Advertisement
Article| Volume 88, ISSUE 5, P1636-1645, May 2005

Download started.

Ok

Rate of Maillard Browning in Sweet Whey Powder

      Abstract

      The objective of this study was to evaluate the rate of Maillard browning in 3 commercial sweet whey powders (WC1, WC2, and MW1), under accelerated shelf-life testing (ASLT) and under normal storage conditions (21°C and 35% RH). Rate of brown pigment formation (k) obtained from short-term ASLT of whey powder was compared with actual findings obtained from the long-term shelf-life testing under normal conditions. Deterioration by Maillard browning, measured by spectrophotometer, was compared with changes in color (Hunter Laboratory), free moisture, titratable acidity, and sensory attributes. Results suggest that estimated k (from ASLT) was comparable with the observed rate (obtained at ambient temperature) for 2 producers (WC1, MW1). The actual k values observed for samples WC1, WC2, and MW1, stored under normal conditions, were 0.0031, 0.0080, and 0.0148 color units/g of solid per mo, respectively. The estimated values of k for samples WC1, WC2, and MW1 were 1.12, 4.90, and 1.35 times more than the observed values, respectively. The Q10 values (increase in reaction rate for a 10°C temperature increase) ranged from 1.77 to 4.14, and the activation energies ranged from 15.9 to 28.4 kcal/mol. Hunter Laboratory values L* and a* appeared most sensitive to changes during storage. Free moisture content, and acidity increased significantly with storage. However, no significant changes were detected by the sensory panel in the attributes considered.

      Key words

      Abbreviation key:

      a* (Hunter Lab red-green parameter), ASLT (accelerated shelf-life testing), b* (Hunter Lab blue-yellow parameter), Ea (energy of activation), k (rate constant), L* (Hunter Lab lightness-darkness parameter), MW (Midwest processor), WC (West coast processor)

      Introduction

      Nonenzymatic browning via the Maillard reaction is an important mode of deterioration in dried milk and whey powders, which limits shelf life (
      • Saltmarch M.
      • Labuza T.
      Influence of relative humidity on the physicochemical state of lactose in spray-dried sweet whey powders.
      ). Whey powders contain relatively high concentrations of lactose (approximately 73%) and protein (approximately 12%) high in lysine content. In the presence of moisture, these components readily participate in Maillard reactions. The Maillard reaction is affected by the concentration of the initial reactant species, pH, water content, and presence of substances such as humectants and bisulfite (
      • Franzen K.
      • Singh R.K.
      • Okos M.R.
      Kinetics of nonenzymatic browning in dried skim milk.
      ). Some physical factors, such as processing and storage temperature, atmospheric oxygen, and packaging during storage can also affect the Maillard reaction in foods. The deleterious effects of nonenzymatic browning include: decreased nutritional value from protein loss, off-flavor development, undesirable color, decreased solubility, texture changes, destruction of vitamins, and increased acidity (
      • Saltmarch M.
      • Labuza T.P.
      SEM investigation of the effect of lactose crystallization on the storage properties of spray dried whey.
      ;
      • Ford J.E.
      • Hurrel R.F.
      • Finot P.A.
      Storage of milk powders under adverse conditions. 2. Influence of the content of water-soluble vitamins.
      ;

      Villota, R., and J. G. Hawkes. 1983. Effect of processing on kinetics of nutrients and organoleptic changes in foods. Paper presented at the Winter Meeting of the Am. Soc. Agric Engr., St. Joseph, MI.

      ).
      Brown pigment formation has been used as an indicator of the Maillard reaction in food (
      • Waletzko P.
      • Labuza T.P.
      Accelerated shelf life testing of an intermediate moisture food in air and in an oxygen-free atmosphere.
      ;
      • Saltmarch M.
      • Labuza T.P.
      SEM investigation of the effect of lactose crystallization on the storage properties of spray dried whey.
      ).
      • Franzen K.
      • Singh R.K.
      • Okos M.R.
      Kinetics of nonenzymatic browning in dried skim milk.
      confirmed that the Maillard reaction is described by zero-order reaction in the sense that the concentration of the brown pigments is negligible compared with the concentration of reactants present. Optimum conditions for the Maillard reaction in whey powders as determined by brown pigment formation have been studied (
      • Choi R.P.
      • O’Malley C.M.
      • Fairbanks B.W.
      A proposed method for the determination of color of dry products of milk.
      ;
      • Labuza T.P.
      • Saltmarch M.
      Kinetics of browning and protein quality loss in whey powders during steady state and non steady state storage conditions.
      ).
      In their method development for accelerated shelf life testing (ASLT) of whey powder,
      • Labuza T.P.
      • Saltmarch M.
      Kinetics of browning and protein quality loss in whey powders during steady state and non steady state storage conditions.
      stored samples in an open system. However,
      • Kim M.
      • Saltmarch M.
      • Labuza T.P.
      Nonenzymatic browning of hygroscopic whey powders in open versus sealed pouches.
      investigated the effects of storing the samples in open vs. sealed pouches. They observed that the nonenzymatic browning reaction is greatly increased in closed samples compared with samples stored open to the environment, and cautioned that care be taken in using data from ASLT to predict kinetics of deteriorative reactions during shelf-life tests of sealed food systems.
      The purpose of this work was to use sealed containers to estimate the rate of deterioration of 3 commercial whey powders under accelerated storage conditions through the use of the Arrhenius equation with extrapolation. The ASLT data were compared with Maillard browning occurring under normal storage conditions (21°C, 35% RH). The rate of deterioration by browning of the 3 commercial Cheddar cheese whey powder samples was compared with changes in microbiological, physicochemical, and sensory quality during storage to establish the keeping quality of the whey powders and to validate the use of Maillard browning in determining shelf life.

      Materials and Methods

      Storage Conditions for Control

      Twelve bags from the same lot of whey powder from 2 West coast processors and 1 Midwest processor (WC1, WC2, and MW1), were stored at 21°C and 35% RH. Samples were withdrawn for analysis after storage for 1, 5, 9, 12, and 19 mo. The storage times were chosen based on the study by
      • Presa-Owens S.
      • López-Sabater M.
      • Rivero-Urgell M.
      Shelf-life prediction of an infant formula using an accelerated stability test (Rancimat).
      . Samples for sensory analyses were packed in 1-L amber glass bottles supplied with polytetrafluoroethylene-sealed screw caps and stored at −37°C until analysis.

