegovoj povezanosti s drugim svojstvima. Ciljevi ovog istraživanja bili su: 1) procijeniti genetske parametre za PM u populaciji holstein goveda u Hrvatskoj; 2) koristiti izračunate genetske parametre za procjenu uzgojnih vrijednosti (UV) za svojstvo PM; i 3) izračunati korelacije između UV za PM s proizvodnim i sa svojstvima vanjštine kako bi se utvrdili međuodnosi između navedenih svojstava. U analizu je bilo uključeno 129.723 zapisa na kontrolni dan za 35.908 prvotelki holstein pasmine, uzetih iz središnje baze podataka Hrvatske poljoprivredne agencije. Podaci o porijeklu sadržavali su zapise za 85.605 životinja. Logaritamska transformacija podataka za svojstvo PM izvršena je s ciljem dobivanja distribucije slične normalnoj. Komponente varijance procijenjene su REML metodom u programu VCE-6. Statistički model je uključivao sljedeće fiksne utjecaje s razredima: sezona teljenja, vrijeme mužnje i razredi količine mlijeka, dok su dob kod prvog teljenja i stadij laktacije korišteni kao kontinuirana varijabla. Slučajni utjecaji u modelu bili su: interakcija stado-kontrolni dan, stalni utjecaj okoliša i aditivni genetski učinak. Interakcija stado-kontrolni dan i stalni utjecaj okoliša su pojasnili 27 % i 15 % ukupne varijabilnosti PM. Aditivni genetski učinak je pojasnio dodatnih 14 % fenotipske varijabilnosti PM. Utvrđene su niske do srednje korelacije UV bikova i krava između PM i proizvodnih te PM i svojstava vanjštine. Izračunate korelacije bile su pozitivne s izuzetkom korelacije između UV za PM i duljine sisa. Genetsko vrednovanje za svojstvo PM pruža korisne informacije za donošenje uzgojnih odluka zbog umjerenog heritabiliteta te bi u budućnosti navedeno svojstvo trebalo uključiti u ukupan selekcijski indeks. Da bi se utvrdile odgovarajuće ekonomske težine za PM u ukupnom selekcijskom indeksu, potrebno je prethodno procijeniti genetske korelacije između PM i proizvodnih svojstava te svojstava vanjštine.
Milking speed (MS) has a growing importance from a dairy management standpoint. Cows with slow MS require more labour, while cows with fast MS could be in greater risk for udder diseases. Although MS ...is considered as a trait of importance, little attention has been given to estimate genetic components for MS and its relationship with other traits. The objectives of this study were: 1) to estimate genetic parameters for MS in Croatian Holstein cattle; 2) to use them for the prediction of breeding values; and 3) to estimate proof correlations of MS with production and conformation traits in order to understand the interrelationships among traits. Data included 129,723 test-day records for 35,908 first calving cows taken from the central database of the Croatian Agricultural Agency. Pedigree file consisted of 85,605 animals. In order to improve the normality, logarithmic transformation for MS was used. Variance components where estimated by REML method using VCE 6 program. Statistical model included calving season, milking time, and milk yield class as fixed class effects, while age at first calving and days in milk were fitted as covariates. Random effects were: common herd-test day, permanent environmental and direct additive genetic effect. Common herdtest day and permanent environmental effect accounted 27 % and 15 % of variability. Direct additive genetic effect explained another 14 % of phenotypic variation for MS. Analysis of proof correlations between bulls and cows BV for MS with production and conformation traits showed low to mediate relationships. Most of these proof correlations were positive with an exception of teats length. Genetic evaluation for MS provide useful tool for breeding decisions due to moderate heritability of MS and the trait should be included in the total merit index in the future. In order to determine the appropriate economic weights for MS in the overall index, genetic correlations among MS and production and conformation traits should be estimated.
