UČINAK SEZONE NA POKAZATELJE VELIČINE LEGLA U CRNE SLAVONSKE PASMINE SVINJA I PASMINE SVINJA“NERO DI PARMA”

The aim of this study was to analyse the litter size traits in two genotypes of pig population with black coat: Black Slavonian (BS) and “Nero di Parma” (NP). Data analysis included records from the 1st to 4th parity separately, and all parities (from 1st to 11th) for the following traits: Total Number of Born (TNB), Number of Born Alive (NBA), and Number of Weaned (NW) piglets, collected from 296 BS and 421 NP sows. Litter size traits from 1st to 4th paritywas analysed separately for each breed and ANOVA Repetead Measure test was used to calculate the difference between parities. The analysis of seasonality in all parities was performed using the General Linear Model.Significant differences (P<0.05) between-parity in BS were observed in the 1st and 3rd as well in the 1st and 4th parities for TNB and NW. Only for the NBA difference (P<0.05) was found between 1st and 3rd parities.Differences (P<0.05) in NP pigs were reported between the 1st and 3rd as between 1st and 4th parity for TNB and NBA. First-parity sows for NW shows significant differences (P<0.05) in relation to 2nd, 3rd and 4th parity. In all parities analysed according to the seasons significant differences was recorded between summer and autumn period for TNB (P<0.05) in BS. Difference (P<0.05) was also obtained for NBA between spring and autumn, as well as for summer and autumn season. In all parity analysis in BS pig, the NW (P<0.05) showed differences only between spring and summer period. Season in all parity analysis had a significant impact on litter size traits in NP pig. Differences (P<0.05) was obtained for TNB, NBA and NW among spring-winter, summerwinter and autumn-winter period.Cilj ovog istraživanja bio je analizirati pokazatelje veličine legla u dvije populacije svinja: crne slavonske pasmine svinja (CS) i crne pasmine svinja “Nero di Parma” (NP). Analizirani su pokazatelji veličine legla: ukupan broj oprasenih (UOO), živooprasenih (ŽO) i broj odbijenih odojaka (BOO) od prvog do četvrtog prasenjaza svaku pasminu. Skupnom analizom od prvog do jedanaestog legala prikazani su rezultati UOO, ŽO i BOO po sezoni prasenja. Istraživanjem je bilo obuhvaćeno 296 krmača CS i 421 krmača NP. Testiranje razlika navedenih pokazatelja od prvog do četvrtog prasenja provedena je analizom varijance s ponovljenim mjerenjima. Podaci skupne analize po sezoni prasenja prikazani su pomoću općeg linearnog modela izračuna. Statističkom obradom podataka utvrđena je značajna razlika (p<0,05) između prvog i trećeg prasenja te prvog i četvrtog prasenja za svojstva UOO i BOO u CS, dok je značajna razlika (p<0,05) u broju ŽO usta-novoljena samo između prvog i trećeg prasenja. Razlika u broju UOO i ŽO bila je značajna (p<0,05) između prvopraskinja u odnosu na treće-i četvrtopraskinje NP. Najmanji BOO u NP zabilježen je u prvopraskinja te su razlike bile značajne (p<0,05) u usporedbi s drugim, trećim i četvrtim prasenjem. Skupnom analizom prasenja utvrđene su značajne razlike (p<0,05) za UOO između ljetne i jesenske sezone te za ŽO između jesenske i proljetne sezone te jesenske i ljetne sezone prasenja (p<0,05). Nadalje, značajna razlika (p<0,05) u BOO zabilježena je između proljetne i ljetne sezone prasenja. Broj UOO, ŽO i BOO u NP tijekom zimske sezone bio je značajno manji (p<0,05) u odnosu na zabilježene vrijednosti tijekom proljetne, ljetne i jesenke sezone prasenja

HERD HEALTH MANAGEMENT, LEGISLATION AND RISK FACTORS IN PRESERVATION OF AUTOCHTHONOUS ANIMAL BREEDS

Zaštita zdravlja je integralni dio uzgoja svih vrsta životinja. Bolesti domaćih životinja, pa tako i izvornih pasmina jesu ne samo zdravstveni već i socio-ekonomski problem. Pojava bolesti unutar populacija izvornih pasmina životinja dovodi do ekonomskih gubitaka uslijed manje proizvodnje, uginuća ili nemogućnosti korištenja proizvoda životinjskog podrijetla. Smanjenje populacija izvornih pasmina je sociološki i ekološki problem, u smislu očuvanja biološke raznolikosti kao dijela kulturne baštine pojedinog kraja. Bolesti su velika opasnost pogotovo za male populacije, rasprostranjene na manjem području, očuvane in vivo i in situ bez ex situ postupaka, jer može doći do ugroze cijele populacije. Zakonom propisane mjere o postupanju u slučaju izbijanja pojedinih bolesti, odnosno o preve-ntivnim postupcima kod pojedinih vrsta odnose se na sve životinja jednako. U Hrvatskoj je zakonska osnova izjednačena ili u procesu izjednačavanja s legislativom EU. Zdravstvena zaštita izvornih pasmina domaćih životinja trebala bi se temeljiti prvenstveno na preventivnim mjerama kako bi se smanjili mogući rizici za navedene populacije. Pod preventivom mislimo na preventivno cijepljenje, ali i pravilnu hranidbu, higijenu vode za piće, optimalne mikroklimatske uvjete u nastambama te redovito kretanje životinja.Heard health management is integral part of animal breeding. Domestic animal, as well as autochthonous breeds diseases presents health and socio-economic problem. Disease outbreaks in autochthonous breeds can cause economic losses due to diminished production, mortality or to inability to use animal products. Decrease in autochthonous breed population size is social and ecological problem in means of loss of animal genetic resources. Especially small populations are at risk in case of disease outbreaks because these populations are usually spread on smaller regions and preserved in vivo and in situ without ex situ methods. Legislation includes preventive and those measures which should be taken in case of disease outbreaks. Croatian legislation is already or is in the process of adjustment according to EU legislations. Herd health management for autochthonous breeds should be based upon preventive measures to diminish all risks. Under preventive measures we consider preventive vaccination of animals, good nutrition, drinking water hygiene, optimal housing conditions and regular animal exercise

