THE IMPACT OF NUT INCLUSIONS ON PROPERTIES AND STABILITY OF DARK CHOCOLATE
by
ANDREA ROSSI-OLSON
A Dissertation submitted to the
Graduate School-New Brunswick
Rutgers, The State University of New Jersey
in partial fulfillment of the requirements
for the degree of
Doctor of Philosophy
Graduate Program in Food Science
written under the direction of
Karen M. Schaich
and approved by
______
______
______
______
______
New Brunswick, New Jersey
May 2011
2011
Andrea Rossi-Olson
ALL RIGHTS RESERVED
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ABSTRACT OF THE DISSERTATION
The Impact of Nut Inclusions on Properties and Stability of Dark Chocolate
By ANDREA ROSSI-OLSON
Dissertation Director:
Karen M. Schaich
Chocolate bars have become increasingly gourmet in the types of chocolate used and addition of a variety of inclusions such as nuts, fruits, and cereal grains. These factors all have marked impacts on shelf life, as do storage conditions and handling.
Understanding interactions among ingredients is crucial for developing improved approaches to maximize shelf life and maintain quality of chocolate products over time.
The most noticeable defect in chocolate is bloom, which presents itself as a white haze on the chocolate surface. Bloom is inevitable over time, but the goal is to prolong its onset as long as possible. One of the many theories proposed to explain the complex phenomenon of bloom is that migration of incompatible fats, specifically from nuts, imposes a second crystal phase, dissolves some cocoa butter, and causes a rearrangement of cocoa butter crystals to highly structured, high melting point forms that deposit on the chocolate surface. Nuts readily develop rancidity and introduce off-flavors into chocolate.
Migration of oil from nuts also affects the chocolate matrix itself, altering snap, molding, and gloss as well as crystal form and texture stability. Although nuts are extensively added to chocolate as inclusions, very little basic research has focused on how different nuts affect chocolate properties and stability.
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To provide a base of fundamental information that can be applied to improving a wide variety of chocolate products, this study follows migration of oils from roasted monounsaturated almonds and polyunsaturated walnuts into dark chocolate with and without anhydrous milk fat as a crystallization modifier. Oil migration kinetics, nut fatty acid and antioxidant profiles, as well as chocolate melting patterns, crystal forms and shifts, texture properties (snap), bloom, lipid oxidation products and oxidative storage stability, and sensory qualities are being measured to determine the major failure mode
(texture, flavor, or bloom) in chocolate. Current industry theories are based primarily on unsaturation and oxidative instability of nuts, but there is little data available. An investigation of nut fatty acid profiles and effects on chocolate crystallization may offer new ways to use nuts that previously have been avoided.
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ACKNOWLEDGEMENTS
It has been a long journey to achieve this milestone. I have many people to thank for their support.
I would first like to thank my advisor Dr. Karen Schaich, who has worked with me through three degrees and has always been encouraging and inspiring. Thank you for your flexibility and your mentorship.
Next I would like to acknowledge Mars Inc., especially Dr. Christopher Johnson.
Dr. Johnson has taught me a plethora of analytical techniques, but also the basics to being a great investigator. I appreciate your practical approach to research and its application and your patience and support through this project.
I would also like to thank the following Mars Inc. associates for training me in the analytical techniques I needed for my research: Dana Carpenter (tocopherols-HPLC),
Haroon Malak (FAME-GC and XRD), Paul Spitz (DSC), Julia Li (Peroxide Value,
Alkenals and Proanthocyanidins), James Zimmer (Texture Analysis), John Munafo and
Vivianna Chaparro (SAFE analysis), Maria Lenzi and Karl Ritter (Colorimeter) and Tom
Collins and Rodrigo Campos for assistance with model system set up. I would also like to thank Barry Glazier, Doug Valkenberg and David Hausman for chocolate making instruction, Mark Kline for nut roasting assistance, Charlotte Liang for sensory testing guidance as well as the Mars Sensory team for descriptive analysis participation and
Wendy Kessell for chocolate and bar making assistance.
Lastly, I would like to thank my family and my husband Dain for allowing me to follow my dreams while being the perpetual student. This has been a very long road and I am grateful to have you all by my side along this journey.
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TABLE OF CONTENTS
Abstract ii
Acknowledgement v
Table of Contents vi
List of Tables xii
List of Figures xiv
1. Introduction 1
2. Literature Review 4
2.1. Chocolate Processing 10
2.1.1. Chocolate Components Structure and Function 10
2.1.1.1. Cocoa butter 10
2.1.1.2. Cocoa liquor 12
2.1.1.3. Milk Products 12
2.1.1.4. Milk Fat 12
2.1.1.5. Milk Protein 14
2.1.1.6. Emulsifiers 14
2.1.1.7. Sugar 15
2.1.2. Molecular interactions responsible for chocolate properties and stability 15
2.1.2.1. Impact of Particle Size 15
2.1.2.2. Cocoa butter crystallization / Texture in chocolate 17
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2.1.2.2.1. Fat Migration in Chocolate 22
2.1.2.2.2. Effect of Minor Lipids 24
2.1.2.2.3. Compatibility 25
2.1.2.3. Bloom 29
2.1.2.3.1. Bloom Theories 31
2.1.2.3.2. Phase Separation 31
2.1.2.3.3. Polymorphic Transitions 31
2.1.2.3.4. Fat Migration 32
2.1.2.3.5. Bloom in Filled Pieces 33
2.1.2.3.6. Chocolate Coatings 36
2.1.2.3.7. Impact of Chocolate Microstructure 37
2.1.2.3.8. Effect of Milk Fat 38
2.1.2.3.9. Effect of Storage 40
2.2. Effects of nuts on chocolate properties 40
2.2.1. Nut Varieties 43
2.2.1.1. Peanuts 43
2.2.1.2. Hazelnuts 44
2.2.1.3. Walnuts 46
2.2.1.4. Macadamia 48
2.2.1.5. Cashews 48
2.2.1.6. Almonds 49
2.2.2. Properties of Nuts that Affect Their Use as Chocolate Bar Inclusions 51
2.2.2.1. Impact of Roasting 52
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2.2.2.2. Impact of Chop Size 54
2.2.2.3 Impact of Storage and Processing 55
2.2.2.4. Impact of Nut Lipids on Chocolate Stability 55
2.2.2.5. Interaction with Chocolate 55
2.2.2.5.1. Oil Migration 55
2.2.2.5.2. Lipid Oxidation 56
2.2.2.6. Antioxidants in Nuts 59
2.2.2.7. Nuts and Health 62
2.3. Measuring Quality Parameters in Chocolate 62
2.3.1. Current Detection Methods 62
2.4. Challenges and Trends 63
2.5. Knowledge Gaps 67
3. Hypothesis and Objectives 68
3.1. Hypothesis 68
3.2. Goals and Objectives of This Study 68
4. Preliminary Experiments to Establish Standards and Methodology 71
4.1. General approach and observations 71
4.2. Experimental Methods for Raw Ingredient Testing and Evaluation 76
4.4. Evaluation of Raw Materials 76
4.5. Ingredient Processing 80
4.5.1. Nut Roasting 80
4.3.2. Nut Grinding 80
4.3.3. Sensory Analysis of Roasted Nuts 82
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4.3.4. Chocolate Processing 82
4.3.4.1. Chocolate Ingredients 84
4.3.4.2. Nut Inclusion Specifications 84
5. Experimental Methods and Procedures 85
5.1. Overall Experimental Design 85
5.1.1. Model Systems 89
5.2. Analytical Procedures 93
5.3. Theory of Methodology, Information Expected and Detailed Procedures 94
5.3.1. Particle Size 94
5.3.2. FAME Gas Chromatography 95
5.3.3. Colorimeter 99
5.3.4. Texture Profile Analysis 101
5.3.5. DSC 102
5.3.6. Lipid Oxidation 106
5.3.6.1. Peroxide Values 107
5.3.6.2. Secondary Products 111
5.3.6.3. Rancimat 113
5.3.6.4. Tocopherols 116
5.3.6.5. Other Antioxidants 121
5.3.6.6. Crystallography X-Ray Diffraction 127
5.3.6.7. SAFE Analysis 131
5.3.6.8. Sensory 134
5.3.6.9. Model System 139
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5.3.7.0. Accelerated Shelf Life 140
6. Results 141
6.1. Nut Stability Testing 141
6.1.1. Oxidative Stability 141
6.1.2. Tocopherols 150
6.1.3. Procyanidins 159
6.1.4. Sensory 161
6.2. Stability of Chocolate Bars with Almonds and Walnuts 166
6.2.1. Lipid Oxidation Products 166
6.2.2. SAFE Test 175
6.2.3. Tocopherols 180
6.2.4. Proanthocyanins 184
6.3. Fat Migration from Nuts to Chocolate 188
6.3.1. FAME-GC Data 188
6.3.2. Texture Analysis for Softening Due to Fat Migration 194
6.3.3. DSC evidence of multiple crystal forms 199
6.4 Quantification of Bloom 215
6.4.1. Accelerated Chamber 220
6.5. Sensory Results 221
6.6. Model System 229
6.6.1. FAME Results 230
6.6.2. DSC Results 230
6.6.3. XRD Results 235
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7. Summary and Integration of Results 245
8. Significance and Impact of Results 259
9. Future Work 261
10. References 262
11. Curriculum Vita 271
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LIST OF TABLES
1. Fatty Acid Composition of Cocoa Butters 11
2. Fatty Acid Profile of Milk Fat 12
3. Polymorphs of Cocoa Butter 19
4. Fatty Acid and Total Fat Content of Nuts 42
5. Typical Shelf Life Values for Almonds 51
6. Volatile Carbonyl Compounds formed by Autoxidation 59
7. Average Polyphenol Content of Almonds and Walnuts 62
8. Roasting Conditions Producing Acceptable Nuts 72
9. Sensory Feedback on Roasted Nuts 73
10. Roasted Nut Batch Sizes 75
11. FAME Analysis Results for Chocolate Bars 77
12. FAME Analysis Results for Cocoa Butter and AMF 78
13. FAME Analysis Results for Raw Nuts 79
14. Basic Dark Chocolate Formulation 83
15. Schedule for Analysis of Chocolate Samples 87
16. Schedule for End of Shelf Life Testing for Chocolate Samples 89
17. Rancimat Induction Times 116
18. Effect of Temperature on Rancimat Induction Time 116
19. Spectrum Method for Flavor Intensity 135
20. Flavor Attributes for Sensory Evaluation 136
21. Oxidative Stability of Oil from Raw and Roasted Nuts 142
22. Peroxide Values in Raw and Roasted Nuts 143
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23. Secondary Products in Raw and Roasted Nuts 149
24. Total Tocopherol Loss from Almonds and Walnuts 151
25. Tocopherol Levels in Nuts 155
26. Procyanidin Levels in Roasted Nuts 160
27. Sensory Ratings of Nuts 163
28. Lipid Hydroperoxide Levels 168
29. Aldehydic Secondary Lipid Oxidation Products 173
30. SAFE Analyses of Volatiles Released from an Oxidized Walnut Sample. 176
31. Procyanidin Levels in Chocolate Bars with Nuts Inclusions 185
32. FAME-GC Oil Migration Trends 190
33. Texture Analysis Values for Chocolate 196
34. Colorimeter Quantification of Bloom 218
35. Whiteness Calculations from Colorimeter Data 219
36. Sensory Ratings of Chocolate Bars Weeks 0, 4, 8, 12, 16, 20, 24, 30 222
37. FAME Results for Model System 230
38. DSC Results for Model System 233
39. XRD Short Spacing Analysis 239
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LIST OF FIGURES
1. Chocolate Tempering Program 5
2. Tricor Temper Unit and Temper Curves 9
3A. Triple Chain Packing of Cocoa Butter TAGs 20
3B. TAG Packing Comparison 20
4. Particle Size Effects on Oil Migration in Chocolate 24
5. Isosolid Diagram for Cocoa Butter and Milk Fat 28
6. Isosolid Diagram for SFC of Nut Oil Systems 29
7. Classic Free Radical Chain of Lipid Oxidation 57
8. Structure of Tocopherol 60
9. Blodgett Convection Oven 80
10. Ro-Tap Sieve Shaker 81
11. Old Tyme Nut Grinder 82
12. Process Flow Diagram 86
13. Model System: Cylinder 90
14. Cocoa butter and Nut Model System 92
15. Surface Dulling and Bloom Formation on Chocolate Bars 100
16. Minolta Colorimeter 100
17. Typical TPA Curves 102
18. Typical DSC Curves for Chocolate 104
19. Rancimat Instrumentation 115
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20. HPLC Chromatography of Tocopherol Isomers 121
21. Phase Diagram for Crystallization of Polymorphism 128
22. Xray Diffractor 129
23. Typical XRD Scan for Cocoa Butter 130
24. Distillation Set-up for SAFE 132
25. Sample Test Panel Response for Evaluation of Nuts and Chocolate 138
26. Peroxide Values for Walnuts 142
27. Alkenal Levels in Roasted Nuts 148
28. Changes in Gamma Tocopherol Levels in Chocolate 152
29. Changes in Total Tocopherol Levels in Chocolate 157
30. Changes in Alpha Tocopherol in Almonds and Walnuts 157
31. Changes in Gamma Tocopherol in Almonds and Walnuts 158
32. Changes in Delta Tocopherol in Almonds and Walnuts 158
33. Effect of Chop and Roast on Peroxide Values for Walnut Bars without Milk Fat 169
34. Effect of Chop and Roast on Peroxide Values for Walnut Bars with Milk Fat 169
35. Peroxide Values for Almond Bars 170
36. Effect of Milk Fat on Peroxide Values for Whole Walnut Bars 170
37. Effect of Milk Fat on Peroxide Values for Chopped Walnut Bars 171
38. Aldehyde Levels in Almond and Walnut Bars 175
39. Reaction for the formation of alkyl pyrazines during roasting of nuts. 175
40. Formation of Oxidation Products via Cleavage Reactions 177
41. SAFE Results Comparing Oxidized and Non-Oxidized Samples 179
42. Changes in Alpha Tocopherol Levels in Almond Bars 182
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43. Changes in Gamma Tocopherol Levels in Almond Bars 182
44. Changes in Gamma Tocopherol Levels in Walnut Bars with MF 183
45. Changes in Gamma Tocopherol Levels in Walnut Bars without MF 183
46. Procyanidin Levels in Chocolate bars 187
47. Procyanidin Levels in Chopped Nut Chocolate bars 188
48. Hardness Values from Texture Analysis 198
49. DSC Curve of Cocoa Butter 201
50. DSC Curve of Chocolate without Milk Fat 202
51. DSC Curve of AMF 203
52. DSC Curve of Chocolate with Milk Fat 204
53. DSC Curve Walnut Dark Chocolate Bar with Milk Fat 205
54. DSC Curve Walnut Dark Chocolate Bar without Milk Fat 206
55. DSC: Changes in Peak Area over Time 209
56. DSC: Changes in Peak Area over Time without Milk Fat 211
57. DSC: Changes in Peak Area over Time with Milk Fat 211
58. Changes in proportions of two crystal forms during storage 214
59a. Colorimeter L Value for Chocolate Bars with Almonds 217
59b. Colorimeter L Values for Chocolate Bars with Walnuts 217
60. DSC Model System Walnut Whole Chopped Low Cycle 4 232
61. Changes in Peak Areas for Model System DSC Results 234
62. XRD Scan Cocoa Butter 237
63. Short and Long Spacings of TAGs 238
64A. XRD Scans of Model System Walnut Whole Medium 241
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64b. XRD Scans of Model System Walnut Whole Medium 242
64c. XRD Scans of Model System Walnut Chop Low 243
64d. XRD Scans of Model System Walnut Chop Medium 244
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INTRODUCTION
Chocolate is a favorite confection the world around. Evidence of cocoa cultivation dates back to 1100 -1400 BC in Honduras. In early times, chocolate solids were consumed mainly in beverages. One of the earliest record drinks was xocolātl, the traditional hot beverage spiced with cinnamon and pepper made famous by the Mayans and Aztecs. Over time chocolate, the rich flavor and unique properties of cocoa butter were also recognized, and the chocolate confections we enjoy today began to be developed (Beckett, 2000).
Although modern day chocolate manufacture is based on the same principles as early chocolate makers, the product has changed in many ways, and chocolate manufacturers face many challenges in offering high quality chocolate products while maintaining profitability. The US chocolate industry is now huge, estimated at $16 billion a year in 2006 according to the U.S. Market for Chocolate (Mindbranch, 2008).
There is a constant need to balance increased ingredient and transportation costs against higher-level expectations of ever more savvy consumers. Chocolate bars today are much more gourmet in types of chocolate used and addition of a variety of inclusions such as nuts, fruits and cereal grains. These factors all have marked impacts on shelf life, as do storage conditions and handling during global distribution. Understanding interactions among ingredients is crucial for developing improved approaches to maximize shelf life and maintain quality of chocolate products over time. At the same time, optimization of processing parameters, recipe formulations and other improvements can potentially offer significant cost savings and have enormous impact on profits.
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For consumers, a major indication of quality in chocolate is the texture, both surface and internal. Desirable texture has a fine grain and smooth shiny surface which results from very specific crystallization of triacylglycerols in cocoa butter during tempering. Notable defects in texture result when this crystallization pattern does not occur, for example when other fats are introduced, either as direct ingredients or in migration from inclusions, and disrupt the normal crystallization and melting patterns.
Even more obvious are defects that arise from rearrangement of crystal forms.
Consumers readily recognize the graininess and white film of crystals on the chocolate surface, called bloom. Bloom results from an accumulation of incorrect crystal forms during defective processing or from temperature cycling during storage. Bloom is inevitable over time, but the goal is to prolong its onset as long as possible.
Bloom can be controlled with relative ease in plain chocolate products by proper tempering, inclusion of crystallization inhibitors such as lecithin, and temperature control during storage. However, many chocolate confections contain either nut fillings or chopped/whole nuts and here the problem is much more complex because of the migration of potentially incompatible fats from the nuts to the chocolate. Nuts are well- known sources of unsaturated fatty acids that are highly prone to oxidation. The stability of nuts themselves as a function of their various fatty acid profiles has been investigated, but little attention has focused on how chopped nuts affect quality and stability of chocolate matrices. According to Patterson et al (1996) “There is no predictability of whole peanut stability based upon oil composition. Since the peanut is being placed in a complex matrix such as a chocolate confection, the stability of the peanut is in this
3 environment is totally unpredictable”; the effect of peanuts and other nuts on chocolate textures and stability is equally unpredictable at the present time.
Since many of the most popular chocolate bars in the US include some sort of nut, elucidating factors that control or modulate the impact of various nuts in chocolate systems could show manufacturers how to optimize their formulations with compatible chocolates and nuts that delay the onset of bloom and other undesirable sensory characteristics such as softening, loss of snap and development of off-flavors, thereby extending the shelf life of such products.
This thesis thus seeks to explore the impact of nut inclusions in two chocolate matrices, one containing milk fat and one that does not. Two nuts, walnut and almonds, which have very different fatty acid profiles and endogenous antioxidant content are the focus of this research. The goal is to gain a better understanding of the interactions between the nut oils and the cocoa butter and milk fat in the chocolate as well as effects of nuts on oxidative stability. The impact on roasting at two levels (low and medium) and with two processing protocols (whole roasted then chopped and also chopped then roasted) on nut antioxidant levels and chocolate physical properties and oxidative stability is investigated. Fatty acid migration from the nuts into the chocolate is followed by FAME-GC, polymorphic transition is tracked with DSC and XRD and also textural changes were monitored. Bloom is quantified using colorimetric techniques and qualitatively described in sensory testing. This study seeks to explore the impact of nut processing on nut stability and overall impact when used as an inclusion in two different dark chocolate formulations focusing on the main modes of product failure: oxidation, bloom and textural changes.
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LITERATURE REVIEW
Science of Chocolate
Chocolate Processing
The process of making chocolate is a very complex task that involves a multitude of steps starting with the cocoa tree itself, then harvesting and fermentation of the beans to develop flavor, followed by drying of the beans, roasting, and separation of the nib from the shell. The roasted beans can then be ground into cocoa mass, combined with the dry ingredients such as sugar and milk powder, and refined. A key step in chocolate manufacture that dictates the melting, snap and textural attributes of chocolate is tempering, which must be conducted before moulding. Because tempering is so critical to product quality, this step will be considered in greater detail (Beckett, 2000).
Tempering
Tempering is a perhaps the most important step in chocolate manufacture because it critically controls the crystallization of the fat into desirable polymorphic form, shape, and size. (Hartel, 1999). Tempering uses a combination of controlled heating and cooling plus crystal seeding to selectively force the β crystal form desired and prolong the onset of bloom (McCarthy, 2003). β crystals are the preferable polymorphic form because they are stable and they provide the dense packing needed for snap and molding characteristics of chocolates. and α forms crystallize and melt at very low temperatures and are unstable in nature. ‟ crystals have high melting points, but lower than crystals
(Dimick,1991).
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Seguine (1991) defines a good temper as “the largest number of the smallest possible crystals of the right crystalline form”. A large number of small crystals are needed to maintain fluid flow, to reduce space between the crystals thus allowing faster set up, and to produce glossy products. If chocolate is not tempered properly, the final product contains large coarse crystals instead of the desired small, fine ones and also has a greater tendency to bloom quickly (Lipp and Anklam, 1998a).
The basic procedure for tempering is to completely melt out the chocolate so no crystals are present, cool to the point of crystallization, crystallize, then melt out unwanted crystal forms by heating slightly. An example of a temperature program for tempering chocolate is shown in Figure 1. Because chocolates vary in their fatty acid composition and TAG structure, temperature programs must be designed specifically for each chocolate being used. The correct temperature program helps to force formation of the desired crystals based on their melting points. See Cocoa Butter Crystallization section, pg 17 for more details.
122 F 1 Melt 2 Cool - no crystallization 3 Form mix of tiny crystals 4 Melt out unstable T° polymorphs
o 32 C 3086--3288o CF
8127 Fo C
time ee Figure 1. Example of a Chocolate Tempering Program showing typical temperatures reached at each stage (Dimick, 1991)
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As the chocolate is cooled the viscosity increases, thus slowing down molecular movement. This increases the potential for molecules to associate with one another.
Small crystals that are spread throughout the mixture provide many nuclei to initiate crystallization. Smaller crystals have less increase in viscosity during cooling, which facilitates orienting and, if necessary, re-orienting of crystals around these seeds or crystallization centers.
Formation of small crystals is facilitated by seeding. Seeding is the process in which previously tempered chocolate is added to a batch in order to create nuclei around which the same crystal form will form. The seed acts a center for TAGs to organize around and attach to in an orderly way. The seed is basically an early developing crystal in the desired polymorph. The seed along with the temperature program and shear ultimately determine the polymorph formed (Dimick, 1986). In automatic tempering units temper is achieved through a temperature program along with specific shearing conditions. Smaller batch systems often use seeding methods (Beckett, 1999).
Shear is also important in tempering because it creates smaller crystals and helps to evenly distribute them as well (Seguine, 1991). Shear during mixing ensures even distribution of the seed, provides energy for the polymorphic transition to the B-V form, and limits the growth of B-V crystals as they are formed. Undershearing allow formation of large crystals that produce a coarse gritty texture. Overshearing reduces the crystal size excessively, leading to collapse of the chocolate structure and a product that does not set
(A. Marangoni, personal communication). Shearing also generates heat so excess shear
7 will create too much heat while undershearing will not allow for heat transfer out of the chocolate or proper mixing (Beckett, 2000).
Tempering Procedures
There is a wide array of methods available for tempering chocolate, including batch, drip feed, and automatic. The underlying principles remain the same in all.
Chocolate leaves the conch at approximately 40° C and enters the tempering unit. The tempering unit is a scraped surface heat exchanger that exposes the hot chocolate to cool walls, and removes crystals from the walls before they grow in size. During tempering, all existing crystals are first melted by heating the chocolate to a high temperature. If the temperature is not high enough, existing crystals can grow in size and increase the viscosity of the chocolate excessively upon molding. Over temper occurs when the chocolate thickens and becomes difficult to work with, while a good-tempered chocolate remains flowing.
After the heat up phase, the chocolate is first cooled down to 90° F to promote βV crystal growth, then heated slightly once again to melt unwanted and ‟ crystals that have lower melting points.
About 70-85% of the cocoa butter is crystallized upon molding and cooling; the remaining chocolate crystallizes slowly during storage (Allen, 2007).
