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Record W2784757425 · doi:10.15414/afz.2017.20.04.95-98

Fatty acid composition of maize silages from different hybrids

2017· article· en· W2784757425 on OpenAlexaboutno aff
Miroslav Juráček, Dániel Bíró, Milan Šimko, Branislav Gálik, Michal Rolinec, Ondrej Hanušovský, Ondrej Pastierik, Adriana Píšová, Norbert Andruška

Bibliographic record

VenueActa fytotechnica et zootechnica/Acta fytotechnica et zootechnica · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural and Food Production Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSilagePalmitic acidHybridLinoleic acidFatty acidOleic acidFood scienceDry matterPolyunsaturated fatty acidChemistryAgronomyForageBiologyAnimal scienceBiochemistry

Abstract

fetched live from OpenAlex

Received: 2016-12-13 | Accepted: 2016-12-18 | Available online: 2017-12-31 http://dx.doi.org/10.15414/afz.2017.20.04.95-98 The aim of this research was to determine the fatty acid content in maize silages of different hybrids. Grain hybrid with FAO number 420 and silage hybrid with stay-green maturation with FAO number 450 were evaluated. Maize hybrids were grown under the same agro-ecological conditions, and harvested on growing degree days 1277 (FAO 420) and 1297 (FAO 450). Whole-plant maize was chopped to 10 mm by harvester with kernel processor and immediately ensiled in plastic barrels (volume 50 dm 3 ). Maize matter was ensiled without silage additives. For fatty acids analyses samples of maize silages were taken after 8 week of ensiling. Content of fatty acids was quantified by gas chromatography. Examined maize of both hybrids had the highest linoleic acid content, followed by oleic acid and third highest content of palmitic acid. The results confirmed differences in fatty acid content in maize silages of different hybrids. In silages of grain hybrid was detected significantly higher content of palmitic acid and cis-11-eicosenoic acid and significantly lower content of oleic acid in compared with silage of silage hybrid. This ultimately resulted in a higher polyunsaturated fatty acids content (P < 0.05) in maize silage from grain hybrid and lower monounsaturated fatty acids content (P < 0.05) in maize silage from stay green hybrid.  Keywords: fatty acid, maize, hybrid, silage References Alezones, J. et al. (2010) Caracterización del perfil de ácidos grasos en granos de híbridosde maíz blanco cultivados en Venezuela. Archivos Latinoamericanos de Nutricion , vol. 60, no. 4, pp. 397–404. Alves, S.P. et al. (2011) Effect of ensiling and silage additives on fatty acid composition of ryegrass and corn experimental silages. Journal of Animal Science , vol. 89, no. 8, pp. 2537–2545. doi: https://dx.doi.org/10.2527/jas.2010-3128 Arvidsson, K., Gustavsson, A.-M. and Martinsson, K. (2009) Effects of conservation method on fatty acid composition of silage. Animal Feed Science and Technology , vol. 148, no. 2–4, pp. 241–252. http://dx.doi.org/10.1016/j.anifeedsci.2008.04.003 Balušíková, Ľ. et al. (2017) Fatty acids of maize silages of different hybrids. In NutriNet 2017 . České Budějovice: University of South Bohemia in České Budějovice, pp. 13–19. Bíro, D. et al. (2014) Conservation and adjustment of feeds. Nitra: Slovak University of Agriculture. 223 p. (in Slovak). Blažková, K. et al. (2012) Comparison of in vivo and in vitro digestibility in horses. In Koně 2012 . České Budějovice: University of South Bohemia in České Budějovice, pp. 1–7. Boufaïed, H. et al. (2003) Fatty acids in forages. I. Factors affecting concentrations. Canadian Journal of Animal Science , vol. 83, no. 3, pp. 501–511. doi: http://dx.doi.org/10.4141/a02-098 Capraro, D. et al. (2017) Feeding finishing heavy pigs with corn silages: effects on backfat fatty acid composition and ham weight losses during seasoning. Italian Journal of Animal Science , vol.16, no. 4, pp. 588–592. doi: http://dx.doi.org/10.1080/1828051x.2017.1302825 Commission Regulation (EC) No 152/2009 of 27 January 2009 laying down the methods of sampling and analysis for the official control of feed. L 54/1. 