Dependence of milk production of dairy sheep on climate conditions

Article Details: Received: 2020-10-14 | Accepted: 2020-11-27 | Available online: 2021-01-31https://doi.org/10.15414/afz.2021.24.mi-prap.85-88The aim of the study was to determine the influence of selected climatic characteristics on the milk production of ewes during lactation. Data of ewes from sheep farm Liptovská Teplička located in moderate climate zone (latitude 48°57'50.3"N, longitude 20°04'31.0"E) were analysed. In period from 2017 to 2019, the following milk traits: total morning milk production (TMPM), total evening milk production (TMPE), total morning+evening production (TMPM+E) and average daily milk production per ewe (ADMP) were measured on a daily basis. Traditional (Carpatian) production system was applied: ewes were on pasture and machine milked twice a day. Climate characteristics were monitored in 10-minute intervals by standard weather station (supplier: firm PHYSICUS), located near sheep farm. The influence of air temperature - T (°C), of relative humidity - RH (%), of wind speed (m.s-1) and of total precipitation (mm)recorded daily between 5 a.m. and 4 p.m. in period from April to September on milk traits was analysed. Temperature-humidity index (THI) was calculated according to National Research formula. The influence of year, of month and of interaction year x month was also analysed. Covariance analysis and Pearson correlation coefficients using statistical programme SASv9.2 (procedures GLM and CORR) were employed. The influence of month and of interaction year x month, respectively, on milk traits was found (P40.0 and THI <= 68.0). Preliminary results suggest that milk production traits of dairy sheep may be significantly influenced by climate also in moderate climatic zone.Keywords:  sheep, thermal stress, milk yield, temperate zoneReferencesAl Dawood, A. 2017. Towards heat stress management in small ruminants – a review. Ann. Anim. Sci., 17(1), 59-88. DOI: 10.1515/aoas-2016-0068Finocchiaro, R., Van Kaam, J.B.C.H.M., Portolano, B., Misztal, I. 2005. Effect of heat stress on production of Mediterranean dairy sheep. J. Dairy Sci., 88, 1855-1864.Gauly, M., Ammer, S. 2020. Review: Challenges for dairy cow production systems arising from climate changes. Animal,. 14:S1, s196-s203. doi:10.1017/S1751731119003239Gauly, M., Bollwein, H., Breves, G., Brugemann, K., Danicke, S., Das, G., Demeler, J., Hansen, H., Isselstein, J., Konig, S., Loholter, M., Martinshon, M., Meyer, U., Potthoff, M., Sanker, C., Schroder, B., Wrange, N., Meibaum, B., von Samson-Himmelstjerna, G., Stinshof, Wrenzycki, C., 2013. Future consequences and challenges for dairy cow production systems arising from climate change in Central Europe – a review. Animal, 7, 843-859. doi:10.1017/S1751731112002352Ramón, M., Díaz, C., Pérez-Guzman, M.D., Carabaño, M.J. 2016. Effect of exposure to adverse climatic conditions on production in Manchega dairy sheep. J. Dairy Sci., 99, 5764-5779. http://dx.doi.org/10.3168/jds.2016-10909Hamzaoui, S., Salama, A.A.K., Albanell, E., Such, X., Caja, G. 2013. Physiological responses and lactational performances of late-lactation dairy goats under heat stress conditions. J. Dairy Sci., 96, 6355-6365. http://dx.doi.org/ 10.3168/jds.2013-6665National Research Council (NRC). 1971. A guide to envronmental research on animals. Washington, DC: National Academy of Science.Sánches-Molano, E., Kapsona, V.V., Ilska, J.J., Desire, S., Conington, J., Mucha, S., Banos., G. 2019. Genetic analysis of novel phenotypes for farm animal resilience to weather variability. BMC Genetics., 20-84. https://doi.org/10.1186/s12863-019-0787-zSilanikove, N., N. Koluman (Darcan). 2015. Impact of climate change on the dairy industry in temperate zones: predications on the overall negative impact and on the positive role of dairy goats in adaptation to earth warming. Small Rumin Res., 123, 27-34. http://dx.doi.org/10.1016/j.smallrumres.2014.11.00

Effect of gluten on the quality of meat products

Article Details: Received: 2020-10-14 | Accepted: 2020-11-27 | Available online: 2021-01-31https://doi.org/10.15414/afz.2021.24.mi-prap.80-84The aim of the study was the evaluation of gluten quality of selected meat products. Gluten is a vegetable protein, which, due to its properties, is very often used in various sectors of the food industry and therefore in the production of meat products. Sensory evaluation, microbiological examination and gluten detection were performed in samples of sausages, Poultry frankfurter, Fine salami and Malokarpatská salami. The meat products came from different producers and were purchased from a retail network. Sensory quality was determined by assessing color, aroma, juiciness, fragility and taste using a 5-point rating scale. The microbiological examination included the determination of the total number of microorganisms, the number of psychrotrophic, coliform microorganisms and coagulase-positive staphylococci. The presence of gluten alone was detected using a commercially produced GlutenTox Home test kit as well as a PCR reaction. Individual testing of selected meat products showed minor differences in the overall quality of gluten free and gluten-free meat products. Keywords:meat products, salami, gluten, quality, microbiological examinationReferencesAbaffyová, Z. et al. (2015). Cereal grain a little different. Bratislava. Pediatria pre prax. 4, 140–146.Frič, P., Keil, R. (2011). Celiac disease for practice. Olomouc. Medicína pro praxi. 8, 354–359.Hulín, P., Dostálek, P., Hochel, I. (2008). Methods for determination of gluten proteins in food. Metódy stanovení lepkových bílkovin v potravinách. Chemické listy,102(5), 327–337.https://www.academia.edu/18759054/Methods_for_determination_of_gluten_proteins_in_foodOlexová, L. et al. (2006). Detection of gluten-containing cereals in flours and ‘‘gluten-free’’ bakery products by polymerase chain reaction. Food Control, 17(3), 234–237. https://doi.org/10.1016/j.foodcont.2004.10.009STN EN ISO 4833-1. Microbiology of food chain. Horizontal method for the enumeration of microorganisms. Part 1: Colony count at 30 degrees C by the pour plate technique. (ISO 4833-1: 2013)STN EN ISO 6888-1. Microbiology of food and animal feeding stuffs. Horizontal method for the enumeration of coagulase-positive staphylococci (Staphylococcus aureus and other species). Part 1: Technique using Baird-Parker agar medium (ISO 6888-1:1999)STN EN ISO 4832. Microbiology. General guidance for the enumeration of coliforms. Colony count techniqueTaylor, S. (1992). Chemistry and detection of food allergens. Food Technology, 46(5), 148–152. https://doi.org/10.1080/10408399609527761Toldrá, F. (2002). Fermentation and starter cultures. Dry-cured meat products, Trumbull : Food & Nutrition Press Inc., 89–112. https://doi.org/10.1002/9780470385111van Hengel, A. J. (2007). Food allergen detection methods and the challenge to protect food-allergic consumers. Analytical and Bioanalytical Chemistry, 389(1), 111–118. https://doi.org/10.1007/s00216-007-1353-5