Temper Measurement
Temper measurement was once more an art then a science. Often an employee with a long-standing position at a chocolate company would taste the chocolate and determine if it was over, under or good temper. Now automation has helped convert
8 temper to an objective measurement. Temper meters (Figure 2A) use heat of crystallization to quantify the growth of crystals. Shapes of temper meter curves (Figure
2B) are commonly studied for indicators of temper (Allen, 2007). The beginning portion of the curve portrays the cooling of the sample. As the sample cools heat is released by sample through heat of crystallization. The slope of the curve is used to interpret whether the temper is good, over or under based on the amount of heat released by the sample
(Beckett, 1999).
As the molten sample cools in the tempering unit, the chocolate cools from the outside in. Eventually the center cools and there is a reduction in temperature difference between the center and outer regions. The center contracts as it cools, and when it reaches a critical volume, it can transfer heat and effect crystallization. If there is enough of the desired crystal form the chocolate can set quickly; latent heat released in the process offsets the cooling and there is no temperature change upon crystallization (good temper).
If enough seed crystals are not present, the chocolate takes longer to set. In this case, there is a longer initial drop in temperature before the latent heat is emitted, then temperature rises with the onset of crystallization (under temper). When no, very few, or too many seed crystals are present, the chocolate will not set properly and latent heat is released more slowly (over temper) (Beckett, 2000).
In summary, if the chocolate is under-tempered then heat can cause a temperature rise; if it is over tempered there is a rate change of the temperature decline. An under temper indicates that there is an insufficient number of crystals formed whereas over temper indicates an over abundance of crystals formed before the center crystallized. If
9 there is instead a constant temperature it is a good temper while if there is no change in the curve there is no temper or no point of inflection (Allen, 2007).
Figure 2. (A)Temper meter and (B) curves produced during tempering of chocolate. http://www.ptl.co.nz/tricor-505A.php
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Chocolate Bar Manufacture
Once a chocolate recipe has been decided upon and the chocolate is made and tempered, inclusions can be added to the chocolate before moulding into the desired form. It is important that the inclusions also be warmed to a temperature very close to that of the chocolate so that the chocolate is not shocked. Addition of excessively cold or hot inclusions can affect the crystallization of the chocolate during tempering, which obviously affects the final sensory properties of the chocolate bar.
Chocolate is mixed with the inclusions by weight and deposited into the preheated moulds. The molds are sent down a shaking belt to evenly distribute the chocolate through the mold and also to remove air bubbles. The moulds then enter a cooling tunnel which allows the chocolate to set and the crystals to form. Cooling usually requires about
20 minutes depending on the type of product, length of tunnel and other factors. The chocolate can then be demolded either by twisting the mold or flipping it over. The bars exit the cooling tunnel and can then be wrapped and boxed.
Chocolate Components: Structure and Function
Cocoa Butter
Cocoa butter is a key ingredient in chocolate, comprising about 30% of the product based on weight (Sonwai, 2006). This fat phase of chocolate is crucial since it is the continuous phase in which all the other components are dispersed (Lipp and Anklam,
1998) and crystallization patterns of cocoa butter control texture and physical properties such as gloss, snap and demolding characteristics (Sonwai, 2006).
Cocoa butter consists mostly of TAGs (triacylglycerols), esters of glycerol and three fatty acids, which are numbered 1 through 3. Positions 1 and 3 are able to be
11 exchanged through processes such as interesterification; position 2 usually contains the unsaturated fatty acid (Lipp and Anklam, 1998a).
The fatty acid profiles of cocoa butter vary with growing region, time of the season, and climate, and these differences affect chocolate properties and stability (Table
1). Most notably, hot climates generate cocoa butter with a higher percentage of saturated fat, but geography can influence fatty acid profile (Lipp et al, 1998). For example, cocoa butter from the Ivory Coast of Africa (e.g. Ghana) has lower levels of oleic acid then does cocoa butter from South America even though both are hot climates (Lipp and Anklam,
1998). Flavor varies by region as well, due to climate and seasonality. The process of deodorization is used if any undesirable off notes are detected (Lipp and Anklam, 1998).
Variation of saturated to unsaturated fatty acids is also seen depending on the harvest time (Schaich, class notes Lipids).
Table 1. Fatty acid composition (%) of cocoa butter for countries of origin (Lipp and
Anklam, 1998).
% of Total Fatty Acids Ivory Country of Origin Ecuador Brazil Ghana Coast Malaysia Java Palmitic Acid 25.6 25.1 25.3 25.8 24.9 24.1 Stearic Acid 36.0 33.3 37.6 36.9 37.4 37.3 Oleic Acid 34.6 36.5 32.7 32.9 33.5 34.3 Linoleic Acid 2.6 3.5 2.8 2.8 2.6 2.7 Linolenic Acid 0.1 0.2 0.2 0.2 0.2 0.2 Arachidic Acid 1.0 1.2 1.2 1.2 1.2 1.2 Behenic Acid 0.1 0.2 0.2 0.2 0.2 0.2
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Cocoa Liquor
After roasting, the cocoa nibs can be made into liquor or cocoa mass. There are various methods to accomplish this, depending on the end use desired. Particle size is key in making sure that no grittiness is detected. Typically, a ball mill is used for this application. Cocoa liquors vary greatly depending on the beans used, which impacts flavor, fat content, etc. (Beckett, 2000).
Milk Products
Fatty Acid Composition of Milk Fat
Milk fat gives milk chocolate its characteristic dairy notes, but also the smooth mouthfeel and reduced snap. The addition of milk fat to chocolate slows the rate of crystallization, reduces the solid fat content, and softens the textural through its fatty acid distribution with shorter chains (Table 2). Cocoa butter has a sharp melting point (93-
95°F) The melting point of milk fat is lower (90F), and its addition to cocoa butter widens the melting curve and provides the lingering mouth coating associated with indulgence (Dea, 2005).
Table 2. Fatty acid composition of milk fat (Beckett, 2000) Fatty Acid Weight (%) C 4:0 Butyric 4.1 C 6:0 Caproic 2.4 C 8:0 Caprylic 1.4 C 10:0 Capric 2.9 C 10:1 Decenoic 0.3 C 12:0 Lauric 3.5 C 14:0 Myristic 11.4 C 16:0 Palmitic 23.2 C 18:0 Stearic 12.4
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C 18:1 Oleic 25.2 C 18:2 Linoleic 2.6 C 18:3 Linolenic 0.9 Others 10.0
Milk fat delays the onset of bloom by disrupting the crystalline matrix in chocolate
(Beckett, 2000). However, there is a critical balance between enough milk fat added to reduce bloom, yet not so much that the chocolate becomes too soft (Pajin and Jovanovic,
2004). Milk fat added at 1 and 3% of total formula weight and a crystallization temperature of 25C produces a desirable high quality chocolate product with good snap, texture and lack of bloom (Pajin and Jovanovic, 2004).
Milk fat in its pure form lacks some of the desirable functional characteristics needed in chocolate formulations. However, specific fractions of anhydrous milk fat
(AMF) offer unique benefits based on their melting properties. AMF is made from either cream or butter. The cream is concentrated to 80% fat and then emulsified. The water and oil are separated and the oil phase is dehydrated (Beckett, 2000). AMF is a plastic fat composed of an oil phase in which crystalline fat is suspended. AMF can be fractionated to manipulate the percent of high, middle and low melting fractions, allowing creation of
AMF with unique properties that can aid in mitigation of bloom (Dimick et al., 1996).
Processing parameters such as the rate of cooling dramatically effects the formation of the crystalline matrix in milk fat-cocoa butter mixtures. Fractal analysis and other microscopic techniques have been used to reveal the details of this crystalline network. Aggregation of the solid fat to form crystalline networks is driven by van der
Waal‟s forces and Brownian motion, but the specific crystal forms that develop are
14 determined by chemical composition of the chocolate as well as the processing parameters (Wright and Marangoni, 2003). A fast rate of cooling causes low melting point fractions to be trapped within a network of the higher melting fraction. A more slowly cooled AMF contains a higher level of solid fat than a rapidly cooled sample
(Dimick et al., 1996).
Milk Proteins
Caseins and whey proteins, the major proteins found in milk, have important effects on chocolate textures. Flowability and the creaminess associated with milk chocolate are less pronounced in low protein samples. The mechanism of action of proteins is complex and poorly understood. It is speculated that the emulsifying properties of the caseins play a role in maintaining chocolate flow. (Beckett, 2000)
Emulsifiers
Emulsifiers reduce the surface tension and provide an interface between two immiscible phases. In chocolate, emulsifiers such as lecithin act more like surface active agents, i.e. link solid and liquid phases, rather than creating an interface between two liquid phases as in water and oil emulsions. Sugar, a hydrophilic particle, must be covered in fat so that the particles can move smoothly past the cocoa-fat coated particles.
Emulsifiers that bind their hydrophilic heads to the sugar surface and hydrophobic tails to the fat phase assist in this fat-coating process. This reduces the viscosity of the chocolate up to a point. However, if surfactants are used in excess, micelles form and increase the chocolate viscosity, which in turn inhibits chocolate flow (McCarthy, 2003).
A second critical function of emulsifiers in chocolate is bloom inhibition.
Emulsifiers such as sorbitan tristearate (STS), sucrose polyesters, or 0.1-0.3% lecithin
15 inhibit bloom by interleaving between triacylglycerols, thus preventing molecular alignment and crystallization. Lactic acid esters of monoglycerides plays a similar role in preventing bloom in filled compound coatings (McCarthy, 2003).
Sugar
Sucrose, a disaccharide consisting of glucose and fructose, is obviously critical for taste in chocolate – it provides sweetness to counterbalance the bitterness of chocolate phenols and round out flavor. In addition, since sugar is dispersed in the fat matrix and does not dissolve, crystal size and shape also contribute importantly to chocolate body and microstructure (Hartel, 1997). Sugar is available in different crystal sizes, and a medium fine sugar is typically used in chocolate (Beckett, 2000).
Lactose or milk sugar, a disaccharide composed of glucose and galactose, is not sweet but has other important functions in chocolate. Usually introduced into chocolate as a component of milk powder, lactose participates in Maillard browning reactions and therefore gives cooked dairy notes to chocolate formulations. Lactose can be used to replace other non-fat milk solids as a cost savings to the manufacturer as well (Beckett,
2000).
Molecular Interactions in Chocolate
Impact of Particle Size of Sugar and Cocoa
Chocolate is a particulate dispersion of cocoa particles and sugar crystals in cocoa butter, so the particle size, shape, and packing of these particles have a significant impact on chocolate texture and quality. Since cocoa processing and grinding can be
16 manipulated to generate particles with a range of size and shape and thus provide a control point (Servais, 2002), effects of particle size distribution (PSD) of ingredients in chocolate has received considerable research attention.
PSD exerts a marked impact on viscosity and other rheological properties through its influence on particle packing and interactions with the fat phase. Finer particles play a prominent role due to their greater surface area, i.e. it takes more fat to cover the particles and less fat remains in free form. Hence, fine particles thicken chocolate more effectively. However, particle size affects Casson yield value alone; once the mass is moving, small and large particles can flow past each another so plastic viscosity remains unaffected (Servais, 2002).
Thickening effects of particle size are counterbalanced by adding cocoa butter or additional emulsifiers to decrease the chocolate viscosity. Addition of even 1% fat can have a large effect on viscosity in some systems. Typically, at fat contents below 32%, each incremental increase in fat adds to the free flowing fat phase, resulting in a visible decrease in plastic viscosity (Beckett, 2000). Since cocoa butter is the more costly ingredient, it is clear that more can be gained in control of both cost and quality by optimizing the particle size distribution for a set fat content.
Cocoa particle size also influences the mouthfeel and flavor of chocolate. In general, particles must be less than 20 - 30 um overall and at least 60% of the particles must be between 1-5 um for the perception of smoothness (Altimiras, 2007). Viscosity of the chocolate during mastication affects the perception of flavor by controlling chocolate contact with flavor receptors on the tongue. Conventional thinking was that finer particle size gave sweeter taste. However, this was not corroborated in a detailed study by Ziegler
17 et al. (2001). Nonfat dry milk and extra fine sugar were ground in a jet mill, coarse and fine fractions were separated via Accucut air classifier, and varying ratios were created and mixed into the cocoa butter, anhydrous milk fat, and lecithin. Viscosities were standardized with addition of fat. Results indicated that particle size had no affect on sweetness, but rather altered how chocolate melts in the mouth– smaller particles melted rapidly and coated the tongue while coarser particles cleared the mouth more quickly.
Particle size is also very important in milk powder. Milk powder affects chocolate properties due to free fat content, particle size, and moisture. Roller drying is often used to create milk powder, but spray drying is also an option. Roller dried milk solids are preferred for chocolate formulations due to small particles with large pores (Keogh et al,
2003); spray dried powders have larger particles so yield lower chocolate viscosities
(Attaie et al., 2003). However, the fat content of the powder outweighs particle size in effect on viscosity: higher fat powders are more easily refined to smaller particle size.
Therefore, particle size influence is a factor, but not necessarily the most influential in certain chocolate formulations.
Cocoa Butter Crystallization and Compatibility
Cocoa butter crystallization and compatibility with other fats is the most important factor in overall stability of a chocolate product. A crystal is defined by
Marangoni (2005) as “an orderly array of symmetrically arranged particles”.
Understanding how cocoa butter crystals form and become organized in a chocolate matrix is critical for creating a high quality product because the strength of the crystal network determines key sensory attributes such as snap, mouthfeel and texture
18
(Marangoni, 2005). The type of crystals that form is determined by the fatty acid profile, the distribution of fatty acids in TAGs, the purity of the sample, and the process conditions (temperature, time, shear etc) (Marangoni, 2005).
Cocoa butter fatty acids are mainly C18:1, 18:0 and 16:0 organized in triacylglycerols
(TAGs) in unique distributions. The three major TAGs are POP (1, 3-dipalmitoyl, 2- oleoyl SN-glycerol), POS (1-palmitoyl, 2-oleoyl, 3-stearoyl SN glycerol) and SOS (1,3- distearoyl, 2-oleoyl SN glycerol) (Nakae et al, 2000), comprising ~82% of total TAG content (Dimick, 1991). These three TAGS are thought to be responsible for the crystallization properties of cocoa butter as well as the steep melting curve with melting point at 93F (Lipp and Anklam, 1998). However, the presence of other TAGS (OOL,
PLP, OOO, PPP, SOO, PPS) modify the main crystal structure, account for many of the differences between different chocolates, and probably play important roles in fat incompatibilities with chocolate.
That the three component fatty acids are within two carbons in chain length facilitates organization of TAGs into multiple similar but different packing arrangements
(called polymorphism) that readily co-crystallize. There are three major polymorphic forms, α, β‟ and β, in chocolate. Crystal forms I, II, III, IV, V and VI have been identified. Forms I and II are in the alpha form, III and IV are ‟ and IV and VI are crystals (Table 3). Note that chain packing in cocoa butter crystals does not follow general crystallization “rules”.
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Table 3. Polymorphs of cocoa butter found in chocolate. Adapted from Beckett, 1999 and Marangoni, 2005.
Crystal Form Crystal Form Melting Point (°F) Chain Packing Density I sub α 61-67 Double Least II Α 70-72 Double Least III β' 78 Double Intermediate IV β' 81-84 Double Intermediate V β 93-95 Triple Most VI β 97 Triple Most
True polymorphism according to Marangoni (2005) is when „solid phases of the same chemical composition upon melting yield the same liquid phases‟. In fat systems, true polymorphism does not exist, but the different TAG‟s pack differently and take on different angles of tilt. The triacylglycerols of cocoa butter are believed to organize in
„chair‟ arrangement in both liquid and solid state. Typically, since bent chains of unsaturated fatty acids cannot align with the straight chains of saturated fatty acids, in cocoa butter the unsaturated fatty acid (oleic acid) is isolated in the SN2 position, forcing a triple chain length packing structure (Dimick, 1991) (Figure 3a). The triple chain structure has greater long spacings than the double chain structure and is not packed as tightly as if all fatty acids were similar (e.g. saturated). Looser packing usually results in a lower melting point then other configurations (Dimick and Davis, 1986). However, in chocolate, this effect is counteracted by tilting of the chains (Figure 3b) which facilitates tight packing, increased melting point, and existence as a polymorph rather than the ‟ structure usually resulting from triple chain crystals. SOS and POP exhibit the triple chain length in order to separate the saturated and unsaturated fatty acids. For these
TAGs the triple chain orientation is most thermodynamically stable. Double chain
20 packing in cocoa butter TAGs is thermodynamically unfavorable since it would align unsaturated fatty acids with saturated fats. However, the α form and mono-acid TAGs preferentially assume double chain orientation (Sato et al., 1989).
Figure 3a. Triple Chain packing facilitates tight chain packing in cocoa butter TAGs.
Figure 3b. TAGs Packing Comparison : Greater tilt allows for tighter packing
The desirable crystal form for chocolate is β-V because it provides good snap, gloss and resistance to bloom (Beckett, 2000). This crystal form provides these benefits
21 due to its ability to align fatty acid chains tightly by assuming a triple chain form where the irregularity of the unsaturated acid in position two is aligned with its corresponding fatty acid on the other TAGs, thus maximizing bonding as described above. This tight packing contracts the chocolate during cooling, thus making demoulding easy, and it also gives chocolate the snap upon breakage. -V has a 6-12 month shelf life and undergoes slow phase transition on standing and with warming and recooling to the stable VI form
(Hartel, 1999). VI is a crystal form comprised of high melting point TAGs that associate during slow cooling; its formation is characterized by the large white crystals recognized as bloom (Nakae et al., 2000).
Solidification or crystallization of cocoa butter follows a stepwise progression
(Dimick and Davis, 1986). The first phase is nucleation in which a crystal nucleus is formed, around which disorganized amorphous crystals can gather and organize. Seeding is a process in which crystals of the desired polymorph are added to liquid fat to provide multiple nuclei that serve as foci for rapid crystallization. Nuclei grow and crystals begin to form as TAG molecules associate at their surfaces with liquid mass surrounding. At the completion of the second stage (crystallization), 50-70% of the fat has become solid.
The third phase is crusting over or hardening off. During this stage, branching between crystal groups takes place and the cocoa butter appears solid to the investigator. Note, during tempering this process is controlled through seeding, temperature programmed units and consistent shear as already described under Tempering, page 13.
The energetics of crystallization are key to understanding which crystals form in specific scenarios. When cocoa butter is cooled, the degree of supercooling is the driving force for crystallization. As the cocoa butter is cooled below its melting point, the system
22 is driven towards a reduction in entropy i.e. more order, so the TAG fatty acid chains try to align with one another. Fast cooling results in the metastable form because the chains have less time to align closely. There is a lower ΔG for the formation of α crystals and it is kinetically favorable. Similar fatty acids compete with each other for sites on the lattice, which limits crystal growth. If a slower cooling rate is used instead, there is time for the fatty acid chains to align more extensively and form a more stable polymorph, either β‟ and β. Cocoa butter polymorphs are monotropic, i.e. they only crystallize from less stable to more stable forms and the process is not reversible. Thus, the order of transformation is α→β‟→β.
Fat Migration in Chocolate
Fat migration to and within the cocoa butter crystal matrix during storage is responsible for changes in chocolate texture and formation of bloom (see Section
2.5.2.3). To study this process, Altimiras et al (2007) used model systems composed of cocoa butter and sand granules of different sizes. They found that 82% of migration occurred during the first four days, and samples made with larger sand particles had less migration then smaller ones.
Marangoni (2010) describes five states of lipid binding in chocolate:
1) co-crystallization of near-liquid TAGs with high melting point TAGs and
incorporation into a lattice
2) van der Waals interactions between liquid TAGs and nanocrystal solid surfaces
(monolayer oil)
3) wetting of monolayer crystallites (multilayer oil)
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4) oil entrapment in capillaries
5) physical entrapment of oil between crystallites.
Binding strength of oil decreases and, conversely, migration rate increases from 1) to 5).
Movement of oil through fat follows Darcy‟s Law (Dibildox-Alvarado et al,
2004):
B * Ac * P Q = L where Q = volume flow rate of oil oozing out
B = permeability coefficient
Ac = cross-section area
= viscosity of the liquid phase
dP/L = pressure drop over the migration distance (Pa/m) and a2 2/D3 B = K
where a = particle size (meters)
K = tortuosity factor
= solid volume fraction
D = fractal network dimensions
They found that high network stiffness created by lots of small crystals formed under rapid cooling and high shear creates a tight matrix within which oil cannot flow, whereas large particle sizes increase oil diffusion. This is because large numbers of crystals increase the tortuosity and impede flow, whereas large crystals leave large capillaries between them, facilitating rapid oil flow. The difference is shown graphically in Figure 4.
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A simplified relationship between flow rate and tortuousity is described by the equation
v = Q/An= q/n where v = average linear velocity
Q = volume flow rate of oil
A = cross-sectional area of flow
n = effective porosity
Thus, small particles have a double effect on limiting oil migration by both reducing cross-sectional area available for flow and increasing effective porosity.
Figure 4. Diagrammatic representation of particle size effects on oil migration in chocolate. Left: Tortuous pathway created by packing of small particles reduces rate of oil migration. Right: Linear channels between large crystals allow for facile fluid flow and rapid oil migration. Figures from www.geology.wisc.edu/courses/g724/Week1b.ppt.
Effect of Minor Lipids
Minor lipid components consist of phospholipids, diglycerides, monoglycerides and glycolipids present in cocoa butter. Hartel (1999) showed that minor lipid components can influence crystallization as well as bloom potential by altering the structure of crystals which provide the matrix through which fat migrates (Hartel, 1999).
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Milk fat with different levels of minor fats was added to cocoa butter and the crystals that formed were studied under confocal laser scanning microscopy. In milk fat alone, excess minor lipids inhibited crystallization while insufficient minor lipids created less dense crystals. In chocolate, adding milk fat with normal levels of minor fats had the greatest resistance to bloom, but when excess or insufficient minor lipids were present, bloom developed much earlier. Conclusions from this work were that minor lipids impact bloom by modifying fat crystallization and hence also fat migration to the chocolate surface.
However, mechanisms by which this occurs require further investigation (Hartel, 1999).
Compatibility
Fat compatibility is defined as the ability of fat to co-crystallize with cocoa butter
TAGs, or to fit into the existing matrix without disrupting the structure. In order to be compatible, fats should have similar properties, such as fatty acid composition, melting point, solid fat content, etc. (Seguine, 2001). As has already been discussed, cocoa butter is often not the only fat in a chocolate formulation. Typically milk fat is also present, and in the case of filled pieces, cocoa butter replacers and unsaturated fats from nut fillings are present as well. These fats obviously have different fatty acid profiles than cocoa butter and can pose incompatibility issues in crystallization.
An extreme example of incompatibility can be seen in filled pieces. Smith et al
(2007) followed crystallization in a filled piece containing hazelnut oil during extended shelf life. At five weeks of storage, cocoa butter alone was only 28% -VI while chocolate with 20% hazelnut oil had complete transformation to -VI. Chocolate with
5% hazelnut oil showed complete transformation after ten weeks at 25°C, and even 1% hazelnut oil led to very rapid crystal transformation. Effects of hazelnut oil levels were
26 not proportional, i.e. 10% did not have twice the effect of 5%, and the rate of transformation to -VI decreased with further increases in hazelnut oil. The enhanced crystal transition was attributed to incompatible low melting TAGs that cannot easily fit inside the cocoa butter matrix (Smith, 2007).
Ali et al (2001A) investigated texture (texture profile analysis), bloom stability, polymorphic transitions, and sensory qualities of filled chocolate pieces containing a center composed of desiccated coconut and palm mid-fractions inside a dark chocolate.
They found that the more dissimilar the blend of fats, the greater the decrease in chocolate melting point and softening of texture for the finished product. Samples with cocoa butter alone were in the form crystals over 6 weeks at 30 C. However, with addition of palm kernel fat and coconut, a ‟ crystal form dominated due to the mixture of different fatty acids (Ali et al, 2001A).
Sometimes different fatty acid profiles can improve the qualities of the finished product by delaying onset of bloom. Milk fat has a complex fatty acid composition that decreases the rate of crystallization as well as melting point in chocolate, thus softening texture. Using DSC to study the role of milk fat in chocolate crystallization behavior,
Metin and Hartel (1998) showed that the addition of high melting fractions of milk fat, in particular, slowed cocoa butter nucleation when compared to the lower melting fractions.
