Applying of non-destructive analysis methods in determination of whey solids*

Similar documents
Comparative Evaluation of Total Solids, Freezing Point and Specific Gravity of Raw Milk Using an Ultrasonic Milk Analyzer Versus Standard Methods

PHYSIOCHEMICAL CHARACTERISTICS OF VARIOUS RAW MILK SAMPLES IN A SELECTED DAIRY PLANT OF BANGLADESH

CRITERIA FOR USE. A GRAPHICAL EXPLANATION OF BI-VARIATE (2 VARIABLE) REGRESSION ANALYSISSys

REGRESSION MODELLING IN PREDICTING MILK PRODUCTION DEPENDING ON DAIRY BOVINE LIVESTOCK

Prediction of sheep milk chemical composition using ph, electrical conductivity and refractive index

Crude and Protein Nitrogen Bases for Protein Measurement and Their Impact on Current Testing Accuracy

JOINT FAO/WHO FOOD STANDARDS PROGRAMME. CODEX COMMITTEE ON METHODS OF ANALYSIS AND SAMPLING Thirty-first Session Budapest, Hungary, 8-12 March 2010

MILK ANALYSIS. Food and Agriculture Organization of the United Nations

ESTIMATION OF THE ENERGY VALUE OF EWE MILK

Soy Lecithin Phospholipid Determination by Fourier Transform Infrared Spectroscopy and the Acid Digest/Arseno-Molybdate Method: A Comparative Study

EDXRF APPLICATION NOTE

Optimization of saccharification conditions of prebiotic extracted jackfruit seeds

EVALUATION OF DEVELOPMENT IN INDIRECT DETERMINATION OF MILK FAT FREE FATTY ACIDS IN CZECH REPUBLIC

UPPER MIDWEST MARKETING AREA ANALYSIS OF COMPONENT LEVELS AND SOMATIC CELL COUNT IN INDIVIDUAL HERD MILK AT THE FARM LEVEL 2008

Material balance calculations involved with dilution and mixing

PROBIOTIC STARTERS VERSUS TRADITIONAL STARTER IN QUARG PRODUCTION

ISO IDF 202 INTERNATIONAL STANDARD

STAKEHOLDER PANEL ON Dietary Supplements Background & Fitness for Purpose Protein

1.4 - Linear Regression and MS Excel

Application Note 201

Session 16/8 CHANGES IN INTENSITY OF BIOSYNTHESIS OF MILK FAT FATTY ACIDS DURING LACTATION IN GRAZING DAIRY COWS

UPPER MIDWEST MARKETING AREA ANALYSIS OF COMPONENT LEVELS AND SOMATIC CELL COUNT IN INDIVIDUAL HERD MILK AT THE FARM LEVEL 2002

Milk protein profile: measure from mid infrared spectra and identification of influence factors

QDCS. Scheme Description. Quality in Dairy Chemistry Scheme

Quality of khoa sold in Washim district

QDCS. Scheme Description. Quality in Dairy Chemistry Scheme

Food Proficiency Testing Program Round 36 Whole Milk Powder

Application of Near-infrared Spectroscopy to Quantify Fat and Total Solid Contents of Sweetened Condensed Creamer

SOUTH AFRICAN NATIONAL STANDARD

UPPER MIDWEST MARKETING AREA ANALYSIS OF COMPONENT LEVELS AND SOMATIC CELL COUNT IN INDIVIDUAL HERD MILK AT THE FARM LEVEL 2007

Simple Linear Regression the model, estimation and testing

Electronic Supporting Information

This annex is valid from: to Replaces annex dated: Location(s) where activities are performed under accreditation

P. Namanee, S. Kuprasert and W. Ngampongsai. Abstract

MULTI-COMPONENT ANALYSIS OF HEAVY METALS

Fast, Simple QA/QC of Milk Powder Formulations using FTIR Spectroscopy. Rob Wills Product Specialist Molecular Spectroscopy

Session code: C6.12 Abstract No Milk SCC and PMN as indicators of milk processability and subsequent cheese quality

Genetic parameters for major milk proteins in three French dairy cattle breeds

The use of near infrared reflectance spectroscopy (NIRS) for prediction of the nutritive value of barley for growing pigs