      High Temperature Storage

      Four incubators were maintained at 35, 45, 50, and 55°C. Whey powders from WC1, WC2, and MW1 were each packaged into 100-mL glass bottles and equilibrated to 0.44 water activity (aw) according to the method outlined by
      • Labuza T.P.
      • Saltmarch M.
      Kinetics of browning and protein quality loss in whey powders during steady state and non steady state storage conditions.
      . The bottles were then sealed with polytetrafluoroethylene-sealed screw caps. This impermeable system enabled Maillard reaction in high-temperature/low-humidity cabinets without moisture loss. Five to 6 bottled whey powder samples from each processor were incubated at each temperature. Samples were withdrawn from the incubators after the specified storage period and immediately stored at −37°C. Samples stored at 35°C were withdrawn after 7, 19, 40, 64, 91, and 174 d of storage. Samples stored at 45°C were withdrawn after 9, 19, 26, 60, and 96 d of storage. Samples stored at 50°C were withdrawn after 11, 20, 24, 37, and 46 d of storage, and samples stored at 55°C were withdrawn after 5, 10, 17, 20, and 21 d of storage.

      Evaluation of Brown Pigment Formation

      Brown pigment formation was analyzed by the modified method for milk powders of
      • Choi R.P.
      • O’Malley C.M.
      • Fairbanks B.W.
      A proposed method for the determination of color of dry products of milk.
      as outlined by
      • Labuza T.P.
      • Saltmarch M.
      Kinetics of browning and protein quality loss in whey powders during steady state and non steady state storage conditions.
      . Chymotrypsin type II from bovine (C4129-1G), trypsin (type IX-5 T0303-1G), and peptidase from porcine intestinal mucosa (P7500-10UN) were purchased from Sigma (St. Louis, MO). Absorbance was measured at 420 nm (
      • Cämmerer B.
      • Wedzicha B.L.
      • Kroh L.W.
      Nonenzymatic browning reactions of retro-adol degradation products of carbohydrates.
      ) (Bio Spec – 1601 DNA/Protein Analyzer cat. # 206-67001-92, Shimadzu, Kyoto, Japan).

      Analytical Methods

      The solubility index was determined by centrifugation according to
      A/S Niro Atomizer
      Determination of moisture.
      , using a Beckman model TJ-6 centrifuge (Beckman, Palo Alto, CA). Titratable acidity as percentage lactic acid and pH were determined according to the methods outlined by the
      American Dairy Products Institute
      Whey and Whey Products: Definitions, Composition, Standard Methods of Analysis.
      . The pH was measured using a pH meter (Accumet Research AR25 dual Channel pH/Lon Meter, Fisher Scientific, Fairlawn, NJ) on a 6.5-g whey powder sample in 100 mL of distilled water. Duplicate analyses were carried out for all analyses.
      Color measurements were determined according to the Hunter Laboratory method of measuring loose powder (
      • Nielsen B.R.
      • Stapelfeldt H.
      • Skibsted L.H.
      Early prediction of the shelf-life of medium-heat whole milk powders using stepwise multiple regression and principal component analysis.
      ). Analysis was by the tristimulus reflectance colorimeter, Hunter Laboratory CT 1100 Color Quest (SNC49038; Hunter Associates Laboratory Inc., Reston, VA). The operating conditions were: illuminant C, 10° observer value, and reflectance mode and 45/0 sensor. The CIE LAB values L*, a*, and b* were measured, with analyses performed in triplicate.
      Fat content was determined by the Mojonnier method (
      AOAC
      Official Methods of Analysis.
      ; method no. 989.05), and protein content determined by the Kjeldahl method (
      AOAC
      Official Methods of Analysis.
      ; method no. 930.29, 991.20). Calcium was determined by atomic absorption spectrophotometry (
      AOAC
      Official Methods of Analysis.
      ; method no. 985.35), and lactose was determined using an enzymatic method (
      AOAC
      Official Methods of Analysis.
      ; method no. 984.15). Salt was determined by indirect Volhart method (
      AOAC
      Official Methods of Analysis.
      ; method no. 935.43), and scorched particles were analyzed according to the method outlined by the
      American Dairy Products Institute
      Whey and Whey Products: Definitions, Composition, Standard Methods of Analysis.
      . Free moisture was determined by oven drying according to the standard methods for the examination of dairy products (
      • Richardson G.H.
      Standard Methods for the Examination of Dairy Products.
      ). Sulfite was quantified and reported as sulfur dioxide (AOAC, 1985; method no. 20:123–125). Duplicate analyses were carried out for all analyses.

      Sensory Evaluation

      Prospective panelists were screened for their ability to recognize and rate the intensity of the 4 basic tastes (salty, sour, sweet, and bitter). Odor perception and descriptive identification were assessed by having the panelists take short sniffs of the attributes cooked, caramelized, and barny via duplicated triangle tests. Results of acuity and rating tests were used to make the final selection of 13 panelists (12 women and 1 man).
      Training was carried out during nineteen 1-h sessions. A modified Spectrum method (
      • Lawless H.T.
      • Heymann H.
      Sensory Evaluation of Food, Principles and Practices.
      ) was used because it uses scientific terms, which relate to product composition, production, and development, rather than consumer terms, making it easier to relate to the science behind the product. The Quantitative Descriptive method (
      • Stone H.
      • Sidel J.L.
      Sensory evaluation practices.
      ) was used. (Panelists created the preliminary lexicon after tasting the whole range of whey powders. Additional descriptors and standards were adopted from
      • Karagül-Yüceer Y.
      • Drake M.
      • Cadwallader K.R.
      Aroma active components of nonfat dry milk.
      . Descriptors used are shown in Table 1. Testing was a complete randomized block design with three coded samples presented to the panelist at one time. Panelists constituted a block.
      Table 1Descriptors, description terms, and preparation of the reference materials for descriptive sensory evaluation of whey powder (adopted from
      • Karagül-Yüceer Y.
      • Drake M.
      • Cadwallader K.R.
      Aroma active components of nonfat dry milk.
      ).
      DescriptorReferenceDescription and preparation
      Cooked aroma and flavorHeated skim milkAroma and flavor associated with cooked milk; slightly sulfuric aroma/taste acquired by a product that has been submitted to heat treatment; pasteurized skim milk heated to 85°C for 55
      Signify standards modified from Karagül-Yüceer, 2001.
      min.
      Caramelized aroma and flavorAutoclaved skim milkMilk autoclaved at 121°C for 30 min; taste suggestive of soft caramel due to Maillard reaction. This characteristic goes with the series biscuit, caramel, and burnt.
      Sweet aromatic/cake mix aroma and flavorPillsbury Moist Supreme classic white premium cake mixAroma and flavor associated with diacetyl.
      Barny/animal-like aroma and flavorp-cresol (C7525, Sigma)10
      Signify standards modified from Karagül-Yüceer, 2001.
      ppm in skim milk.
      Oxidized aroma and flavor(E,E)-2,4-decadienal (12117CB, Aldrich)Aroma/flavor associated with old oil, metallic, paint; 2 ppb in skim milk.
      Papery/cardboard aromaCardboardAroma associated with cardboard; sensation provoked by defective packaging or by a slight oxidation of product; pieces of cardboard paper (3% wt/vol) soaked in skim milk overnight.
      SweetSucroseBasic taste associated with sucrose; 1%
      Signify standards modified from Karagül-Yüceer, 2001.
      wt/vol sucrose solution.
      SaltyNaClBasic taste associated with salt; 0.2%
      Signify standards modified from Karagül-Yüceer, 2001.
      wt/vol NaCl solution.
      SourCitric acidBasic taste associated with acid; 0.05%
      Signify standards modified from Karagül-Yüceer, 2001.
      wt/vol citric acid solution.
      * Signify standards modified from
      • Karagül-Yüceer Y.
      • Drake M.
      • Cadwallader K.R.
      Aroma active components of nonfat dry milk.
      .
      For aroma and flavor evaluation, 10 g of whey powder and 0.01 mL of color (McCormick red food color to prevent the appearance of whey from influencing a panelist's decision) were suspended in 100 mL of spring water at 40°C and mixed by electric mixer at 200 rpm for 2 min. Samples (70 mL) were served in clear wine glasses covered with plastic lids, and were evaluated at 25 ± 2°C after standing for 2 h (
      • Kamath A.
      • Ravi R.
      • Rajalakshmi D.
      Sensory profiling and positioning of commercial samples of milk powder.
      ) to allow for release of volatile aroma into the head space. After evaluation of aroma, flavor was evaluated. Each panelist judged each sample twice.