Barna et al (1992) also observed a decrease in chocolate melting point when higher levels
(20%) of milk fat fractions were added. This study noted the need for more fundamental research on TAG organizations in mixed fat systems to better understand crystallization in mixed fat systems.
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There is a limit to the amount of milk fat that can be added to a chocolate matrix because milk fat and cocoa butter TAG‟s form separate phases rather than co- crystallizing (Marangoni, 2005). Fats that have different TAGs and polymorphic forms have different melting points from each other. If these two fats are combined into a mixture a eutectic will result which means this new mixture will have a melting point lower than the two principle components. The eutectic results in a decrease in hardness and melting point. Milk fat is a complex fat composed of ~11% high melting fractions,
23 % medium melting fractions, and 66% low melting fractions. Adding low melting fractions of milk fat to cocoa butter leads to a more extreme eutectic than middle or high melting fractions. Elucidation of how each of these fractions, along with time and temperature of processing, influences cocoa butter crystallization can lead to improved formulation and production of a higher quality, delayed bloom chocolate product
(Marangoni, 2005).
In contrast to milk, nut oils contain high proportions of long chain unsaturated fatty acids. When fats with different fatty acid contents and distribution fats are blended, different levels of compatibilities become evident as reflected in the product solid fat content. The closer the two fats of the mixture are to each other in terms of chemical make up the more compatible they will be i.e. they will form mixed crystals. If the fats are very different from one another then they will not co-crystallize and therefore be non- compatible. Compatibilities or lack thereof are displayed in isosolid diagrams, where linear or parallel lines indicate compatible fats while curved lines indicate lack of compatibility. In Figure 5 below, fat compatibility between cocoa butter and milk fat (A) and cocoa butter and high melting fractions of AMF is obvious (Lonchampt and Hartel,
28
2004). In scenario A, the eutectic or drop in SFC is evident at around 30% addition of
AMF, whereas in scenario B the eutectic occurs at lower percent addition of high melting fraction milk components. The eutectic is determined by the percent addition of the component that decreases the SFC or causes softening. The cause of a eutectic is incompatibility between the two components in the blend (Lonchampt and Hartel, 2004).
Lonchampt and Hartel (2004) also explored compatibility of nut oils and cocoa butter. They were unable to determine the eutectic effect because the oil is liquid at room temperature and dilutes the cocoa butter (Figure 6).
Figure 5. Isosolid diagrams of (A) cocoa butter and AMF blend and (B) cocoa butter and
HMF blends. The drop in SFC indicates a eutectic or point at which addition of a component to cocoa butter increases the softening. Addition at this level is considered the maximum and is dictated by compatibility (Lonchampt and Hartel, 2004).
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Solid fat Solid content, % Solid fat Solid content, %
Figure 6. Isosolid diagrams showing relationships between solid fat content and nut oil
% in cocoa butter systems (Lonchampt and Hartel, 2004).
Chocolate Bloom
Bloom is widely considered to be the major problem in chocolate stability:
“Fat bloom has been a problem in chocolate manufacturing for many years because it significantly damages the commercial value of the products” (Sonwai, 2006).
“Fat bloom is a major concern to the chocolate industry because it compromises both visual and textural quality”(Bricknell and Hartel, 1998).
“Although there have been many observations to support each theory, the exact mechanism of bloom formation has not been confirmed” (Bricknell and Hartel, 1998).
“Although fat bloom has been studied extensively for many years, the bloom mechanisms and kinetics are not completely understood” (McCarthy et al., 2003).
“There is no single, universally accepted theory that describes fat bloom in chocolate” (McCarthy, 2003).
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“Although the mechanism of its formation is not completely understood, the causes seem to be multiple, such as improper tempering, use of incompatible fats, and large temperature fluctuations during storage” (Walter and Cornillon, 2001).
Attempts to combat bloom have included process optimization, fat substitution and emulsifier addition (Nakae et al., 2000).
Chocolate bloom is most often recognized as a whitish haze that is formed on the surface of chocolate; it a physical phenomenon caused by the dispersion of light from small fat crystals (<5um) (Altimiras et al, 2006). However, other forms of bloom are also possible (Hartel, 1999). Kinta (2006) describes bloom as the result of cocoa butter separation at the surface of the chocolate, accompanied by polymorphic transitions. A whitish appearance is seen when the transition from -V to -VI occurs and also when unstable crystals transform to -V. Another type of bloom resulting from uneven distribution of fat content is seen when chocolate solidifies without tempering. This type of bloom is light brown in color (Kinta, 2006).
Although it is important to understand the fundamental causes of bloom, it is also desirable to be able to diagnose macro causes of bloom during manufacturing. According to Seguine (2001), bloom is a result of chocolate formulation and its environment. When faced with a lot of chocolate that displays bloom, a food scientist must try to uncover the cause. Areas that should be considered are the time of onset of the bloom, if it is sugar or fat bloom, formulation characteristics i.e. coated pieces, what was run previously on the same line, storage environment, etc.
While our knowledge about bloom is increasing, the mechanisms and kinetics of bloom initiation and proliferation are still incompletely understood and controversial. It is
31 clear that bloom involves multiple variables such as solid fat content, melting characteristics, crystal structure, degree of saturation/unsaturation, chain length structure and symmetry of TAG composition, migration of liquid fat to the surface, fat incompatibility, storage conditions, polymorphic transitions, and others (Lohman and
Hartel, 1994). However, Hartel (1999) suggests that most current explanations are overly simplistic and future research must focus on structural elements, surface interactions, and lipid mixtures in order to gain a better understanding of the mechanism of bloom.
Bloom Theories
Popular theories to explain fat bloom usually fall into three categories: phase separation, polymorphic transitions, or fat migration.
Phase separation
In 1958, Becker suggested that bloom results from a phase separation in which different TAGs separate based on their differences in melting points, promoting a transition from the -V to the -VI form. Adenier et al (1993) supported this argument, proposing that the lower melting fraction separates and helps to transport the higher melting fraction to the surface where it recrystallizes. Detailed analyses of bloom showed increased levels of higher melting fractions (Hartel, 1999) and different distributions of
TAGs compared to the rest of the chocolate (McCarthy, 2003).
Polymorphic Transitions
Perhaps the most popular bloom theory is that bloom involves an uncontrollable transition from an unstable to stable high melting crystal form (Hartel, 1999). Early research of Wille and Lutton (1966) first demonstrated that transition from -V to more
32 stable -VI crystals resulted in bloom. However, it is possible to have a polymorphic transition and not have visual bloom; therefore the transition itself may not be the cause of bloom but rather a result (Bricknell and Hartel, 1998). There are other issues that also impact bloom (Hartel, 1999). For example, bloom may involve a new crystal form or a more purified form. The recrystallization results in a „spike‟-like crystal formation on the surface which reflects light and therefore gives it whiter appearance. These crystal spikes are dependent on the surface and exactly how they form is not known (Hartel,
1999).
Fat Migration
Hartel (1999) proposed that changes in temperature during storage create a heat gradient within the chocolate. More liquid fractions migrate in this gradient, moving towards the surface and carrying with them the higher-melting fractions which then recrystallize on the surface. Migration can be hindered if the chocolate matrix is tight, or facilitated when matrix structures are loose (Hartel, 1999). The surface itself may also be important, with the presence of cracks or abrasions at the surface aiding bloom formation.
Fat migration has similarly been explained by the capillary rise theory, which speculates that liquid fat migrates to the outside by being pulled or drawn by surface tension into pores that exist on the surface. The mechanisms by which this occurs is unknown, but is thought to include capillary rise and diffusion (Smith et al., 2007).
Rousseau (2006) disagrees with any role for pores and cracks. He demonstrated that pores or cracks in the chocolate surface do not affect the migration of fat from the interior to the exterior of the chocolate, and that migration occurs in areas with or without pores,
33 with pore structure and size remaining unaltered. However, surface discontinuities may still provide preferential deposition sites for crystals.
Bloom in Filled Chocolate Pieces
Most research studying ways to prevent bloom formation in solid chocolate bars has focused on the fat system. Less attention has been given to other ingredients such as nuts and fillings in the finished chocolate that may play a role in bloom.
The mechanism responsible for bloom in filled pieces is thought to be mostly fat migration from the filling into the chocolate shell. The center of the piece and the chocolate shell often have different TAG contents and the center usually has a higher level of liquid fat which can migrate into the shell (McCarthy, 2003). Fillings with low melting fractions and short chain or unsaturated fatty acids are more likely to cause bloom problems.
At the 2004 IFT meeting, concerns were raised regarding migration of nut oils in a chocolate bar and the impact of this fat migration on sensory properties. Using GLC
(for oleic acid content), DSC (for solid fat content) and NMR (for solid fat content),
Shetty et al. (2004) created a model to monitor the migration of hazelnut oil into chocolate. Khan and Rousseau (2006) also investigated the migration of hazelnut oil into dark chocolate, using as a model filled pieces of dark chocolate with hazelnut filling which were then exposed to different storage temperatures. Migration of hazelnut oil was followed by HPLC and XRD. In each case, migration was attributed to a concentration gradient of TAGs, but the overall mechanism of fat migration remains poorly understood.
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Polymorphic transitions play a role in bloom of filled chocolates. Ali et al
(2001B) studied the effect of storage conditions on migration and polymorphism of incompatible lauric fats from the center of coconut-filled chocolate pieces. Using a model system in which coconut filling was layered on top of a model dark chocolate in a plastic container, they measured solid fat content (NMR), melting point (DSC), texture (TPA), polymorphic structure (XRD) and bloom (cycling chamber) with various combinations of coconut, dark chocolate, palm kernel oil and coconut oil stored for eight weeks. DSC showed that coconut oil is inferior to palm kernel as a base for the coconut filling due to the larger decrease in chocolate melting point due to migration. However, polymorphic transitions were also involved. XRD revealed that β crystals dominated at 18 C, while a mixture of β‟and β crystals formed during storage at 30 C. Bloom analysis found that palm kernel oil, coconut oil and cocoa butter TAGs recrystallized on the surface to create bloom. Increased temperature increased bloom and lower temperatures slowed down these reactions.
Compatibility between chocolate shell and filling fatty acids also affects bloom
(Ali et al., 2001B). Liquid fractions can transfer cocoa butter fractions to the surface where they recrystallize as bloom (McCarthy, 2003). As noted above, this migration is enhanced with increased storage temperatures (Ali et al., 2001B). Other factors to consider when formulating and producing a filled piece include ratio of fats, SFC, viscosity, and particle size (Smith et al., 2006). The degree to which bloom is an issue in a filled piece depends on the formulation of the filling, the ratio of filling to shell and the storage and manufacturing conditions. Fillings often contain nut oils which are high in triolein and other TAGs composed of linoleic and oleic acids (OOO, LOO, LLO, POO,
35
SOO) whereas the chocolate outer shell is composed mostly of POS, POP, SOS. Storage studies have shown that the TAGs from the filling migrate into the shell over time.
In one study lasting 200 days at 20 C, OOO, LOO and LLO from hazelnut oil migrated from the center to the chocolate shell, evenly dispersing between cocoa butter crystal layers until a point of saturation was reached. Analysis of the bloom revealed approximately 10% triolein, thereby demonstrating migration. Reverse migration from the shell to the filling occurred at much lower levels.
There are ways to reduce the undesirable textural and visual changes of a filled piece over time. Thick shells are desirable to minimize migration and softening, but this might not be desirable for sensory qualities. Thick shells are not pleasing texturally and do not provide a good balance of chocolate to center ratio. The migration of oil depends on the ration of filling to shell: the more filling, the more migration. This follows the diffusion principle
mt/ms = √(D * t)/d where mt is the amount of migrated filling after time t, ms is the amount of migrated oil after saturation, D is the diffusion constant for the oil, and d is the thickness of the shell.
So, oil migration decreases as shell thickness increases (Ziegleder, 1997).
Filling formulations can be adjusted to prevent or slow these degradative reactions. Structured fats can be added to the filling to create a network that traps free fat.
Also, ingredient exclusion may also be desirable as is the case with emulsifiers which can increase the ability for fat to migrate. Similarly, incompatible fats like lauric are often excluded from fillings since they can also increase the rate of migration (Ziegleder,
1997).
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A layer can be created between the center and the shell to prevent the exchange of fats, or a harder fat can be put into the center to have a sponge like function. An anti- blooming fat may be added to the center to migrate with the oil to the outer shell where it will slow down the process of bloom. Behenic acid derivative, marketed by the Fuji Oil
Company, is used in this way. However, this compound cannot yet be used legally in many countries (Beckett, 2000).
Migration leads to not only softening of the shell, but also results in hardening of the center. Other adverse effects include swelling of the piece and color discoloration
(Smith et al., 2006).
Other Factors Influencing Bloom
Chocolate Coatings
Chocolate coatings formulations are often palm kernel oil based, but in addition sometimes alternate fats are added such as milk fat and cocoa butter. The challenge in adding these fats is TAG incompatibility which can lead to a less bloom-resistant product. Increasing the level of cocoa butter leads to more extensive blooming. A study conducted at University of Wisconsin (Williams et al, 1997) looked at chocolate coatings with the addition of milk fat, which had not been explored previously. The goal was to look at compatibility of chocolate coating supplemented with either cocoa butter or milk fat and the resulting bloom stability. It was determined the theories regarding bloom in chocolate do not hold true for chocolate coatings. Chocolate coating typically is in the β‟ polymorph it was determined that milk fat showed compatibility with the coating given its β‟ crystals as well. Cocoa butter had limited compatibility given the primarily β
37 crystals. Polymorphic changes were not seen with the addition of milk fat which was not the case with the addition of cocoa butter in which a transition did take place if used at levels of 40 or higher. Therefore the mechanism of bloom in chocolate coatings differs from chocolate and requires further exploration (Williams et al., 1997).
Chocolate Microstructure
The structure of chocolate is made up of sugar granules and cocoa particles dispersed in cocoa butter and potentially also milk fat. Hartel (1999) feels that by understanding the microstructure that the manufacturer can gain insight in how to prepare chocolate of the highest quality (Hartel, 1999). In a study where Hartel (1999) looked at the impact of sugar on the chocolate matrix he found that if he used amorphous sugar
(rounded particles) vs crystalline sugar that a difference in bloom was seen, ie. intensity of chocolate haze. Potentially the more rounded sugar particles allow for a more compact chocolate matrix that helps to hinder migration of fat to the surface or rather perhaps the sugar impacts the type of bloom that forms such as flatter less white bloom vs the spiky crystals seen with crystalline sugar. It is clear that sugar plays a role in the microstructure of chocolate and impacts bloom formation.
Obviously, the fat phase and interfaces play key roles in chocolate structure and bloom. Polymorphic form, and size and shape of fat crystals plays a role is the microstructure of the chocolate specifically around how tightly packed the matrix becomes. Surprisingly, structure of interfaces is also important. Hartel (1999) noted that compounds such as emulsifiers help to coat sugar particles perhaps binding amorphous and crystalline sugar differently. This may account for differences seen in bloom when
38 the two different sugar forms were used in chocolate recipes. The matrix is very complex and therefore determining the major factor contributing to the bloom is challenging.
Particle‟s shape and size is thought to play an important role in microstructure, yet many researchers such as Hartel (1999) acknowledge there are still many gaps in our knowledge in this area.
In dark chocolate, sugar provides approximately 40-50% of the solids, so its contributions to chocolate microstructure can be considerable. The size and shape of the sugar granules can impact the structure of chocolate due to its impact to packing and therefore the formation of potential pores. Gloria et al. (2001) studied effects of processing on amorphous sugar. It was determined that studying the impact of amorphous sugar on bloom is complicated by the fact that the amorphous sugar becomes crystallized during chocolate manufacture which was confirmed with XRD. Also if amorphous sugar is combined with crystalline sugar the resulting finished chocolate is 100% completely crystalline.
The impact of cocoa particle shape and size in the matrix may also play a role in the microstructure of chocolate. This area has not been explored according to this literature search. Although cocoa particle size is easy to control the shape would not be given processing constraints. This remains an area of research that has yet to been fully explored.
Effect of Milk Fat
Bloom is an issue seen most frequently in dark chocolate, so manufacturers often add between 1-3% of milk fat into dark chocolate formulations to increase stability. It is
39 worthwhile to understand milk fat and its impact on product quality especially in a dark chocolate system (Marangoni, 2005).
The main fat component of milk fat is triacylglycerols (TAGs). Milk fat is unique in its high content of short chain fatty acids. The wide variety of component fatty acids in milk fat, ranging from butyric acid (C4) to arachidic (C20) generate TAGS with a wide melting point range, -40 to 35 C. It thus is possible to fractionate milk fat into fractions with different melting points, e.g. HMF (high melting point fraction), MMF (middle melting fraction), and LMF (low melting fraction), differentiable through peak analysis using DSC. The common ways to carry out the fractionation are dry fraction, detergent fractionation and solvent fractionation (van Aken et al., 1999).
“Milk fat and milk fat fractions successfully inhibit bloom, are an inexpensive cocoa butter substitute, and can be legally added to pure chocolate products (both dark and milk chocolate)” (Bricknell and Hartel, 1998). The higher melting fractions are thought to be the active bloom inhibitors since they are not easily melted during temperature fluctuations and therefore are less likely to migrate to the surface (Bricknell and Hartel, 1998). Fatty acid and TAG components of the higher melting fraction are not specifically known. Lower melting fractions have no effect or slightly increase bloom.
It is thought that milk fat may play a role in the polymorphism changes, although the exact mechanism is unknown (Hartel, 1999). In general, the most stable polymorphic form for milk fat is the ‟crystal, but depending on the TAGs, it may also be β (van Aken et al., 1999). Addition of milk fat lowers the rate of fat crystallization and softens texture; therefore the correct usage level is critical so to balance the formulation (Metin and Hartel, 1998).
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Effect of Storage
Bloom develops over time during storage as TAGs rearrange themselves and migrate through the chocolate matrix. If chocolate is cooled too rapidly, there is not enough time to form stable crystals so unstable forms are formed. Subsequently, when temperature fluctuates greatly, a great deal of melting and uncontrolled recrystallization occurs, leading to bloom (Bricknell and Hartel, 1998). It is during temperature cycling that polymorphic transitions from -V to -VI occur (Bricknell and Hartel, 1998). The
-VI haze is initially gray and grows progressively whiter as crystal size increases.
Internal blooming is also possible, and the crystals thus formed can migrate from the surface to the inside (Hartel, 1999).
Fast cooling, e.g. storing in a cold room or placing in a refrigerator after softening on a hot day, also results in surface cracks and pore formation that serve as foci for extensive bloom development, while slower cooling does not generate such defects
(Campbell et al., 1969). Cooling facilitates crystallization and the formation of a more dense structure as the chocolate changes polymorphic forms. Cracks can form on the surface during cooling, these cracks serve as pores for liquid fat which can migrate through the pore to the surface of the chocolate. Fat recrystallizes on the surface resulting in bloom.
Effects of nuts on chocolate properties
Nuts come in a number of varieties the most popular being almonds followed by walnuts, with production of 683,286 and 382,675 megatons, respectively, in 2006/2007
41
(Alasalvar et al., 2009). All nuts are notoriously high in fat. The overall fat content varies between nut types, with cashews and pistachios at the low end with about 46% fat and macadamia at the high end with 76% fat (Refer to table 4). Nuts are high in unsaturated fatty acids, specifically oleic, linoleic and linolenic although the specific fatty acid profiles vary with variety (Dea, 2004). This high unsaturation can present considerable instability to oxidation and incompatibility with high solids cocoa butter when nuts are mixed with chocolate.
Most studies of nuts and their oils have compared different cultivars of the same nut variety. Few studies have compared various nut types. Maguire et al (2004) compared the fatty acid profiles and tocopherol levels of walnuts, almonds, peanuts, hazelnuts and macadamia nuts purchased from a local market with no control over origin, age of the nuts, handling, treatment, etc. Macadamia nuts were found to have the highest oil content of 59.2%. Contrary to expectations, no such correlation could be found between tocopherol levels and fatty acid profile to peroxide values. More controlled studies comparing effects of various nut types on stability and matrices in various food systems, particularly chocolate, are needed to understand nut interactions and to predict nut effects as ingredients.
An overview of characteristics of individual nut varieties is provided in the following subsections.
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Table 4. Fatty acid and total fat content of commonly-eaten nuts.
Fatty Acid % total fatty acids Saturates Peanuts Hazelnuts Walnut Cashews Almonds Pistachios Macadamia 6:0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 8:0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 10:0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 12:0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 14:0 0.03 0.0 0.0 0.0 0.0 0.0 0.7 16:0 11.1 3.1 4.4 4.2 3.2 4.9 6.0 17:0 0.0 0.0 0.0 0.1 0.0 0.0 0.1 18:0 2.7 1.3 1.7 3.4 0.7 0.5 2.3 20:0 1.6 0.1 0.1 0.3 0.0 0.0 1.9 22:0 0.1 0.0 0.0 0.2 0.0 0.0 0.6 24:0 0.0 0.0 0.0 0.1 0.0 0.0 0.3 Total SFA 15.5 4.5 6.1 8.3 3.9 5.4 12.1 16:1 0.15 0.1 0.0 0.3 0.2 0.5 13.0 17:1 0.0 Nd Nd nd nd nd nd 18:1 w9 38.4 45.4 8.8 25.2 31.9 22.7 43.8 20:1 w9 0.0 0.1 0.1 0.1 0.0 0.2 1.9 22:1 w9 0.0 0.0 0.0 0.0 0.0 0.0 0.2 24:1 w9 0.0 0.0 0.0 nd 0.0 0.0 0.0 Total MUFA 38.6 45.5 8.9 25.5 32.2 23.3 58.9 18:2 w6 44.6 7.8 38.1 8.3 12.2 13.2 1.3 18:3 0.6 0.1 9.1 0.1 0.0 0.3 0.2 18:3 w3 nd nd nd nd nd nd nd 18:3 w6 nd nd nd nd nd nd nd 20:4 w6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Total PUFA 45.2 7.9 47.2 8.4 12.2 13.5 1.5 Total fat (%) 47.9 60.6 64.9 43.2 47.0 44.8 71.0 Ref 1 2 2 2 2 2 2 1 Macquire et al 2004 2 Alasalvar et al 2009
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Nut Varieties
Peanuts
Of the thousands of peanut cultivars grown, Spanish, Runner, Virginia, and
Valencia are the dominant ones. Five major producers/exporters of peanuts -- the United
States, Argentina, Sudan, Senegal, and Brazil -- account for 71% of total world exports.
Edible peanuts in such popular confections as salted peanuts, peanut butter (sandwiches, candy bars, and cups), peanut brittle, and shelled nuts (plain/roasted) account for two- thirds of the total peanut use in the United States (American Peanut Council, 2010).
Peanut oil is high in unsaturated fatty acids, specifically oleic and linoleic (Table
4). The high degree of unsaturation makes peanuts and peanut oil very susceptible to oxidation. Indeed, oxidation is the reaction most limiting shelf life for roasted peanuts and peanuts in confectionery products. Oxidized nuts lose their characteristic nut flavor and take on cardboardy, paint-like notes that migrate into cocoa butter along with oil
TAGs.
According to Mugendi et al (1997) and Sanders (1980) factors that influence the fatty acid distribution and associated shelf life of peanuts include maturity level, grade/quality, size, processing techniques and production conditions. Investigators use the OL (oleic to linoleic acid) ratio to determine stability. Because higher oleic acid peanuts have been found to be more stable, a great deal of effort has gone into the breeding high oleic peanuts (HOP). HOP usually contains at least 70% oleic acid by weight in the peanut oil (Patterson, et al., 1996). Chocolate coated standard peanuts exhibited a higher oxidation rate in than in uncoated nuts stored under the same
44 conditions, even though chocolate was thought to serve as an oxygen barrier (Reed et al
2000). However, HOP coated in chocolate oxidized at a rate similar to HOP without the chocolate coating (Mugendi et al 1997), and chocolate formulations using HOP were much more stable then those with regular peanuts (Patterson et al 1996). Shelf life was extended from 8 months with standard peanuts to more than a year with HOP, thus establishing a link between nut fatty acid profile and finished product stability in a complex chocolate matrix. This research needs to be expanded to investigate effects of nut fatty acid profiles on other sensory properties and quality issues such as bloom, in addition to oxidation.