Research Methods in Forest Sciences: Learning Diary. Yoko Lu December Research process

Abstract. Keywords: Tropical grasses, Degradability, Nutrient, Rumen fermentation. Introduction. Chaowarit Mapato a* and Metha Wanapat a

Validated UV Spectrophotometric Method Development And Stability Studies Of Acamprosate Calcium In Bulk And Tablet Dosage Form

DQCI Services. Trusted Dairy Laboratory Services for more than 50 Years. Dairy Instrument Calibration Validation Standards

Randomness Rules: Living with Variation in the Nutrient Composition of Concentrate Feeds 1

Validation of Near Infrared Spectroscopy (NIRS) Milling Index Method

Determination of Cannabis Extract Potency Degradation Mechanism and Rate by Infrared Spectroscopy

Method development for expanding the application of Fourier-Transform Near-Infrared Spectroscopy (FT-NIR) in food samples

The Effects of Various Milk By-Products on Microbial. Mehmet GÜN, Cemalettin SARIÇOBAN, Hasan İbrahim KOZAN

1 Analytical Methods 2 3 Electronic Supplementary Information Ultra-trace determination of sodium fluoroacetate (1080) as

The reference method for the determination of the protein

,*+*. 1,*+* ,,- 0 0 ALT BMS, BCS, BFS, 0* 2+ (), ,,*+*

2007 Revisions to FDR and DPR regarding Cheese. Framework for Inspection. October 30, 2008 Dairy Stakeholder Meeting. Aussi disponible en français

Effect of exposure to heat stress conditions on milk yield and quality of Aosta dairy cows grazing on Alpine pasture

Analytical Chemistry of Foods

WDHS Curriculum Map Probability and Statistics. What is Statistics and how does it relate to you?

Statistics for Psychology

Chapter 2 Organizing and Summarizing Data. Chapter 3 Numerically Summarizing Data. Chapter 4 Describing the Relation between Two Variables

Chapter 11: Advanced Remedial Measures. Weighted Least Squares (WLS)

True Metabolizable Energy and Amino Acid Digestibility of Distillers Dried Grains with Solubles

Productive And Reproductive Performance Of Friesian Cows Under Different Feeding System

Study Report Effects of Corn Distillers Dried Grains with Solubles (DDGS) Under Hot Summer Conditions in Lactating Dairy Cows

Changes in Testing for and Paying for Milk Components as Proposed under the Final Rule of Federal Order Reform: Implications for Dairy Producers

Guidelines to authors

LIST OF PUBLISHED STANDARDS

Making Forage Analysis Work for You in Balancing Livestock Rations and Marketing Hay

Application Note. NPN - Calculated Urea.

Relationship Between Lactoferrin, Minerals, and Somatic Cells in Bovine Milk

Genetic and Environmental Info in goat milk FTIR spectra

Bioenergetic factors affecting conception rate in Holstein Friesian cows

For more information, please contact: or +1 (302)

Randomness Rules: Living with Variation in the Nutrient Composition of Concentrate Feeds

Evaluation of Models to Estimate Urinary Nitrogen and Expected Milk Urea Nitrogen 1

Abstract. M. De Marchi, M. Penasa, F. Tiezzi, V. Toffanin & M. Cassandro

ULTRA HIGH TEMPERATURE (UHT) TREATMENT EFFECT ON IODINE FORTIFIED MILK THROUGH COW FEED

Development and validation of an enzymatic assay for the measurement of lactose in lowlactose and lactose-free products

Method Comparison Report Semi-Annual 1/5/2018

The Effect of Feed and Stage of Lactation on Milk Processability

Influence of different carbon sources on in vitro rooting of sour cherry cv. Oblačinska

Copyright 1992 Revised 2002 by. American Dairy Products Institute. Elmhurst, Illinois. Printed in U.S.A. American Dairy Products Institute

Model for Computer Simulation of Bone Tissue

Schedule of Accreditation issued by United Kingdom Accreditation Service 2 Pine Trees, Chertsey Lane, Staines-upon-Thames, TW18 3HR, UK