Occurrence of epigeic groups, with emphasis on the families of beetles (Coleoptera) in various types of soil management

Article Details: Received: 2020-10-27 | Accepted: 2021-03-14 | Available online: 2021-09-30 https://doi.org/10.15414/afz.2021.24.03.167-173 The aim of this study was to assess the occurrence of epigeic groups of animals in five types of soil management. Research areas were marked as V1-EKO, whereas on the V1 area, mulching technology was used, on the V2 area, conventional technology, on V3 area, minimization technology, on the V4 area, no-till technology and the EKO area was managed in an ecological way. A ground pitfall trap was placed in the variety of a hybrid of Triticum aestivum × Triticum spelta – PS Lubica. The experiment was carried out between 2016 and 2018 in the research areas of the Research Institute of Plant Production in Borovce. In the course of three years, 11,365 specimen from 8 epigeic groups and 6 families were collected. At the eudominant level, Coleoptera and Hymenoptera groups were found in every research area. At the dominant level, Arachnoidea group were found on the V1 research area. and larvae on the EKO research area. The most numerous variant in terms of the number of individuals, but the number of groups also, collected over three years, was variant 1 – mulching technology. This means that shallow tillage, which decreases evaporation, soil loose and eliminates the weeds, is most beneficial to epigeic groups. Based on the statistical evaluation, we were unable to demonstrate the effect of rainfall on the occurrence of groups each year in the compared research areas. On the contrary, we were able to demonstrate the effect of temperature changes on the occurrence of epigeon.Keywords: epigeic groups, Coleoptera, ecological agriculture, pitfall trap ReferencesAratrakorn, S., Thunhikorn, S., & Donald P.F. (2006). Changes in bird communities following conversion of lowland forest to oil palm and rubber plantations in southern Thailand. Bird Conser Int, 16, 71–82. https://doi.org/10.1017/S0959270906000062Balmford, A., Green R.E., & Scharlemann J.P.W. (2005). Sparing land for nature: exploring the potential impact of changes in agricultural yield on the area needed for crop production. Glob Change Biol, 11, 1594–1605. https://doi.org/10.1111/j.1365-2486.2005.001035.xBrussaard, L., Ruiter, P.C., & Brown, G.G. (2007). Soil biodiversity for agricultural sustainability. Agriculture, Ecosystems & Environment, 121(3), 223–244. https://doi.org/10.1016/j.agee.2006.12.013Donald, P.F., Sanderson F.J., Burfield I.J., & Van Bommel F.P.J. (2006). Further evidence of continent‐wide impacts of agricultural intensification on European farmland birds 1990–2000. Agricul Ecosyst Environ, 116, 189–196. https://doi.org/10.1016/j.agee.2006.02.007Field, C.B., Campbell, J.E., & Lobell, D.B. (2008). Biomass energy: the scale of the potential resource. Trends Ecol Evol, 23, 53–112. https://doi.org/10.1016/j.tree.2007.12.001Diehl, E., Wolters, V., & Birkhofer, K. (2012). Arable weeds in organically managed wheat fields foster carabid beetles by resource-and structure-mediated effects. Arthropod-Plant Interactions, 6(1), 75–82. https://doi.org/10.1007/s11829-011-9153-4Gallé, R., Happe, A.-K., Baillod, A. B., Tscharntke, T., & Bátary, P. (2018). Landscape configuration, organic management, and within-field position drive functional diversity of spiders and carabids. Journal of Applied Ecology, 56, 63–72. https://doi.org/10.1111/1365-2664.13257Hurka, K. (1996). Carabidae of the Czech and Slovak Republic. Zlín: Kabourek. 9–35 s. (a) ISBN 80-901466-2-7.Lieskovský, J., Bezák, P., & Izakovičová, Z. (2010). Protection of representative landscape ecosystem of Slovakia – new landscape ecological approach. In: 10th International multidisciplinary scientific geoconference: SGEM conference 2010, pp. 717–72. https://doi.org/10.1515/geo-2017-0044Mazúr, E., & Lukniš, M. (1980). Geomorphological units. In Mazúr, E. (ed.) Atlas of the Slovak Socialist Republic. Bratislava: SAV a SÚGK, pp. 54–55Melnychuk, N.A., Olfert, O., Yongs, B., & Gillott, C. (2003). Abundance and diversity of Carabidae (Coleoptera) in different farming systems. Agriculture, Ecosystems and Environment, 95, 69–72. https://doi.org/10.1016/S0167-8809(02)00119-6Perrings, C., Jackson, L., Bawa, K. et al. (2006). Biodiversity in agricultural landscapes: saving natural capital without losing interest. Conserv Biol, 20, 263–264. https://doi.org/10.1111/j.1523-1739.2006.00390.xPorhajášová, J. (2019). Impact of Soil Management on Biodiversity of Epigeic Groups. Applied Ecology and Environmental Research, 17(6). https://doi.org/10.15666/aeer/1706_1389713908Ivanič Porhajašová, J., Babošová, M., Noskovič, J., & Ondrišík, P. (2018). Long-Term Developments and Biodiversity in Carabid and Staphylinid (Coleoptera: Carabidae and Staphylinidae) Fauna during the Application of Organic Fertilizers under Agroecosystem Conditions. Polish Journal of Environmental Studies, 27(5), 2229–2235. https://doi.org/10.15244/pjoes/77072Pokorný, V. (2002). Atlas of beetles. Praha – Litomyšl: Paseka, 144 p. ISBN 80-7185-484-0 Remenár, M. (2017). Recreation area Lake Borovce, documentation for territorial proceedings (CM PROJECT). 60–65 p.Röder, J., Detsch, F., Otte, I., Appelhans, T., Nauss, T., Peters, M. K., & Brandl, R. (2017). Heterogeneous patterns of abundance of epigeic arthropod taxa along a major elevation gradient. Biotropica, 49(2), 217–228. https://doi.org/10.1111/btp.12403Scharlemann, J.P.W., Balmford, A., & Green, R.E. (2005). The level of threat to restricted‐range bird species can be predicted from mapped data on land use and human population. 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Linkage disequilibrium, genomic inbreeding and effective populations size to unravel population history