Hazelnuts
Hazelnuts belong to the genus Corylus, specifically Corylus avellana for the
European varieties. There are many varieties of hazelnuts, best known of which are
Clark, Butler and Filber. 75% of the world‟s hazelnuts are grown in Turkey, with the remainder in Italy, Spain and the United States. Hazelnuts are typically harvested in the
Fall, when most farmers allow the nuts to drop off the tree on their own and then gather the nuts with sweepers.
Hazelnut confectionery products are very popular in Europe, but are being seen in more domestic products as well (Nattress et al., 2004), including in chocolate (Amaral et al., 2006). Little research has yet been conducted on the impact of fatty acid profile of various cultivars on shelf stability of chocolate. Like olive oil, hazelnut oil is dominantly oleic acid -- 72.8-83.5% oleic, linoleic 7.6-16.6%, palmitic 4.1-6.8%, stearic 1.9-2.8% and linolenic 0.1-0.6% (Benitez-Sanchez et al, 2003). Perhaps not unexpectedly, there is
45 great variation in fatty acid profiles among hazelnuts from different origins (Turkey,
France, Italy and Spain) and within single hazelnut varieties themselves (Amaral et al.,
2006). Differences are also seen among nuts that are processed differently, i.e. roasted vs non-roasted (Amaral et al., 2006). These differences are important since most hazelnuts are roasted to develop the desirable nutty flavor, color and texture as well as to inactivate microorganisms and enzymes such as lipase (Benitez –Sanchez et al., 2006) and peroxidase to improve long term oxidative stability (Ozdemir et al., 2001). Different roasting conditions affect free fatty acid content and levels of oxidation products. Roasted nut oils have higher sterol and aliphatic (C22, C23) contents.
Many studies have been conducted on nut oils themselves, but few have focused on effects of nut oils or meats in applications such as chocolate. Incorporation of nuts in a food matrix creates a much more complicated situation, but provides real world information that can be valuable to the confectionary industry. Khan and Rousseau
(2006) used atomic force microscopy (AFM) to visualize the formation of bloom via crystal peak formations in dark chocolate containing hazelnut oil. Overall, hazelnut oil greatly destabilized chocolate. Test samples stored at 26 C bloomed within two weeks and were too excessively bloomed for AFM to be applied; samples stored at 11 C for 5 weeks could be analyzed but showed greatly accelerated bloom and considerable product degradation in loss of gloss and softening in texture. Although research such as this is very valuable for filled chocolate products, effects of nut meat inclusion on crystallization and other properties in solid chocolate confections remains poorly understood.
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Walnuts
Walnuts belong to the genus Juglans and there are 21 species world wide, grown from the Mediterranean to Asia, Central America, and the United States. Walnuts are related to hickory trees (Menninger, 1977). Walnuts are typically harvested in October, when they are either removed from the tree or the already fallen nuts are collected from around the base of the tree. Walnuts, like other nuts, are subject to a grading system according to USDA standards that take into account appearance such as color, piece size, presence of defects etc. Detailed information is available at ams.usda.gov.
Walnuts are unique in that their PUFA levels are roughly five times the MUFA levels, in contrast to almonds where MUFA levels are higher then PUFA (Alasalvar et al,
2009). The main fatty acids in walnuts are (in decreasing order) linoleic, linolenic, oleic, and palmitic acids (Table 5). The PUFA (linoleic and linolenic) content determined by
Zwarts et al (1999) on New Zealand varieties was 57.3 to 76.6 % of total fatty acids.
Using HPLC with evaporative light scattering detection (ELSD) to determine the major
TAGs in 9 different walnut cultivars from 3 consecutive years, grown in different regions, Amaral et al (2004) determined that the major TAG in walnuts are trilinolein
(LLL) followed by dilinoleoyl-oleoyl-glycerol (OLL) and dilinoleoyl linolenyol glycerol
(LLLn) with mean percentages of 37%, 18.5% and 18.4% respectively. Other TAGs include LLnLn, OLLn, PLLn and PLO. This data is in line with the ~ 60% linoleic acid content expected in walnuts.
Variations are seen in fatty acid levels depending on the cultivars, origin and irrigation procedures. Zwarts et al. (1999) found significant differences in the fatty acid profiles between the 10 cultivars grown in New Zealand, particularly in oleic acid content
47 with a range of 14 to 30%. Different cultivars therefore have different degrees of oxidative stability, and differences in flavor characteristics may depend on the ratios of the fatty acids in various walnut cultivars. They further suggest that the information regarding differences in fatty acid profiles, specifically oleic acid and other PUFAs should be considered when developing end products and that certain varieties may be more suitable for specific applications. Thus, knowledge of fatty acid profiles of nuts, in this case walnuts, is valuable and meaningful to the food industry for determining whether nuts with specific fatty acid profiles may lend themselves to certain applications better then other varieties, and for the link with flavor stability and sensory properties over time.
Walnut oil is more unstable to oxidation than hazelnut oil due in part to higher levels of polyunsaturated fatty acids, which can be as high as 78% of the total fatty acids depending on the variety (Savage et al, 1999), and in part to low tocopherol contents
(Lavedrine, 1997). Counterbalancing this, walnuts have high levels of phenolic compounds, 16 tannins including glansrins plus other phenolics such as epicatechin, and other radical scavenging antioxidant components such as high superoxide dismutase activity that stabilize the nuts (Alasalvar and Shahidi, 2009). The L-ORAC value (one indicator of antioxidant activity) for walnuts in one study was 4.84 +/- 1.25 μmol of TE/g and the H-ORAC was 130.57 +/- 35.20 μmol of TE/g vs almonds which had values of
1.72+/1 0.5 and 42.82 +/- 8.71 μmol of TE/g respectively (Alsalvar et al., 2009).
Flavor and aromas associated with roasted walnuts come from oxidative break down products of the unsaturated fatty acids, especially linoleic acid (Alasalvar et al.,
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2009). These products and the nut oils can migrate into the cocoa butter phase of chocolate to interfere with crystallization and induce off-flavors.
Macadamia
Macadamia nuts are grown in Australia, Hawaii and New Zealand. There has been very little research conducted regarding the fatty acid profiles of various cultivars of macadamia nuts and little is known regarding the oxidative stability of the nuts. Kaijser et al (2000) found great variation in oxidative stability and fatty acid content, particularly oleic acid content, among different macadamia varieties. While there was no clear relationship between the fatty acid profiles and nut stability, linoleic acid content did correlate with peroxide values and low tocopherol levels in one variety. Interestingly, the tocopherol levels were generally lower in macadamia nuts than other nuts such as hazelnuts and walnuts, which may account for the typical rapid development of rancidity in macadamia nuts under ambient conditions.
Cashews
Cashews, a member of the genus Anacardium, are indigenous to Brazil and are now also grown in other warm regions of the world including Vietnam, India and
Nigeria. Cashews are used in many confectionary applications and as an oil. The total fat contact in eight varieties of cashews representing multiple countries of origin ranged from 43 to 50% with an average unsaturated fat content of 78.9% (Table 4) (Toschi et al,
1993). The main unsaturated fatty acids are oleic and linoleic acid. Cashew kernels are
49 rich in α-tocopherol which, in conjunction with high oleic acid content, contributes to greater stability (Toshci et al, 1993).
Almonds
Almonds, a member of the Prunus dulcis group, are the most extensively grown and consumed nut. In 2004 the world produced 1,725,638 MT of almonds, with
California producing nearly half of this (761,286 MT). Other major producers include
Italy, Syria, Iran and Spain (Alasalvar et al., 2009). Varieties of almonds grown in
California include Nonpareil, Mission, Neplus, Carmel, Monterey and California.
Nonpareil are the most common, comprising ~37% of the almonds grown in CA. They have a good appearance, uniform size, and are popular with growers as well as purchasers. Mission almonds have a stronger flavor and greater variation in size; they are not readily blanched so are commonly used in candy and ice cream where enzyme activity is not a problem. Neplus are blander in flavor than Mission and blanchable.
Carmel almonds are similar to Nonpareils in uniform piece size. Monterey is in the same family as the California variety which has a less uniform piece size and is used mostly in manufacturing (bluediamond.com).
The USDA has a grading system for almonds as for all nuts: US Fancy, US Extra
No. 1, US No. 1, US Select Sheller Run, US Standard Sheller Run, US No. 1 Whole and
Broken, US No. 1 Pieces. These classifications are based on the number of allowed defects, number of broken pieces or splits, allowed levels of piece size variation etc.
More detail can be found at ams.usda.gov.
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Almonds have high MUFA to PUFA ratios (Table 4). The major TAGs identified in 10 different almond cultivars by HPLC, in descending prevalence were OOO, OLO,
POO, OLL, PLO, StOO, LLL, PLL and PLP (Prats-Moya et al, 1999). Almonds also have a high antioxidant content that varies with the location in the nut. Antiradical activity is greatest in the skin followed by the shell then the fruit itself. Almonds have high tocopherol content as well (Alasalvar and Shahidi, 2009). This high antioxidant content gives almonds one of the longest shelf lives of nuts if handled properly.
According to the Blue Diamond Almond Company, almonds should be stored in a cool, dry place avoiding heat, light and odors. The ideal storage temperature is 35-45 F and a relative humidity of 55-65% in vacuum sealed and/or nitrogen flushed packs. The absolute shelf life depends on a variety of factors such as the crop that year, the weather conditions, post harvest handling, etc., as well as exposure to oxygen, type of roasting method used (dry or oil), surface area of the pieces, exposure to light, moisture level in the finished product, and the presence of any catalysts such as metals (bluediamond.com,
2009).
One focus of the dissertation research presented here is the roasting procedure, specifically dry roasting. Roasting is important with nuts because it reduces moisture, sharpens textures, and develops characteristic nutty flavors and aroma volatiles such as 4 hydroxy-2,5–dimethyl-3(2H)-furanone and pyrazines produced in the Maillard reaction
(Alasalvar et al., 2009). In addition, according to Blue Diamond, dry roasted nuts have longer shelf lives than oil roasted. Addition of antioxidants or some sort of barrier like a chocolate coating can further extend the shelf life. Packaging is critical for creating an
51 effective barrier against oxygen, light and moisture as well as insects. Table 5 lists expected shelf life of almonds treated and packaged in different ways.
Table 5. Typical shelf life values for almonds treated in various ways then stored at 25-
45 F and relative humidity 55-65% (bluediamond.com).
Treatment type Whole/diced Storage/package Shelf life (months) Raw Whole Ambient/carton 24
Raw Diced Ambient/carton 12
Dry Roast Diced Nitrogen Flush/carton 18
Oil Roast Diced Nitrogen Flush/carton 12
Properties of Nuts That Affect Their Use as Chocolate Bar Inclusions
Nut variables that can significantly affect chocolate properties and stability include fatty acid profile (which can be affected by genotype, country of origin, irrigation/farming techniques), processing (dry roasting, oil roasting, or non-roasted), and size of the nut piece and available surface area. Studies on nut stability have suggested that determining the fatty acid profile of nuts of varying origins, cultivars etc. can guide selection of the most appropriate nut for individual food applications, including chocolate
(Alasavar, 2009).
Extensive research has focused on fatty acid profiles of nuts, specifically peanuts and hazelnuts, and the shelf life stability of the roasted nuts themselves. Much less attention has been given to how nuts affect stability and shelf life of foods in which they are ingredients. Many confectionary products use whole and chopped nuts, but interactions of the nuts with a complex chocolate matrix makes it difficult to predict how
52 nuts with various fatty acid distributions will affect the shelf life of finished goods. A few studies have investigated peanut effects, but little information is available about effects of other nuts such as macadamia, almonds, cashews etc. Also, research to date has not dealt with many quality issues such as bloom and sensory aspects such as snap and appearance when nuts are used in a chocolate matrix. Bloom is a complex phenomenon and fat migration theories are still being developed. The effect of incorporating whole and/or chopped nuts into chocolate bars on the extent and mechanism of bloom still needs to be explained.
Impact of Roasting
Roasting of nuts has both positive and negative effects on nut stability. Nuts are roasted before their addition to a confectionary product to generate desirable flavor, as noted previously, but also as a kill step to ensure microbiological safety. As noted above, nuts are high in fat -- 50 to 75% oil on a dry basis, most of which is unsaturated and therefore prone to oxidation. To limit oxidation, nuts are protected by the presence of natural antioxidants (Perren and Escher, 2007). In addition, nuts are highly organized structurally in oleosomes to maximize protection from outside elements and to segregate regions of 1-2 um fat globules by means of a cytoplasmic network; this compartmentalization allows for isolation of any oxidative events or migration of oxygen.
On the negative side, heat from roasting breaks down this compartmentalization, freeing the fat and making it more available, which can increase the likelihood of migration of the nut oil to the product it is contained in (Patterson et al., 1996).
Destruction of oleosomes allows oxygen access to the unsaturated fats and also permits access of once-segregated enzymes to their substrates. Direct thermal degradation of nut
53 oils generates high levels of primary and secondary oxidation products and, unfortunately, also destroys some endogenous antioxidants in the process. These effects increase with temperature up to some threshold which varies with nut variety and need to be determined experimentally.
On the positive side, roasting increases stability by inactivating enzymes such as lipoxygenase which catalyzes oxidation of linoleic acid, and it generates the desired color, flavor and texture of roasted nuts. Three different processes lead to the formation of flavors and volatiles: Maillard browning, caramelization and lipid degradation
(Alasalvar et al., 2009). These reactions are influenced by pH, the presence and amount of reagents (sugar and amino acid containing compounds), moisture content, and especially roasting time and temperature (Alasalvar et al., 2009). Typical products of
Maillard browning include 3-methylbutanal, 2,3-butanedione, and methional among others. Through Maillard browning and the Strecker degradation reactions aldehydes and ketones are formed which become major aroma and flavor compounds (Belitz and
Grosch, 1987). Other compounds such as pyrazines, pyridines, furans etc are also products of this complex reaction and play important roles in characteristic flavor profiles of roasted nuts (Alasalvar, 2009). Roasting also creates Maillard browning products
(Perren and Escher, 2007) which have antioxidant properties. This process is complicated and the exact products and their mechanism of action are unknown. Products of lipid oxidation can also interact with proteins and form similar types of products which may also have antioxidant properties. Severini et al (2000) explored the antioxidant properties of Maillard reaction products (MRP) through application of MRPs on almonds in the headspace of the sample in comparison to vacuum packed and control non-vacuum sealed
54 samples of almonds. It was determined that the vacuum sealed sample had the lowest PV followed by the MRP sample then control. The conclusion drawn was MRPs have antioxidant effects and potential for industrial application. The mechanism of MRP activity is not known and most likely due to a reducing or chelating potential (Severini et al., 2000). This area of research of antioxidant action of maillard browning is still in its infancy (Mastrocola and Munari, 2000).
Carmelization results in flavor and aroma generation plus moisture loss. High heat in roasting also breaks down fats, resulting in flavor generation (Alasalvar, 2009).
Heating increases fragmentation of molecules and therefore aids in the formation of aroma compounds.
Buckholz et al (1980) studied the effect of roasting parameters on peanuts to link sensory data and instrumental analysis. Different roasting parameters and different varieties of peanuts gave different sensory and volatile profiles, without any clear correlations. The authors thus emphasized that, although knowledge of roasting in the generation of specific desirable and undesirable flavors is important, overall it is sensory data that must be used to determine desirable roasting parameters.
Impact of Chop Size
Chopped nuts are popular in confectionery products due to the flavor and texture contribution to the finished product. Fine chops, specifically pastes, are very prone to oil migration; larger chops may not have this same tendency (Dea, 2004). Exploration of different chop sizes may reveal a threshold at which oil migration becomes a clear problem. According to the Blue Diamond Almond Company, which has conducted a
55 variety of shelf life studies, the greater the surface area, the greater the opportunity for autoxidation (bluediamond.com, 2009). Whether the order of roasting (whole then dicing or dicing then roasting) has an impact as well will be determined in this study.
Impact of Storage and Processing on Nut Quality
Only high quality nuts with no oxidative degradation can produce acceptable products when added to chocolate. The key to maintaining nut quality is rapid packing in a nitrogen flush bag immediately after roasting, followed by storage in a cold environment with monitored relative humidity. As a benchmark, relative humidity below
60% is acceptable. Cold storage helps to keep the liquid fat stabilized, minimizes movement to the chocolate surface, and inhibits lipid oxidation, all of which increase shelf life.
Impact of nut lipids on chocolate stability
The major fatty acids in nuts are unsaturated while cocoa butter, the fat in chocolate, is higher in saturated fats. A chocolate product with nuts thus has both liquid and solid fats at room temperature. This incompatibility ultimately leads to two major modes of deterioration: oil migration and oxidative rancidity (Dea, 2004).
Oil migration: Oil migration is one theory of chocolate bloom that is well supported in practice. Unsaturated fats, liquid at room temperature, can migrate from the nuts into the chocolate carrying with them saturated fats to the chocolate surface, ultimately leading to bloom. This fat migration also leads to other undesirable qualities, such as softening which causes loss of snap (Dea, 2004).
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The chocolate matrix into which the nuts are added plays an important role in limiting nut oil migration. A well refined, small particle size chocolate can mitigate oil migration through denser particle packing and increased tortuousity. The key word in this phrase is mitigation; oil migration is inevitable and can only be slowed through processing, formulation, storage and handling.
Lipid oxidation: The second critical mode of failure for nut-containing chocolate products is oxidative rancidity that generates off-flavors such as „cardboard‟ or „paint‟.
Nuts are high in unsaturated fatty acids and therefore are very prone to these degradative reactions. Walnuts, which are especially high in PUFAs (Alsalvar et al., 2009), are especially at risk.
Understanding oxidation in nuts in terms of the products of oxidation, the rate of the reaction, and what natural antioxidants are present is key for mitigating oxidation. Very simply, lipid oxidation occurs in three main steps: initiation, propagation and termination as shown in Figure 7. Initiation of oxidation caused by heat, light, catalysts, etc. generates lipid alkyl radicals. These radicals then react with oxygen to form peroxyl radicals, which establish and propagate a chain reaction by abstracting hydrogens from other lipid chains.
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CLASSICAL FREE RADICAL CHAIN REACTION MECHANISM OF LIPID OXIDATION Initiation (formation of ab initio lipid free radical) k i L1H L1 (1)
Propagation Free radical chain reaction established
ko L + O L OO (2) 1 2 k 1
kp1 L1OO + L2H L1OOH + L2 3) k p1 L2OO + L3H L2OOH + L3 etc. LnOOH (4)
Free radical chain branching (initiation of new chains)
kd1 – LnOOH LnO + OH (reducing metals) (5)
kd2 + LnOOH LnOO + H (oxidizing metals) (6)
kd3 LnOOH LnO + OH (heat and uv) (7)
LnO kp2 LnOH (8a) LnOO + L4H k p1 LnOOH + L4 (8b) HO k p3 HOH (8c)
k p4 L1OO + LnOOH L1OOH + LnOO (9)
kp5 L1O + LnOOH L1OH + LnOO (10)
Termination (formation of non-radical products)
Ln Ln Radical recombinations (11a) kt1 LnO + LnO polymers, non-radical monomer products (11b) kt2 (ketones, ethers, alkanes, aldehydes, etc.) kt3 LnOO LnOO (11c)
Radical scissions LOO k ts1 (12a) non-radical products LO (12b) kts2 (aldehydes, ketones, alcohols, alkanes, etc.)
i - initiation; o-oxygenation; - O2 scission; p-propagation; d-dissociation; t- termination; Figure ts–termination/scission 7. Classical free radical chain of lipid oxidation (Schaich, 2005c).
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This forms hydroperoxides and new lipid radicals that repeat the process continuously.
Hydroperoxides decompose in the presence of heat, light, and metals to form alkoxyl radicals that also abstract hydrogens from other lipids, generating lipid alcohols and more new radicals to continue the chain.
Alkoxyl radicals also undergo scission reactions on either side of the alkoxyl group to generate a wide variety of aldehydes and other carbonyls and volatile products that are responsible for characteristic “rancid” off-odors and flavors. Primary products of oxidation (radicals and hydroperoxides) are flavorless, but secondary products have low odor and taste thresholds i.e. they can be smelled and tasted at ppb to ppm levels. For example, 1-octen-3-one, 2t-heptenal and 2t,6c-nonadienal have threshold values of values of 2, 5 and 10 ug/g respectively (Alasalvar, 2009). Hydrocarbons and alcohols also contribute to off-notes. Some characteristic products of lipid oxidation that contribute to off-flavors and odors are listed in Table 6.
The volatiles in walnuts have been attributed to the oxidation of the unsaturated fatty acids, specifically linoleic acid. Some information about flavor and aroma components of walnuts is available, but there have been few detailed studies of walnut nut meat oxidation (as opposed to oil oxidation) (Alasalvar, 2009). The study proposed here will employ the SAFE method to determine which chemical compounds are contributing to the rancid off notes being detected by sensory testing.
Almonds are perhaps more well studied then walnuts. The flavor components are attributed mostly to Maillard browning generated products such as pyrazines. Almonds also contain high levels of unsaturated fatty acids, especially oleic, and therefore are also susceptible to oxidation (Alasalvar, 2009).
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Termination of lipid oxidation is perhaps a misnomer. A single chain terminates when radicals recombine or undergo scission to non-radical products. However, since multiple chains are always active, once started, lipid oxidation as a process never really stops in food products (Schaich, 2005b).
Table 6. Volatile Carbonyl Compounds Formed by Autoxidation of Unsaturated Fatty
Acids (Belitz and Grosch, 1987)
Oleic Linoleic Linolenic Heptanal Pentanal Propanol Octanal Hexanal 1-Penten-3-one Nonanal Heptanal Butenal (2tr) Decanal Heptenal Pentenal (2tr) (2c) Decenal (2tr) Octanal Hexenal (2tr) (3tr) (3c) Undecenal (2tr) Octenal Heptenal (2tr) Heptadeinal (2tr,4c) Nonenal (3c) (3tr), (2tr) (2tr,4tr) Decenal (2c) Octadienal (2c,5c) Nonadienal (2tr,4tr) 3,5 Octadien-2-one Decadienal (2tr,4c) Nonadienal (2tr,6c) 2,4,7 Decatrienal
Antioxidants in Nuts
Tocopherols. Although nut lipids readily oxidize, there are compounds naturally present to help mitigate or slow these degradative reactions from occurring. The major antioxidants present are mixed α, β, δ and γ tocopherols. Figure 8 shows the structures of these compounds. Each form has different antioxidant efficiency, measured as the rate at which each reacts with peroxyl radicals in the propagation step. The α form is the most
60 abundant in plants and is the most reactive. The mechanism of action is donation of the hydrogen from the phenoxyl group to a lipid peroxyl radical, thus generating a hydroperoxide and an α-tocopheroxyl radical which can go on to react with another lipid radical. Thus, one vitamin E molecule reacts with two lipid radicals and terminates the chain. The rate at which the tocopherol isomer can turn over and react with each radical is a measure of its efficiency as an antioxidant (Yamauchi, 1997).
Figure 8. Structures of the various tocopherol isomers. (http://palmnutraceuticals.com)
The effectiveness of the various isomers of vitamin E has been studied extensively in a wide range of food systems. Results vary tremendously depending on the food system, the test conditions, the isomer, the concentration used, and the product analyzed (Seppanen et al, 2009). -Tocopherol reacts faster than the other isomers, and that is important for in vivo physiological activity, but in foods that reactivity often means that -tocopherol is used up too fast for prolonged effects. For example, when lard was stored at 20-60 °C, α-tocopherol was most effective, but if the temperature was raised to 80-120°C then the δ form was the most effective (Teledgy and Berndorfer,
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1968). Similarly, α and γ had identical effectiveness in mitigating the production of primary oxidation products in vegetable oil at 50 °C, but γ inhibited production of secondary oxidation products, e.g. aldehydes, more extensively. With regard to concentration, α-tocopherol is effective at much lower levels than the other isomers because it is a stronger hydrogen donor. However, γ and are more effective at higher concentrations, higher temperatures, and over longer times because their slower reactions prevent their being used up in non-productive side reactions. It is also critical to recognize that high concentrations of antioxidants can actually become pro-oxidant (Borg and Schaich, 1989).
Other Antioxidants. Nuts are rich in a variety of phenolic compounds with antioxidant activity. Especially in walnuts where tocopherol levels are lower than in other nuts, phenolic compounds such as proanthocyanidins play critical roles in delaying onset of oxidation. Phenolic compounds are found mostly in the skins of nuts, referred to as the pellicle, which comprises about 5% of the total fruit weight. Polyphenol profiles vary even among nut varieties. Frequently, polyphenols are bound to cellular macromolecules and are released only upon acid hydrolysis, as is the case with ellagic acid in walnuts.