Fat Content Determination Methods Teresa McConville Chem 311 Dr. Weisshaar

Kjeldahl Nitrogen Analysis As A Reference Method For

OPTIQUAD Application list January 2016

Multiple Regression Analysis

Adjustment for Heterogeneous Herd-Test-Day Variances

INTERNATIONAL SYMPOSIUM ON ANIMAL SCIENCE (ISAS) th - 10 th June 2017, Herceg Novi, Montenegro

High protein content determination in food and animal feed by combustion using the Thermo Scientific FlashSmart Elemental Analyzer

Chapter 5: Analysis of water content, total solids & water activity

Whey powders Specification

Pearson Education Limited Edinburgh Gate Harlow Essex CM20 2JE England and Associated Companies throughout the world

Pitfalls in Linear Regression Analysis

Composition and Nutritive Value of Corn Fractions and Ethanol Co-products Resulting from a New Dry-milling Process 1

BENCHMARKING FORAGE NUTRIENT COMPOSITION AND DIGESTIBILITY. R. D. Shaver, Ph.D., PAS

ISO IDF 20-5 INTERNATIONAL STANDARD. Milk Determination of nitrogen content Part 5: Determination of protein-nitrogen content

BUCHI NIR Applications Milling & Bakery Industry

Effects of L-Carnitine in the Diet of Weanling Pigs II. Apparent Nutrient Digestibility, Whole Body Composition, and Tissue Accretion

Supplementary crude protein and phosphorus levels: effect on spring milk production in dairy cows Michael Reid 1,2

INTRODUCTION. Key Words : Near-infrared Reflectance Spectroscopy, Carcass Composition, Broilers

Using Membrane Filtration Techniques to Fractionate Greek Yogurt Acid Whey into Value Added Ingredients

Transcription:

S. Mišanovič at ali: Applying of non-destructive... Mljekarstvo 45 (4) 243-252, 1995. Applying of non-destructive analysis methods in determination of whey solids* Silva Mišanović, Đ. Mišanović, Mara Banovć, Matilda Grüner Conference paper - Izlaganje sa znanstvenog skupa UDC: 637.344 Summary Possibility of applying non-destructive mettiods in detenvination of whey solids was investigated. The non-destructive methods used were: infrared spectroscopy, cryoscopy, conductometry and gravimetric method as a referent method. With statistical interpretation of results the stochastic relation of variable between independent variable (investigated method) and dependent variable (referent method) was established. The stochastic relation showed satisfactory dependency of variables with linear equation: Y = b^xq + b^x^ + e. Determination coefficient verified model's efficacy. Infrared spectroscopy and cryoscopy were successful methods for determination of whey solids. Less precise were conductometry results. Additional index words: whey, dry matter of whey, infrared spectroscopy, cryoscopy, conductometry. Introduction Whey has been considered for a long time as waste product of dairy industry, its main use was in cattle - feeding (P o s a v e c, 1992). At present it is regarded as a product of wide-ranging application potentials (Baković & Tratnik, 1972; Grba et all., 1988; Nickerson & Vujičić, 1977; Marošević & Peraković 1981). Assessment of whey solids Is as important as its alternative quality parameters. An assay method should meet the requirements of rapidity and precision and also it should be nondestructive. The objective of the present paper was to compare three methods, i.e., infrared spectroscopy (method 2) (D e V i I d e r & Bossuyt 1983; Golc - Teger 1989; Leray 1989; Lynch & Barbano 1990; Mendehall & Brown 1990.), cryoscopy (method 3) (Black & Van Leeuwen, 1985.) and electroconductivlty (method 4) to gravimertic method (method 1) as a reference. Presented on 1«' Slovenian International Congress "l\/lilk and Dairy Products", Portorož, Slovenia, 1995-09-20/22 243