      Microbiological Analysis

      The microbiological analyses carried out on the whey sample were standard plate count, mesophilic and psychrophilic spores, coliform bacteria, and yeast and molds. All methods used were from the
      American Dairy Products Institute
      Whey and Whey Products: Definitions, Composition, Standard Methods of Analysis.
      . The microbiological media were supplied by VWR International (West Chester, PA).

      Statistics

      Multivariate and univariate ANOVA were performed. For the compositional and microbiological analyses, ANOVA with means separation was performed using SPSS version 11.0 (SPSS Inc., Chicago, IL) at 95% confidence. Differences between whey powders were recognized by principal component analysis. For the sensory data, 3-way ANOVA for each descriptor was performed using multivariate ANOVA using SAS version 8 (SAS Institute, Inc., Cary, NC). The factors storage time, panelist, and replication were taken into consideration. Based on the results of the ANOVA, simultaneous confidence interval for differences on the 5% level were calculated using Tukey LSD.

      Results and Discussion

      Composition

      The compositional data of the whey powders is given in Table 2. Principal component analysis (Figure 1) demonstrated that the 3 samples were significantly different based on principal component 1. Principal component 1 separates the samples based on calcium, salt, and fat. Samples MW1 and WC2 were significantly different from WC1 based on principal component 2. Principal component 2 separates the samples based on moisture, pH, lactose, and protein.
      Table 2Proximate composition
      Means from triplicate analysis of composite sample.
      with separation of means of commercial Cheddar whey powder samples from processors from the West coast (WC1 and WC2) and the Midwest (MW1).
      ProcessorSalt (%)Calcium (%)Protein (%)Free moisture (%)Fat (%)Lactose (%)pHSulfite (ppm)
      WC12.197
      Means within columns with different letters are statistically different (P<0.05).
      488.0
      Means within columns with different letters are statistically different (P<0.05).
      12.8967
      Means within columns with different letters are statistically different (P<0.05).
      1.2967
      Means within columns with different letters are statistically different (P<0.05).
      1.2300
      Means within columns with different letters are statistically different (P<0.05).
      71.0
      Means within columns with different letters are statistically different (P<0.05).
      6.1533
      Means within columns with different letters are statistically different (P<0.05).
      ND
      ND = Not detected.
      WC22.187
      Means within columns with different letters are statistically different (P<0.05).
      559.7
      Means within columns with different letters are statistically different (P<0.05).
      11.8700
      Means within columns with different letters are statistically different (P<0.05).
      1.6000
      Means within columns with different letters are statistically different (P<0.05).
      1.2367
      Means within columns with different letters are statistically different (P<0.05).
      72.2
      Means within columns with different letters are statistically different (P<0.05).
      6.2900
      Means within columns with different letters are statistically different (P<0.05).
      ND
      MW12.530
      Means within columns with different letters are statistically different (P<0.05).
      403.7
      Means within columns with different letters are statistically different (P<0.05).
      12.6800
      Means within columns with different letters are statistically different (P<0.05).
      1.5967
      Means within columns with different letters are statistically different (P<0.05).
      1.6067
      Means within columns with different letters are statistically different (P<0.05).
      71.8
      Means within columns with different letters are statistically different (P<0.05).
      6.2667
      Means within columns with different letters are statistically different (P<0.05).
      ND
      a–c Means within columns with different letters are statistically different (P < 0.05).
      1 Means from triplicate analysis of composite sample.
      2 ND = Not detected.
      Figure thumbnail gr1
      Figure 1First 2 principal components (PC1, PC2) of compositional analysis of commercial whey. Processors (WC1, WC2, MW1) in same circle have no significant difference at 95% confidence interval. Bold line separated on PC2; dotted line separated on PC1.

