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Title:Uporabnost NIR spektroskopije za določanje lastnosti mesa
Authors:Prevolnik, Maja (Author)
ŠKORJANC, DEJAN (Mentor) More about this mentor... New window
ČANDEK-POTOKAR, MARJETA (Co-mentor)
NOVIČ, MARJANA (Co-mentor)
Files:.pdf DR_Prevolnik_Maja_2011.pdf (3,68 MB)
 
Language:Slovenian
Work type:Dissertation (m)
Organization:FKBV - Faculty of Agriculture and Life Sciences
Abstract:V predstavljenih raziskavah smo preucevali uporabnost bližnje infrardece (NIR) spektroskopije za napovedovanje kemijske sestave in kakovosti mesa. Spektralne analize smo izvedli s spektrofotometrom NIR Systems model 6500 (Silver Spring, MD, USA), dobljene podatke pa obdelali s statisticnim programom WinISI II. Kar zadeva kemijsko sestavo, smo napovedovali vsebnost intramuskularne mašcobe, beljakovin, vode, soli, neproteinskega dušika in prostih aminokislin v razlicnih vrstah mesa in mesnih izdelkov, pri cemer smo zaradi velike prakticne vrednosti namenili posebno pozornost dolocanju intramuskularne mašcobe v mesu prašicev in goveda ter napovedovanju kemijske sestave kraškega pršuta. NIR spektroskopija se je za dolocanje kemijske sestave izkazala kot izjemno zanesljiva metoda, ki bi lahko nadomestila konvencionalne kemijske analize. V zvezi s kakovostjo pa smo v mesu prašicev napovedovali tehnološke parametre, kakršni so pH, barva in sposobnost za vezavo vode. Tocnost napovedovanja lastnosti kakovosti mesa je bila v primerjavi s kemijsko sestavo manjša, toda napake napovedovanja so bile primerljive s ponovljivostjo referencnih metod, ki so v tem primeru hitre, enostavne, odvisne od okolja in zato manj natancne. Prednosti NIR spektroskopije (hitrost, nedestruktivnost, hkratnost dolocanja razlicnih lastnosti) skupaj z visoko zanesljivostjo napovedovanja dajejo velike možnosti za dolocanje kakovosti mesa v industriji. Z ustrezno izbiro nekaterih dejavnikov tocnosti (priprava vzorca, spektralno obmocje, vrsta vzorca, kemometricna metoda) lahko uspešnost napovedovanja z NIR spektroskopijo še izboljšamo.
Keywords:NIR spektroskopija, meso, mesni izdelki, kemijska sestava, kakovost mesa
Year of publishing:2011
Source:Maribor
NUK URN:URN:SI:UM:DK:RIDJHYVD
Views:4088
Downloads:333
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Categories:FKBV
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Secondary language

Language:English
Title:Ability of NIR spectroscopy to predict meat characteristics
Abstract:The usefulness of near-infrared (NIR) spectroscopy to predict meat chemical composition and quality was tested. Spectral data were gathered using NIR System model 6500 spectrophotometer (Silver Spring, MD, USA) and statistical package WinISI II was used to analyse data. Within chemical composition, the content of intramuscular fat, protein, water, salt, non-protein nitrogen and free amino acid composition was predicted in different meats and meat products. Due to high practical importance, special attention was given to the prediction of intramuscular fat content in pork and beef and to the prediction of Kraški pršut dry ham chemical composition. NIR spectroscopy proved to be a highly reliable method for the determination of chemical composition and thus presents an interesting alternative to replace conventional chemical analyses. Within meat quality, some parameters of pork technological quality were studied, such as pH, color and water-holding capacity with the emphasis on the latter property. Compared to the prediction of chemical constituents, the ability of NIR spectroscopy to determine meat quality characteristics was lower. However, the predicition errors approached to the accuracy/repeatability of the reference methods, which are in case of meat quality fast and simple, subjected to many environmental factors and therefore less accurate and repeatable. The advantages of NIR spectroscopy (i.e. fast, simple, non-destructive, simultaneous determination of many properties) together with a satisfactory reliability offer great potential of NIR spectroscopy for industrial applications of meat quality analyses. Choosing appropriate options of different factors affecting accuracy (such as sample preparation, spectral range, type of sample, chemometric method) the prediction performance of NIR spectroscopy could be noticeably improved.
Keywords:NIR spectroscopy, meat, meat products, chemical composition, meat quality


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