S. Mišanović at ali: Applying of non-destructive... Mljekarstvo 45 (4) 243-252, 1995. Material and methods From the batches of Zdenka DD.'s semi-hard cheeses produced at PPI Veliki Zdenci 40 samples of sweet whey were collected immediately or the very last an hour after its separation and processing. Three methods, i. e. infrared spectroscopy - Milko Scan 133B(De Vilder & Bossuyt, 1983; Golc-Teger, 1989.), cryoscopy using Krioskop 4D2 device (Black & Van Leeuwen.l985.), and electroconductivity measurement with an MA 5964 conductometer accompained by sample drying to constant mass (105 C) were used to determine the level of solids in whey. Samples acidity ranged from ph 6.2 to 6.5, titration acidity varied from 4.0 to 5.5 SH. The results were analyzed statistically on a PC. For individual components Milko Scan 133B was gauged using classic methodsikjeldahl's (A 0 A C, 1990.a) for proteins, polarimetric (A O A C, 1990.b) for lactose, and Gerber's (I S 0,1984.) for milk fat, and adding a constant of 0.65% for mineral content. Results and discussion To determine solids levels in 40 whey samples methods 2, 3 and 4, were used respectively infrared spectroscopy, cryoscopy and electroconductivity. The results were compared to those obtained using standard method of drying to constant mass (105 C) (method 1). Table 1 shows the results obtained using these methods and Table 2 gives the basic statistical indicators. Whereas the solids assay, emploing drying to constant mass, gave the lowest relative dispersion (2.75%), the electroconductivity method produced the highest relative dispersion (4.34%). Positive correlation between methods 1-2 (r=0.96) and for methods 1-4 (r=0.82) was high and significant (p < 0.05) high and significant negative correlation between methods 1-3 (r= -0.94). There was a slightly lower correlation coefficient in electroconductivity measurement, due to inequality of samples milk fat content. Because the electroconductivity metdoh is incapable of measuring milk fat, this has caused larger deviations. Correlation coefficients showed high qualitative interrelation among individual methods, and the scatter diagram show a linear relationship between the gravimetric and other methods (Figs. 1-3). This may thus be expressed by a linear regression equation of the type: Y = bqxq + b^x^ + e where: bo = (2y)'/n b^ = linear regression coefficient e = random error 244

5. Mišanovič at all: Applying of non-destructive.. Mljekarstvo 45 (4) 243-252, 1995. Table 1 Experimental data for used methods Tablica 1. Eksperimentalni podaci provedenih mjerenja Solids/suha tvar (%) Solids/suha tvar (%) Freezing point/"ročl<a Conductivity/Elektropro smrzavanja ( C) -vodljivost (ms/cm) Method 1/Metoda 1 Method 2/Metoda 2 Method 3/Metoda 3 Method 4/Metoda 4 5.36 5.4O -O.412 4.965 5.57 5.56 -O.435 5.136 5.64 5.65 -O.444 5.215 5.65 5.62 -O.441 5.33O 5.65 5.68 -O.449 5.141 5.67 5.66 -O.447 5.23O 5.69 5.68 -O.446 5.2OO 5.70 5.7O -O.448 5.188 5.71 5.68 -O.456 5.242 5.71 5.71 -O.454 5.2O7 5.72 5.66 -O.444 5.255 5.72 5.7O -O.457 5.4O7 5.72 5.73 -O.448 5.23O 5.75 5.75 -O.454 5.246 5.76 5.76 -O.456 5.256 5.76 5.79 ' -O.44O : 5.176 5.77 5.75 -O.465 5.456 5.77 5.77 -O.454 5.194 5.78 5.75 -O.458 5.154 5.80 5.82 -O.463 5.3O2 5.81 5.83 -O.462 5.1O1 ; 1 5.82 5.81 -O.45O 5.397 ^ 5.82 5.89 -O.472 5.58O ' 5.85 5.81 -O.465 5.318 5.85 ^ 5.89 -O.468 5.32O 5.85 5.92 -O.471 5.4O3 5.85 5.92 -O.477 5.661 5.88 5.88 -O.472 5.655 5.89 5.99 -O.481 5.457 5.9O 5.92 -O.474 5.653 5.91 6.O4 -O.48O 5.553 5.95 6.O1 -O.468 5.632 f 5.97 6.O3 -O.481 5.465 'hi 6.0O 5.96 -O.483 5.436, 6.01 5.98 -O.482 5.382 6.02 6.O3 -O.475 5.452 6.O4 5.95 -O.477 5.372 6.O6 6.15 -O.492 5.887 6.1O, 6.13 -O.488 5.387 6.2O 6.18 -O.5O5 5.5O6 Methods / Metode: 1. Solids (7o) - using gravimetry / Suha tvar (%) - gravimetrijski 2. Solids (%) - using Milko Scan 133 B / Suha tvar {%) - s Milko scan-om 133B 3. Freezing point ( C) - using Advanced 4D2 cryoscope / Točka smrzavanja - s Advanced 4D2 krioskopom 4. Conductivity (ms/cm) - using MA5964 conductometer / Elektroprovodljivost s konduktometrom MA5964 245