An average polyphenol content comparison of almonds and walnuts is given in
Table 7. It is worth mentioning that these are averages and that different varieties, e.g.
English vs Persian walnuts, will have somewhat different profiles (Alasalvar, 2009). The complete polyphenol profiles of different walnut varieties is unavailable and remains an area of active research.
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Table 7. Average polyphenol contents of almonds and walnuts. Adapted from Alasalvar,
2009.
Nut Type Total Phenolic Total Flavonoid Total Proanthocyanidin (mg GAE/g) (mg/100g) (mg/100g)
Almond 4.18 15.24 184.00
Walnut 15.56 2.71 67.30
* GAE = gallic acid equivalents
Nuts and Health
Nuts have received attention from the nutritionists due to their high monounsaturated fatty acid (MUFA) and polyunsaturated fatty acid (PUFA) content. The term „heart healthy‟ is often linked with nut consumption. Although nuts have a high fat content on a weight basis, it is their low saturated fatty acid content that makes them a healthier fat choice for consumers. In addition, high phytosterol contents have been linked to anticancer and immune system support (Amaral et al, 2006).
Measuring Quality Parameters in Chocolate
Current Methods for Detecting and Quantifying Bloom
Foubert et al. (2005) investigated whether TPA, DSC and SFC and bloom measurements shortly after manufacture could predict which samples would bloom in filled pieces. The team looked at 14 different chocolates with differing method of tempering, temper levels (under, over and well) and varying AMF levels. The constants of this experiment were a hazelnut filling formulation, cooling time and temperature,
63 storage temperature and humidity. They conducted measurements at time 0, and 1 and 4 hours after production and then every two weeks up to 24 weeks. Chocolate variations included types of tempering (under, over, good), amounts of anhydrous milk fat (AMF), and other factors. Visual observation of bloom revealed fastest bloom development in undertempered samples. Samples with AMF bloomed faster at 6% usage level than at 0 or 3% addition. SFC and texture analysis showed that samples with less AMF were harder and SFC increased over time, i.e. the bars got harder due to crystallization. Also, undertempered bars were softer then overtempered samples. Principle component analysis was conducted using DSC, SFC and TPA. From this analysis it was determined that readings at time 0 are not needed and that these three analyses could accurately predict bloom development.
Challenges and Trends
Projected to climb from 16 billion dollars sales in 2006 to an estimated 18 billion dollars by 2011 (Tyler, 2009), chocolate is clearly big business in the United States.
Increasing consumption of organic and premium chocolate is the current hot trend, estimated to account for 4.5 billion dollars in sales by 2011(Tyler, 2009). With such large sales, cost saving initiatives while maintaining an ever higher consumer demand for quality is therefore very important.
Bloom is a major problem for the chocolate manufacturing industry post production during distribution and storage (Altimiras, 2007). Every year, bloom results in reduction in quality and monetary losses. “In a competitive market, players want to eradicate, or minimize, any negative factors that could harm their sales, so while the
64 white powdery film does not affect taste, it might nonetheless impact sales. Should the fat bloom arise, manufacturers might be obliged to sell their product at a lower price, or re-melt the chocolate to then reuse in lower grade formulations” (Food Navigator, 2004).
Hartel (1999) stresses the importance of understanding the microstructure of chocolate in order to address bloom, specifically noting special challenges in understanding microstructure in nut-containing chocolate products in order to improve chocolate quality and prevent loss. Marangoni (2005) reiterated this message and added the view that understanding the interaction of fat blends through technologies such as
DSC and XRD will provide better insight into sensory characteristics such as snap and mouthfeel and allow for optimization of processing and formulations to produce higher quality products (Marangoni, 2005).
There are five or more theories to explain bloom, but these only take into account pure solid chocolate but bloom is a complex phenomenon impacted by recipe and with many potential mechanisms, none of these theories addresses all of these scenarios
(Lonchampt and Hartel, 2004). As a case in point, models of bloom created by chocolate manufacturer Barry Callebaut (Food Navigator, 2004) have been reasonably successful in predicting onset of bloom in model systems, but fall short of predicting stability in real products because too many factors affect chocolate crystal structure, texture, oxidative stability, and bloom, and very little is understood about the relative impact of each factor on these properties. To put it simply, the chemistry is much more complex than previous recognized, and much more needs to be learned to gain consistent control over the process.
Inclusions complicate the issue even more in terms of phases, migration of
65 different fatty acids into the chocolate, and fat compatibility with cocoa butter. The importance of fat migration and compatibility is quite obvious for filled confectionary products, but holds equally true for chocolate bars with nut inclusions. Fat incompatibility leads to phase separation, bloom, and a wide range of stability issues.
Currently, many manufactures address the bloom issue in plain chocolate with the addition of milk powder for milk chocolate and milk fat ± butter oil for dark chocolate because these fats are compatible with cocoa butter (Beckett,2000). However, trends towards increasing use of alternative oils as cocoa butter substitutes or extenders are pushing the limits of current understanding of fat compatibilities and effects on textural, bloom, and oxidative stabilities of chocolate. Similarly, increasing use of nut and other inclusions to meet consumer demand for more gourmet chocolates is stressing the ability of industry to provide products with acceptable shelf life.
A major component of the compatibility issue is the fatty acid content of additive oils and inclusions relative to cocoa butter. The assumption has always been that fats will be compatible as long as the TAGs can co-crystallize with or fit into the matrix structure of cocoa butter TAGs. However, there is increasing recognition that different fatty acids also play other roles, including solubilizing minor cocoa butter TAGs and creating new phases and phase interfaces. Also, the same fatty acids in different positions on the triacylglycerol backbone can have very marked differences in effects on chocolate texture and bloom. Greater insight into effects of non-cocoa butter fatty acid profiles may identify handling and process modifications that can improve quality and stability of chocolate with non-traditional ingredients (Food Navigator, 2004).
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If developing bloom is a problem, detecting and quantitating it before it becomes visible to the naked eye is an even more distinctive challenge.
Current approaches to addressing and mitigating bloom have been developed through „merely trial and error‟ (Nopens et al., 2008) because insufficient information about causes and changes at the molecular level has been available. However, new technologically advanced analytical techniques such as HPLC, NMR and atomic force microscopy (AFM) are increasingly being used to detect molecular changes that may provide early signs of bloom onset and may also contribute to determining the potential causes of this troublesome phenomenon (Boal, 2006). Results from these analyses should suggest new opportunities for preventing bloom by multiple approaches from formulation through processing, storage, and perhaps even packaging.
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Knowledge Gaps
Numerous research articles on chocolate make it very clear that chocolate is a well-studied topic, yet there are many chocolate behaviors that scientists are still not able to explain with one unanimous theory. Specific area where key information is still missing include:
molecular level understanding of how bloom develops
factors contributing to or inhibiting bloom, and their active mechanisms
developing methods for early detection and quantification of bloom
texture properties associated with sub-bloom changes in crystal structure
oil migration rates, processes, and effects in chocolate matrices
oxidative stability of chocolate with different component fats/oils
effects of inclusions, particularly nuts, on all of the above
quality factors of nuts that affect their behavior in chocolate matrices
volatiles profiles for roasted vs oxidized nuts
translation of observations in model systems to real products.
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HYPOTHESIS
This study aimed to gain a greater understanding of how nut inclusions affect chocolate properties. The specific hypothesis posed for testing was:
The fatty acid composition, chop size and roasting treatment of nut inclusions alter the rate and extent of oil migration, bloom formation and overall stability in chocolate.
Specifically,
a) Fatty acid profiles for various nut types will be major factors affecting to stability.
b) Higher unsaturation and associated oxidation and hydrolysis products will
decrease storage stability of chocolate.
c) Small piece sizes, although convenient for processing, offer a greater surface area
for fat migration and therefore are more likely to lead to bloom.
d) Roasting level will impact stability of each nut variety. Higher roasting levels will
result in greater instability due to expedition of rancidity.
e) Nut bars made with chocolate containing milk fat will have greater bloom
stability (not necessarily oxidative stability) than samples without milk fat due to
the ability of milk fat to reduce the incidence of bloom.
Goals/Objectives of this Study
Effects of the following nut factors were investigated to test the hypothesis:
The performance of two nuts (almond and walnut) with very different fatty acid
profiles (monounsaturated vs polyunsaturated, respectively) in a control dark
chocolate formula
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Impact of different fatty acid profiles and treatments on fat migration from nuts,
cocoa butter crystallization, chocolate texture and flavor properties, oxidative
stability, and bloom development
Impact of nut chopping protocols on migration, bloom, and oxidative stability for
two nut varieties
Impact of roasting by comparing analytical test results of raw versus nuts roasted
at two different levels
Impact of milk fat in combination with nuts on overall stability in a dark
chocolate formula.
Chocolate bars are often sold as plain, solid bars, but are also sold with inclusions such as nuts, fruits, cereal grains and others. Different nuts are known to have varying degrees of stability based on their fat content and fatty acids profiles. Varying chop sizes and nut varieties can lead to differences in shelf life. A systematic study of differences in fat migration and bloom stability in chocolate bars as a function of nut variety, roasting method and roasting level has not been reported previously.
Therefore, this study investigated effects of two different nut inclusions -- walnuts and almonds -- at a fixed usage level in a standard dark chocolate recipe prepared with and without milk fat for crystallization and bloom control. Roasting parameters are key for generating a raw material with acceptable sensory properties. Hence, two roasting protocols -- roast whole then chop vs chop then roast --were used, with a high and low roast variant of each nut type. Nut-roast combinations found to be acceptable in sensory testing were incorporated into chocolate bars then subjected to accelerated and long term
70 shelf life testing and analyzed for bloom, fat compatibility via crystallography, texture
(snap), sensory qualities, and lipid oxidation.Correlation between fatty acid profiles of the nuts with the finished product performance was a major focus of this study. We predicted that nuts with fatty acid profiles closest to that of the cocoa butter would out-perform other varieties in maintaining characteristic texture properties of chocolate and in delaying or preventing bloom. We expected that the influence of nut age, roast treatment and surface area would be key factors in determining performance in regards to bloom, rancidity and texture. Results were evaluated to determine whether some types of nuts are more compatible with specific chocolates and cocoa butters used in different chocolate formulations.
The presence of milk fat impacts bloom stability in chocolate. Samples containing milk fat are softer in texture and have more mixed crystals which should be reflected in
DSC plots. Milk fat should help mitigate the migration of nut oil to the surface of the chocolate bars and therefore delay the transition from βV to βVI. Greater insight into polymorphic transitions was investigated using x-ray diffraction in model systems consisting of nuts surrounded by cocoa butter.
Constants in this study were the control dark chocolate formula and the packaging for the raw materials and finished goods. Storage conditions were 40F for raw and processed nuts and ambient for finished bars.
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Preliminary experiments to establish standards and methodology
General approach and observations
Pre-testing of raw materials ensured a very controlled study with fresh ingredients. The raw materials were all available for analysis since the chocolate base was custom-synthesized for full control of product in this set of experiments. Starting with quality materials is critical in this study since chocolate stability is the focus. Also, examining roasting parameters ensured that nut products would be considered acceptable to sensory panels and therefore have real world application.
Various nuts are often added as inclusions into chocolate confections. The selection of almonds and walnuts was based on the large difference in fatty acid profiles.
Also, almonds are very common inclusions and fairly stable over the shelf life of chocolate confections whereas walnuts have been less commonly used due to their perceived instability. In order to explore fat compatibility and oxidative stability, it is best to use two very different nuts so that the changes in quality over time can be more easily contrasted. Also, since this study explored process parameters, the comparison also can lead to an opportunity to find ways to use more „unstable‟ nuts in chocolate confections that previously were not able to be used.
Instead of purchasing pre-roasted nuts, this study used raw nuts which were then roasted in-house. Knowledge of nut age and roasting parameters greatly facilitates close control of study parameters. Raw material quality before starting was verified through peroxidation tests to ensure that only fresh, recently harvested nuts were used. Indeed, the first batch of walnuts was rejected based on this testing protocol. From this experience,
72 specifications for new, recently harvested nuts were issued to prevent the use of sub- optimal starting materials which would compromise the results of this study.
Preliminary testing was needed to assure that processing parameters resulted in roasted nuts that would pass sensory standards for low and medium roast levels. Low and medium roast levels are more complementary to most confectionary products, which is why these levels were selected. Two roasting protocols were tested. In the first method, the nut was roasted whole and then chopped. In the second method, the raw nut was chopped, sorted for particle size and then roasted. These two methods were employed for each nut to achieve the two different roast levels as well. Time and temperature combinations for roasting the various nut forms are given in Table 8.
Table 8. Roasting conditions producing nuts that pass sensory standards for texture, quality, and absence of off odors and flavors.
Nut Type Treatment Roast Level Roast Temp (°F) Roast Time (min) % Moisture
Almond Whole Low 310 12.0 2.0 Almond Whole Medium 310 17.0 1.5 Almond Chopped Low 310 6.0 0.8 Almond Chopped Medium 310 7.0 0.7 Walnut Whole Low 310 12.0 1.1 Walnut Whole Medium 310 15.0 0.7 Walnut Chopped Low 310 3.0 1.3 Walnut Chopped Medium 310 4.0 0.7
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All roasted nuts were then evaluated by a sensory panel composed of in-house sensory nut experts. For both nuts, low and medium roast levels for whole roasting followed by chopping yielded products judged acceptable (Table 9). When the nut experts deemed the samples worthy for evaluation, then in-house sensory raw material experts evaluated the samples to assess which nut samples were truly low and medium roasts and whether they would be acceptable quality for use in finished products. From this feedback, the roasting conditions were adjusted and samples were resubmitted until acceptable products were obtained with walnuts. However, chopped almonds did not give acceptable products at any roast level due to pronounced off-flavors.
Table 9. Sensory feedback on roasted nut samples.
Nut Variety & Treatment Sensory Comments
Almonds Whole Roast Low Acceptable roast character, no off notes Almonds Whole Roast High Slightly too high roast level, suggestion reduce roast time Almonds Chop Low Roast Benzaldehyde too pronounced. Roast level too low. Almonds Chop Medium Roast Benzaldehyde too pronounced. Roast level too low. Walnuts Whole Roast Low Slightly bitter flavor, skins pronounced but good walnut flavor Walnuts Whole Roast Medium Roast level too high and bitter unacceptable. Reduction in roasting time needed Walnuts Chop Low Roast Acceptable roast character, no off notes Walnuts Chop Medium Roast Acceptable roast character, no off notes
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Therefore, after the preliminary roasting experiments the following variables were adopted for use in bars: whole low roast almonds and whole medium roast almonds; whole low roast walnuts, whole medium roast walnuts, chop then low roast walnuts and chop then medium roast walnuts, for a total of 6 variables.
Once successful roasting procedures were developed, the particle size was optimized to size, 3-5 mm. Uniform particle size was achieved by setting a Dayton
Rotary Nutmeat Granulator (grinder) to the appropriate opening and then passing the samples through the Ro-Tap sieve which uses pans of various sizes to select for specific particle sizes. See the Experimental Section for methods details.
Finally, after all process parameters were determined for the nuts (Table 10), the nuts were processed in larger quantities. The same lot of nuts was used for the entire study. Table 10 shows the quantities roasted and chopped for each of the test systems.
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Table 10. Amounts of material prepared for each nut-treatment combination tested.
Experimental Design Total Amt Amt Total AMF Nuts Nuts Amt Total AMF Free Nut Roast Chocolate (testing) (finished Choc Nuts Choc Choc Type Whole/Chop Level Type lbs bar) lbs (lbs) (lbs) (lbs) (lbs) Walnut Whole Low W/ MF 7.00 0.75 5.10 Walnut Whole Medium W/ MF 7.00 0.75 5.10 Walnut Whole Low W/O MF 7.00 0.75 5.10 Walnut Whole Medium W/O MF 7.00 0.75 5.10 Walnut Chop Low W/ MF 7.00 0.75 5.10 Walnut Chop Low W/O MF 7.00 0.75 5.10 42.00 4.50 46.50 15.30 15.30
Almond Whole Low W/ MF 7.00 0.75 5.10 Almond Whole Medium W/ MF 7.00 0.75 5.10 Almond Whole Low W/O MF 7.00 0.75 5.10 Almond Whole Medium W/O MF 7.00 0.75 5.10 28.00 3.00 31.00 10.20 10.20 25.50 25.50
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Experimental Methods for Raw Ingredient Testing and Evaluation
The base chocolate formulation has no milk fat to keep the matrix uncomplicated and to simplify exploration of fat interactions. Since milk fat is often added to dark chocolate to preserve texture, extend shelf life, and prevent bloom, a variation of the base formulation was created with anhydrous milk fat as a second fat component. Unlike many studies which used off-the-shelf chocolate, this study generated the chocolate bases in the laboratory in order to control raw materials and know exact ingredient proportions and processing. The raw materials were all tested. The chocolates, AMF and cocoa butter were all analyzed for fatty acid content (see below), and the nuts were tested for peroxide values prior to incorporation into finished product to assess quality and to gather information of fat composition and other qualities. Peroxide value limits were set for <5 meq/kg.
The processing parameters used for a typical premium chocolate dictated a specific particle size of 15-17 microns to ensure a high quality base (detailed procedures using a micrometer for determining particle size are presented in the experimental methods section, p.91).
Evaluation of Raw Materials
Pre-testing of raw materials ensured a very controlled study with fresh ingredients. The raw materials were all available for analysis since the chocolate base was custom-synthesized for full control of product in this set of experiments. Starting with quality materials was critical in this study since chocolate stability was the focus.
Also, examining roasting parameters ensured that nut products would be considered
77 acceptable to sensory panels and therefore have real world application. The nuts were tested for peroxide values and the cocoa butter, AMF and chocolate bases were tested for fatty acid content.
Fatty acid profiles for the chocolate base, cocoa butter plus milk fat, and raw nuts were determined by gas chromatography. Initial values are presented in Tables 11-13, and detailed methods are described in the experimental methods section below (pp.92).
Results were comparable to values for these materials reported in the literature for differences in cocoa butter source, AMF, and the varieties of nuts (Lipp and Anklam,
1998, Beckett, 2000 and Alasalvar, 2009).
Table 11. Fatty acid methyl ester analysis of cocoa butter and anhydrous milk fat, time zero, determined by gas chromatography.
% Total Fatty Acids Cocoa butter Anhydrous milk fat Fatty acid Ave St Dev Ave St Dev C8:0 0.000 0.00 1.555 0.02 C10:0 0.000 0.00 3.245 0.04 C12:0 0.000 0.00 4.170 0.04 C14:0 0.100 0.00 12.025 0.12 C14:1 0.000 0.00 1.330 0.01 C16:0 26.280 0.03 30.120 0.27 C16:1 0.255 0.03 2.105 0.25 C18:0 35.255 0.02 10.550 0.06 C18:1 33.010 0.10 22.485 0.16 C18:2 2.820 0.00 1.500 0.00 C18:3 0.170 0.00 0.980 0.01 C20:0 1.075 0.01 0.170 0.00 C20:1 0.000 0.00 0.160 0.00 C22:0 0.185 0.01 0.055 0.06 C22:1 0.350 0.00 0.000 0.00 C24:0 0.085 0.09 0.325 0.02 Total 99.570 0.01 90.680 0.18 Unknown(s) 0.430 0.01 9.320 0.18
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Table 12. Fatty acid methyl ester analysis of the chocolate bases, time zero, determined by gas chromatography.
% Total Fatty acids Choco. w/o MF Choc. w/ MF Avg. Stdev Avg. Stdev Fatty acid C8:0 0.090 0.000 C10:0 0.200 0.000 C12:0 0.265 0.004 C14:0 0.110 0.000 0.840 0.000 C14:1 C16:0 25.730 0.016 26.120 0.008 C16:1 0.250 0.016 0.420 0.000 C18:0 36.185 0.012 35.050 0.000 C18:1 32.720 0.033 32.295 0.004 C18:2 2.985 0.012 2.895 0.004 C18:3 0.205 0.004 0.250 0.000 C20:0 1.085 0.004 1.025 0.004 C20:1 C22:0 0.195 0.012 C22:1 0.285 0.004 0.265 0.004 C24:0 Total 99.740 99.710 Unknowns 0.290
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Table 13. Fatty acid methyl ester analysis of raw nuts (non-roasted), time zero, determined by gas chromatography.
Walnut Almond Fatty Acid ave stdev ave stdev C8:0 C10:0 C12:0 0.005 0.004 C14:0 0.040 0.000 0.035 0.004 C14:1 0.000 0.000 0.000 0.000 C16:0 8.380 0.000 6.680 0.008 C16:1 0.110 0.000 0.625 0.004 C18:0 5.260 0.041 1.910 0.049 C18:1 14.005 0.029 63.075 0.412 C18:2 56.300 0.392 26.075 0.086 C18:3 12.860 0.098 0.050 0.016 C20:0 0.175 0.004 0.105 0.020 C20:1 0.175 0.004 0.070 0.008 C22:0 0.065 0.004 0.075 0.061 C22:1 0.060 0.049 0.260 0.024 C24:0 0.220 0.180 0.215 0.176 Total 97.625 0.265 99.170 0.147 Unknown(s) 1.375 0.551 0.830 0.147
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Moisture content of nuts
% Moisture was determined in 8 g samples of each roasted nut sample using a
Mettler LP16 PM 480 Delta Range Moisture Balance (Mettler Toledo). Analyses were performed in triplicate with drying carried out at 110°C. Drying time varied with treatment and nut type.
Ingredient Processing
Nut Roasting
Batches of nuts, 500 g at a time, were placed on preheated mesh trays and evenly spread out, then roasted at 310°F in a Blodgett Model V electric convection oven
(Blodgett Oven Company, Burlington, VT) (Figure 9). Roasting times varied depending on nut variety and desired treatment levels. Halfway through the designated cook time, the tray was rotated to ensure even cooking.
Figure 9. The Blodgett Mark V Convection Oven used to roast nuts for this study
(www.blodgett.com/convection_full.htm)
Nut Grinding
The roasted or raw nuts were fed into the rotary nutmeat granulator (Dayton
Appliances, Dayton, Ohio). The gap between the blades was set to generate a particle size of 3-5 mm by turning the setting 2.5 rotations clockwise. Since the nut grinder can generate fines, the nut samples were sorted with the Ro-Tap (W.S. Tyler, Mentor, Ohio)
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(Figure 10) to ensure this specific particle size range. Pans were stacked in the following order: 6.35mm, 4.76mm (#4), 2.36mm (#8) and pan. The Ro-Tap was run for 3 minutes.
Nuts were collected from pans #4 and #8. The samples in the top pan or in the bottom were discarded. Recovery rates were ~ 350-375 g per 500 g samples.
Figure 10. Ro-Tap Test Sieve Shaker www.wstyler.com
Generation of nut pastes for sensory evaluation
Whole nut pieces were used for texture evaluation, but in order to obtain a more homogenous mixture for evaluating nut flavor, a paste was made using an Old Tyme
Peanut Butter Maker (Pleasant Hill Grain, Hampton, Nebraska) (Figure 11). Fine products with the consistency of peanut butter were generated, then evaluated for flavor at room temperature by an expert sensory panel, using procedures described in the next section.
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Figure 11. Old Tyme Peanut Butter Grinder www.pleasanthillgrain.com
Sensory Analysis of Roasted Nuts
Roasted and chopped nuts as well as nut pastes were evaluated by trained sensory professionals specializing in raw materials. The roasted then chopped and chopped then roasted almonds and walnuts were evaluated for texture in chopped state and for flavor in paste form. Samples were evaluated for desirable flavors defined as appropriate roast level, no off notes, no benzaldehyde or green flavors. Characteristic flavors for each nut were also taken into account. Preliminary processing parameter studies were conducted until the nuts passed sensory evaluation for acceptability. See Section 5.3.6.8. for additional details.
Chocolate Processing
Chocolate formulations were produced in a pilot plant facility. The chocolate recipe (Table 14) was based on published formulations so that a representative, basic dark chocolate base could be used and the knowledge would be easily transferable to other confections.