Article Details: Received: 2021-03-25 | Accepted: 2021-04-16 | Available online: 2021-06-30https://doi.org/10.15414/afz.2021.24.02.161-166The use of single nucleotide polymorphism (SNP) data had become commonplace in animal breeding activities and management of livestock populations. The cost-effective genotyping allowed us to assess entire populations and learn about their history on the genomic level. This paper reviews several approaches that are commonly used in the context of genomic diversity in livestock, such as the linkage disequilibrium (LD) and assessment of autozygosity via runs of homozygosity (ROH). Both methods, however, are being used to assess the impact of natural or artificial selection on the livestock genome. Apart from these selection signatures, both the LD and ROH are used to assess the effective population size (Ne), which likewise, serves as a diversity management tool and describes the historical events in populations.Keywords: livestock, genomics, SNP, selection signatures, diversityReferencesAblondi, M. et al. (2020). Genetic Diversity and Signatures of Selection in a Native Italian Horse Breed Based on SNP Data. Animals, 10(6), 1005. https://doi.org/10.3390/ani10061005Almeida, O.A.C. et al. (2019). Identification of selection signatures involved in performance traits in a paternal broiler line. BMC Genomics, 20(1), 449. https://doi.org/10.1186/s12864-019-5811-1Ardlie, K.G., Kruglyak, L. & Seielstad, M. (2002). Patterns of linkage disequilibrium in the human genome. Nature Reviews Genetics, 3(4), 299–309. https://doi.org/10.1038/nrg777Baes, C. F. et al. (2019). Symposium review: The genomic architecture of inbreeding: How homozygosity affects health and performance. Journal of Dairy Science, 102(3), 2807–2817. https://doi.org/10.3168/jds.2018-15520Barbato, M. et al. (2015). SNeP: A tool to estimate trends in recent effective population size trajectories using genomewide SNP data. Frontiers in Genetics, 6. https://doi.org/10.3389/fgene.2015.00109Bradley, D. et al. (2004). Secondary guidelines for development of national farm animal genetic resources management plans. Food and Agricultural Organization of United Nations (FAO), Roma.Brüniche-Olsen, A. et al. (2018). Runs of homozygosity have utility in mammalian conservation and evolutionary studies. Conservation Genetics, 19(6), 1295–1307. https://doi.org/10.1007/s10592-018-1099-yCeballos, F. C. et al. (2018). Runs of homozygosity: Windows into population history and trait architecture. Nature Reviews Genetics, 19(4), 220–234. https://doi.org/10.1038/nrg.2017.109Curik, I., Ferenčaković, M. & Sölkner, J. (2017). Genomic dissection of inbreeding depression: A gate to new opportunities. Revista Brasileira de Zootecnia, 46(9), 773–782. https://doi.org/10.1590/s1806-92902017000900010Deng, T. et al. (2019). Genome-Wide SNP Data Revealed the Extent of Linkage Disequilibrium, Persistence of Phase and Effective Population Size in Purebred and Crossbred Buffalo Populations. Frontiers in Genetics, 9. https://doi.org/10.3389/fgene.2018.00688Fariello, M.I. et al. (2017). Accounting for linkage disequilibrium in genome scans for selection without individual genotypes: The local score approach. Molecular Ecology, 26(14), 3700–3714. https://doi.org/10.1111/mec.14141Ferenčaković, M., Sölkner, J. & Curik, I. (2013). Estimating autozygosity from high-throughput information: Effects of SNP density and genotyping errors. Genetics Selection Evolution, 45(1), 42. https://doi.org/10.1186/1297-9686-45-42Frankham, R., Bradshaw, C.J.A. & Brook, B.W. (2014). Genetics in conservation management: Revised recommendations for the 50/500 rules, Red List criteria and population viability analyses. Biological Conservation, 170, 56–63. https://doi.org/10.1016/j.biocon.2013.12.036Gazal, S. (2017). Linkage disequilibrium-dependent architecture of human complex traits shows action of negative selection. Nature Genetics, 49(10), 14.Georges, M., Charlier, C. & Hayes, B. (2019). Harnessing genomic information for livestock improvement. Nature Reviews Genetics, 20(3), 135–156. https://doi.org/10.1038/s41576-018-0082-2Granado-Tajada, I. et al. (2020). Inbreeding, effective population size, and coancestry in the Latxa dairy sheep breed. Journal of Dairy Science, 103(6), 5215–5226. https://doi.org/10.3168/jds.2019-17743Grilz‐Seger, G. et al. (2019). Analysis of ROH patterns in the Noriker horse breed reveals signatures of selection for coat color and body size. Animal Genetics, 50(4), 334–346. https://doi.org/10.1111/age.12797Hayes, B. J. et al. (2003). Novel Multilocus Measure of Linkage Disequilibrium to Estimate Past Effective Population Size. Genome Research, 13(4), 635–643. https://doi.org/10.1101/gr.387103Hickey, J. M. et al. (2017). Genomic prediction unifies animal and plant breeding programs to form platforms for biological discovery. Nature Genetics, 49(9), 1297–1303. https://doi.org/10.1038/ng.3920Hill, W.G. & Robertson, A. (1968). Linkage disequilibrium in finite populations. TAG. Theoretical and Applied Genetics. Theoretische Und Angewandte Genetik, 38(6), 226–231. https://doi.org/10.1007/BF01245622Jasielczuk, I. et al. (2020). Comparison of linkage disequilibrium, effective population size and haplotype blocks in Polish Landrace and Polish native pig populations. Livestock Science, 231, 103887. https://doi.org/10.1016/j.livsci.2019.103887Karimi, K., Esmailizadeh Koshkoiyeh, A. & Gondro, C. (2015). Comparison of linkage disequilibrium levels in Iranian indigenous cattle using whole genome SNPs data. Journal of Animal Science and Technology, 57. https://doi.org/10.1186/s40781-015-0080-2Kasarda, R. et al. (2015). Genome-wide selection signatures in Pinzgau cattle. Potravinarstvo Slovak Journal of Food Sciences, 9(1), 268–274. https://doi.org/10.5219/478Kasarda, R., Jamborová, Ľ. & Moravčíková N. (2020). Genetic diversity and production potential of animal food resources. Acta fytotechnica et zootechnica, 23(2), 102–108. https://doi.org/10.15414/afz.2020.23.02.102-108Khatkar, M. S. et al. (2008). Extent of genome-wide linkage disequilibrium in Australian Holstein-Friesian cattle based on a high-density SNP panel. BMC Genomics, 9(1), 187. https://doi.org/10.1186/1471-2164-9-187Kijas, J. W. et al. (2014). Linkage disequilibrium over short physical distances measured in sheep using a high-density SNP chip. Animal Genetics, 45(5), 754–757. https://doi.org/10.1111/age.12197Kim, E.-S. et al. (2013). Effect of Artificial Selection on Runs of Homozygosity in U.S. Holstein Cattle. PLoS ONE, 8(11), e80813. https://doi.org/10.1371/journal.pone.0080813Lu, D. et al. (2012). Linkage disequilibrium in Angus, Charolais, and Crossbred beef cattle. Frontiers in Genetics, 3. https://doi.org/10.3389/fgene.2012.00152Makanjuola, B.O. et al. (2020). Effect of genomic selection on rate of inbreeding and coancestry and effective population size of Holstein and Jersey cattle populations. Journal of Dairy Science, 103(6), 5183–5199. https://doi.org/10.3168/jds.2019-18013Mastrangelo, S. et al. (2014). Genome wide linkage disequilibrium and genetic structure in Sicilian dairy sheep breeds. BMC Genetics, 15(1), 108. https://doi.org/10.1186/s12863-014-0108-5McHugo, G.P. et al. (2019). A Population Genomics Analysis of the Native Irish Galway Sheep Breed. Frontiers in Genetics, 10. https://doi.org/10.3389/fgene.2019.00927McKay, S.D. et al. (2007). Whole genome linkage disequilibrium maps in cattle. BMC Genetics, 8(1), 74. https://doi.org/10.1186/1471-2156-8-74McQuillan, R. et al. (2008). Runs of Homozygosity in European Populations. The American Journal of Human Genetics, 83(3), 359–372. https://doi.org/10.1016/j.ajhg.2008.08.007 Meuwissen, T.H.E., Hayes, B.J. & Goddard, M.E. (2001). Prediction of Total Genetic Value Using Genome-Wide Dense Marker Maps. Genetics, 157(4), 1819–1829.Mills, M.C. & Rahal, C. (2019). A scientometric review of genome-wide association studies. Communications Biology, 2(1), 1–11. https://doi.org/10.1038/s42003-018-0261-xMoravčíková, N. et al. (2019). Analysis of selection signatures in the beef cattle genome. Czech Journal of Animal Science, 64(12), 491–503. https://doi.org/10.17221/226/2019-CJASMoravčíková, N. & Kasarda, R. (2020). Use of High-density SNP analyses to develop a long-term strategy for conventional populations to prevent loss of diversity – review. Acta fytotechnica et zootechnica, 23(4), 236–240. https://doi.org/10.15414/afz.2020.23.04.236-240Otto, S.P. (2000). Detecting the form of selection from DNA sequence data. 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Runs of homozygosity for autozygosity estimation and genomic analysis in production animals. Pesquisa Agropecuária Brasileira, 53(9), 975–984. https://doi.org/10.1590/s0100-204x2018000900001Reich, D.E. et al. (2001). Linkage disequilibrium in the human genome. Nature, 411(6834), 199–204. https://doi.org/10.1038/35075590Rodríguez-Ramilo, S.T., Elsen, J.M. & Legarra, A. (2019). Inbreeding and effective population size in French dairy sheep: Comparison between genomic and pedigree estimates. Journal of Dairy Science, 102(5), 4227–4237. https://doi.org/10.3168/jds.2018-15405Sabeti, P.C. et al. (2002). Detecting recent positive selection in the human genome from haplotype structure. Nature, 419(6909), 832–837. https://doi.org/10.1038/nature01140Saravanan, K.A. et al. (2020). Selection signatures in livestock genome: A review of concepts, approaches and applications. Livestock Science, 241, 104257. https://doi.org/10.1016/j.livsci.2020.104257Schiavo, G. et al. (2020). 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Effect of feeding conditions on the quality traits of rainbow trout