5. Mišanovič at all: Applying of non-destructive. Mljekarstvo 45 (4) 243-252, 1995. Table 2 Basic statistical indicators Tablica 2. Osnovni statističld pokazatelji Method Mean Standard deviation Coefficient of variation Metode Srednja vrijednost Standardna devijacija Koeficijent varijacije X (s) % (V) 1 5.82 0.16 2.75 2 5.83 0.17 2.92 3-0.462 0.02 3.91 4 5.43 O.24 4.34 Methods / Metode: 1. Solids (%) - by gravimetry / Suha tvar (%) - gravimetrijski ^ 2. Solids (%) - using Mllko Scan 133B / Suha tvar (%) - s Milko Scan-om 133B 3. Freezing point ( C) - using Advanced 4D2 cryoscope / Točka smrzavanja ( C) - s Advanced 4D2 krioskopom 4. Conductivity (ms/cm) - using MA5964 conductometer / Elektroprovodljivost - s konduktometrom MA5964 - Figure 1 Scatter diagram (metliods 1-2) Slika 1. Dijagram rasipanja podataka (metode 1-2) o2 o eo 1-H o^ ed 5.3 5,3 Measurements; Mjerenja; ~T 5.5 5.7 5.9 6,1 6.3 SoKds (%) - using MS133B Suha tvar SMS133B 246

S. Mišanovic at ali.: Applying of non-destructive. Mljekarstvo 45 (4) 243-252, 1995. Table 3 Equations of linear regresion Y(x) Tablica 3. Jednadžbe linearne regresije Y(x) Methods Metode 1-2 1-3 1-4 Linear regression Linearna regresija Y = 0.547778 + 0.904044 x Y= 1.964223-8.333O3OX Y = 2.788193+ 0.557771 x Methods / Metode:,> i 1. Solids (%) - using gravlmetry I Suha tvar (%) - gravimetrijski 2. Solids (%) - using Milko Scan 133BI Suha tvar (%) - s Milko Scan-om 133B 3. Freezing point { C) - using Advanced 4D2 cryoscope / Točka smrzavanja ( C) - s Advanced 4D2 krioskopom 4. Conductivity (ms/cm) - using MA5964 conductometer / Elektroprovodljivost - s konduktometrom MA5964 Figure 2 Scatter diagram (methods 1-3) Slika 2. Dijagram rasipanja podataka (metode 1-3) o o -0,52 -oiso -0.48-0,46 -OM 'Measurements; 'Mjerenja; Freezimg point ( C) Točka smrzavanja ( C) -0.42-0.40 247

S. Mišanovid at ali: Applying of non-destructive... Mljekarstvo 45 (4) 243-252, 1995. The calculation of linear regression was done with least square technique (Dawies, 1964.). Equations of linear regression Y(x) appears in Table 3. A PC using ABDO software computed the linear model's coefficients (Coob, 1988.). The confidence limits of methods 1-2, 1-3 and 1-4 arey±0.09,?±0.11 andy±0.19, respectively. Verification of relationships between regresion models (1-2, 1-3, 1-4) was done with conventional methods of mathematical statistic (Tables 4, 5 and 6). The efficiency of the above methods was assessed as follows (Diagram 1): 1. Dry substance level using the MS 133B technique 93.09% 2. Dry substance level by cryoscopy r 88.93% 3. Dry substance level measured using electroconductivity 67.80% Figure 3 Scatter diagram (mettiods 1-4) Slika 3. Dijagram rasipanja podataka (metode 1-4) 2 s. II </3 </J 5,3 "~r~ 4,9 5,1 5.3 5.5 5,7 Electroconductivity (ms/cm) Elektroprovodljivost (ms/cm) ~r~ 5.9 6,1 Measurements; Mjerenja; 248