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Liquor and sugar were combined in a Hobart mixer (Hobart Corp., Troy, Ohio) for approximately 20 minutes to generate a paste-like mixture. Particle size was then reduced by feeding the mixture between two rollers, adjusted to achieve a particle size of
15-17 microns. Next, the paste was dry-conched at 60° C for approximately 2 hours to remove off flavors and undesirable volatiles. The lecithin and cocoa butter were added and mixed for approximately 1 hour. The chocolate was then ready for tempering and moulding.
Table 14. Basic Dark Chocolate Formulations used in this study. Adapted from Beckett
Industrial Chocolate (1999).
Recipe 1 (2.5% AMF)
Paste % kgs %fat Enrob. Liq 62.35 39.90 33.67 Sugar 37.62 24.08 0.00 Vanillin 0.03 0.02 0.00 100.00 64.00 33.67
Conche % kgs %fat Refinings 93.03 63.26 31.32 CB 4.00 2.72 4.00 AMF 2.50 1.70 2.49 Lecithin 0.47 0.32 0.32 100.00 68.00 38.13
Recipe 2 (No AMF)
Paste % kgs %fat Enrob. Liq 62.35 39.90 33.67 Sugar 37.62 24.08 0.00 Vanillin 0.03 0.02 0.00 100.00 64.00 33.67
Conche % kgs %fat Refinings 93.03 63.26 31.32 CB 6.50 4.42 6.50 AMF 0.00 0.00 0.00 Lecithin 0.47 0.32 0.32 100.00 68.00 38.13
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Chocolate Ingredients:
Chocolate Liquor: West African blend of liquors Sugar: Fine grind, supplied from Imperial Granulated Inc. Cocoa Butter: natural cocoa butter non-deordorized AMF: anhydrous milk fat, peroxide value <0.25 meq/kg fat stored at <25°C Lecithin: soy lecithin supplied by Cargill Inc. Vanilla: vanillin supplied by Prova Inc.
Nut Inclusion Specifications
Walnuts
English walnuts grown in the Central Valley of California were harvested in early
November 2009. Acquired from the Ready Roast Nut Company, the walnuts were QA assured and analyzed for aflatoxin (<5ppb), foreign material, defects (i.e. splits, broken pieces). After roasting, the nuts were tested for microbial contamination (Salmonella,
Listeria etc.). The nuts were certified Kosher by the Orthodox Union.
Almonds
Mission Almonds grown in Central California and harvested in late October early
November 2009 were acquired from Treehouse California Almond, LLC of Earlimart,
CA were QA assured and analyzed for aflatoxin (<5ppb), foreign material, defects (i.e. splits, broken pieces). After roasting, the nuts were tested for microbial contamination
(Salmonella, Listeria etc.) to assure safety. The nuts were certified Kosher by the
Orthodox Union.
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EXPERIMENTAL METHODS AND PROCEDURES
OVERALL EXPERIMENTAL DESIGN
Chocolate bar studies
Oil migration from nut inclusions to chocolate and resulting effects on chocolate crystallization, stability, and sensory properties during storage were studied in a dark chocolate base formulated with and without anhydrous milk fat, using two nuts (almonds and English walnuts) with two roast treatments (low and medium) and two chop treatments (roast whole then chop and chop then roast), followed by storage at room temperature for up to 30 weeks. At specified times, chocolate samples were withdrawn and analyzed for physical properties, oxidative degradation, and bloom as described in the following sections. The overall flow diagram describing this study is shown in Figure
12.
For each batch of processed nuts, half were added to the two chocolate formulations (with and without milk fat) as inclusions and the other half were vacuum packed in bags as controls and retained for future analytical testing. For the finished bars there were 12 variables encompassing the 6 nut treatments and the 2 different chocolate formulations. The schedule developed for periodic sampling and analysis is presented in
Table 15. Testing points were initial (week 0) and weeks 4, 8, 12, 20, and 30. The detailed schedule for end of shelf life testing is presented in Table 16.
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1 2 3 4
Oil migration Crystal structure Bloom Oxidation Sensory FAME DSC TPA Colorimeter PV/aldehydes Flavors XRD Visual eval. Rancimat TPA Antioxidants
Figure 12. Process Flow Diagram for proposed systematic study of effects of nut inclusions on dark chocolate properties and stability.
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Table 15. Schedule for analyses of chocolate samples in shelf life testing.
Sample Estimated Date FAME Tocop/Pro Perox/2nd DSC Rancimat TPA Sensory Raw Materials
Cocoa Butter 12/1/2009 X X
Milk Fat 12/1/2009 X X
Chocolate Base 1 12/1/2009 X X
Chocolate Base 2 12/1/2009 X walnut raw 12/21/2009 X X X X almond raw 12/21/2009 X X X X
Roasted Nuts X (initial Walnut Whole Low initial, 4, 8, 12, 16, 20, 24, 30 only) X X X (initial) X X (initial Walnut Whole Med initial, 4, 8, 12, 16, 20, 24, 30 only) X X X (initial) X X (initial Walnut Chop low initial, 4, 8, 12, 16, 20, 24, 30 only) X X X (initial) X X (initial Walnut Chop medium initial, 4, 8, 12, 16, 20, 24, 30 only) X X X (initial) X X (initial Almond whole low initial, 4, 8, 12, 16, 20, 24, 30 only) X X X (initial) X X (initial Almond whole medium initial, 4, 8, 12, 16, 20, 24, 30 only) X X X (initial) X 9 6 6 3 6
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Sample Estimated Date FAME Tocoph/pro Perox/2nd DSC Rancimat TPA Sensory Walnut Whole Low w/MF initial, 4, 8, 12, 16, 20, 24, 30 X X X X X X Walnut Whole Low w/o MF initial, 4, 8, 12, 16, 20, 24, 30 X X X X X X Walnut Whole Medium w/MF initial, 4, 8, 12, 16, 20, 24, 30 X X X X X X Walnut Whole Medium w/o MF initial, 4, 8, 12, 16, 20, 24, 30 X X X X X X Walnut Chop Low w/ MF initial, 4, 8, 12, 16, 20, 24, 30 X X X X X X Walnut Chop Low w/o MF initial, 4, 8, 12, 16, 20, 24, 30 X X X X X X Walnut Chop Medium w/ MF initial, 4, 8, 12, 16, 20, 24, 30 X X X X X X Walnut Chop Medium w/o MF initial, 4, 8, 12, 16, 20, 24, 30 X X X X X X Almond Whole low w/MF initial, 4, 8, 12, 16, 20, 24, 30 X X X X X X Almond Whole Low w/o MF initial, 4, 8, 12, 16, 20, 24, 30 X X X X X X Almond Whole Medium w/MF initial, 4, 8, 12, 16, 20, 24, 30 X X X X X X Almond Whole Medium w/o MF initial, 4, 8, 12, 16, 20, 24, 30 X X X X X X
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Table 16. Schedule for end of shelf life testing of chocolate with nut inclusions.
Sample Timing Colorimeter
Walnut Whole Low w/MF Development of Bloom X Walnut Whole Low w/o MF Development of Bloom X Walnut Whole Medium w/MF Development of Bloom X Walnut Whole Medium w/o MF Development of Bloom X Walnut Chop Low w/ MF Development of Bloom X Walnut Chop Low w/o MF Development of Bloom X Walnut Chop Medium w/ MF Development of Bloom X Walnut Chop Medium w/o MF Development of Bloom X Almond Whole low w/MF Development of Bloom X Almond Whole Low w/o MF Development of Bloom X Almond Whole Medium w/MF Development of Bloom X Almond Whole Medium w/o MF Development of Bloom X
Model system studies
Model systems allow particular phenomenon, such as oil migration or lipid oxidation, to studied in greater detail due to a reduced number of variables. The goal was to understand the modes of failure of these bars and learn how to prevent them. This approach used was to look at the intact system first, identify specific limitations, then utilize model systems where appropriate to provide a greater level of understanding while also allowing for direct application back to the intact system.
Three designs for studying fat migration were tested. In the first model system, a cylindrical mould was constructed so that chopped nuts could be placed on the bottom and topped with chocolate in the ratio of 13% nuts to 87% chocolate (Figure 13). The mould can be disassembled so that the chocolate cylinder can be removed intact.
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Chocolate cylinders were incubated for varying periods to allow oil migration from the nuts, and then sliced into sections to determine the extent of fat migration. A limitation with this mould was the potential for nut oils to migrate up the walls of the mould, reducing the fat migration through the chocolate.
Figure 13. Cylinder model system for testing oil migration. Nuts are placed at the bottom and topped with chocolate in appropriate proportions. The mould comes apart to demould the cylinder, which is then incubated and sliced into sections for fatty acid analysis to determine nut oil migration.
The second model system used an adapted circular plastic holder with dimensions similar to a petri dish. The idea was to isolate the nuts in the center of the mould so the migrating fat would radiate out, and circular sections could be collected and tested. The
91 challenge with this design was the very large diameter needed to maintain the 13% nuts and 87% chocolate proportion. The sample size was so large that fat did not migrate far enough for accurate analysis. A smaller scale system was needed.
The model finally used was constructed to address the limitations of the first two models. Since the ratio of nuts to chocolate is difficult to attain in model systems of 100 g or more, a smaller „micro‟ system was created in which one nut piece (approximately 3-5 mm in dimensions) was embedded in sufficient chocolate or cocoa butter to obtain the
13% to 87% nut to chocolate ratio (Figure 14). Pre- tempered cocoa butter was added to the moulds to obtain a true „time zero‟ for each sample, eliminate the possibility of migration during tempering in the mould, and provide more accurate tracking of fat over time. Each model then served as one sample, i.e. all the cocoa butter was collected from each system. For each time pull all the cocoa butter was collected and tested for FAME.
The fatty acid migration was tracked using the fatty acid profile changes over time for the collected cocoa butter.
Although probing for texture could not be performed on these small samples, changes in lipid composition (FAME-GC), phase behavior (DSC) and crystal structure
(XRD) were possible. Since these models required small amounts of materials and required little space, a large number could be prepared and incubated in an accelerated chamber for analysis after various time periods. Chocolate, especially with nuts, is difficult to view under XRD due to the presence of sugar crystals which interfere with the deflection of the x-ray and make visualization very difficult, therefore this model system offered a way to gain insight into crystallization changes, that can be applied to the intact system.
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Figure 14: Cocoa butter and nut model system Top: mould used to construct model system, Bottom: intact model „micro‟ system
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ANALYTICAL PROCEDURES
The following analytical methods were used in this study:
Particle Size Analyzer: to ensure the correct particle size of the dark chocolate
used in the formulation. Target is 15-17 microns
FAME/GC: to determine the fatty acid composition of nuts as well as chocolate,
cocoa butter and milk fat
Colorimeter: to determine the whiteness index on bloomed samples
Texture Profile Analyzer: to determine the snap and hardness of the chocolate
DSC: to determine the phase behavior of the chocolate
Peroxide Value/Secondary Oxidation Products via SAFE Test: to monitor lipid
oxidation chemistry and evaluate oxidative stability of chocolate bars over time
Rancimat: to predict resistance to oxidative deterioration
Tocopherols/Proanthocyanidins: to determine the inherent antioxidant content
of the nuts
SAFE test/ GC-MS: to identify and quantify specific oxidation products and nut
flavor components
Sensory: to evaluate any changes in flavors, particularly regarding nuts
X-ray Diffraction (XRD) Crystallography : to determine fat crystallization
patterns and crystal forms
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The theory underlying each of these analyses and the information expected from them is presented here as background for understanding why the method was used, followed by detailed protocols for each analysis.
Theory of Methodology, Information Expected, and Detailed Procedures
Particle Size
Chocolate manufacturers often desire a particle size distribution rather than a single micron value which may not be completely representative of the sample. The two methods in common use to determine particle size are mass vs size distribution and number vs size distribution. Mass vs size depends on the mass of the particle and the proportion of the total weight, therefore the volume, whereas number vs size depends on the size of particles, therefore particle diameter. Most typically, mass vs size is used, focusing on the 90th percentile (size at which 90% of the particle mass is comprised of particles with a smaller diameter).
Detailed experimental procedures
Equipment: Micrometer, Mitutoyo America Corporation
Reagents: Mineral oil
Method to determine Particle Size of Refinings (i.e. cocoa liquor and sugar blend)
1. The dried refinings are mixed with enough mineral oil to create a paste
(approximately 2-3 drops).
2. The paste was spread on the surface between the two jaws of the micrometer. The
dial is turned until jaws were completely closed until it can no longer be
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tightened. There is a delicate ratchet built into the device to prevent over
tightening, the scale will read 0. The particle size is measured by closing the gap
until the ratchet clicks, then the diameter of the object is read from the scale.
3. Readings were repeated 5 times to determine an average particle size.
Fatty Acid Methyl Ester-Gas Chromatography (FAME-GC)
Compositions of cocoa butter and nut oils were determined as fatty acid methyl esters (FAME) through a process in which TAG components are hydrolyzed by alkali or acid then converted to volatile methyl esters by reaction with methanol. Briefly, TAGS were dissolved in diethyl ether, saponified with TMAH (tetramethylammonium hydroxide), then esterified with methanol. Base-catalyzed reactions have the advantage of being fast and requiring only mild heating conditions.
FAME analysis was also used to detect oil migration from nuts into the chocolate by documenting the appearance of polyunsaturated fatty acids.
Detailed Experimental Procedures
Sample Preparation and Pentane Extraction of Fat in Chocolate and Nuts:
Nuts in a finished chocolate bar were separated by melting the chocolate then sieving out the nuts to leave a homogenous chocolate sample. Fat from the chocolate
(plus nut oil) was then extracted using the general procedure described below for chocolate.
Pentane was chosen as the solvent based on its rapid evaporation and effectiveness in extracting the fat (Nielsen, 1998). Chocolate (35ml) was melted
96 completely in a 50 ml centrifuge tube and pentane was added to the 50 ml mark. The sample was vortexed 10 seconds then centrifuged for 10 minutes at 4900 rpm at 19°C.
The top layer was collected and transferred to a scintillation vial. The sample was put under the hood and the pentane was allowed to volatize off, 2-3 hours in open hood no vacuum. The lipid remaining was then analyzed by the following GC-FAME analysis procedure.
Equipment:
1. Scintillation vials, 20 ml borosilicate glass, Fisher Scientific, Cat. # 03-337-7
or equivalent.
2. Lab Scraper / Spatula, Fisher Scientific, Cat # 14-373 or equivalent.
3. Pasteur Pipets, Borosilicate Glass, Fisher Scientific, Cat # 13-678-20A or
equivalent.
4. Disposable pipettes, 5 ml, Cat # 13-678-35A or equivalent.
5. Chromatography autosampler vials/caps, Fisher Cat # 03-391-5&3 or
equivalent.
6. Vial Crimper, Wheaton, Cat # W225302 or equivalent.
7. Gas Chromatograph – Agilent 6950 with split/splitless & FID or equivalent.
GC Column and Instrumental Parameters
GC system: Agilent 6850GC
Column HP INNOWax Polyethylene Glycol
Length: 30 m
ID: 0.25 mm
Film Thickness: 0.25 micron
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Carrier: Helium
Flow Rate: 1.3mL/min - Constant Flow
Oven
Initial temperature: 175°C
Initial time: 0 minutes
Rate: 5°C/minute
Final temperature: 250°C
Final time: 20 minutes
Run time: 20 minutes
a) Inlet temperature: 230C
b) Detector temperature: 260C
c) Injection:
Split ratio: 100:1
Injection Volume – 1 µl
Syringe Size – 10 µl
Syringe Wash – Hexanes
Standard Preparation:
a. Weigh 125 mg 1,2,3 tridecanoyl-sn glycerol (C13 triglyceride) into a 200 ml
volumetric flask. Record exact weights.
b. Dilute to 1mg/1ml using 125 ml of diethyl ether. This solution is then used in
step b of sample preparation below.
Sample Preparation
a. Weigh100 mg oil into empty, labeled scintillation vial, record exact weight.
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b. To each vial, add volumetrically 4 mL diethyl ether solution containing
standard (from Step b in Standard Preparation above) and dissolve the sample
by shaking a few times. All of the material should go into the ether solution,
leaving no residue on the bottom.
c. Add 0.25 mL TMAH solution to vial and shake for one minute.
d. After shaking, allow vial to stand for 4 minutes.
e. Add 5 mL DI water, very slowly, to the vial by placing tip of pipette on the
side of the vial and allowing water to flow slowly down the side.
f. Rock the vial slowly back and forth, mixing until ether layer is formed. Allow
layers to separate until top ether layer becomes clear.
g. Add approximately 1 gram of anhydrous sodium sulfate to a second
scintillation vial. Using a Pasteur pipette, transfer the top ether layer from the
original vial to the second vial, being careful not to transfer any of the bottom
aqueous phase.
h. Shake the ether and sodium sulfate briefly. Allow sodium sulfate to settle and
use the clear ether layer for GC analysis.
i. Transfer 2-3 ml of clear ether layer into a GC vial for chromatographic
analysis.
Fatty acids were quantitated using external standard calibration with Nu-Chek GLC
Reference Standard 68 C. One point calibration curves were constructed for all components thus accounting for differences in relative response factors of fatty acids.
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Colorimeter
As chocolate bars age, surfaces become more dull and take on an increasingly whitish haze as bloom develops (Figure 15). These changes can be quantified using a computerized colorimeter (Minolta CM-3500-d Spectrophometer, Konica Minolta,
Tokyo) (Figure 16). This method has been used in other studies with great success
(Pastor et al, 2007). Lessons from their results include using the same testing points on each bar and the same bars over time to minimize differences per sample that could interfere or misrepresent the true data. Triplicate samples of chocolate bars (33 g conformance mould samples) were subjected to accelerated bloom cycling conditions, and L*, a*, b* values were measured using a Minolta CM-3500-d Spectrophotometer with 1 3/8” aperture, Spectra Match Software, and Black box to cover samples.
Testing Protocol:
Pastor et al (2007) cautioned that, because variation in bloom among positions is possible, colorimeter readings to detect bloom should be taken in consistent positions.
Hence, each variable was placed over the 1 3/8” aperture and three readings were recorded for each sample at the right, middle and left side of the bar on the top side of the bars. Duplicate samples were analyzed per treatment variable. A black box was placed over the sample to prevent interference with light.
Data analysis:
Simplistically, the L values were expected to increase over time as an indicator of lightness. A more complex calculation involving changes in colors as well is the whiteness index (Osborn, 2002), calculated according to the formula
WI = 100 – [(100-L)2 + a2 + b2] 0.5
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Although Bricknell and Hartel (1998) developed this formula, they found the colorimeter limited in ability to differentiate between visibly different white spots and concluded that this method is actually less sensitive than using just pure visual evaluation. The colorimeter data was used to see if subtle differences is blooming could be detected, but later were supplemented with visual analysis.
Figure 15. Examples of surface dulling and bloom formation on chocolate bars. Top row
5th bar walnut chop low without milk fat, 2nd row 3rd bar Almond whole medium without milk fat and 5th bar almond whole low without milk fat show indications of bloom.
Minolta CM-3500-d Spectrophotometer
Figure 16. Computerized version of Minolta colorimeter used in this study (http://www.konicaminolta.com).
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Texture Analysis of Chocolate Bars
Texture Profile Analyzers (TPAs) can be used to measure snap of a solid chocolate. A probe is driven into a chocolate sample at a constant speed, force and distance from the sample, and the distance vs the force require to fracture the bar is recorded (Figure 17). A bar with good snap will have a sharp peak whereas a bar with poor snap will bend before breaking and have a wide peak.
Detailed Experimental Procedures
Equipment:
1. Texture Analyzer: TA-XT-2i plus – Texture Tech Corp.
2. Three point bend probe attachment
Testing Parameters for Texture Analyzer:
Pretest Speed: 3 mm/sec
Test Speed: 3 mm/sec
Post Test Speed: 10 mm/sec
Distance: 5 mm
Trigor Force: 5 g
Gap Distance: 2 cm
Testing Protocol for Texture Analysis of Snap in Chocolate Bars:
Attach three point break probe to texture analyzer.
1. Align chocolate bar in the center for consistency. If there is no center choose a
reproducible location. Make sure bar is flat and properly aligned. Avoid divots
and inclusions.
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2. Engage probe to break product. After each sample, clean the probe and testing
stand to prevent interference with next sample.
3. Repeat texture analysis procedure on 8 bars of each variable and average results
to determine the snap value, i.e. the force needed to break the bar.
Force (g)
Time (sec)
Figure 17. Typical Texture Profile Analysis Curve. Peaks indicate the force at which
the sample breaks.
Differential Scanning Calorimetry (DSC)
DSC is a thermoanalytical technique used to measure temperatures and energies
of phase transitions in materials. A test sample and reference are heated in special cells
and the amount of heat needed to maintain identical temperatures in the two samples is
recorded. Endothermic processes such as melting require more heat to match the
temperature of the sample to that of the reference. With exothermic processes such as
103 crystallization, less heat is needed to raise the temperature (Nielsen, 1998). Samples must be heated in a controlled manner. When the heating protocol is too slow, e.g. 1°C/min, fats can recrystallize, but if the process is too fast, e.g. 10°C/min, phase transitions may be missed (Marangoni, 2005).
Figure 18 shows a typical DSC melting and crystallization curve for a fat. The energy absorbed during melting and released during cooling can be easily seen in valleys and peaks of the curve, respectively. The peak temperature for either melting or crystallization is the average of the melting point or crystallization point for the matrix.
The onset of melt and crystallization indicate when the fat just starts to melt or crystallize and is detected through the heat flow deviation from the base line. The peak area is used to determine the total amount of liquid or crystalline material using ΔH = KA where H is the enthalpy of transition, K is the calorimetric constant and A is the area (Marangoni,
2005). The ΔH is calculated as the area under the curve times K which is directly proportional to the total amount of crystalline material formed. Crystallization and melting profiles can be used to indicate polymorphisms as well based on melting point and crystallization temperatures, but should be used only as a guideline and confirmed with XRD. If a peak is seen at 34°C the chocolate is well tempered (Beckett, 2000). DSC can be used to determine the relationship between melting point, TAG composition and crystal composition of the bloomed regions in chocolate (Walter, 2001).
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Figure 18. Typical DSC curve for chocolate, showing transitions and diagnostic features.
Adapted from Maragoni, 2005
DSC can be used to determine amounts of different crystals types in a chocolate sample (Beckett, 2000) and to analyze polymorphic transitions. Over time, fat crystals can rearrange themselves into a more stable form with higher melting point and increased density due to tighter packing structure. These differences, specifically melting point shifts, can be detected using DSC. For example, when changes in milk fat crystallization were tracked during storage, a difference in melting point of 13 to 20 C over 7 days of storage indicated a polymorphic change from a less stable to a more stable form
(Marangoni, 2005). However, polymorphic assignments based on DSC curves need to be
105 confirmed with XRD since the melting points of different polymorphs are different for each fat system.
Different crystal forms and fractions appear as independent peaks in DSC curves.
As chocolate ages, the transition from mostly β-V to β-VI becomes evident in the shift to a higher melting/crystallization peak. Similarly, when foreign fats such as milk fat are present, lower melting point fractions have peaks separate from the chocolate peaks.
Thus, multiple crystal fractions, even from different fat sources, can be readily distinguished.
Detailed Experimental Procedures for Determination of Polymorphic Transitions
Equipment
DSC- TA Instruments Inc.
Test pans/lids
Tweezers
Analytical balance
Sample Preparation Method
Preweigh sample pan and lid on an analytical balance, using tweezers to handle pans and lids.
Weigh approximately 5-10 mg of fat sample into the pan and record weight.
Place the lid on the pan and seal with the press. Make sure there is a good seal so that sample does not leak.
Place the sample pan in the sample cell next to the standard (i.e. empty cell).
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DSC Temperature Program
1: Equilibrate at 20.00°C
2: Ramp 5.00°C/min to 60.00°C
3: Isothermal for 1.00 min
4: Mark end of cycle 1
5: Ramp 5.00°C/min to 0.00°C
6: Isothermal for 1.00 min
7: Mark end of cycle 2
8: End of method
Analysis of DSC data
The peak area was calculated using the TA instruments software package, which determines the total amount of liquid or crystalline material using ΔH = KA where H is the enthalpy of transition, K is the calorimetric constant and A is the area. In many cases more than one melting and crystallization peak were present for each sample so each area was calculated and tracked over time for changes in area to demonstrate polymorphic transitions i.e. two peaks turning into one. Also peak melting and crystallization temperatures were recorded for each sample.