      Rate of Brown Pigment Formation

      Rate constants were obtained for brown pigment formation assuming a zero-order rate relationship based on the work of
      • Labuza T.P.
      • Saltmarch M.
      Kinetics of browning and protein quality loss in whey powders during steady state and non steady state storage conditions.
      on kinetics of browning and protein quality loss in whey powders. Most parameters that influence browning were kept constant except for composition, core-actant level, history of the raw material, and presence of trace metals and other catalysts. Therefore, variation in the rate of brown pigment formation would likely be a result of one or a combination of these factors.
      Rate constants at 21, 35, 45, and 50°C were obtained from the plots of color units/g of solid vs. storage time (Figures 2A and 2B). The temperature dependence of browning was determined using the typical Arrhenius (Figure 2C) relationship to obtain activation energies (Ea) and Q10 values (increase in reaction rate for a 10°C increase in temperature). The data presented in Figure 2 were based on sample MW1. The Arrhenius equation is derived from a plot of log k vs. 1/T(K), whose slope = −Ea/2.303R, where k = rate constant for deteriorative reaction at temperature T, Ea = activation energy (kcal/mol), and R (ideal gas constant) = 1.98722 cal/K per mol. The Q10 factor is defined as the rate of reaction a temperature (T + 10) divided by the rate of reaction at temperature (T). Color units/g of solid was calculated from the standard curve.
      Figure thumbnail gr2
      Figure 2Plots for determining rate of brown pigment formation under accelerated shelf life testing (ASLT), ambient conditions and the Arrhenius plot for whey powder sample from Midwest. A. Rate of brown pigment formation for sweet whey powder stored at elevated temperatures: 35°C (♦), 45°C (▴), and 50°C (■). B. Rate of brown pigment formation at 21°C, 35% RH. C. Arrhenius plot for the rate of brown pigment formation.
      Plots of color units/g of solid vs. storage time for the 3 whey samples gave straight lines as supported by a high correlation to zero order, R2 between 0.82 and 1.00. Equations and respective R2 values at the different temperatures for the various processors as determined from the graphs (Figure 2) are summarized in Table 3 and confirm that the Maillard reaction follows zero order in whey powder. Although only results from MW1 were plotted, other samples exhibited similar behavior.
      Table 3Equations and R2 values for the Arrhenius plots (log k vs. 1/K) and the plots of color units/g of solid vs. storage time.
      Storage temperature (°C)Processor
      WC = Processors from West coast; MW = processor from Midwest.
      EquationR2
      35WC1y = 0.0006x + 0.30760.8247
      45WC1y = 0.0018x + 0.24470.9327
      50WC1y = 0.0057x + 0.21290.8647
      21WC1y = 0.0031x + 0.15920.9395
      35WC2y = 0.0034x + 0.31810.9831
      50WC2y = 0.0073x + 0.38290.9803
      55WC2y = 0.0199x + 0.23870.8811
      21WC2y = 0.0084x + 0.28950.8431
      35MW1y = 0.0028x + 0.30460.9945
      45MW1y = 0.0116x + 0.20070.988
      50MW1y = 0.00204x + 0.27720.8923
      21MW1y = 0.0148x + 0.1181.000
      Arrhenius plotWC1y = 6206.4x − 16.8910.9542
      Arrhenius plotWC2y = 3468.3x − 8.75550.8684
      Arrhenius plotMW1y = 5770.2x − 16.1880.9982
      1 WC = Processors from West coast; MW = processor from Midwest.
      The estimated values from accelerated testing of k at room temperature were determined by extrapolation from the Arrhenius plots of log k vs. 1/T(K) (Figure 2C). The estimated k values were 1.12, 4.90, and 1.35 times bigger than the actual k values for WC1, WC2, and MW, respectively. Actual k values were obtained from samples stored at 21°C and 35% RH. Sample WC2 had the lowest Ea and the highest initial pH, which should result in increased Maillard reaction rate. However, WC2 had a Q10 of 1.77, which is below the range of 2.0 to 8.0 reported for brown pigment formation for a number of food systems (
      • Labuza T.P.
      • Saltmarch M.
      Kinetics of browning and protein quality loss in whey powders during steady state and non steady state storage conditions.
      ). Although WC2 was most prone to Maillard reactions, it had the smallest Q10 implying that for the same increase in temperature, the increase in rate of brown pigment formation was the smallest. One possible cause of the lower than expected rate of Maillard reaction in WC2 might be the presence of an additive that could inhibit or retard the Maillard reaction. The most commonly implicated Maillard reaction inhibitor is sulfur dioxide. No sulfite was detected in the sample (Table 2), but this does not exclude the possibility of sulfur dioxide addition, as it is not readily recovered following reaction (
      • McWeeny D.J.
      Sulfur dioxide and the Maillard reaction in food.
      )
      The higher color units/g of solid in WC2 under high temperature storage could be due to its high mineral content; WC2 had the highest calcium content although the salt content was similar to WC1 (Table 2). It is well known that certain salts and buffers have an accelerating effect on Maillard reactions in solution (
      • Saunders J.
      • Jervis F.
      The role of buffer salts in non-enzymatic browning.
      ;
      • Bell L.N.
      Maillard reaction as influenced by buffer type and concentration.
      ).
      • Burin L.
      • Jouppila K.
      • Roos Y.
      • Kansikas J.
      • Buera M.
      Color formation in dehydrated modified whey powder systems as affected by compression and Tg.
      reported an increased Maillard reaction with increased salt content in anhydrous systems. The salt content of MW1 was significantly higher than for the other samples, which may explain the higher level of browning for this sample when stored under normal storage conditions (Table 4).
      Table 4Rate of brown pigment formation (k), Q10, and activation energy (Ea) for 3 sweet whey powders (WC1, WC2, MW1).
      Processor
      WC = Processors from West coast; MW = processor from Midwest.
      Actual
      Actual k was determined from whey powders stored at 21°C and 35% RH.
      k × 103
      Estimated
      Rate of brown pigment formation (k) determined from accelerated shelf-life testing.
      k × 103
      Estimated
      Factor by which the estimated value is bigger than the actual k.
      k/actual k
      Q10Ea
      In kcal/mol.
      WC13.13.51.123.0028.40
      WC28.039.24.901.7715.872
      MW114.820.11.354.1426.41
      1 WC = Processors from West coast; MW = processor from Midwest.
      2 Actual k was determined from whey powders stored at 21°C and 35% RH.
      3 Rate of brown pigment formation (k) determined from accelerated shelf-life testing.
      4 Factor by which the estimated value is bigger than the actual k.
      5 In kcal/mol.
      Sample WC1 was the most stable whey powder with the highest Ea and the lowest rate of deterioration as measured by the rate of Maillard reaction, k (Table 4). Activation energy values of 20 to 40 kcal/mol have been reported by
      • Labuza T.P.
      • Saltmarch M.
      Kinetics of browning and protein quality loss in whey powders during steady state and non steady state storage conditions.
      in food systems. Samples WC1 and MW1 fell within this range, unlike WC2. Sample WC1 also had the lowest free moisture content (Table 1). The higher free moisture contents in WC2 and MW1 likely contributed to their higher rates of brown pigment formation.
      • Labuza T.P.
      • Saltmarch M.
      Kinetics of browning and protein quality loss in whey powders during steady state and non steady state storage conditions.
      found that an increase in water content above the monolayer value dissolves and mobilizes reactant species for the Maillard reaction, hence increasing the reaction rate.