S. Mišanović at all.: Applying of non-destructive. Mljekarstvo 45 (4) 243-252, 1995. Table 4 Analysis of variance for regression model 1-2 Tablica 4. Analiza varijance modela regresije 1-2 Source of variation Izvor varijacija SS Degrees of freedom Stupnjevi slobode Total 1354.494 40 Ukupno bo 1353.500 1 bo Total (corr.) O.994 39 Ukupno (korig.) Model b, O.926 1 O.926 Model b. O.OO181 512.2097*** Residual O.O68 38 Ostatak Foo, (1/38) = 7.35 p«o.oo1 Efficiency of model SS (bj / SS (total corr.) x 100 = 93.09% Efikasnost modela SS (b^j / SS (ukupno korig.) x 1OO = 93.09% Not explained by model 6.91 % Nije objašnjeno modelom 6.91% Methods / Metode: 1. Solids (%) - using gravimetry / Suha tvar (%) - gravimetrijski 2. Solids (%) - using Mllko Scan 133B / Suha tvar (%) - s Mllko Scan-om 133B Table 5 Analysis of variance for regression model 1-3 Tablica 5. Analiza varijance modela regresije 1-3 Source of variation Izvor varijacija Total Ukupno bo bo Total (corr.) Ukupno (korig. Model b^ Model b^ Residual Ostatak Fo.o, (1/38) = 7.35 SS 1354.494 1353.500 0.994 O.884 O.11O p«o.oo1 Degrees of freedom Stupnjevi slobode 40 1 39 1 m MS MS O.884 Efficiency of model SS (b1) / SS (total corr.) x 1OO = 88.93% Efikasnost modela SS (bi) / SS (ukupno korig.) x 1OO = 88.93% Not explained by model 11.07% Nije objašnjeno modelom 11.07% O.OO2898 Fo 305.1534* Methods / Metode: 1. Solids (%) - using gravimetry / Suha tvar (%) - gravimetrijski 2. Freezing point ( C) - using Advanced 402 cryoscope / Točka smrzavanja ( C) - s Advanced 4D2 krioskopom 249

5. Mišanovid at ali: Applying of non-destructive... Mljekarstvo 45 (4) 243-252, 1995. Table 6 Analysis of variance for regression model 1- Tabica 6. Analiza varijance modela regresije 1-4 Source of variation Izvor varijacija SS Total 1354.494 Ukupno 1353.500 Degrees of freedom Stupnjevi slobode 40 1 MS Total (corr.) O.994 Ukupno (korig.) Model b^ O.674 Model b. Residual O.32O Ostatak Foo, (1/38) = 7.35 p«o.oo1 Efficiency of model SS (b.) / SS (total corr.) x 1OO = 67.80% Efikasnost modela SS (b^) / SS (ukupno korig.) x 1OO = 67.80% Not explained by model 32.20% Nije objašnjeno modelom 32.20% 39 1 38 O.674 8O.O39O7*** O.OO8425 Methods / Metode: 1. Solids (%) - using gravlmetry / Suha tvar (%) - gravimetrijski 2. Conductivity (ms/cm) - using MA5964 conductometer / Elektroprovodljlvost - s konduktometrom MA5964 Diagram 1 Efficiency of the regression model Dijagram 1. Efikasnost modela regresije 100% 1-2 1-3 1-4 metliod pairs - parovi metoda unexplained ^^^^ explained neobjašnjeno ot 250