Lipid oxidation
Lipid oxidation is a common product failure during shelf life of most foods, especially nut based products. The fatty acid profile, antioxidants, storage conditions, presence of trace metals, and other factors all play roles in determining oxidation
107 pathways and rates ( Lundberg, 1962), particularly in nuts (Pershern et al., 1994). Three methods for determining extent of lipid oxidation were used in this study:
peroxide values, a measure of early oxidation
rancimat analyses of induction periods, a measure of secondary
decomposition products and innate resistance to oxidation
loss of antioxidants (tocopherols and polyphenols).
Peroxide Values (PV)
During lipid autoxidation, molecular oxygen reacts with fat via free radical chain mechanisms (Lundberg, 1962). Peroxide values measure lipid hydroperoxides, the second product of lipid oxidation, and it is probably the most common indicator of rancidity.
The classical method for measuring peroxide values is by iodometric titration which uses oxidative liberation of molecular iodine from potassium iodide to quantitate peroxide levels as in meq / kg lipid (AOAC Official Method Cd 8-53):
ROOH + 2KI → ROH + I2 + K2O
A starch solution provides the reaction indicator. Amylose forms clathrates with iodine released in the hydroperoxide reaction and turns bluish black. The amount of bound iodine is then determined by titration with standard thiosulfate, and loss of the blue color marks the endpoint. As a benchmark, peroxide values of fresh oil are less than 1 meq/kg whereas rancid oil may be as high as 30-40 meq/kg. Sensory panels typically reject foods with peroxide values about 10.
Peroxide values determined over the shelf life of a product can be very useful in determining the rate and progression of oxidation. Typically, there is an induction period during which PVs are very low, then at some point PVs will begin to increase rapidly,
108 reach a peak and then decrease again as bimolecular decompositions become faster than hydroperoxide formation. Thus, PVs of single isolated samples are simply a snap shot in time and cannot accurately reflect the history of the sample. In order to understand deterioration kinetics of a product, peroxide values must be determined over time.
Peroxide values were expected to reflect the differences in oxidative stability of walnuts and almonds over time. The values for walnuts should increase at a much faster rate for walnuts than for almonds given their fatty acid profile rich in PUFAs.
Detailed experimental procedures -- PeroxySafe™ analysis
(PeroxySafe™ MSA Test, MP Biomedicals, Solon, Ohio)
Sample Preparation (Fat extraction)
Dispense 1.0 gm +/- 0.05 gm of a sample into a conical 15 ml tube. Add 10 glass beads and 3 ml of Standard Prep Reagent. This makes a 1:4 initial dilution. Vortex the sample for 1 minute and warm in a heating block at 40º C for 10 minutes. Vortex the sample for another 30 seconds and place the sample back in the heat block for 5 more minutes.
Filter warm through membrane and collect filtrate. Vortex for 15 seconds and place sample in heat block to warm to 40º C. Subsequent dilutions may be needed for higher peroxide content samples. Keep samples in the heating block until all the tests are completed.
Test Preparation
Label a set of 12mm glass test tubes: RB for the Reagent Blank, C1 through C3 for the three Calibrators; L, M, and H for Controls; and 1, 2, 3, etc. for the samples. When running duplicates, label two tubes for each control and sample.
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Pipetting Calibrators, Control(s) and Samples
Using a positive displacement pipette, transfer 50 µl of Reagent Blank, 50 µl of each calibrator, and 50µl of one or more controls. Vortex each sample for 10 seconds and add
50µl of each sample into the designated 12mm test tubes. Wipe the pipette tip prior to dispensing the reagent blank, calibrators, control(s), and samples. Use a new tip for each reagent blank, calibrator, control, and sample. When running STAT curves, just use one control in the appropriate concentration range and the samples. Run at least one control with each assay. The control will ensure that the assay is being performed correctly.
Adding Detector
Dispense 5-6 aliquots of Reagent A from the bottle into a waste container. This will ensure that no air bubbles are present in the nozzles. Dispense one aliquot 2.5 ml each of
Reagent A into each of the reagent blank, calibrators, controls, and sample tubes.
Dispense 1-2 aliquots of Reagent B from the bottle into a waste container to clear the line, then dispense one aliquot each of Reagent B into each of the reagent blank, calibrators, controls, and samples. Dispense 1-2 aliquots of Reagent C from the bottle into a waste container to clear the line, then dispense one aliquot each of Reagent C into each of the reagent blank, calibrators, controls, and samples. Start the timer for 15 minutes. Cap the tubes and vortex each tube for 30 seconds. Place the tubes in the tube rocker at room temperature for the remaining time.
Reading Calibrators and Controls
Turn on the SafTest™ Analyzer. Check the 570/690 filter to be sure it is in place.
Begin reading test by choosing RUN or STAT and selecting PERSTD. At the „Blank
Tube‟ prompt, thoroughly wipe then insert a tube containing distilled water. Calibrate
110 the instrument by wiping, then inserting the reagent blank and then calibrators 1 through
3 as prompted by the SafTest™ Analyzer. If using Stat mode, always check new test by including a control. NOTE: Prior to insertion in the SafTest™ Analyzer, wipe each test tube with a lint-free tissue.
Successful Calibration
Calibration must be performed whenever a new kit is opened or whenever there is a problem such as a control is out of established ranges. The slope and intercept should be consistent when performing this test if the time and temperature are kept consistent. The slope should generally be between 0.8-1.2. The intercept should be close to zero +/–
0.02. Correlation must be >0.99 for test to be acceptable. If it is not, dilute or concentrate samples and rerun test.
Reading Samples
Following successful calibration, wipe then insert the controls making sure the values of the controls fall within the ranges provided for that lot of controls. If the control is outside the reported or established range or the control exhibits CV‟s >10%, rerun the assay. If the control(s) value(s) falls within the ranges, wipe then insert the sample tubes and analyze in the SafTest™ Analyzer in the designated order. If duplicate sample CV‟s are greater than 10%, repeat test on samples.
Reporting Results
The SafTest™ Analyzer uses calibrators to calculate the lipid peroxide content as milliequivalents of peroxides per kilogram of sample. These results must be multiplied by the sample dilution. The final result can be expressed as milliequivalents of peroxides per kilogram of fat by dividing the final SafTest result by the weight of fat in the sample.
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If the sample value is greater than the value of the highest calibrator, the instrument will flag the results as „HI‟ and the sample must be diluted and retested. If the sample value is less than the value of the lowest calibrator, the instrument will flag the results as „LO‟ and a new more concentrated sample must be prepared for retesting.
Completing Testing
At the end of the day, store calibrators, controls, and reagent bottles with dispensers attached in the refrigerator (2-6°C).
Secondary Products of Oxidation
Secondary lipid oxidation products (e.g. alcohols, aldehydes, hydrocarbons) are generated by hydrogen abstraction, β-fragmentation of hydrogen peroxides, or scission of alkoxyl radicals, or other fragmentation reactions. Hydroperoxide primary products of oxidation are odorless and tasteless, but many secondary products of oxidation have low odor thresholds so very low concentrations be detected by taste or smell. Often by the time the oxidation reaction has proceeded this far the product is already inedible.
Detailed experimental procedure - AlkalSafe™
(AlkalSafe™ MSA Test, MP Biomedicals, Solon, Ohio)
Reagent Preparation
Remove AlkalSafe™ Reagents A, B, calibrators, controls and preparation reagents from the refrigerator and allow them to reach room temperature (18–25°C).This should take approximately 2 hours.
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Setting up the Calibration Curve
Label 4 new 12mm glass test tubes to correspond to Calibrator 1, 2, 3 and 4; and 2 new
12mm tubes for duplicates of the Control. Mix amber bottles containing the calibrators and control to ensure you have a homogenous solution. Use a positive displacement pipette to transfer 150μl of each calibrator into the corresponding labeled test tube. Use a positive displacement pipette to transfer 150μl of the Control into the corresponding labeled test tube.
Adding Reagents & Vortexing
Dispense 1 aliquot of AlkalSafeTM Reagent A into every calibrator and control test tube.
Dispense 1 aliquot of AlkalSafeTM Reagent B into every calibrator and control test tube.
Once you have aliquoted Reagent B into the last test tube start the timer for 20 minutes.
Cap the test tubes and vortex them at the fastest dial setting for 15 seconds. Place the test tubes back in the test tube rack for the remaining time.
Successful Calibration
Calibration must be performed whenever a new kit is opened or whenever there is a problem such as a control is out of established ranges. The slope and intercept should be consistent when performing this test if the time and temperature are kept consistent. The slope should generally be 0.005 +/-0.001. The intercept should be close to 0.01 +/-0.01.
Correlation must be >0.99 for test to be acceptable and if it is not rerun test.
Reading Samples
Dispense 1 aliquot of AlkalSafeTM Reagent A into every sample test tube. Dispense 1 aliquot of AlkalSafeTM Reagent B into every sample test tube. Once you have aliquoted
Reagent B into the last test tube start the timer for 20 minutes. Cap the test tubes and
113 vortex them at the fastest dial setting for 15 seconds. Place the test tubes back in the test tube rack for the remaining time.
Following successful calibration, wipe then insert the controls making sure the values of the controls fall within the ranges provided for that lot of controls. If the control is outside the reported or established range or the control exhibits CV‟s >10%, rerun the assay. If the control(s) value(s) falls within the ranges, wipe then insert the sample tubes and analyze in the SafTest™ Analyzer in the designated order. If duplicate sample CV‟s are greater than 10% repeat test on sample.
Reporting Results
The SafTest Analyzer will use the calibrators to calculate the alkenal content as nanomoles of alkenals per milliliter of sample.
Adjust instrument results by taking into account the dilution factor.
For example: Dilution Factor SafTest Results Dilution x Results Final Results
1:10 4 nmol/mL 10x4nmol/mL 40 nmol/mL
Completing Testing
At the end of the day, store calibrators, controls, and reagent bottles with dispensers attached in the refrigerator (2-6°C).
Rancimat for predictive oxidative stability
The Rancimat method is a rapid test method used to assess oxidative stability of oils and food materials by collecting volatile secondary products in water and measuring the increase in conductivity. A test sample (oil pressed from nut pieces) is placed in a test
114 vessel (Figure 19), the vessel is sealed, and air is bubbled through the oil or over food solids at increasing temperatures. Volatile products picked up in the air stream are carried out of the oxidation cell to the collecting cell where they condense in the water.
Because oxidation products are polar, they increase the conductivity of the collecting water, which provides a means of measuring levels of oxidation products generated.
Following conductivity over time generates a curve that shows an induction period in which little oxidation occurs, then identifies the point of onset for active oxidation (Nielsen, 1998). Less stable samples have short induction periods; samples with lower oxidizability or higher antioxidants have longer induction periods. While rancimat analyses provide no specific information about reactions, the test provides valuable insight into stability differences between nuts. In preliminary studies, Rancimat data showed quite clearly that the almonds have a much longer induction period than walnuts (which are higher in PUFAs) and therefore should be more stable over time. This test also assisted in planning sampling times in experiments; short induction periods warned that the walnuts are many orders of magnitude less stable then almonds so samples should be analyzed on a more frequent basis than normal practice.
A limitation of this test is that it exposes the oil to harsh conditions, high temperatures and oxygen in order to simulate the overall shelf life while accelerating reactions. Rancimat assays are reasonably good predictors, but detect only secondary products far downstream from initiation reactions, and they do not distinguish individual products so give no mechanistic information. They should be supplemented with analyses of early products such as the peroxide values or conjugated dienes to be able to track oxidative degradation more accurately.
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Figure 19. Rancimat instrumentation used to measure oxidative stability of chocolate.
(Metrohusa.com).
Detailed Experimental Procedures
1. Nut oil is added to the reaction vessel (3 ml) of the Rancimat 743 (Metrohm, Herisau).
2. Parameters for the Rancimat are set to the following: temperature (100C), Delta T
(1.6C) and gas flow (20L/h)
3. The sample is heated while air is being bubble through the sample, data is collected until the induction period is achieved which varies per sample.
This test was conducted on the nut oils rather than intact nut meats. Results from intact nuts were highly variable, probably due to difference in surface area for access to air and release of volatiles, while duplicate readings for nut oils were very close (Table
17). Although using nut oils greatly reduces the induction period due to the lack of the protection of the nut structure and endogenous antioxidants, it is much more consistent for testing since all samples are treated identically, simplifying comparison.
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Table 17. Rancimat induction times at 120 C for nut oil and raw nut meat samples.
Sample Sample Type Average St Dev Almond Oil 4.750 0.010 Almond Ground nut 11.630 0.190 Walnut Oil 1.175 0.005 Walnut Ground nut 6.315 0.335
One necessary adjustment was reduction of the temperature from 120°C to 100°C in order to distinguish between walnut samples. At 120°C the walnut samples had such short induction periods that it was impossible to differentiate samples by history or treatment (Table 18). At 120°C, the raw walnuts had an induction period of just over an hour, while at 100° C the induction period increased to about 5 hours and differences between samples became more apparent. This change allowed determination of treatment impact (roast method and nut type) with greater sensitivity.
Table 18. Effect of temperature on rancimat induction periods of raw nut oils.
Sample Temp Ave St dev Almond 120 4.755 0.015 Walnut 120 1.175 0.005
Almond 100 20.370 0.080 Walnut 100 5.305 0.355
Tocopherols
Tocopherols are phenolic compounds that exist in four forms -- alpha, beta, gamma and delta -- differing in the number and placement of methylated groups on the
117 aromatic ring (Figure 8). Alpha tocopherol is commonly referred to as Vitamin E. The antioxidant activity of these compounds stems from their ability to donate hydrogens from the phenol groups to free radicals on oxidizing lipids. It was expected that almonds would have higher overall levels of tocopherols, especially alpha, while walnuts would have appreciable amounts of gamma tocopherol (Alasalvar, 2009). The stability of tocopherols in nuts alone is expected to decrease over time as lipids oxidize and consume antioxidants, but in chocolate bars the situation is more complex because cocoa butter has its own tocopherols, and migration of tocopherols back and forth between phases is possible.
Detailed Experimental Procedures
Equipment
1. HPLC Agilent 1100 with Agilent Chemstation (Agilent, Santa Clara, CA)
2. Analytical Balance
3. Volumetric Flasks – 5, 10, 50, 100 ml
4. Syringe Filters – PTFE, 0.45 micron, 13mm diameter
5. HPLC vials/caps – Agilent 2 ml wide top crimp vial
HPLC Test Parameters
Agilent 1100/1200 HPLC system modules
G1316A Column Thermostat
G1321A Fluorescence Detector
G1311A Quaternary Pump
G1329A Thermostatted Autosampler
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Column
Agilent ZORBAX NH2
Size: 4.6 x 150mm
Particle size: 5m
Mobile Phase
Hexanes (70%)
Ethyl Acetate (30%)
a) Flow Rate:1.000 ml/min
b) Stoptime: 20.00 min
c) Injection Mode: Standard
d) Injection Volume: 5.00 L
e) Fluorescence Detection: Excitation at 295 nm and Emission at 330 nm
Reagents
1. Hexanes, HPLC grade, Fisher # H303-4 or equivalent
2. Ethyl Acetate, HPLC grade, Fisher # E196-4 or equivalent
3. 2-Propanol, Fisher # A520-4 or equivalent
4. (±)-α-Tocopherol, ≥90% (HPLC), Sigma T3251.
5. (+)-γ-Tocopherol, Sigma T1782.
6. (+)-δ-Tocopherol, approx. 90%, Sigma T2028.
Preparation of Standards
1. Weigh 10 mg of each standard (reagents 3-5) into a 100 ml volumetric flask. Record the exact weight of each component.
119
2. Dilute to volume with hexanes and mix well. This is identified as the 100 ppm standard for the three tocopherols.
- Dilute the 100 ppm standard, 1 into 10, to make the 10 ppm standard
- Dilute the 10 ppm standard, 1 into 10, to make the 1 ppm standard
- Dilute the 1 ppm standard, 1 into 2, to make the 0.5 ppm standard
- Dilute the 1 ppm standard, 1 into 10, to make the 0.1 ppm standard
Separation of Nuts from Finished Product
Materials for Separation of Nuts from Finished Product
Warming box
Sieve, large and small
Reagents: Neobee 20 (Stepan Co., Northfield) Ethanol (Fisher Scientific), Pentane
(HPLC grade, Fisher Scientific)
50 ml centrifuge tubes
Vortex
Centrifuge unit (4900 rpm, 15 minutes)
Glass beakers
Scintillation Vials (25 ml)
Method for Separation of Nuts from Finished Product
1. Heat the chocolate in the warm box (50°C) just until the chocolate is melted.
2. Using a sieve separate the chocolate from the nuts. Collect the nuts
3. Create two baths, one containing MCT (Neobee 22) and the second containing ethanol.
4. Using a sieve immerse the nuts into the MCT to remove the remaining chocolate. Then immerse the sieve into the ethanol bath to remove the MCT.
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5. Allow the nuts to dry on a paper towel.
6. Grind the nuts and place in a 50 ml centrifuge tube, roughly to the 25 ml mark.
7. Fill to the 50 ml line with pentane.
8. Vortex each sample tube then place in the centrifuge at 4900 rpm at 20°C for 15 min.
9. Once centrifuged remove the top layer containing the fat and pentane and pour into a glass beaker. Allow the pentane to flash off in the hood for approximately 3-4 hours.
10. Collect the oil into scintillation vials and proceed to Preparation of Test Materials.
Preparation of Test Materials:
1. Weigh about 0.25 g of nut oil into a 5 ml volumetric flask and record its exact weight.
2. Dilute to volume with hexanes and shake the volumetric flask to mix the solution well.
3. Pass the solution through a 0.45 PTFE micron filter and capture the sample in a HPLC vial prior to chromatographic analysis.
Quantification of Tocopherols:
1. Three five-point calibration curves over a concentration range (0.1~100 ppm) are constructed for α-, γ- and δ-tocopherols, respectively. A linear correlation should be developed with a correlation coefficient at least 0.9999 for each.
2. Quantification is accomplished using an external standard (ESTD) approach. The contents of α-, γ- and δ-tocopherols are reported with a unit of μg/g.
A typical chromatogram is shown in Figure 20.
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Figure 20. HPLC chromatogram of tocopherol isomers separated on a ZORBAX NH2 column.
Other Antioxidant Compounds (Flavanols and Procyanidins)
Proanthocyanidins are known to be significant phenolic compounds in nuts, so these were also analyzed in order to gain a greater understanding of all the major factors affecting oxidative stability of nuts. The testing protocol for proanthocyanidins uses normal phase HPLC which has been proven to be more effective then reverse phase
HPLC in separating trimers and has proven to be reliable and reproducible through multiple laboratory testing and comparisons (Adamson et al, 1999). Quantification of proanthocyanidins in chocolate samples by this method paralleled ORAC results indicating that proanthocyanidins are key in antioxidant capability. The skins of nuts, walnuts especially, are known to contain procyanidins which will inhibit oxidation.
Almonds also contain procyanidins. Little data is available in the literature regarding antioxidant profiles of walnuts, so this data will be particularly interesting.
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Detailed Experimental Procedures
Equipment
1. HPLC, Agilent 1100 (Agilent Technologies, Santa Clara) with fluorescence detection
or equivalent.
2. Chromatography Data Acquisition Software, Agilent Chemstation Plus Family,
Revision A.08.03 or equivalent.
3. HPLC Column –Develosil Diol 100 Å 5µm, 250 x 4.6 mm, purchased from
Phenomenex (Torrance), Catalog # DI11546250W.
4. Ultrasonic Bath (VWR Model 150D, VWR, Radnor) – Capable of sonication and
heating to at least 50 °C, or equivalent.
5. Analytical Balance - Mettler Model AT201 (Mettler Toledo, Columbus) or
equivalent.
6. Volumetric Flasks, TC – 5 ml, 10ml, 50 ml or 100 ml.
7. Syringe Filters – PTFE, 0.45 micron, 13 mm
8. HPLC vials/caps
9. Krups Coffee Mill, Type 203
9. Solid Phase Extraction Cartridges, Strata SCX – Phenomenex Catalog # 8B-S010-
HBJ (55µm, 70 Ǻ, 500 mg/3mL
10. Syringes with Slip Tip (not Luer lock) (3ml)
11. Disposable Centrifuge Tubes – 15 ml and 50 ml
12. Cyano Guard columns (4 x 3.0 mm) and cartridge holder, Phenomenex Kit # KJ0-
4282.
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Reagents
1. Water, Millipore quality (18 M resistivity) or equivalent.
2. Hexanes, HPLC grade
3. Methanol, HPLC grade
4. Acetone, HPLC grade
5. Acetonitrile, HPLC grade
6. Acetic Acid, Glacial
7. Reference Standard
HPLC Parameters: f) HPLC system:
Agilent 1100/1200 Series (Agilent Technologies, Santa Clara)
G1311A Quaternary Pump
G1329A Thermostated Autosampler
G1330A Thermostat Unit
G1316A Column Compartment
G1321A Fluorescence Detector
G1322A Degasser g) Column:
Develosil Diol 100 Ǻ Phenomenex
Size: 250 x 4.6 mm
Particle size: 5 micron
Pore Size: 100 Angstrom
Pre-column: CN cartridge from Phenomemex
124 h) Mobile Phase:
A: 98:2 Acetonitrile:Acetic Acid.
B: 95:3:2 Methanol:Water:Acetic Acid.
Gradient conditions Time %B 0 7.0 3 7.0 60 37.6 63 100 70 100 76 7.0 Re-equilibration - 10 minutes i) Flow Rate:1.0 ml/min j) Column Temperature: 35°C k) Injection Volume: 5.0 microliters l) Fluorescence detection: Excitation 230 nm / Emission 321 nm.
Gain gradient employed*: Photomultiplier tube-gain setting
Time PMT gain 0.00 7 8.00 7 8.10 9 15.0 9 15.10 10 76.00 10 * Gain gradient time changes need to be assessed per column - shift in retention time caused by column change – needs to be accounted for.
Preparation of Reference Standards
Acetone Buffer (AWAA) for reference standards and extraction of flavanols and procyanidins from samples
Combine 700 ml of acetone, 295 ml purified water, and 5 ml glacial acetic acid
(70:29.5:0.5 Acetone:Water:Acetic Acid, AWAA).
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Preparation of flavanol / procyanidin standard(s)
1. Weigh 0.3000 grams of selected reference standard into a 25 ml volumetric flask and
dilute to volume with AWAA. This will be the 12 mg/ml standard.
2. For the higher end calibration: prepare the following dilutions using AWAA:
Dilute the 12 mg/ml standard, 1:2 (6 mg/ml) (as needed for higher conc.)
Dilute the 12 mg/ml (stock solution) standard, 1:4 (3 mg/ml)
Dilute the 12 mg/ml standard, 2:25 (0.96 mg/ml)
Dilute the 3 mg/ml standard, 1:4 (0.75 mg/ml)
Dilute the 12 mg/ml standard, 1:25 (0.48 mg/ml)
Dilute the 12 mg/ml standard, 0.5:25 (0.24 mg/ml)
3. Prepare other standard concentrations as needed to appropriately bracket
concentrations of samples (e.g. for lower concentrations).
Dilute the 3 mg/ml standard, 1:25 (0.12 mg/ml)
Dilute the 0.75 mg/ml standard, 1:10 (0.075 mg/ml)
Dilute 0.48 mg/ml standard, 1:25 (0.02 mg/ml)
4. Storage of Standards: The stock solutions were stored in –80°C. Vials were prepared
as needed and stored in the –20°C freezer.
Sample Preparation
Removal of Lipid Fraction a) Place approximately 10 grams of ground nuts for roasted nut test or chocolate for
finished bar test into a labeled 50 ml disposable centrifuge tube b) Fill tube(s) to the 45 ml mark with hexane and cap tightly. c) Vortex at least 1 minute to facilitate complete dispersion / dissolution.
126 d) Place tube(s) in a sonic bath at 50°C and sonicate for 5 minutes. e) Remove centrifuge tubes from the sonic bath, vortex briefly, and centrifuge all tubes
for 5 minutes at 3000 rpm. f) Decant off the hexane phase from each tube. g) Repeat this extraction procedure twice more with each sample so that the extraction
has been performed a total of three times. h) Allow the residual solids to dry in an appropriate fume hood until remaining hexane
has evaporated roughly 3 hours.