      Physicochemical and Microbiological Analyses

      Principal component analysis of the microbiological and physicochemical properties of sample MW1 stored under normal storage conditions (Figure 3) showed that Hunter Laboratory values L* (lightness-darkness parameter) and a* (redness-greenness parameter) provided optimal sensitivity for detecting changes in whey powders during storage. An increase in a* represents an increase in red; a decrease in L* represents an increase in darkness (
      • Hutchings J.B.
      ). Sample WC1 did not change in a* parameter, whereas WC2 and MW1 gained in redness. All 3 samples darkened with storage (Table 5).
      Figure thumbnail gr3
      Figure 3First 2 principal components (PC1, PC2) on physicochemical and microbiological data for Midwest whey processor (MW1). There was no significant difference in storage time in the same circle at 95% confidence interval. L* = Hunter Lab lightness-darkness parameter; a* = Hunter Lab red-green parameter; b* = Hunter Lab blue-yellow parameter; SPC = standard plate count; M = mo of storage at 21°C and 35% RH. Bold line separated on PC2; dotted line separated on PC1.
      Table 5Microbiological and physicochemical properties of whey powder stored for up to 19 mo at 21°C and 35% RH.
      Processor
      WC = Processors from West coast; MW = processor from Midwest.
      Storage time (mo)TA
      Titratable acidity determined as % lactic acid.
      (%LA)
      pHSI
      SI = Solubility index.
      (mL)
      % MC
      MC = Moisture content (%).
      L*a*b*SPC
      SPC = Standard plate count.
      (cfu/g)
      MSC
      MSC = Mesophilic spore count.
      (cfu/g)
      Y&M/Coli
      Y&M/Coli = Yeast, molds, and coliform bacteria.
      (cfu/g)
      WC110.11
      Means within columns with different letters are statistically different (P<0.05).
      6.13
      Means within columns with different letters are statistically different (P<0.05).
      <0.1
      Means within columns with different letters are statistically different (P<0.05).
      1.31
      Means within columns with different letters are statistically different (P<0.05).
      91.63
      Means within columns with different letters are statistically different (P<0.05).
      +1.11
      Means within columns with different letters are statistically different (P<0.05).
      +21.99
      Means within columns with different letters are statistically different (P<0.05).
      Means within columns with different letters are statistically different (P<0.05).
      <10ND
      ND = Not detected.
      <10/<10
      50.11
      Means within columns with different letters are statistically different (P<0.05).
      6.10
      Means within columns with different letters are statistically different (P<0.05).
      <0.1
      Means within columns with different letters are statistically different (P<0.05).
      1.32
      Means within columns with different letters are statistically different (P<0.05).
      91.15
      Means within columns with different letters are statistically different (P<0.05).
      +1.25
      Means within columns with different letters are statistically different (P<0.05).
      +22.01
      Means within columns with different letters are statistically different (P<0.05).
      Means within columns with different letters are statistically different (P<0.05).
      <10ND<10/<10
      90.12
      Means within columns with different letters are statistically different (P<0.05).
      6.12
      Means within columns with different letters are statistically different (P<0.05).
      0.11
      Means within columns with different letters are statistically different (P<0.05).
      1.34
      Means within columns with different letters are statistically different (P<0.05).
      90.92
      Means within columns with different letters are statistically different (P<0.05).
      +1.22
      Means within columns with different letters are statistically different (P<0.05).
      +21.69
      Means within columns with different letters are statistically different (P<0.05).
      <10ND<10/<10
      100.10
      Means within columns with different letters are statistically different (P<0.05).
      5.97
      Means within columns with different letters are statistically different (P<0.05).
      0.12
      Means within columns with different letters are statistically different (P<0.05).
      1.14
      Means within columns with different letters are statistically different (P<0.05).
      90.81
      Means within columns with different letters are statistically different (P<0.05).
      +1.17
      Means within columns with different letters are statistically different (P<0.05).
      +22.12
      Means within columns with different letters are statistically different (P<0.05).
      <10ND<10/<10
      190.12
      Means within columns with different letters are statistically different (P<0.05).
      6.00
      Means within columns with different letters are statistically different (P<0.05).
      0.2
      Means within columns with different letters are statistically different (P<0.05).
      1.90
      Means within columns with different letters are statistically different (P<0.05).
      90.69
      Means within columns with different letters are statistically different (P<0.05).
      +1.27
      Means within columns with different letters are statistically different (P<0.05).
      +21.86
      Means within columns with different letters are statistically different (P<0.05).
      Means within columns with different letters are statistically different (P<0.05).
      <10ND<10/<10
      WC210.08
      Means within columns with different letters are statistically different (P<0.05).
      6.45
      Means within columns with different letters are statistically different (P<0.05).
      0.26
      Means within columns with different letters are statistically different (P<0.05).
      1.64
      Means within columns with different letters are statistically different (P<0.05).
      90.90
      Means within columns with different letters are statistically different (P<0.05).
      −0.59
      Means within columns with different letters are statistically different (P<0.05).
      +22.02
      Means within columns with different letters are statistically different (P<0.05).
      400
      Means within columns with different letters are statistically different (P<0.05).
      70
      Means within columns with different letters are statistically different (P<0.05).
      <10/<10
      40.08
      Means within columns with different letters are statistically different (P<0.05).
      Means within columns with different letters are statistically different (P<0.05).
      6.44
      Means within columns with different letters are statistically different (P<0.05).
      0.25
      Means within columns with different letters are statistically different (P<0.05).
      1.65
      Means within columns with different letters are statistically different (P<0.05).
      90.82
      Means within columns with different letters are statistically different (P<0.05).
      −0.72
      Means within columns with different letters are statistically different (P<0.05).
      +21.94
      Means within columns with different letters are statistically different (P<0.05).
      200
      Means within columns with different letters are statistically different (P<0.05).
      85
      Means within columns with different letters are statistically different (P<0.05).
      <10/<10
      50.09
      Means within columns with different letters are statistically different (P<0.05).
      6.31
      Means within columns with different letters are statistically different (P<0.05).
      0.25
      Means within columns with different letters are statistically different (P<0.05).
      1.61
      Means within columns with different letters are statistically different (P<0.05).
      90.42
      Means within columns with different letters are statistically different (P<0.05).
      −0.66
      Means within columns with different letters are statistically different (P<0.05).
      +22.84
      Means within columns with different letters are statistically different (P<0.05).
      260
      Means within columns with different letters are statistically different (P<0.05).
      90
      Means within columns with different letters are statistically different (P<0.05).
      Means within columns with different letters are statistically different (P<0.05).
      <10/<10
      70.09
      Means within columns with different letters are statistically different (P<0.05).
      Means within columns with different letters are statistically different (P<0.05).
      6.4
      Means within columns with different letters are statistically different (P<0.05).