 The effect of use of complete feed with different protein levels on the morphological composition of the body and the amino acid content of trout meat proteins is studied in the article. For this purpose, five experimental groups were formed by the analog method. The study lasted 210 days and was divided into two periods: equalizing (10 days) and basic (200 days).  In the equalizing period, the trial fish consumed feed of the control group. In the basic period, the level of protein in the feed of trout of the experimental groups was regulated by changing individual components of the feed. Feeding of rainbow trout in the study period was performed 4-6 times a day, in the day time at regular intervals. The required amount of feed was calculated according to the indicators of individual fish weight and ambient temperature at the time of feeding. Rearing of commercial two-year-old ones was performed in ponds with an area of 100 m2 at a fish-holding density of 50 specimens/m2 and a water level of 1 m. The total number of trout in experimental studies was 25 thousand specimens. The use of feed with high crude protein content in the period of commercial rainbow trout rearing improves their commercial properties, while fish feeding with feed with crude protein content at the level of 44% leads to a decrease in their productivity. Keywords: rainbow trout, fish feeding, protein, morphological composition, amino acid conten

Comparison of pig classification using Fat-O-Meater in Slovakia

Article Details: Received: 2021-02-09 | Accepted: 2021-04-01 | Available online: 2021-09-30 https://doi.org/10.15414/afz.2021.24.03.238-242Pig carcass classification is based on instrumental prediction of lean meat content and application of the common SEUROP scale. Each member country uses an authorised apparatus with respective regression equation to predict the lean meat content. These equations may differ between countries since they are calculated on different populations. Differences in equations may lead to different predictions of lean meat content. In Slovakia, a significant portion of slaughtered fatteners come from abroad, especially from the Czech Republic and Hungary. Since the same apparatus is approved in neighbouring countries, our study was aimed on the Fat-O-Meater and the comparison of lean meat prediction using three equations from neighbouring countries. Overall, the Slovak equation overestimated the lean meat content by 2.1% compared to the equation from Czech Republic and 2.56% compared to the equation from Hungary. Higher differences were observed in the R, O, P classes and lower differences were observed in the S, E, U classes when individual classes were considered. Different predicted lean meat content led to different carcass distribution over the SEUROP classes. Most visible changes were in the S and E classes. These changes suggest that the inclusion of carcasses from different suppliers should be considered in the authorisation trial.Keywords: SEUROP, grading, lean meat content, backfat thickness, muscle thickness, FOMReferencesCommission Decision 2009/622/EC of 20 August 2009 authorising methods for grading pig carcases in Slovakia (OJ L 224, 27.8.2009, pp. 11–14).Commission Decision 2005/1/EC of 27 December 2004 authorising methods for grading pig carcases in the Czech Republic (OJ L 1, 4. 1. 2005, pp. 8–11), as amended by the Commission Implementing Decision 2013/187/EU.Commission Decision 2005/382/EC of 18 May 2005 authorising methods for grading pig carcases in Hungary (OJ L 126, 19.5.2005, pp. 55–58), as amended by the Commission Implementing Decision 2011/507/EU.David, L., Pulkrábek, J., & Vališ, L. (2014). Pig carcass value parameters analysed within the context of SEUROP grading system. Research in pig breeding, 8(2), 1–3.Engel, B., Lambooij, E., Buist, W. G., & Vereijken, P. (2012). Lean meat prediction with HGP, CGM and CSB-Image-Meater, with prediction accuracy evaluated for different proportions of gilts, boars and castrated boars in the pig population. Meat Science, 90(2), 338–344. https://doi.org/10.1016/j.meatsci.2011.07.020Eurostat. (2020). Slaughtering in slaughterhouses/ annual data/pigmeat [Internet]. [Cited 2020 Dec 15] Available from: http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=apro_mt_pann&lang=enFont i Furnols, M., & Gispert, M. (2009). Comparison of different devices for predicting the lean meat percentage of pig carcasses. Meat Science, 83(3), 443–446. https://doi.org/10.1016/j.meatsci.2009.06.018Font-i-Furnols, M., Čandek-Potokar, M., Daumas, G., Gispert, M., Judas, M., & Seynaeve, M. (2016). Comparison of national ZP equations for lean meat percentage assessment in SEUROP pig classification. Meat Science, 113, 1–8. http://doi.org/10.1016/j.meatsci.2015.11.004Fortin, A., Jones, S. D. M., & Haworth, C. R. (1984). Pork carcass grading: A comparison of the New Zealand Hennessy Grading Probe and the Danish Fat-O-Meater. Meat Science, 10(2), 131–144. https://doi.org/10.1016/0309-1740(84)90065-2Krška, P., Bahelka, I., Demo, P., & Peškovičová, D. (2002). Meat content in pigs estimated by various methods and compared with objective lean meat content. Czech Journal of Animal Science, 47(5), 206–211.Kvapilík, J., Přibyl, J., Růžička, Z., & Řehák, D. (2009). Results of pig carcass classification according to SEUROP in the Czech Republic. Czech Journal of Animal Science, 54(5), 217–228. https://doi.org/10.17221/1662-CJASLisiak, D., Borzuta, K., Janiszewski, P., Magda, F., Grześkowiak, E., Strzelecki, J., & Lisiak, B. (2012). Verification of regression equations for estimating pork carcass meatiness using CGM, IM03, Fat-O-Meat’er II and UltraFom 300 devices. Annals of Animal Science, 12(4), 585–596. https://doi.org/10.2478/v10220-012-0049-8Lowe, B. K., Clark, D. L., Boler, D. D., Dilger, A. C., McKeith, F. K., Eggert, J. M., & Killefer, J. (2011). Characterization of loin shape from Duroc and Duroc composite finishing gilts. Meat Science, 87(2), 146–150. https://doi.org/10.1016/j.meatsci.2010.10.004National Food Chain Safety Office (NFCSO). (2017): A  minősítésre kötelezett vágóhidak sertésvágásának alakulása 2016-ban. Available at: https://sertesinfo.aki.gov.hu/publikaciok/publikacio/a:1045/A+min%C5%91s%C3%ADt%C 3%A9sre+k%C3%B6telezett+v%C3%A1g%C3%B3hidak+sert%C3%A9sv%C3%A1g%C3%A1s%C3%A1nak+alakul%C3%A1sa+2016-banNissen, P. M., Busk, H., Oksama, M., Seynaeve, M., Gispert, M., Walstra, P., & Olsen, E. (2006). The estimated accuracy of the EU reference dissection method for pig carcass classification. Meat Science., 73(1), 22–28. https://doi.org/10.1016/j.meatsci.2005.10.009Olsen, E. V., Candek-Potokar, M., Oksama, M., Kien, S., Lisiak, D., & Busk, H. (2007). On-line measurements in pig carcass classification: Repeatability and variation caused by the operator and the copy of instrument. Meat Science, 75(1), 29– 38. https://doi.org/10.1016/j.meatsci.2006.06.011Szőllősi, L., Molnár, S., Ladányi, K., Karnai, L., & Szűcs, I. (2017). Cost analysis of pig slaughtering: A hungarian case study. Applied Studies in Agribusiness and Commerce, 11(3–4), 121–130. https://doi.org/10.19041/APSTRACT/2017/3-4/17Tomka, J., Demo, P., Gondeková, M., & Salagová, Z. (2021). The analysis of pig carcass classification in Slovakia. Czech Journal of Animal Science, 66(3), 78–86. https://doi.org/10.17221/231/2020-CJA