Prediction of reproductive performance of ewes based on the early production data, ewe birth rank, dam age, and dam birth rank

This research aimed to analyze whether ewes' total reproductive performance up to the fourth year of life (RP4) can be predicted based on the data available at an early stage of a ewe's productive life. The RP4 of 133 Romanov ewes was measured in terms of the total number of lambs born per ewe (TNLE) and total birth weight of lambs per ewe (TBLE). Multiple regression was used to analyze whether early reproductive performance indicators (first litter size – FLS, age at first lambing – AFL, first lambing interval – FLI), ewe birth rank, dam age, and dam birth rank can be used as the predictors of RP4. Predicted R2 and 95 % prediction intervals were used as indicators of the precision of prediction. Average TNLE and TBLE at the end of fourth year of ewe life were 11.84 lambs and 37.96 kg, respectively. FLS and FLI significantly (P&lt;0.05) influenced TNLE and TBLE, while AFL was not a significant (P&gt;0.05) variable. Ewes with shorter FLI had significantly (P&lt;0.05) higher TNLE (10.94 lambs) and TBLE (36.17 kg) than ewes with long FLI (TNLE = 9.12 lambs and TBLE = 28.05 kg). R2 predicted for TNLE and TBLE was 7.54 % and 11.49 %, respectively. The ewe's birth rank and the dam's birth rank significantly (P&lt;0.05) influenced TNLE and TBLE. Ewes born as singletons and ewes from singleton-born dams had significantly (P&lt;0.05) lower TNLE and TBLE than ewes born as triplets and ewes from triplet-born dams. R2 predicted for TNLE was 16.76 %, and 25.69 % for TBLE. FLS and FLI are better predictors of RP4 than AFL. The birth rank of ewe and dam also proved significant predictors of RP4. For both sets of predictors (early reproductive indicators and birth rank data), low values of R2 predicted indicate that precise prediction of RP4 cannot be made.</p

EFFECT OF SEASONALITY ON LITTER SIZE TRAITS IN BLACK SLAVONIAN AND “NERO DI PARMA” PIGS

The aim of this study was to analyse the litter size traits in two genotypes of pig population with black coat: Black Slavonian (BS) and “Nero di Parma” (NP). Data analysis included records from the 1st to 4th parity separately, and all parities (from 1st to 11th) for the following traits: Total Number of Born (TNB), Number of Born Alive (NBA), and Number of Weaned (NW) piglets, collected from 296 BS and 421 NP sows. Litter size traits from 1st to 4thparitywas analysed separately for each breed and ANOVA Repetead Measure test was used to calculate the difference between parities. The analysis of seasonality in all parities was performed using the General Linear Model.Significant differences (P<0.05) between-parity in BS were observed in the 1st and 3rd as well in the 1st and 4th parities for TNB and NW. Only for the NBA difference (P<0.05) was found between 1st and 3rd parities.Differences (P<0.05) in NP pigs were reported between the 1st and 3rd as between 1st and 4th parity for TNB and NBA. First-parity sows for NW shows significant differences (P<0.05) in relation to 2nd, 3rd and 4th parity. In all parities analysed according to the seasons significant differences was recorded between summer and autumn period for TNB (P<0.05) in BS. Difference (P<0.05) was also obtained for NBA between spring and autumn, as well as for summer and autumn season. In all parity analysis in BS pig, the NW (P<0.05) showed differences only between spring and summer period. Season in all parity analysis had a significant impact on litter size traits in NP pig. Differences (P<0.05) was obtained for TNB, NBA and NW among spring-winter, summerwinter and autumn-winter period

Principal component analysis for authorship attribution

Background: To recognize the authors of the texts by the use of statistical tools, one first needs to decide about the features to be used as author characteristics, and then extract these features from texts. The features extracted from texts are mostly the counts of so called function words. Objectives: The data extracted are processed further to compress as a data with less number of features, such a way that the compressed data still has the power of effective discriminators. In this case feature space has less dimensionality then the text itself. Methods/Approach: In this paper, the data collected by counting words and characters in around a thousand paragraphs of each sample book, underwent a principal component analysis performed using neural networks. Once the analysis was complete, the first of the principal components is used to distinguish the books authored by a certain author. Results: The achieved results show that every author leaves a unique signature in written text that can be discovered by analyzing counts of short words per paragraph. Conclusions: In this article we have demonstrated that based on analyzing counts of short words per paragraph authorship could be traced using principal component analysis. Methodology could be used for other purposes, like fraud detection in auditing