      0.25
      Means within columns with different letters are statistically different (P<0.05).
      1.66
      Means within columns with different letters are statistically different (P<0.05).
      90.67
      Means within columns with different letters are statistically different (P<0.05).
      −0.73
      Means within columns with different letters are statistically different (P<0.05).
      +22.87
      Means within columns with different letters are statistically different (P<0.05).
      230
      Means within columns with different letters are statistically different (P<0.05).
      150
      Means within columns with different letters are statistically different (P<0.05).
      <10/<10
      100.10
      Means within columns with different letters are statistically different (P<0.05).
      6.2
      Means within columns with different letters are statistically different (P<0.05).
      0.20
      Means within columns with different letters are statistically different (P<0.05).
      1.93
      Means within columns with different letters are statistically different (P<0.05).
      90.66
      Means within columns with different letters are statistically different (P<0.05).
      −0.11
      Means within columns with different letters are statistically different (P<0.05).
      +20.57
      Means within columns with different letters are statistically different (P<0.05).
      150
      Means within columns with different letters are statistically different (P<0.05).
      90
      Means within columns with different letters are statistically different (P<0.05).
      Means within columns with different letters are statistically different (P<0.05).
      <10/<10
      190.09
      Means within columns with different letters are statistically different (P<0.05).
      6.35
      Means within columns with different letters are statistically different (P<0.05).
      0.20
      Means within columns with different letters are statistically different (P<0.05).
      2.04
      Means within columns with different letters are statistically different (P<0.05).
      90.15
      Means within columns with different letters are statistically different (P<0.05).
      −0.21
      Means within columns with different letters are statistically different (P<0.05).
      +22.55
      Means within columns with different letters are statistically different (P<0.05).
      220
      Means within columns with different letters are statistically different (P<0.05).
      85
      Means within columns with different letters are statistically different (P<0.05).
      <10/<10
      MW110.12
      Means within columns with different letters are statistically different (P<0.05).
      6.18
      Means within columns with different letters are statistically different (P<0.05).
      0.3
      Means within columns with different letters are statistically different (P<0.05).
      1.80
      Means within columns with different letters are statistically different (P<0.05).
      91.38
      Means within columns with different letters are statistically different (P<0.05).
      −0.42
      Means within columns with different letters are statistically different (P<0.05).
      +22.89
      Means within columns with different letters are statistically different (P<0.05).
      1910
      Means within columns with different letters are statistically different (P<0.05).
      ND<10/<10
      50.13
      Means within columns with different letters are statistically different (P<0.05).
      6.06
      Means within columns with different letters are statistically different (P<0.05).
      0.3
      Means within columns with different letters are statistically different (P<0.05).
      2.02
      Means within columns with different letters are statistically different (P<0.05).
      Means within columns with different letters are statistically different (P<0.05).
      91.22
      Means within columns with different letters are statistically different (P<0.05).
      −0.46
      Means within columns with different letters are statistically different (P<0.05).
      +22.50
      Means within columns with different letters are statistically different (P<0.05).
      2480
      Means within columns with different letters are statistically different (P<0.05).
      ND<10/<10
      90.15
      Means within columns with different letters are statistically different (P<0.05).
      6.15
      Means within columns with different letters are statistically different (P<0.05).
      0.28
      Means within columns with different letters are statistically different (P<0.05).
      2.26
      Means within columns with different letters are statistically different (P<0.05).
      91.35
      Means within columns with different letters are statistically different (P<0.05).
      −0.43
      Means within columns with different letters are statistically different (P<0.05).
      +21.75
      Means within columns with different letters are statistically different (P<0.05).
      4060
      Means within columns with different letters are statistically different (P<0.05).
      ND<10/<10
      110.12
      Means within columns with different letters are statistically different (P<0.05).
      6.08
      Means within columns with different letters are statistically different (P<0.05).
      0.27
      Means within columns with different letters are statistically different (P<0.05).
      1.86
      Means within columns with different letters are statistically different (P<0.05).
      90.53
      Means within columns with different letters are statistically different (P<0.05).
      −0.27
      Means within columns with different letters are statistically different (P<0.05).
      +24.34
      Means within columns with different letters are statistically different (P<0.05).
      1070
      Means within columns with different letters are statistically different (P<0.05).
      ND<10/<10
      190.12
      Means within columns with different letters are statistically different (P<0.05).
      6.09
      Means within columns with different letters are statistically different (P<0.05).
      0.24
      Means within columns with different letters are statistically different (P<0.05).
      2.37
      Means within columns with different letters are statistically different (P<0.05).
      89.80
      Means within columns with different letters are statistically different (P<0.05).
      −0.40
      Means within columns with different letters are statistically different (P<0.05).
      +24.31
      Means within columns with different letters are statistically different (P<0.05).
      180
      Means within columns with different letters are statistically different (P<0.05).
      ND<10/<10
      a–e Means within columns with different letters are statistically different (P < 0.05).
      1 WC = Processors from West coast; MW = processor from Midwest.
      2 Titratable acidity determined as % lactic acid.
      3 SI = Solubility index.
      4 MC = Moisture content (%).
      5 SPC = Standard plate count.
      6 MSC = Mesophilic spore count.
      7 Y&M/Coli = Yeast, molds, and coliform bacteria.
      8 ND = Not detected.
      Storage time had a highly significant effect on moisture. During the 19-mo storage period, moisture content increased by 32% for MW1, 45% for WC1, and 24% for WC2. Variations in moisture gain might be attributed to differences in water vapor transmission rate of the packaging material and to differences in hygroscopicity. Furthermore, differences in the gain in free moisture could be a result of the lactose crystal formed as bound water can be released during the transformation among amorphous and crystal lactose as well as the different lactose crystalline forms. A decreasing trend in pH was observed for all 3 samples. Decreases in whey pH as browning progresses were reported by
      • del Pilar Buera M.
      • Chirife J.
      • Resnik S.L.
      Nonenzymatic nonoxidative browning in hydrolyzed shelf-stable concentrated cheese whey.
      . Other causes for variation in deterioration rate of the whey powders might be related to differences in processing. No information was available regarding differences in processing parameters at the 3 manufacturing plants. Standard plate count decreased during storage for WC2 and MW1. Sample MW1 exhibited a 10-fold decrease, and WC2 had a 2-fold decrease (Table 5). However, there was no significant change in the mesophilic spore count with storage for WC2, the only sample that contained mesophilic spores. The microbiological quality of WC1 was excellent, as no standard plate count or mesophilic spore count was detected. No yeast, molds, or coliform bacteria were detected in any of the samples.