Candidate genes for congenital malformations in pigs

Received: 2021-06-07 | Accepted: 2021-06-21 | Available online: 2021-12-31https://doi.org/10.15414/afz.2021.24.04.309-314Congenital malformations occur in numerous pig breeding programs. Clinical symptoms, etiopathogenesis and candidate genes of the most critical congenital malformations in pigs were briefly overviewed in the study. Based on the recent literature, identifying and evaluating the genomic regions associated with defects, such as splay legs syndrome, hernias, cryptorchidism, atresia ani, kyphosis, intersexuality, and malignant melanoma, can enhance the selection response. As promising genes were published e.g. NREP, FBXO32, and HOMER1 for splay leg syndrome, SRC, OSM, COL family, and CGRP for hernias, GNRHR, GATA2, and RLF for cryptorchidism, and GLI2 for atresia ani. Potential candidate genes associated with defects were mainly detected in literature by the genome-wide association approach. Reviewing the studies and following the suggestions in some of papers it is indicated the necessity for molecular and more comprehensive evaluation in terms of the sample standardisation and accurate phenotyping of a broad spectrum of populations and breeds. Moreover, knowledge transmission among all livestock species and humans is recommended in literature to better understand malformation biology.Keywords: swine, congenital defects, health, association studies, genomic selectionReferencesAtkinson, M. et al. (2017). Evaluation of the effect of umbilical hernias on play behaviors in growing pigs. Canadian Veterian Journal, 58, 1065–1072.Bourneuf, E. et el. (2018). New susceptibility loci for cutaneous melanoma risk and progression revealed using a porcine model. Oncotarget, 9(45), 27682–27697. https://www.oncotarget.com/article/25455/text/Brening, B. et al. (2015). Porcine SOX9 gene expression is influenced by an 18bp indel in the 5’-untranslated region. PLoS ONE, 10(10), e0139583. https://doi.org/10.1371/journal.pone.0139583Cassini, P. et al. (2005). Genetic analysis of anal atresia in pigs: evidence for segregation at two main loci. Mammalian Genome, 16(10), 164–170. https://doi.org/10.1007/s00335-004-3024-6Ding, N.S. et al. (2009). A genome-wide scan reveals candidate susceptibility loci for pig hernias in an intercross between white Duroc and Erhualian. Journal of Animal Science, 87(8), 2469–2474. https://doi.org/10.2527/jas.2008-1601Du, Z.Q. et al. (2009). Association and haplotype analyses of positional candidate genes in five genomic regions linked to scrotal hernia in commercial pig lines. PLoS One, 4(3), 4837. https://doi.org/10.1371/journal.pone.0004837Grindflek, E. et al. (2018). Genome-wide association study reveals a QTL and strong candidate genes for umbilical hernia in pigs on SSC14. Genomics, 19, 412. https://doi.org/10.1186/s12864-018-4812-9Grindflek, E. et al. (2006). Genome-wide linkage analysis of inguinal hernia in pigs using affected sib pairs. BMC Genetics, 7, 25. https://doi.org/10.1186/1471-2156-7-25Hao, X. et al. (2017). Genome-wide association study identifies candidate genes for piglet splay leg syndrome in different populations. BMC Genetics, 18, 64. https://doi.org/10.1186/s12863-017-0532-4Hori, T. et al. (2001). Mapping loci causing susceptibility to anal atresia in pigs, using a resource pedigree. Journal of Pediatric Surgery, 36, 1370–1374. https://doi.org/10.1053/jpsu.2001.26373Jin, Q. et al. (2013). Molecular characterization and genomewide mutations in porcine anal atresia candidate gene GLI2. Mammalian Genome, 24, 500–507. https://link.springer.com/article/10.1007%2Fs00335-013-9485-8Krupová, Z. et al. (2017). New breeding objectives for the Czech pig population. Indian Journal of Animal Sciences, 87(6), 778–781.Liao, X. et al. (2015). Susceptibility loci for umbilical hernia in swine detected by genome-wide association. Russian Journal of Genetics, 51(10), 1000–1006. https://doi.org/10.1134/S1022795415100105Lindholm-Perry, A.K. et al. (2010). Genomic regions associated with kyphosis in swine. BMC Genetics, 11, 112. https://doi.org/10.1186/1471-2156-11-112Long, Y. et al. (2016). A genome-wide association study of copy number variations with umbilical hernia in swine. Animal Genetics, 47, 298–305. https://doi.org/10.1111/age.12402Mahmud, M.A. et al. (2015). Cryptorchidism in mammals – a review. Global Journal of Animal Scientific Research, 3(1), 128–135.Mattsson, P. (2011). Prevalence of congenital defects in Swedish Hampshire, Landrace and Yorkshire pig breeds and opinions on their prevalence in Swedish commercial herds (MSc Thesis). Sweden, Uppsala: Swedish University of Agricultural Sciences, 35 p.Maak, S. et al. (2009). Identification of candidate genes for congenital splay leg in piglets by alternative analysis of DNA microarray data. International Journal of Biological Sciences, 5(4), 331–337. https://www.ijbs.com/v05p0331.htmMisdorp, W. (2003). Congenital and hereditary tumours in domestic animals. 2. Pigs. A review. Veterinary Quarterly, 25(1), 17–30. https://doi.org/10.1080/01652176.2003.9695141Moravčíková, N. and Kasarda, R. (2020). Use of High-density SNP analyses to develop a long-term strategy for conventional populations to prevent loss of diversity – review. Acta fytotechnica et zootechnica, 23, 236–240. https://doi.org/10.15414/afz.2020.23.04.236-240Morey-Matamalas, A. et al. (2021). Neoplastic lesions in domestic pigs detected at slaughter: literature review and a 20-year review (1998–2018) of carcass inspection in Catalonia. Porcine Health Management, 7, 30. https://doi.org/10.1186/s40813-021-00207-0Nowacka-Woszuk, J. (2021). The genetic background of hernia in pigs: A review. Livestock Science, 244, 104317. https://doi.org/10.1016/j.livsci.2020.104317Papatsiros, V.G. (2012). The splay leg syndrome in piglets: a review. American Journal of Animal and Veterinary Sciences, 7(2), 80–83.Prunier, A. et al. (2009). High physiological demands in intensively raised pigs: impact on health and welfare. Animal, 4(6), 886–898. https://doi.org/10.1017/S175173111000008XQiushi, J. et al. (2013). Molecular characterisation and genome-wide mutations in porcine anal atresia candidate gene GLI2. Mammalian Genome, 24, 500–507. https://doi.org/10.1007/s00335-013-9485-8Rohrer, G.A. et al. (2015). A study of vertebra number in pigs confirms the association of vertnin and reveals additional QTL. BMC Genetics, 16,129. https://doi.org/10.1186/s12863-015-0286-9Rousseau, S. et al. (2013). A Genome-wide association study points out the causal implication of SOX9 in the sex-reversal phenotype in XX pigs. PLoS ONE, 8(11), e79882. https://doi.org/10.1371/journal.pone.0079882Schumacher, T. et al. (2021). Congenital splay leg syndrome in piglets – current knowledge and a new approach to etiology. Frontiers in Veterinary Science, 8, 609883. https://doi.org/10.3389/fvets.2021.609883Sevillano, C.A. et al. (2015). Genome-wide association study using deregressed breeding values for cryptorchidism and scrotal/inguinal hernia in two pig lines. Genetics Selection Evolution, 47, 18. https://doi.org/10.1186/s12711-015-0096-6Stenberg, H. et al. (2020). A review of congenital tremor type A-II in piglets. Animal Health Research Reviews, 21, 84–88. https://doi.org/10.1017/S146625232000002XSzczerbal, I. et al. (2019). Elevated incidence of freemartinism in pigs detected by droplet digital PCR and cytogenetic techniques. Livestock Science, 219, 52–56. https://doi.org/10.1016/j.livsci.2018.11.009Tomboc, M. et al. (2000). Insulin-like 3/Relaxin-like factor gene mutations are associated with cryptorchidism. The Journal of Clinical Endocrinology & Metabolism, 85(11), 4013–4018. https://doi.org/10.1210/jcem.85.11.6935Wiedemann, S. et al. (2005). Genome-wide scan for anal atresia in swine identifies linkage and association with a chromosome region on Sus scrofa chromosome 1. Genetics, 171(3), 1207–1217. https://doi.org/10.1534/genetics.104.032805Wu, T. et al. (2018). Transcriptome analysis reveals candidate genes involved in splay leg syndrome in piglets. Journal of Applied Genetics, 59, 475–83. https://doi.org/10.1007/s13353-018-0454-5Xu, S. et al. (2018). Polymorphisms of HOMER1 gene are associated with piglet splay leg syndrome and one significant SNP can affect its intronic promoter activity in vitro. BMC Genetics, 19, 110. https://doi.org/10.1186/s12863-018-0701-0Xu, W. et al. (2019). Rediscover and refine QTLs for pig scrotal hernia by increasing a specially designed F3 population and using whole-genome sequence imputation technology. Frontiers in Genetics, 10, 890. https://doi.org/10.3389/fgene.2019.00890Žáková, E. et al. (2020). System of collection and storage of health data in the performance testing of pigs. Certified methodology. Prague: Institute of Animal Science, 17 p. http://vuzv.cz/en/publications/system-sberu-a-uchovanizdravotnich-dat-v-kontrole-uzitkovosti-prasat. In Czech