Današnje krave za mužnju selektirane su s obzirom na zdravlje i prilagođenost vimena strojnoj ili robotiziranoj mužnji. Budući da sisne čaše robot postavlja automatski, ključne su eksterijerne ...osobine vimena. Morfološki adekvatno vime, koje ima dobar omjer prednjih i stražnjih četvrti, odgovarajući oblik, veličinu i položaj sisa, preduvjet je dobroga zdravstvenog stanja krave i njezine prilagođenosti robotiziranoj mužnji. Prednost robotizirane mužnje ogleda se u individualnome pristupu svakoj kravi i mogućnosti analize velikoga seta podataka koji se svakodnevno prikupljaju po svakoj mužnji. Razvijaju se nove uzgojne vrijednosti, poput RZ Robota, koje kombiniraju svojstva koja su od velikoga značenja u selekciji bikova na farmama koje se koriste robotima za mužnju. Kako se broj robota za mužnju svake godine povećava, radi se na njihovu unaprjeđenju, pa se današnji modeli robota, koji se mogu pronaći na tržištu, vješto suočavaju s izazovima nepravilnosti vimena te su vrlo opremljeni. Njihovo unaprjeđenje najviše se ogleda u uspješnosti stvaranja nove hibridne ruke s jako puno pozitivnih karakteristika u ostvarenju pravilne mužnje, pri čemu se pazi na dobrobit i zdravlje krava.
The present-day milking cows are selected with regard to the health and adaptability of the udder to a machine or robotic milking. Since the teat cups are placed automatically by a robot, the exterior features of the udder are crucial. A morphologically adequate udder, which has a good ratio of forequarters and hindquarters and an appropriate shape, size, and position of the teats, is a prerequisite for the cow’s good health and its adaptability to robotic milking. The advantage of robotic milking is reflected in an individual approach to each cow and a possibility to analyze a large set of data, collected daily after each milking. The new breeding values, such as the RZ Robot, are being developed, which combine the traits that are of great importance in the selection of bulls on farms that use the milking robots. As a number of milking robots increases every year, a work has been done to improve them, and the current robotic models that can be found on the market skillfully face the challenges of udder irregularities and are well equipped. Their improvement is mostly reflected in the success of creation of a new hybrid hand, with a lot of positive characteristics in the achievement of proper milking while taking care of the cows’ well-being and health.
Milkability traits have an increasing importance in modern cattle production, although they are the secondary selective trait. The machine milking of cows has indicated that there is no complete ...alignment between the machine and the animals, what lead to increasing duration of milking and disturbances in health of udder. Because of that, the aim of this study was to investigate the influence of the ordinal number of lactation and stage of lactation on milkability traits (amount of milk per milking (KMM), maximum milk flow rate (MPM), average milk flow rate (PPM), duration of the start of milk flow (tS500), duration of the ascending phase of milking (tUFM), duration of the plateau phase of milking (tPFM), duration of the descending phase of milking (tSFM), duration of the main phase of milking (tGFM)), and recommend the same for the selection work. The study was done on 322 Holstein cows in the period from the first to third lactation, arranged in three stages of lactation (the first of the 50-90 day, the second stage of the 91-135 day and a third of 136-180 day of lactation). The results showed that the ordinal number of lactation had a highly statistically significant influence (P<0.01) on KMM and MPM, and on the PPM and tGFM (P<0.05). Statistically significant influence of the stage of lactation on the KMM was recorded in the first and second lactation (P<0.05) respectively in the third lactation (P<0.01). Was recorded a significant positive influence of KMM (P<0.05) on the MPM, tPFM, tSFM and tGFM (r = from 0.22 to 0.52). The negative correlation of the MPM (P<0.05) was recorded with some parts of the milking phase duration (r = -0.14 to -0.47). The results indicate that there are opportunities for selection work to improve milkability traits, which can have a positive impact on the economy of expenditure of time during milking, and indirectly improve the health of the udder.
The objective of this study was to estimate genetic parameters and environmental effects on somatic cell count in Croatian dairy cows. Data consisted of 861,417 test-day records for Simmental and ...656,272 for Holstein cows. For Simmental breed, number of animals in pedigree was 123,199, while pedigree file for Holstein breed included 94,294 animals. A single-trait repeatability fixed regression test-day model was used to estimate genetic parameters. Fixed effects in the model were parity and calving season. Days in milk was fitted using Ali-Schaeffer lactation curve nested within parity. Age at first calving was modelled as quadratic regression. Direct additive genetic effect, herd, herd-test-date, and permanent environmental effect of cow within parity were included in the model as random effects. Variance components were estimated using Residual Maximum Likelihood method as implemented in the VCE-6 program. Estimated heritabilities were 0.21 for Simmental and 0.15 for the Holstein breed. Permanent environmental effect explained 19 % of phenotypic variation in Simmental and 20 % in Holstein breed. Herd and herd-test-date accounted for another 9 % and 5 % of variability for Simmental breed. The effects of herd and herd-test-date explained 10 % and 5 % of phenotypic variance in Holstein breed.