      Sensory Evaluation

      Even though the sensory panel was highly trained, no significant differences were found in odor and flavor of the whey powders during 19 mo of storage. The mean rating and standard deviation for each of the descriptors tested are given in Table 6. The Maillard reaction has been reported to lead to flavor and aroma changes during storage. However, in this study, even the most rapidly deteriorating whey powder, as determined by the Maillard reaction, still had flavor and aroma perceived to be similar to that after 1 mo of storage.
      Table 6Mean rating
      Mean of duplicate testing by 13 panelists; rating scale was a 15-point scale, where 3 = slight, and 7 = moderate.
      (± standard deviation) for sensory descriptors tested of sweet whey powder (WC1, WC2, MW1)
      WC = Processors from West coast; MW = processor from Midwest.
      stored for up to 19 mo at 21°C and 35% RH.
      Storage time (mo)Sweet aromatic flavorCaramelized flavorCooked flavorCardboard flavorOxidized flavorBarnySweet aromatic aromaCaramelized aromaCooked aromaCardboard aromaOxidized aromaSweet flavorSour flavorSalty flavor
      WC1
      11.41 (1.53)2.41 (1.59)3.92 (1.75)1.82 (1.54)1.21 (1.30)0.82 (1.36)1.46 (1.52)2.72 (1.60)4.38 (1.98)1.41 (1.23)1.21 (1.26)4.10 (2.06)1.59 (1.74)2.59 (2.42)
      51.44 (1.41)2.72 (1.54)4.03 (1.89)1.51 (1.41)1.13 (1.26)0.95 (1.17)1.51 (1.59)3.03 (1.76)4.46 (1.78)1.56 (1.29)1.23 (1.22)4.31 (1.79)1.49 (1.41)2.72 (2.46)
      91.18 (1.28)2.72 (1.61)4.15 (2.20)1.59 (1.55)1.10 (1.14)1.21 (1.36)1.38 (1.33)3.05 (1.86)4.36 (2.01)1.62 (1.27)1.54 (1.65)3.82 (1.80)1.26 (1.48)2.72 (2.32)
      121.26 (1.29)2.54 (1.92)3.90 (1.20)1.92 (1.58)1.10 (1.94)1.36 (1.87)1.41 (1.33)2.92 (1.80)4.36 (1.83)1.79 (1.30)1.31 (1.54)4.31 (1.95)1.44 (1.52)2.49 (2.30)
      191.38 (1.39)2.44 (1.85)4.10 (2.44)1.87 (1.61)1.56 (1.31)1.59 (2.15)1.36 (1.42)2.49 (2.00)4.21 (2.52)1.79 (1.13)1.90 (1.73)3.79 (1.542)1.41 (1.52)2.56 (2.22)
      WC2
      11.23 (1.35)2.67 (1.87)3.77 (1.97)1.92 (1.69)1.74 (1.63)1.62 (1.81)1.59 (1.41)2.77 (1.56)4.28 (1.91)1.95 (1.54)1.41 (1.71)4.82 (1.89)1.15 (1.25)2.21 (1.92)
      51.31 (1.32)2.67 (2.04)3.97 (2.18)2.10 (1.55)1.44 (1.41)1.41 (1.48)1.54 (1.54)2.85 (1.73)4.15 (2.05)1.77 (1.56)1.44 (1.59)4.79 (1.70)0.90 (1.07)2.33 (1.98)
      100.97 (1.11)2.51 (2.02)4.00 (2.25)2.15 (1.46)1.85 (1.48)1.49 (1.45)1.31 (1.10)2.87 (2.31)4.33 (2.09)1.69 (1.26)1.97 (1.61)3.87 (1.56)1.23 (1.40)2.74 (2.12)
      120.97 (1.20)2.74 (1.93)3.74 (1.59)2.44 (1.20)1.85 (1.51)2.00 (1.59)1.31 (1.10)3.05 (1.79)3.95 (1.81)2.00 (1.34)2.15 (1.91)4.23 (1.98)0.90 (1.07)2.31 (1.91)
      191.00 (1.17)2.72 (1.99)4.03 (2.67)2.38 (1.70)1.97 (1.83)1.85 (1.73)1.46 (1.43)2.72 (1.959)4.16 (2.746)1.95 (1.30)1.67 (1.60)4.54 (2.10)1.00 (1.34)2.26 (1.76)
      MW1
      11.10 (1.19)2.90 (2.32)3.95 (2.08)1.97 (1.40)1.64 (1.46)1.64 (1.56)1.10 (1.12)3.10 (2.25)4.18 (2.38)1.79 (1.40)1.72 (1.65)3.54 (1.55)1.41 (1.48)2.64 (2.40)
      51.23 (1.08)2.08 (1.65)3.87 (2.14)2.31 (2.12)1.64 (1.63)1.44 (1.35)1.23 (1.14)2.44 (2.14)4.28 (2.20)2.03 (1.530)1.74 (1.67)3.15 (1.48)1.69 (1.95)3.46 (2.60)
      90.92 (1.13)3.05 (2.13)4.10 (1.90)2.49 (1.54)1.69 (1.54)1.13 (1.32)1.03 (1.04)2.92 (2.03)3.97 (1.91)2.28 (1.45)1.64 (1.60)3.51 (1.67)2.15 (2.38)3.53 (2.69)
      121.21 (1.49)2.56 (1.92)3.85 (2.28)2.31 (1.85)1.49 (1.34)1.59 (1.48)1.03 (1.11)3.03 (1.94)4.15 (2.37)2.00 (1.40)1.54 (1.67)3.72 (1.64)1.33 (1.56)2.67 (2.42)
      191.18 (1.10)3.08 (2.10)4.11 (2.18)2.62 (1.89)1.77 (1.53)1.18 (1.17)1.10 (1.07)3.18 (2.08)4.38 (1.84)2.21 (1.26)1.59 (1.55)3.85 (1.58)1.38 (1.53)2.79 (2.51)
      1 Mean of duplicate testing by 13 panelists; rating scale was a 15-point scale, where 3 = slight, and 7 = moderate.
      2 WC = Processors from West coast; MW = processor from Midwest.