The effect of different vegetable oils on energy content of table eggs yolk

Article Details: Received: 2020-08-31 | Accepted: 2020-11-16 | Available online: 2021-06-30https://doi.org/10.15414/afz.2021.24.02.137-140The aim of this study was to analyse the gross energy (GE) value of egg yolk from hens feed with different vegetable oils addition and based on gained results calculate the linear regression between GE and dry matter % (DM) in yolk. Total 66 hens Lohmann brown lite were divided in to 11 groups according to concentration and type of used vegetable oil (pumpkin oil 3%, flax seed oil 3%, indian hemp seed oil 2.5% and 5%, grape seed oil 2.5% and 5%, olive oil 2.5 and 5%, apricot seed oil 2.5% and 5%). Hens were in 40th week of life and were housed per 6 in cage. From each group eight eggs were randomly selected. In total 88 egg yolks were separated and analysed for DM and GE content. The highest yolk GE was detected in group with 3% pumpkin oil addition (1639 kJ/100g) followed by groups with 2.5 and 5% indian hemp seed oil addition 1632 and 1632 kJ/100g, respectively. Difference between these three groups compared to yolk GE content (1584 kJ/100g) in control group was significant (P0.05). GE concertation of yolk can be calculated as follows: GE = -17.34 + (32.73 * DM), R2 = 0.819.Keywords: laying hens, egg yolk gross energy, regressionReferencesAntova, G. A. et al. (2019). Comparative analysis of nutrient content and energy of eggs from different chicken genotypes. Journal of the Science of Food and Agriculture, 99(13), 5890–5898. https://doi.org/10.1002/jsfa.9863AOAC. (2000). Official methods of analysis AOAC. International 17th edition. Association of Analytical Communities, Gaithersburg.Benková, J. (2008). Artificial hatching of poultry is nothing simple. Slovenský chov, 13(6), 45-47. In Slovak.Gálik, B.et al. (2014). The effect of dietary Rhus coriaria L. on table eggs yolk nutrients composition. Acta fytotechnica et zootechnica, 17(3), 93–95. https://doi.org/10.15414/afz.2014.17.03.93-95Herkeľ, R. et al. (2016). Fatty acid profile and nutritional composition of table eggs after supplementation by pumpkin and flaxseed oils. Acta Veterinaria Brno, 85(3), 277–283. https://doi.org/10.2754/avb201685030277Hrnčár, C. & Bujko, J. (2012). Effect of pre-storage incubation of hatching eggs on hatchability of poultry. Acta fytotechnica et zootechnica, 15(2), 34-37. http://www.acta.fapz.uniag.sk/journal/index.php/on_line/article/view/31Javad, N. et al. (2011). Effects of amino acids and metabolizable energy on egg characteristics and broiler breeder performance. African Journal of Biotechnology, 10(49), 10066–10071. https://doi.org/10.5897/ajb11.1268Noble, R. C. et al. (1996). Yolk lipids and their fatty acids in the wild and captive ostrich (Struthio camelus). Comparative Biochemistry and Physiology Part B: Biochemistry and Molecular Biology, 113(4), 753–756. https://doi.org/10.1016/0305-0491(95)02097-7Pearson, R. A. & Herron, K. M. (1981). Effects of energy and protein allowances during lay on the reproductive performance of broiler breeder hens. British Poultry Science, 22(3), 227–239. https://doi.org/10.1080/00071688108447881Pištěková, V. et al. (2011). The quality comparison of eggs laid by laying hens kept in battery cages and in a deep litter system. Czech Journal of Animal Science, 51(7), 318–325. https://doi.org/10.17221/3945-cjasRadu-Rusu, R. et al. (2014). Chemical features, cholesterol and energy content of table hen eggs from conventional and alternative farming systems. South African Journal of Animal Science, 44(1), 33. https://doi.org/10.4314/sajas.v44i1.5Roe, M. et al. (2013). Nutrient analysis of eggs. Analytical Report (revised version). UK Government, Department of Health and Social Care. Retrieved December 10, 2020 from https://assets.publishing.service.gov.uk/government/uploads/system/ uploads/attachment_data/file/167973/Nutrient_analysis_of_ eggs_Analytical_Report.pdfRoztočilová, A. et al. (2018). Effect of purple wheat RU 687- 12 on performance parameters of laying hens at the end of the lay. In NutriNET 2018. Proceedings of reviewed scientific papers. Mendel University in Brno (pp. 92–97).Vojtaššáková, A. et al. (2000). Milk and eggs. Food nutrition tables. Výskumný ústav potravinársky, Bratislava. In Slovak.Van der Wagt, I. et al. (2020). A review on yolk sac utilization in poultry. Poultry Science, 99(4), 2162–2175. https://doi.org/10.1016/j.psj.2019.11.041Zhang, Y. (2016). Studies on chicken hatchability and its relation with egg yolk metabolites. Dissertation thesis. GeorgAugust-University, Göttingen

Nutritional indicators in the technological process of sausage processing