130 p. Eurostat 1 Green maize by area, production and humidity. [Online] Available from: http://ec.europa.eu/eurostat/tgm/table.do?tab=table&init=1&language=en&pcode=tag00101&plugin=1 [Accessed: 2017- 10-30]. Galassi, G. et al. (2016) Digestibility, metabolic utilisation and effects on growth and slaughter traits of diets containing whole plant maize silage in heavy pigs. Italian Journal of Animal Science , vol. 16, no. 1, pp. 122–131. doi: http://dx.doi.org/10.1080/1828051x.2016.1269299 Glasser, E. et al. (2013) Fat and fatty acid content and composition of forages: a meta-analysis. Animal Feed Science and Technology , vol.185, no. 1–2, pp. 19–34. doi: http://dx.doi.org/10.1016/j.anifeedsci.2013.06.010 Guermah, H., Maertens, L. and Berchiche, M. (2016) Nutritive value of brewersʼ grain and maize silage for fattening rabbits. World Rabbit Science , vol. 24, no. 3, pp. 183–189. doi: http://dx.doi.org/10.4995/wrs.2016.4353 Han, L. and Zhou, H. (2013) Effects of ensiling process and antioxidants on fatty acids concentrations and compositions in corn silages. Journal of Animal Science and Biotechnology , vol. 4, no. 1, pp. 1–7. doi: http://dx.doi.org/10.1186%2f2049-1891-4-48 Kalač, P. and Samková, E. (2010) The effects of feeding various forages on fatty acid composition of bovine milk fat: A review. Czech Journal of Animal Science , vol. 55, no. 12, pp. 521–537. Khan, N.A., Cone, J.W. and Hendriks, W.H. (2009) Stability of fatty acids in grass and maize silages after exposure to air during the feed out period. Animal Feed Science and Technology , vol. 154, no. 3–4, pp. 183–192. doi: http://dx.doi.org/10.1016/j.anifeedsci.2009.09.005 Khan, N.A. et al. (2011) Changes in fatty acid content and composition in silage maize during grain filling. Journal of Science of Food and Agriculture , vol. 91, no.6, pp. 1041–1049. doi: http://dx.doi.org/10.1002/jsfa.4279 Khan, N.A. et al. (2012) Causes of variation in fatty acid content and composition in grass and maize silages. Animal Feed Science and Technology , vol. 174, no. 1–2, pp. 36–45. doi: http://dx.doi.org/10.1016/j.anifeedsci.2012.02.006 KHAN, N.A. et al. (2015) Effect of species and harvest maturity on the fatty acids profile of tropical forages. The Journal of Animal & Plant Sciences , vol. 25, no. 3, pp. 739–746. Kokoszyński, D. et al. (2014) Effect of corn silage and quantitative feed restriction on growth performance, body measurements, and carcass tissue composition in White Kołuda W31 geese. Poultry Science ,   vol. 93, no. 8, pp.1993–1999. doi: http://dx.doi.org/10.3382/ps.2013-03833 Loučka, R. and Tyrolová, Y. (2013) Good practice for maize silaging . Praha: Institute of Animal Science. Mir, P.S. (2004) Fats in Corn Silage. Advanced Silage Corn Management 2004. [Online] Available from: http://www.farmwest.com/chapter-8-quality-of-corn-silage [Accessed: 2017- 10-30]. Mojica-Rodríguez, J.E. et al. (2017) Effect of stage of maturity on fatty acid profile in tropical grasses. Corpoica Ciencia Tecnología Agropecuaria , vol. 18, no.2, pp. 217–232. doi: http://dx.doi.org/10.21930/rcta.vol18_num2_art:623 Nazir, N.A. et al. (2011) Changes in fatty acid content and composition in silage maize during grain filling. Journal of the Science of Food and Agriculture , vol. 91, no. 6, pp.1041–1049. http://dx.doi.org/10.1002/jsfa.4279 Oliveira, M.A. et al. (2012) Fatty acids profile of milk from cows fed different maize silage levels and extruded soybeans. Revista Brasileira de Saúde e Produção Animal , vol. 13, no. 1, pp. 192–203. doi:  http://dx.doi.org/10.1590/s1519-99402012000100017 SAS Institute (2008) Statistical Analysis System Institute, Version 9.2 . SAS Institute, Cary, NC, USA. Van Ranst, G. et al. (2009) Influence of herbage species, cultivar and cutting date on fatty acid composition of herbage and lipid metabolism during ensiling. Grass and Forage Science , vol. 64, no. 2, pp. 196–207. doi: http://dx.doi.org/10.1111/j.1365-2494.2009.00686.x Zeman, L. et al. (2006) Nutrition and feeding of livestock . Praha: Profi Press. 360 p. (in Czech).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Open science, Research integrity
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.308
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0000.001
Science and technology studies0.0020.002
Scholarly communication0.0010.002
Open science0.0060.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.263
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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