      Conclusion

      Our data suggest that whey powder has a shelf life longer than 12 mo, which is the typical shelf life reported by commercial suppliers. The deterioration rates of the sweet whey powders from the 3 processors were different. The sample with the fastest rate of deterioration, as determined by the Maillard reaction, was found to deteriorate the fastest as determined by the physicochemical parameter (Hunter Laboratory color parameter L*). However, the flavor and aroma of all whey powder samples remained constant. Although the Maillard reaction plays a major role in determining the rate of deterioration of whey powders at elevated temperatures, the rate at ambient conditions for the 3 samples was too low to cause any significant difference during storage up to 19 mo. Because free moisture content changed significantly with storage at ambient temperature, parameters related to moisture content, such as hygroscopicity and caking, should be explored in shelf-life studies of whey powder. It appears likely that whey powders deteriorate because of loss of functional properties such as flowability and dispersibility before any changes in taste and aroma are observed.

      Acknowledgments

      Financial support was provided by Tillamook County Creamery Association, and the Eckelman Foundation.

      Supplementary data

      References

        • American Dairy Products Institute
        Whey and Whey Products: Definitions, Composition, Standard Methods of Analysis.
        Bulletin W-16. American Dairy Products Inst., Chicago, IL1991 (7–19)
        • AOAC
        Official Methods of Analysis.
        16th ed. Association of Official Analytical Chemists International, Gaithersburg, MD1995
        • AOAC
        Official Methods of Analysis.
        17th ed. Association of Official Analytical Chemists International, Gaithersburg, MD2000
        • A/S Niro Atomizer
        Determination of moisture.
        in: Haugaard Sorensen I. Krag J. Piecky J. Westergaard V. Analytical Methods for Dry Milk Products. 4th ed. De Forenede Trykerier A/S, Copenhagen, Denmark1978: 10-11
        • Bell L.N.
        Maillard reaction as influenced by buffer type and concentration.
        Food Chem. 1997; 59: 143-147
        • Burin L.
        • Jouppila K.
        • Roos Y.
        • Kansikas J.
        • Buera M.
        Color formation in dehydrated modified whey powder systems as affected by compression and Tg.
        J. Agric. Food Chem. 2000; 48: 5263-5268
        • Cämmerer B.
        • Wedzicha B.L.
        • Kroh L.W.
        Nonenzymatic browning reactions of retro-adol degradation products of carbohydrates.
        Eur. Food Res. Technol. 1999; 209: 261-265
        • Choi R.P.
        • O’Malley C.M.
        • Fairbanks B.W.
        A proposed method for the determination of color of dry products of milk.
        J. Dairy Sci. 1949; 32: 580-586
        • del Pilar Buera M.
        • Chirife J.
        • Resnik S.L.
        Nonenzymatic nonoxidative browning in hydrolyzed shelf-stable concentrated cheese whey.
        J. Food Sci. 1990; 55: 697-700
        • Ford J.E.
        • Hurrel R.F.
        • Finot P.A.
        Storage of milk powders under adverse conditions. 2. Influence of the content of water-soluble vitamins.
        Br. J. Nutr. 1983; 49: 355-364
        • Franzen K.
        • Singh R.K.
        • Okos M.R.
        Kinetics of nonenzymatic browning in dried skim milk.
        J. Food Eng. 1990; 11: 225-239
        • Hutchings J.B.
        Hutchings J.B. Instrumental Specification, Food Color and Appearance. Blackie Academic & Professional, Glasgow, UK1994: 221
        • Kamath A.
        • Ravi R.
        • Rajalakshmi D.
        Sensory profiling and positioning of commercial samples of milk powder.
        J. Sens. Stud. 1999; 14: 303-319
        • Karagül-Yüceer Y.
        • Drake M.
        • Cadwallader K.R.
        Aroma active components of nonfat dry milk.
        J. Agric. Food Chem. 2001; 49: 2948-2953
        • Kim M.
        • Saltmarch M.
        • Labuza T.P.
        Nonenzymatic browning of hygroscopic whey powders in open versus sealed pouches.
        J. Food Process. Preserv. 1981; 5: 49-57
        • Labuza T.P.
        • Saltmarch M.
        Kinetics of browning and protein quality loss in whey powders during steady state and non steady state storage conditions.
        J. Food Sci. 1981; 47: 92-96
        • Lawless H.T.
        • Heymann H.
        Sensory Evaluation of Food, Principles and Practices.
        Aspen Publishers, Inc., Frederick, MD1999 (pages 358–362)
        • McWeeny D.J.
        Sulfur dioxide and the Maillard reaction in food.
        Prog. Food Nutr. Sci. 1981; 5: 395-404
        • Nielsen B.R.
        • Stapelfeldt H.
        • Skibsted L.H.
        Early prediction of the shelf-life of medium-heat whole milk powders using stepwise multiple regression and principal component analysis.
        Int. Dairy J. 1997; 7: 341-348
        • Presa-Owens S.
        • López-Sabater M.
        • Rivero-Urgell M.
        Shelf-life prediction of an infant formula using an accelerated stability test (Rancimat).
        J. Agric. Food Chem. 1995; 43: 2879-2882
        • Richardson G.H.
        Standard Methods for the Examination of Dairy Products.
        15th ed. American Public Health Association, Washington, DC1985
        • Saltmarch M.
        • Labuza T.
        Influence of relative humidity on the physicochemical state of lactose in spray-dried sweet whey powders.
        J. Food Sci. 1980; 45: 1231-1236
        • Saltmarch M.
        • Labuza T.P.
        SEM investigation of the effect of lactose crystallization on the storage properties of spray dried whey.
        Scan. Electron Microsc. 1981; 3: 659-665
        • Saunders J.
        • Jervis F.
        The role of buffer salts in non-enzymatic browning.
        J. Sci. Food Agric. 1966; 17: 245-249
        • Stone H.
        • Sidel J.L.
        Sensory evaluation practices.
        Academic Press, Inc., Boston, MA1993
      1. Villota, R., and J. G. Hawkes. 1983. Effect of processing on kinetics of nutrients and organoleptic changes in foods. Paper presented at the Winter Meeting of the Am. Soc. Agric Engr., St. Joseph, MI.

        • Waletzko P.
        • Labuza T.P.
        Accelerated shelf life testing of an intermediate moisture food in air and in an oxygen-free atmosphere.
        J. Food Sci. 1976; 41: 1338-1344