Received: 2020-09-29 Accepted: 2021-02-08 Available online: 2021-02-28https://doi.org/10.15414/afz.2021.24.mi-apa.15-20According to biological and nutritional value, meat and meat products are among the most important components of humannutrition. The risk of meat contamination is a great concern from the point of view of food safety, and especially human health. Theaim of this study was the determination of nutritional values in meat samples of fresh and smoked sausage. From a technologicalpoint of view, the water content was the highest in meat samples and continually decreased in the samples that underwentprocessing. The water content of the meat samples was 68.2%. In the samples of unsmoked and smoked sausages, the measuredvalues were slightly lower. In the samples of unsmoked sausages, the water content was 63.1%. As the water content decreased,the fat content of the sausages increased. The protein content has not changed significantly in the production process. In the meatthe value of proteins was 19.07 g 100 g-1 and in the samples of smoked sausages the result was 18.78 g 100 g-1. The content ofessential fatty acids was the highest in meat samples. This value decreased in unsmoked as well as smoked sausages. Cholesterollevels were rising over the course of the experiment. Results of this study clearly show difference in technological parametersrelated to technological process.Keywords: meat, sausage, technological process, nutritional indicatorsReferencesAngelovičová, M. et al. (2016). Comparison of fatty acid profile in the chicken meat after feeding with narasin, nicarbazin andsalinomycin sodium and phyto-additive substances. Journal of Environmental Science and Health, Part B, 51(6), 374–382. https://doi.org/10.1080/03601234.2016.1142320ČUBOŇ, J. et al. (2012). Hodnotenie surovín a potravín živočíšneho pôvodu. Nitra : Slovak University of Agriculture, 381 p.ČUBOŇ, J. et al. (2019) Protein degradation and fat oxidation changes in salted meat processing. Journal of Microbiology,Biotechnology and Food Sciences, 9(6), 376–379. https://doi.org/10.15414/jmbfs.2019.9.special.376-379COLE, L. J. et al. (2020). A critical analysis of the potential for EU Common Agricultural Policy measures to support wild pollinatorson farmland. Journal of Applied Ecology, 57(4), 681–694. https://doi.org/10.1111/1365-2664.13572 DEBRECENI, O. et al. (2016). Comparison the physicochemical quality indicators of Musculus longissimus Dorsi from MangalitsaBreed and their crossbreeds. Journal of Central European Agriculture, 17(4), 1253–1263. https://doi.org/10.5513/jcea01/17.4.1840DELGADO, C. L. (2003). Rising consumption of meat and milk in developing countries has created a new food revolution. TheJournal of Nutrition, 133(11), 3907S–3910S. https://doi.org/10.1093/jn/133.11.3907SGRIFFITHS, P.; DE HASSETH, J. A. (2007). Fourier transform infrared spectrometry. 2nd ed., Wiley-Blackwell.GÓMEZ, I. et al. (2020). The effects of processing and preservation technologies on meat quality: Sensory and nutritionalaspects. Foods, 9, 1416. https://doi.org/10.3390/foods9101416GRUSAK, M. A. et al. (1999). Improving the nutrient composition of plants to enhance human nutrition and health. AnnualReview of Plant Biology, 50(1), 133–161. https://doi.org/10.1146/annurev.arplant.50.1.133GUPTA, V. et al. (2017). Lifestyle, Stress, and Disorders. Basic and Applied Aspects of Biotechnology. Springer : Singapore, pp. 475–486. https://doi.org/10.1007/978-981-10-0875-7_22Haščík, P. et al. (2019a). Spracovanie hydiny a minoritných živočíšnych produktov. Nitra : Slovak University of Agriculture, 176 p.HAŠČÍK, P. et al. (2019b). The profile of fatty acids in chicken’s meat after humic acid and phytobiotics application. Journalof Microbiology, Biotechnology and Food Sciences, 9(6), 439–444. https://doi.org/10.15414/jmbfs.2019.9.special.439-444HIRD, S. J. et al. (2014). Liquid chromatography-mass spectrometry for the determination of chemical contaminants in food.TrAC Trends in Analytical Chemistry, 59, 59–72. https://doi.org/10.1016/j.trac.2014.04.005IMRICH, I. et al. (2020). Comparison of the physico-chemical meat quality of the breeds Mangalitsa and Large white with regardto the slaughter weight. Potravinarstvo Slovak Journal of Food Sciences, 14, 135–141. https://doi.org/10.5219/1334JIMÉNEZ-COLMENERO, F. et al. (2001). Healthier meat and meat products: Their role as functional foods. Meat Science, 59, 5–13.https://doi.org/10.1016/S0309-1740(01)00053-5KROČKO, M. et al. (2016). Effect of spices commercial mixture with GDL on the quality of fermented dry-cured sausages. SlovakJournal of Food Sciences, 10(1), 295–299. https://doi.org/10.5219/603LÍPOVÁ, P. et al. (2019). Efect of intramuscular fat content on physical-chemical parameters of pork from Mangalitsa and theircrossbreed. Potravinarstvo Slovak Journal of Food Sciences, 13(1), 422–428. https://doi.org/10.5219/1095ORZECHOWSKA, B. et al. (2008). Relationships between muscle fibre characteristics and physico-chemical properties oflongissimus lumborum muscle and growth rate in pig fatteners of three breeds. Animal Science Papers and Reports, 26(4), 277–285.PREZIOSI, P. et al. (1998). Effects of supplementation with a combination of antioxidant vitamins and trace elements, atnutritional doses, on biochemical indicators and markers of the antioxidant system in adult subjects. Journal of the AmericanCollege of Nutrition, 17(3), 244–249. https://doi.org/10.1080/07315724.1998.10718754SHARMA, M. et al. (2009). Occupational lifestyle diseases: An emerging issue. Indian Journal of Occupational and EnvironmentalMedicine, 13(3), 109. https://doi.org/10.4103/0019-5278.58912STEINHAUSEROVÁ, I. et al. (2015) Hygiene and sanitation in meat production. Meat, 4, 7–13.STOLL-KLEEMANN, S. et al. (2017). Reducing meat consumption in developed and transition countries to counter climatechange and biodiversity loss: a review of influence factors. Regional Environmental Change, 17(5), 1261–1277. https://doi.org/10.1007/s10113-016-1057-5ZAJÁC, P. et al. (2015). Analysis of texturometric properties of selected traditional and commercial sausage. PotravinarstvoSlovak Journal of Food Sciences, 9(1), 458–467. https://doi.org/10.5219/47