Determining the urea concentration in milk is a useful indicator of the nutritional protein status of the organism as well as of the ratio between the energy and the protein in ruminant rations, with ...increasing practical usage. In addition to nutrition, milk urea concentration is influenced by a whole range of factors, for example: breed, stage and number of lactations, body weight, daily production and chemical composition of milk, somatic cell count, season and milking. The objective of this research was to determine the impact of the cow breed (Holstein and Simmental), the number of lactation (1st, 2nd, 3rd, 4th, 5th), milking time (morning-evening) and season (spring-summer and autumn-winter) on milk urea concentration. The following was determined for each breed: daily milk yield, milk fat, protein and lactose content, urea concentration and somatic cell count in milk. Statistical data processing was carried out by applying General Linear Model procedure, SAS system (1999). The cow breed had a significant influence on daily milk yield and log somatic cell count (P<0.001), lactose content in milk (P<0.01), milk fat content and milk urea concentration (P<0.05). The number of lactations significantly influenced daily milk yield (P<0.001), protein content (P<0.001 and P<0.01) and milk urea concentration, but only for Holstein breed (P<0.05). Milking time significantly influenced the fat and protein content (P<0.001) in the milk of Holstein cows, that is, lactose content (P<0.05) and urea concentration (P<0.05) in the milk of Simmental cows. The season significantly influenced the fat and protein content of milk (P<0.001), that is, urea concentration and log somatic cell count (P<0.01). Determining of urea concentration in cow milk should also be systematically conducted in the Republic of Croatia, in order to determine standard physiological values characteristical for a particular cow breed, aiming to determine the balance of energy and protein in rations.
Milk urea nitrogen concentration is a reliable indicator of protein energy balance in dairy cows. Concentration of milk urea nitrogen is mostly affected by nutritional factors, but also its ...concentration can be influenced by some non-nutritional factors. The aim of this research was to determine the effect of season, parity and stage of lactation on concentration of milk urea nitrogen, as well as its association with daily milk yield, milk fat and protein content and somatic cell count. For that purpose, milk control data were collected for 5061 Holstein dairy cows from four dairy farms during five-year period (between January 1999 and December 2005). When milk urea nitrogen was associated with season, the higher concentration was found in the summer and autumn period, while significantly lower concentration was found in the winter and spring period. Milk urea nitrogen was the lowest in first lactation (27.34 mg/dL) and significantly increased with parities. The highest milk urea nitrogen concentration was recorded during mid-lactation stage (100-200 days), while the lowest concentration was found during late lactation stage (>200 days). Daily milk yield increased notably until above 35.00 mg/dL concentration of milk urea nitrogen, and above that level daily milk yield decreased. Milk fat and protein, content and somatic cell count had negative relationship with milk urea nitrogen concentration. The highest value of milk protein (3.41 %) was recorded when milk urea nitrogen ranged from 15 to 25 mg/dL, while milk fat percentage was the highest (4.06 %) when milk urea nitrogen ranged from 15 to 20 mg/dL. Cows with milk urea nitrogen concentration <15 mg/dL had the highest mean somatic cell count (333x103/mL). Results of this study show significant influence of analyzed non-nutritional factors on milk urea nitrogen concentration. These results may be useful in improving the accuracy of models for controlling protein-energy balance in Holstein dairy cows.