S. Mišanović at ali: Applying of non-destructive... Mljekarstvo 45 (4) 243-252, 1995. Conclusion Results suggest that the Milko Scan (infrared spectroscopy) method is suitable for determination of whey solids in dairy industry laboratories. The cryoscopy method, method for whey the freezing point determination was also reliable and could be recommended for laboratory use. Electroconductivity, between three methods, affords the lowest precision when used to measure the level of whey solids. :h, PRIMJENA NEDESTRUKTIVNIH METODA ANALIZE U ODREĐIVANJU SUHE TVARI SIRUTKE Sažetak U radu je istražena mogućnost primjene nedestruktivnih metoda za određivanje suhe tvari sirutke. Korištene su slijedeće nedestruktivne metode: infracrvena spektroskopija. krioskopija i mjerenje elektroprovodljivosti, a kao referentna korištena je gravimetrijska metoda. Statističkom obradom rezultata utvrđenje stohastički odnos između nezavisne varijable (provjeravana metoda) i zavisne varijable (referentna metoda). Stohastički odnos pokazao je zadovljavajuću ovisnost varijabli linearnom funkcijom oblika Y=b^o+b^x^+z. Efikasnost modela je provjerena koeficijentom determinacije. Infracrvena spektroskopija i krioskopija bile su uspješne metode za određivanje suhe tvari sirutke. Rezultati dobiveni mjerenjem elektroprovodljivosti manje su precizni. Riječi natuknice: sirutka, suha tvar sirutke, infracrvena spektroskopija, krioskopija, mjerenje elektroprovodljivosti.. 'i-i' Literatura AOAC, Association of Official Analytical Chemists (1990), Official Methods of Analysis, 15th Ed., Arlington, sees, a) 920.105, and b) 896.01 BAKOVIĆ, D., TRATNIK, U. (1972): Mogućnost korištenja sirutke u prehrani, Mljekarstvo 29 (2) 36-402. BLACK, R. G., VAN LEEUWEN, J. (1985): Optimization of an automatic milk cryoscope, Australian Journal of Dairy Technology, September, 123-128. COOB, S. (1988): Using quatro: The Professional Spreadsheet, Borland-Osbome, Mc Graw hill. DE VILDER, J., BOSSUYT, R. (1983): Practical experiences with the infra analyzer 400 in determining the water, protein and fat content of milk powder, Milchwlssenschaft 38 (2) 65-69 DAWIES, O.L. (1964): Statistical Methods in Research and Production, Oliver and Boyd, London-Edinburgh. 251

S. Mišanović at ali.: Applying of non-destructive... Mljekarstvo 45 (4) 243-252, 1995^- GOLC-TEGER, S. (1989): Kriteriji i mjerenja kvalitete u mljel<arstvu, Mljekarstvo 39 (10) 255-260 GRBA, S., STEHLIK-TOMAS, V., IVIAJDAK, K. (1988): Proizvodnja alkohola i vina iz sirutke, Mljekarstvo 39 (6) 143-150. ISO 7280 (1984) LERAY, O. (1989): Influence de Torigine geographique sur la precision des dosages de matiere grasse et de proteines par spectroscopie dans moyen infrarouge, Le Lait 69 (6) 547-560. LYNCH, J.M., BARBANO, D.M. (1990): Variation in the ash and nonprotein nitrogen content of milk, and use of milk protein content to predict milk ash content, 85th Annual Meeting of the ADSA, June 24-27, 1990, North Carolina State University. Journal of Dairy Science 73 (Suppl. 1) 92 MAROŠEVIĆ, S., PERAKOVIĆ, K. (1981): Potrebe i mogućnosti iskorištavanja sirutke kod nas. Mljekarstvo 31 (1) 10-22 MENDEHALL, I.V., BROWN, R.J. (1990): Alternative wavelenghts for measurement of fat, protein and lactose in milk, 85th Annual Meeting of the ADSA, June 24-27,1990, North Carolina State University. Journal of Dairy Science 73 (Suppl. 1) 92. NICKERSON, T.A., VUJIČIĆ, I. (1977): Iskorištavanje i upotreba sirutke, Mljekarstvo 27 (7) 146-151. POSAVEC, J. (1992): Utjecaj različitih količina sirutke u mliječnoj zamjenici na othranu jaradi, Mljekarstvo 42 (4) 271-280. Author's adresses - Adrese autora Received - Primljeno Mr. Silva Mišanović 15.12.1995. Mr. Đuro Mišanović D.D. "Zdenka" P.P.I. Veliki Zdenci Prof.dr. Matilda Grüner Mr. Mara Banović Faculty of food technology and biotechnology Zagreb, Pierottljeva 6 252