Plasma chemical method of extending the apples shelf life

Article Details: Received: 2020-12-21 | Accepted: 2021-02-10 | Available online: 2021-09-30 https://doi.org/10.15414/afz.2021.24.03.202-205 The efficiency of using ozone and plasma chemical technology to reduce the concentration of ethylene impurities to extend the shelf life of apples has been studied. The ozone concentration was measured by sensors located in the experimental box. The ethylene concentration was measured with an ICA56 meter (in the experimental box) and monitored by sampling from the circulation lines of both boxes. The ICA56 meter use electrochemical sensor with ethylene resolution 0.2 ppm. This sensor have cross sensitivities for CO (40%), ethanol (72%), CO2 (0%), H2 S (220%) and its reason use control method of measuring ethylene. Control samples were analyzed with a Thermo Scientific Trace 1310 gas chromatograph with a flame ionization detector. The chromatograph was pre-calibrated with calibration gas mixtures with ethylene content of 10 and 100 ppm. It has been shown that Gala, McIntosh and Jonathan apples are stored several times better when the air in which apples are stored is treated with a plasma-chemical system. After 40 days of storage in the control box, the weight of apples acceptable for consumption (absence of rot and mold) was for varieties Gala – 3.3 kg (31%), Jonathan – 2.1 kg (15.6%), McIntosh – 2 kg (20%). In the experimental boxing varieties Gala – 12.1 kg (66.4%), Jonathan – 10.2 kg (59.3%), McIntosh – 9.3 kg (52.5%). Thus, the combined plasma-ozone method of air treatment of stored apples has shown high efficiency and has prospects for use.Keywords: plasma treatment, barrierless plasma chemical reactor, ethylene ReferencesBagher, H. et al. (2020). Effect of Cold Plasma on Quality Retention of Fresh-Cut Produce. Journal of Food Quality, 8. https://doi.org/10.1155/2020/8866369Crocker, W. et al. (1935). Similarities in the effects of ethylene and the plant auxins. Contrib. Boyce Thompson inst., 7, 231–248.Concello, A. et al. (2005). Effect of chilling on ethylene production in eggplant fruit. Food Chemistry, 92, 63–69.  https://doi.org/10.1016/j.foodchem.2004.04.048Dong, L. et al. (2002). Effect of 1-methylcyclopropene on ripening of ‘Canino’ apricots and ‘Royal Zee’ plums. Postharvest Biology and Technology, 24, 135–145. https://doi.org/10.1016/S0925-5214(01)00130-2Golden, K. (2014). Ethylene in Postharvest Technology: A  Review. Asian Journal of Biological Sciences, 7(4), 135–143. https://doi.org/10.3923/ajbs.2014.135.143Golota, V. et al. (2003). Patent US #6,544,486 B2 Date 04/18/2003. Golota, V. et al. (2018), Decomposition of ethylene in low temperature plasma of barrierless discharge. Problems of Atomic Sci. and Technol. Ser. Plasma Electronics and New Methods of Acceleration, №4 (116), 160–163. http://dspace.nbuv.gov.ua/handle/123456789/147342Golota, V. et al. (2018). The use of ozone technologies in grain storage. Problems of Atomic Science and Technology, 116(4), 185–188. http://dspace.nbuv.gov.ua/handle/123456789/149325Ma, L. et al. (2017). Recent developments in novel shelf life extension technologies of fresh-cut fruits and vegetables. Trends in Food Science & Technology, 64, 23–38. https://doi.org/10.1016/j.tifs.2017.03.005Miller, F. A. et al. (2013). Review on Ozone-Based Treatments for Fruit and Vegetables Preservation. Food Eng Rev, (5), 77–106. https://doi.org/10.1007/s12393-013-9064-5Nakatsuka, A. et al. (1998). Differential Expression and Internal Feedback Regulation of 1-Aminocyclopropane-1- Carboxylate Synthase, 1-Aminocyclopropane-1-Carboxylate Oxidase, and Ethylene Receptor Genes in Tomato Fruit during Development and Ripening. Plant Physiol, 118, 1295–1305. https://doi.org/10.1104/pp.118.4.1295Skog, L. J. et al. (2001). Effect of ozone on qualities of fruits and vegetables in cold storage. Canadian Journal of Plant Science, 81(4), 773–778. https://doi.org/10.4141/P00-110Taran, G.V. et al. (2019). Plasma-chemical methods for control of biotic contaminants. Problems of Atomic Sci. and Technol. Ser. Plasma Electronics and New Methods of Acceleration, 2019, №4 (122), 198–202. https://vant.kipt.kharkov.ua/ARTICLE/ VANT_2019_4/article_2019_4_198.pd