Za potrebe vrjednovanja kvalitete kukuruzne silaže, u ovome je istraživanju analizirano 270 uzoraka na mliječnim farmama u dvanaest (12) županija. Pripremljeni uzorci analizirani su uz pomoć FT-NIR ...uređaju uz primjenu spektrometra AgriQuant-B1 (Model: QIA 1020), kojim su analizirane vrijednosti devet (9) nutritivnih, dva (2) pokazatelja fermentacije buraga te tri (3) pokazatelja fermentacije silaže kukuruza. Jedan fizički pokazatelj, distribucija veličine čestica silaže, određen je prosijavanjem preko sustava triju sita (Penn State Separator). Prosječne vrijednosti većine praćenih nutritivnih pokazatelja bile su zadovoljavajuće: suha tvar (ST) = 349 g kg-1, sir. protein = 65 g kg-1ST, sir. pepeo = 38 g kg-1ST, sir. vlakna = 180 g kg-1 ST, kisela deterdžentska vlakna (KDV) = 210 g kg-1ST, neutralna deterdžentska vlakna (NDV) = 387 g kg-1ST, kiseli deterdžentski lignin (KDL) = 17 g kg-1ST, škrob = 336 g kg-1ST, neto energija mlijeka = 6,76 MJ g kg-1ST. Značajnija odstupanja u Max. i Min. utvrđena su za vrijednosti ST (156 nesukladnih uzoraka), za sirovi protein utvrđen je čak 231 nesukladan uzorak, za kisela deterdžentska vlakna 90, a za škrob 233 uzorka. Pokazatelji fermentacije buraga kao prosječna probavljiva organska tvar (pOT) iznosila je = 75,6 %, a probavljiva neutralna deterdžentska vlakna (pNDV) = 52,8 %. Prosječna pH vrijednost je bila poželjnih 3,85, uz prosječnu koncentraciju mliječne (54,9 g kg-1ST) i octene (21,1 g kg-1ST) kiseline. Prosječne vrijednosti distribucije veličine čestica silaža, mjerene četirima frakcijama rezultirale su sljedećim vrijednostima: sito 1–5,7 %; sito 2–55,7 %; sito 3–26,1 % i posuda na dnu–12,6 %. Najjača pozitivna korelativna povezanost utvrđena je između sirovih vlakana u odnosu na KDV (r = 0,870), NDV (r = 0,959) i KDL (r = 0,790) te između NDV-a i KDV-a (r = 0,845). Korelativna povezanost negativnoga predznaka bila je najjača između KDL-a i pOT-a (r = -0,844), škroba u odnosu na sir. vlakna (r = -0,835) i NDV (r = -0,809), te pH i mliječne kiseline (r = -0,804). Navedene korelativne veze između pokazatelja bile su i statistički visoko značajne (p < 0,001).
For the purpose of corn silage quality evaluation, 270 samples on dairy farms in twelve (12) counties were analyzed in this study. The prepared samples were subjected to the FT-NIR device using the AgriQuant-B1 spectrometer (Model: QIA 1020), which analyzed the values of nine (9) nutritional, two (2) indicators of rumen fermentation, and three (3) indicators of corn silage fermentation. One physical indicator, the silage particle size distribution, was determined by sieving through a three-sieve system (Penn State Separator). The average values of most of the monitored nutritional indicators were satisfactory: DM = 349 g kg-1, crude protein = 65 g kg-1 DM, crude ash = 38 g kg-1 DM, crude fiber = 180 g kg-1 DM, acid detergent fiber = 210 g kg-1 DM, neutral detergent fiber = 387 g kg-1 DM, acid detergent lignin = 17 g kg-1 DM, starch = 336.59 g kg-1 DM, net energy of milk = 6.76 MJ g kg-1 DM. Significant deviations in Max. and Min. were found for the DM values (156 non-compliant samples), as many as 231 non-compliant samples were found for crude protein, 90 noncompliant samples were detected for the acidic detergent fibers, and 233 for starch. The rumen fermentation indicators, expressed as average digestible organic matter (dOM), amounted to 75.6%, and those of digestible neutral detergent fiber (dNDF) amounted to 52.8%. The average pH value reached a desirable value of 3.85, with an average concentration of lactic acid (54.9 g kg-1 DM) and acetic acid (21.1 g kg-1 DM). The average values of silage particle size distribution, measured through four fractions, resulted in the following values: sieve 1 – 5.7%; sieve 2 – 55.7%; sieve 3 – 26.1% and bottom vessel – 12.6%. The strongest positive correlation was found between the crude fiber in relation to the ADF (r = 0.870), NDF (r = 0.959), and ADL (r = 0.790) and between the NDF and ADF (r = 0.845). Negative correlation was strongest between the ADL and dOM (r = -0.844), between the starch compared to the CF (r = -0.835) and NDF (r = -0.809), and between the pH and lactic acid (r = -0.804). These correlations between the indicators were also statistically highly significant (p<0.001).
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