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Application of fluorescent markers for homogeneity assessment of grain mixtures based on maize content

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The paper presents test results for the assessment of the tracer content in a three-component (green peas, sorghum, maize) feed mixture that is based on the fluorescent method. The homogeneity of mixtures was determined on the basis of the maize content (as the key component), which was treated with fluorescent substance: tinopal, rhodamine B, uranine and eosin. The key components were wet-treated with fluorescent substances with different concentrations. Feed components were mixed in a vertical funnel-flow mixer. 10 samples were collected from each mixed batch. Samples were placed in a chamber equipped with UV light and, then, an image recorded as BMP file was generated. The image was analysed by means of the software programme Patan. On the basis of the an alyses conducted, data on the maize content marked with a fluorescent marker were obtained. Additionally, the content of the key component was determined in a conventional =using an analytical scale. Results indicate the possibility of using this method for homogeneity assessment of the three-component grain mixture. From these tests, fluorescent substances that can be applied in the case of maize as a key component, together with their minimum concentrations, were identified: tinopal 0.3%, rhodamine B 0.001%.
Rocznik
Strony
505--512
Opis fizyczny
Bibliogr. 28 poz., rys., tab.
Twórcy
  • Opole University of Technology, Department of Biosystems Engineering, ul. Prószkowska 76, 45 - 758 Opole, Poland
  • Wroclaw University of Science and Technology, Department of Information Systems, Wybrzeże Wyspiańskiego 27, 50 - 370 Wroclaw, Poland
Bibliografia
  • 1. Aczel A., D., 2012. Complete business statistics. 8th edition, Wohl Publishing.
  • 2. Alonso M., Alguacil F.J., 1999. Dry mixing and coating of powders. Revista de Metalurgia, 35, 315-328.
  • 3. Berthiaux H., Mosorov V., Tomczak L., Gatumel C., Demeyre J.F., 2006. Principal component analysis for characterising homogeneity in powder mixing using image processing techniques. Chem. Eng. Process., 45, 397- 403. DOI: 10.1016/ j.cep.2005.10.005.
  • 4. Boss J., Krótkiewicz M., Tukiendorf M., 2002. Porównanie metod oceny jakości stanu mieszaniny ziarnistej podczas mieszania w przesypie. Inżynieria Rolnicza , 4 (37), 27-32.
  • 5. Çiftc I., Ercan A., 2003. Effects of diets of different mixing homogeneity on performance and carcass traits of broilers. J. Anim. Feed Sci.,12, 163–171. DOI: 10.22358/jafs/67693/2003.
  • 6. Coppeta J.R., Rogers C.B., 1995. A quantitative mixing analysis using fluorescent dyes. AIAA paper number 0539, American Institute of Aeronautics and Astronautics.
  • 7. Daumann B., Nirschl H., 2008. Assesment of the mixing efficiency of solid mixtures by means of image analysis. Powder Technol., 182, 415-423. DOI: 10.1016/j.powtec.2007.07.006.
  • 8. Djuragic O., Levic J., Sredanovic S., Lević L., 2007. Evaluation of homogeneity in feed by method of microtracer. Archiva Zootechnica, 12 (4), 85- 91.
  • 9. Eisenberg D., 2008. Measuring mixer variation-performance and cross-contamination validation. 16th Annual ASA-IM SEA Feed Technology and Nutrition Workshop, Singapore 26-30 May 2008.
  • 10. Hogg R., 2009. Mixing and segregation in powders: Evaluation, mechanisms and processes. KONA Powder Part.J., 27, 3-17. DOI: 10.14356/kona.2009005.
  • 11. Karumanchi V.,Taylor M.K., Ely K.J., Stagner W.S., 2011. Monitoring powder blend homogeneity using light-induced fluorescence. AAPS PharmSciTech. 2,1031–1037. DOI:10.1208/s12249-011-9667-1.
  • 12. Królczyk J.B., 2016. Homogeneity assessment of multi-element heterogeneous granular mixtures by using Multivariate Analysis of Variance. Tehnicki Vjesnik, 23,383-388. DOI: 10.17559/TV-20151031183255.
  • 13. Królczyk J., Tukiendorf M., 2006. Optymalizacja procesu sporządzania wieloskładnikowej paszy dla gołębi w pionowym mieszalniku z mieszadłem ślimakowym. Agricultural Engineering, 12 (87), 267-275.
  • 14. Lai C.K., Holt D., Leung J.C., Raju G.K., Hansen P., Cooney C.L., 2001.
  • 15. Real-time and non-invasive monitoring of dry powder blend homogeneity. AIChE J. 47, 2618– 2622. DOI: 10.1002/aic.690471124.
  • 16. Matuszek D., 2015. Modelling selected parameters of granular elements in the mixing process. Int. Agrophys., 29, 75-81. DOI: 10.1515/intag-2015-0002.
  • 17. Matuszek D., Szwedziak K., 2013. The use of fluorescent markers in assessing the feed homogeneity. Problems of intensification the animal production with regard to infrastructure, environmental protection and alternative energy production. Monography, Institute of Technology and Life Sciences Warsaw, 160-166 (in Polish).
  • 18. Matuszek D., Tukiendorf M., 2007. Komputerowa analiza obrazu w ocenie mieszania niejednorodnych układów ziarnistych (system funnel-flow). Agricultural Engineering, 2 (90), 183-188.
  • 19. Matuszek D., Tukiendorf M., 2008. Application of roof shaped and double cone inserts in mixing of granular elements in the flow process. Int. Agrophysics., 22, 147-150.
  • 20. Poux M., Lescure M., Steinmetz D., Bertrand J., 1995. Optical sensors for the characterization of powder mixtures. Sens. Actuators: A, 47, 494-496.
  • 21. Przeniosło-Siwczyńska M., Kwiatek K., 2010. Determination of active substances in medicated feedstuffs. Krmiva (Zagreb), 52 (3), 165-169.
  • 22. Realpe A., Velazqez C., 2003. Image processing and analysis for determination of cencentrations of powder mixtures. Powder Technol., 134, 193-200. DOI: 10.1016/S0032-5910(03)00138-4.
  • 23. Rocha A.G., Montanhini R.N., Dilkinb P., Tamiosso C.D., Mallmannb C.A., 2015. Comparison of different indicators for the evaluation of feed mixing efficiency. Anim. Feed Sci. Technol.,209, 249–256. DOI: http://dx.doi.org/10.1016/ j.anifeedsci.2015.09.005.
  • 24. Satoh M., Miya nami K., 1988. Continuous measurement of degree of mixing in powder mixer by an optical method. Bulletin of University of Osaka Prefecture. Series A, Engineering and Natural Sciences, 36 (2), 141-148. Available at: http://hdl.handle.net/10466/8456.
  • 25. StatSoft, Inc. 2015. STATISTICA (data analysis software system), version 12. Available at: www.statsoft.com.
  • 26. Walczyński S., Korol W., 2007. Inter-laboratory investigations on evaluation of industrial fodder mixtures homogeneity. Pol J Food Nutr Sci.,2007,57, 2(A), 187-190.
  • 27. Weinekötter R., Reh L., 1994. Characterization of particulate mixtures by in line measurements. Part. Part. Syst. Char., 11 (4), 284-290. DOI: 10.1002/ppsc.19940110403.
  • 28. Zelko I., Lux A., Sterckeman,T., Martinka M., Kollárová K., Lišková D., 2012. An easy method for cutting and fluorescent staining of thin roots. Ann.Bot., 110, 475 –478. DOI:10.1093/aob/mcs046.
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-27141dfa-d641-4999-b05a-eac7a61277a0
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