Extraction of Flavanols / Procyanidins for all Solid Samples a) Accurately weigh 0.1, 0.5, or 1.00 +/- 0.02 g of sample into a 15 ml disposable
centrifuge tube. b) Accurately add 5 mls of acetone buffer. c) Hand shake, then vortex all samples at least 2 minutes to facilitate dissolution. d) Place tube(s) in a sonic bath at 50°C and sonicate for 5 minutes. Promptly remove
tubes and vortex again. e) Centrifuge all tubes for 5 minutes at 3000 rpm at room temperature. f) Pass the supernatant through a solid phase extraction (SPE) cartridge. Perform
conditioning of the SPE bed with 5 mL of de-ionized water on a vacuum manifold.
Set the vacuum to 0.2bar. Do not allow packing bed to dry at any time prior to
loading the sample. After conditioning the SPE cartridge with water, load 2 mL of the
supernatant solution (sample) on the cartridge. Push about 1ml sample through at a
low flow rate with a syringe plunger into waste (to remove conditioning water). This
ensures that sample is not diluted with the water used for conditioning the cartridge),
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then placing 0.45 PTFE micron filter at the end of the SPE cartridge and capturing
rest of the sample(1ml) in the HPLC vial prior to chromatographic analysis. The
purpose of the SPE is to clean the sample, the procyanidins are not retained on it.
Quantification
Quantification was accomplished with an external standard (ESTD) approach. A calibration curve was constructed for each flavanol / procyanidin fraction. A calibration curve is constructed for monomer, dimmers etc. up to decamer individually - total 10 calibration curves. The sum of the quantities determined for each fraction (1 – 10) was taken as the total procyanidin content of the sample. Run the sample against Batch 10 standard and get monomer content, dimer content thru decamer content, the sum of monmer-decamer is the CP content of your sample. Linear regressions/calibration curves included zero but do not force zero.
Crystallography-X-ray Diffraction
The crystal structure of fats such as cocoa butter can be elucidated by the use of x- ray diffraction, a form of crystallography. X-ray diffraction is based on the reflectance of x-rays by crystal structures (Marangoni, 2005). There are seven crystal systems and the system to which a fat belongs is determined by the angles between the crystal faces as well as how many axes are needed to define the shape, e.g. monoclinic (Marangoni,
2005). XRD is the primary method by which lipid scientists gain information about crystal structure of fats. XRD regions for different crystal forms are shown in Figure 21.
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Figure 21. Phase diagram for crystallization of polymorphs in chocolate (Smith and van
Malssen, 2002)
Currently, it is challenging to view chocolate samples under the XRD (see Figure
22 ) due to the presence of sugar particles. Since sugar is crystalline in nature it too reflects x-rays thus complicating the visualization. Guthrie et al (2005) were able to visualize low sugar content chocolate (less than 30% sugar) using XRD, but they noted that XRD analysis is only possible with certain chocolate formulations and the reflectance of the sugar must be taken into account and subtracted to determine the diffraction of the cocoa butter crystals alone.
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Figure 22. X-ray diffractor from Bruker available at: http://www.bruker- axs.com/x_ray_diffraction.html
Detailed Experimental Procedure
Equipment:
Bruker AXS X-ray Diffractor (Figure 22)
Method:
Settings for XRD
Starting 2-theta angle
Stop: 30 degrees Step size: 0.05 degrees
Time/Step: 3 sec Rotation speed: 30 rpm
Def Generator: 50 kV 40mA
Sample Preparation:
Place approximately 0.5 g fat sample into sample holder, minimize manipulation. Sample must be flat on the surface. Place sample into the Bruker AXS. The sample runs for
130 approximately 22 minutes. A diffraction pattern records the X-ray intensity as a function of 2-theta angle and a scan similar to the one below (Figure 23) results for each sample:
Figure 23. Typical XRD scan for cocoa butter.
From these data the formula d = λ / (2 Sin θ) where λ = 1.54 Ǻ can be applied to solve for d where d is the short spacings as noted by the arrows to the corresponding peaks above. The sinθ data is acquired from the graph and plugged into the formula in order to solve for d. This data is then compared to the literature for known short spacing patterns for various polymorphs to determine the crystal structure of the sample.
Data Analysis
Data is analyzed using EVA software. Open the Eva program. Go to file, import, scan file. The short spacings are determined as mentioned in Figure 23 and then the polymorphic crystal formed is identified.
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SAFE (Solvent Assisted Flavor Evaporation)
Solvent Assisted Flavor Evaporation (SAFE) is a high vacuum transfer technique
(HVT) for isolating and collecting volatiles from a material. It uses a two-compartment distillation apparatus (Figure 24) in which one side is heated while the other is exposed to liquid nitrogen, allowing the collection of solids on one side and the volatiles on the other
(Engel et al, 1999). Engel et al (1999) made improvements to this technique so that high fat systems could be tested, less bench top space was needed for equipment, and more flexibility with solvents was possible. Components isolated by SAFE can then be separated, identified, and quantitated by GC-MS.
In this study, SAFE testing was performed to isolate volatiles that contribute to off-flavors in the walnut and almond bars. Oxidation of oleic, linoleic and linolenic acids into hydroperoxides followed by decomposition to alkoxyl radicals, then - or -scission products generates many carbonyl compounds that are responsible for rancid odors and flavors (Belitz and Grosch, 1987).
SAFE has many advantages over older techniques such as steam distillation that can often create artifacts through high heat. High heat can create products that are not actually present and therefore do not accurately reflect the chemistry that has occurred in the product. The selection of a technique for analyzing volatiles should address the following needs according to Engel et al (1999): the conditions used should not alter the aroma compounds present, unwanted non-volatile compounds must be removed, and major contributing compounds should not be discriminated against.
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Detailed Experimental Procedures
Equipment:
SAFE Distillation unit: (constructed in laboratory) (Figure 24): dropping funnel, cooling trap, central head with two off shoots each connected to a beaker. The inlet and outlet for water are connected to the center of the distillation unit. A water bath is located on the right of the set up, the decanted fluid is fed into the lower beaker, the volatiles are then trapped on the left side which is cooled with liquid nitrogen. The pump is located on the left to apply a vacuum to the system. Clamps and seals are required in order to maintain the vacuum.
Liquid N trap A.Sample fed in
C. Volatiles condensed
B. Solids collected Liquid Nitrogen Water Pump Bath
Figure 24. Distillation unit set up for Solvent Assisted Flavor Evaporation analyses of volatiles from chocolate (Engel et al 1999).
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Sample Preparation
1. Freeze a chocolate bar sample by placing broken up pieces into a plastic beaker
and covering with liquid nitrogen. Grind into a powder using a coffee grinder..
2. Transfer the powder to a plastic centrifuge bottle and add 100 μl of
izobutylthiozole (standard at 444 ppm) with 100 ml of ethyl ether.
3. Shake the bottle for 15 minutes on a rotary shaker at 150 rpm, then centrifuge at
4500 rpm for 10 minutes.
4. Collect the yellow supernatant and transfer to the top right section of the
apparatus (A, Figure 23).
5. Slowly drip the supernatant from A into the collection beaker (B, Figure 23) and
allow the fluid to bubble to flash off volatiles. This takes approximately 1 hour
depending on the sample size. Released volatiles are collected by condensation in
a cold trap (C, Figure 23).
6. At the end of the purge period, add an additional 50 ml of ether to the remaining
sample, shake, centrifuge for an additional half hour, and add to the first
collection of supernatant as previously described. Vacuum extract the volatiles
and collect over liquid nitrogen. Allow the solution to cool to room temperature
(approximately 1 hour) and filter over sodium sulfate to remove any water.
7. Concentrate the sample to about 5 ml using a vigreux column, heating the sample
in a water bath.
8. Collect the sample and concentrate to approximately 0.25 ml under nitrogen.
9. Analyze volatiles in the sample by GC-MS on an FFAP column.
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Sensory Quality Changes Over Shelf life
Sensory attributes are a main consideration in chocolate manufacture and key for the chocolate consumer. Processing parameters are set to ensure desirable flavor and texture attributes, which are best judged by the human tongue and mouth. The initial bite through viscosity, grittiness and meltaway in the mouth are all important characteristics that can be more accurately assessed by sensory perception than by instrumental analysis.
Viscosity and micron size of the particles affect the perception of all these attributes so are a main target in processing control. However, although instrumental analyses can provide numbers that describe a specific property, only sensory analysis can show how the intensity of attributes are perceived and interpreted by humans. For example, particles can be sized as 20 or 30 microns, but only sensory analysis can reveal that consumers perceive 20 micron particle as smoother (Beckett, 2000).
Detailed Experimental Methods
The evaluators of the nut samples were sensory experts in raw materials trained at
MARS, so no additional training was required. A sample of the rating sheet used for sensory evaluation of nuts and chocolate is shown in Figure 25. Evaluations were conducted on the open bench and results were based on a consensus from the raw material experts. Therefore only one ballot was collected for all participants, i.e. the group made a collective decision based on consensus. Descriptive analysis can be customized depending on the product and attributes of interest. Appearance, aroma, flavor and texture are all attributes that can be assessed.
Also different intensity scales can be used, although a 15 point scales is typical. Two reference points are mandatory to provide an anchor at each end, e.g. from none to
135 strong, often 3-5 reference points are used along the scale (Meilgaard et al., 1999). For the flavor evaluation of this study specifically rancidity a 15 point scale based on the
Spectrum method which uses the universal scaling method of rating intensities was used
(Table 19). Where each point on the scale equals the intensity of the aromatics see chart below. Nut samples were presented in order of low roast to high roast; chocolate bars were presented control first which was a frozen version of each chocolate bar so that a
„time zero‟ could be used for comparison. The order of sampling started with the sample without milk fat followed by chocolate with milk fat. The important descriptive attributes typically considered in nut evaluations are: degree of roast (benzaldehyde/red fruit, raw/green), off notes (cardboard and painty), texture (hardness and fracturability) and other characteristic notes such as woody/hull/skin. These attributes were addressed in the ballot under the respective categories and also captured in the comment section as well.
Table 19. Spectrum Method for Flavor Intensity Rating (Civille, 1996 page 57)
Point on Scale Intensity
0 None
1 Just detectable
2.5 Very slight
5 Slight
7.5 Slight-Moderate
10 Moderate
12.5 Moderate-Strong
15 Strong
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For flavor attributes such as rancidity there is a reference for rancidity and the intensity of this flavor is assessed using the scale mentioned above. There is a rancid standard (no per say slightly rancid sample or very rancid) and the presence and extent of this flavor is rated using the scale above. So for example an oxidized nut is used as a reference and the intensity of this flavor is evaluated. The reference is an internal standard that has been selected to exemplify a rancid note. The panel is trained to be able to recognize a rancid note and then can determine the intensity of this flavor in the sample. Examples of attributes and references are listed in Table 20.
Some key flavor attributes are listed below along with their definition and reference. Often references are company or laboratory specific and use in house references for comparison purposes instead of general standards.
Table 20. Flavor Attributes for the Sensory Evaluation of Nut and Nut Containing
Bars (Adapted from Civille, 1996)
Flavor Attribute Definition Reference example
Almond Nutty Aromatic of roasted almond that is not cherry like Almonds
Walnut Nutty Aromatic of roasted walnut (non-oxidized) Walnut
Chocolate Aromatic associated with chocolate liquor Dark Chocolate
Ex. West African/Ivory Coast liquor
Degree of Roast Aromatics associated with level of roast Roasted nuts
Time and temperature of roast dependent
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Ex. Low, medium and dark
Oxidized General and non-specific character of
oxidized foods ex. painty, stale, cardboard Aged nuts
Texture is assessed using standard industry references for fracturability including corn muffin (1), graham cracker (4) and ginger snap (8) and Life Saver (15). Fracturability of the nuts was evaluated in this way while snap instead was evaluated through comparison to in house chocolate samples which demonstrated good to poor snap characteristics.
Lastly bloom was assessed visually by the team through comparison to a control bar that did not have any bloom vs a bar with extensive bloom. This bar was subject to accelerated chamber cycling and was extensively bloomed.
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Nut Flavor (in paste)
Roast Level Green light roast Medium Roast High roast 1------2------3.5------7.5------15
Off Notes Strong No off note Sl. Off note Off notes 1------2------3.5------7.5------15
Rancidity None Strong 1------2------3.5------7.5------15
Nuts Texture (in chopped nuts) Texture Fracturable/Hard Not Hard 1------2------3.5------7.5------15
Chocolate Bar Overall appearance No bloom Sl.bloom Extensive Bloom
1------2------3.5------7.5------15
Rancidity (flavor of nuts in bar) No Rancidity Rancid 1------2------3.5------7.5------15
Texture (snap of chocolate) Good Snap Poor Snap 1------2------3.5------7.5------15
Any additional Comments:
Figure 25. Response sheet used for descriptive evaluation of nuts and chocolate.
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Model System: Creation of Cocoa Butter Seed
Equipment:
Temperature controlled chambers/water baths (VWR, Digital water bath, Radnor)
Beaker (250 ml)
Parafilm
Cocoa butter tempering:
1. Completely melt out solid cocoa butter at 80°C for 30 minutes.
2. Transfer beaker containing cocoa butter to 60°C chamber for 30 minutes.
3. Place beaker in a 0°C chamber for 90 minutes
4. Transfer beaker to a water bath at 26°C for 40 hours.
5. Confirm cocoa butter is tempered through Xray Diffraction.
5. Use seed directly or to seed a larger batch of cocoa butter.
Model System Assembly:
Each individual model contained a nut piece approximately 60-80 mg in weight embedded in 400 mg cocoa butter to provided the same cocoa butter:nut ratios used in finished bar (87:13 ratio of cocoa butter to nut inclusion). A chocolate mould was selected with dimensions to hold the targeted weight of cocoa butter (400 mg) to nut while covering and surrounding the nut. A small amount of cocoa butter was placed in the mould to cover the bottom. The nut was placed on the chocolate surface and covered with the remaining cocoa butter; the cocoa butter was then smoothed with a spatula. Each mold in the tray was filled in this manner, and the tray was placed in a refrigerator at 40
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°F to cool for 2 hours. Samples were then demoulded and placed in the accelerated chamber for aging.
Accelerated Shelf Life Study
Model systems were incubated for a maximum of 12 days, with samples withdrawn at 3 day intervals for analysis, hence 4 sampling points. The chamber was programmed to cycle every 8 hours from 31°C to 21°C. Samples were static with no exposure to light. Samples were withdrawn periodically for analysis. The nut was separated from the cocoa butter, and the cocoa butter was analyzed for changes in crystallization by DSC and XRD and for modifications in fatty acid composition by
FAME analysis (gas chromatography).
141
RESULTS
1. 1. Nut stability testing (Series 1 and 3 on Experimental Flow Diagram, Figure 15)
Oxidative Stability of Raw and Roasted Nuts
Rancimat analyses: Innate oxidative stability of raw and roasted nuts (alone, not in chocolate), whole, and chopped, as determined by the rancimat method is shown in
Table 21. Three points are clear: 1) almonds are much more stable than walnuts initially and throughout the incubation period, and 2) roasting increases stability of almonds but decreases stability of walnuts, and 3) chopping decreases stability of walnuts (according to rancimat but not overall). Rancimat results were consistent with peroxide values
(Table 22, Figure 26) and soluble aldehydic products (Table 23, Figure 27) throughout the incubation period although the rancimat data for the walnuts‟ induction period is so short that differences among samples cannot be considered significant.
Peroxide values: Chemical product analyses also showed superior stability in almonds. Almonds did not oxidize until late in the study; PV‟s remained negligible until week 24 (Table 22, Figure 26). The innate stability of almonds reflects their lower degree of polyunsaturation (Table 13) and higher levels of antioxidants (Table 7), while walnuts are more highly unsaturated and have overall lower levels of tocopherols and other antioxidants.
Walnuts were considerably less stable. As shown in Table 24, peroxides had already developed in both whole and chopped walnuts at the beginning of the experiment, and were higher than in almonds throughout the study. Peroxide values for whole walnuts peaked at week 12, then dropped continually until the end of the study, week 30.
Surprisingly, PVs of chopped walnuts with increased surface exposure area remained low
142
Table 21. Oxidative stability of oils from raw and roasted nuts as determined by rancimat analyses at 100 C (series 1 and 3, Figure 15). Data is average of two replicates.
Sample Treatment Induction Time (hr) Almond Raw 20.81 ± 0.549 Almond Whole Low 27.00 ± 0.021 Almond Whole Medium 29.80 ± 1.380
Walnut Raw 5.31 ± 0.502 Walnut Whole Low 6.11* Walnut Whole Medium 5.26* Walnut Chop Low 5.18* Walnut Chop Medium 3.88* * one replicate
Peroxide Values (meq/kg) in Roasted Walnuts
12
10 8 Walnut w hole low Walnut w hole medium 6 Walnut chop low 4 Walnut chop medium 2
(meq/kg) Value Peroxide 0 0 4 8 12 20 24 30 Incubation time (weeks)
Figure 26: Peroxide values for walnuts during a 30 week time period while in refrigerated conditions (40°F)
143
Table 22. Peroxide values in raw and roasted nuts. Data is an average of two replicates. PV (meq/kg) Week Week Week Week Week Week Sample Initial Stdev 4 stdev 8 stdev 12 stdev 20 stdev 24 stdev 30 Raw Almond Nd N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A
Almond whole low Nd <0.05 nd <0.05 nd <0.05 0.90 <0.05 0.34 <0.05 2.10 <0.05 6.55
Almond whole
medium Nd <0.05 nd <0.05 nd <0.05 0.60 <0.05 0.77 <0.05 1.90 <0.05 5.22
Raw Walnut 0.24 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A
Walnut whole low 1.47 <0.05 4.45 <0.05 1.43 <0.05 9.30 <0.05 7.60 <0.05 3.00 <0.05 1.17
Walnut whole medium 1.51 <0.05 3.59 <0.05 1.32 <0.05 9.80 <0.05 3.10 <0.05 2.60 <0.05 0.51
Walnut chop low 1.07 <0.05 1.27 <0.05 0.56 <0.05 8.70 <0.05 8.60 <0.05 6.20 <0.05 7.83
Walnut chop
medium 1.28 <0.05 1.04 <0.05 1.00 <0.05 2.80 <0.05 2.10 <0.05 3.90 <0.05 7.66
144
(~1) over the first eight weeks before beginning to increase. PVs of chopped low roast walnuts reached a PV comparable to whole nuts (8.7 vs 9.3 and 9.8) at 12 weeks and thereafter remained high. PVs of chopped medium roast walnut also began increasing after 8 weeks, increasing more slowly but steadily throughout the study, ending at PVs comparable to low roast samples.
These results may seem paradoxical for the first twenty weeks. However, it is important to remember that oxidation in nuts is controlled by a combination of endogenous and environmental factors, including enzymes, degree of cellular compartmentalization of disruption, surface exposure to air, and heat, and the balance between these factors changes with conditions and time. Factors expected to play major roles in the nuts are lipoxygenase and peroxidase enzymes, endogenous antioxidants, degree of tissue disruption and separation of reactants, surface exposure, and heat.
The prolonged rancimat and PV induction periods in roast almonds and low roasted walnuts are most likely due to inactivation of lipoxygenase. Lipoxygenase levels are higher in walnuts than in almonds. Branasompob et al (2007) reported initial lipoxygenase (LOX) activity of 0.26 µM O2/sec in raw walnuts versus 0.11 µM O2/sec in almonds. LOX activity was reduced by short time high temperature heat treatments at both 55 and 60°C. Final levels of LOX depended on the length and temperature of the treatment. Almonds had lower LOX levels at 55°C for 10 minutes and 60°C for 10 minutes whereas walnuts had higher levels in all cases with the exception of 60°C for 2 minutes in which the same level was found.
The data of Branasompob et al (2007) is in line with the current study in which differences were seen among chop vs whole treatment groups. Instead of different
145 temperatures, the current study investigated effects of different pretreatments and heating time. Walnut samples that were chopped then roasted had longer induction times when tested in the Rancimat. The medium roast (4 minute roast time) had a longer induction time than low roast (3 minute roast time). Both of these effects were unexpected since increased surface area and temperature usually accelerate lipid oxidation. The increased surface area of chopped vs whole roasted nuts can be explained by greater heat penetration and inactivation of lipoxygenase. The whole roasted samples had shorter induction times and the medium roast (15 minute roast time) had a longer induction time than the low whole roast (12 minute roast time). Buranasompob (2007) also found that higher temperatures and longer times led to more stable walnut samples. This behavior can also be explained by greater LOX inactivation with more extensive heat treatment.
Another difference found between the samples in the Buranasompob study (2007) was the antioxidant activity. A soybean lipoxygenase was added to the samples of ground nuts to assess the antioxidant activity of each. The soybean lipoxygenase had a LOX activity level of 1.58 µM O2/1s to start when added to the ground walnuts the level dropped to 0.66 µM O2/1s and in almonds dropped further to 0.47 µM O2/1s. This demonstrates that not only are lipoxygenase levels higher in walnuts, both in the raw form and the heat treated form, but walnuts have another disadvantage of having lower protective antioxidants as well as higher polyunsaturated fat levels. Lipoxygenase specifically targets 1,4 pentadiene units which are found only in polyunsaturated fats such as linoleic and linolenic, which are both considerably higher in walnuts than almonds.
146
Ozdemir et al (2001) explored the impact of temperature and time of roast on hazelnuts. The results were mixed and demonstrate the complexity of oxidation. The hazelnuts showed a reduction in PV with increased temperature and time up to a point,
158°C. However, at 162°C PV values increased. Thiamine was tracked to show the impact of thermal degradation of the samples. High temperatures over a longer roast time may account for loss of protective antioxidants and therefore the higher PV values
(Ozdemir et al., 2001).
Heat also enhances oxidation, in part by decomposing existing hydroperoxides and enhancing propagation reactions, so oxidation should increase in the order raw < low roast < medium roast. However, almonds and walnuts were the reverse of this in rancimat, and all samples had comparable starting PVs after heating. Thus, any effects of heat on oxidation during storage were indirect, e.g. through enzyme (in)activation or structural changes during heating.
Chopping disrupts the cellular structure, separates the oil bodies from the enzymes in nutmeats, and increases surface area and exposure to air. Separation of reactants is most likely responsible for the early inhibition of oxidation in chopped walnuts. Up to eight weeks, hydroperoxides do not increase so LPOx cannot be active, and any tocopherol present can inhibit any autoxidation occurring. Over the long term, however, the high surface area and greater exposure to air in chopped nuts appears to be the most important factor since PVs increased and stayed elevated throughout incubation.
147
Alkenals and short chain aldehydes: Aldehydes surprisingly showed patterns of development that were nearly identical to those of peroxide values instead of following the decrease in PVs. The expected reaction was decomposition of hydroperoxides to alkoxyl radicals which would then undergo and scission to form aldehydes after peroxide peaks had been passed. This pattern suggests that aldehydes were produced in pathways in parallel to equilibrium between hydroperoxide formation and decomposition so that the net curves reflect the balance between the two pathways at any given time.
Whole roasted nuts had slightly higher alkenal values than chopped. Chopped walnuts showed lower levels of hydroperoxides and aldehydes than whole walnuts in contrast to the shorter induction periods observed in the Rancimat test. These results might seem counterintuitive but are consistent if Rancimat results are considered.
Peroxide values and aldehydes measure soluble products in the oil while rancimat measures volatile released from the oil. The decrease in rancimat induction time in chopped walnuts reflects increased decomposition of hydroperoxides to small volatile products that escape from the oil into the headspace. The same thing happens during incubation, where the larger surface area in chopped nuts allows greater escape of small molecules from oxidative breakdown.
Overall, these results demonstrate differences in the innate stability of almonds versus walnuts and further indicate that walnuts are severely limited in their tolerance to heat treatments. The question now is, do the two nuts behave the same in chocolate, generating volatile oxidation products that accumulate in the chocolate and contribute to off-flavors, or do the barrier properties and antioxidants of chocolate protect the nuts and
148 maintain a reasonable stability during storage? Answers to these questions will be presented in the section on Oxidative Stability of Chocolate with Nut Inclusions, p. 141.
Alkenal Levels(nmol/ml) in Roasted Nuts
800
700
600 Almond whole low Almond whole medium 500 Walnut whole low 400 Walnut chop low Walnut chop medium 300 Walnut whole medium
Alkenal (nmol/ml)Alkenal 200
100
0 0 4 8 12 20 24 30 Incubation time (weeks)
Figure 27. Alkenal levels in Roasted nuts over 30 week shelf life study
149
Table 23. Secondary oxidation products (aldehydes) in raw and roasted nuts. Data is an average of two replicates.
WEEKS OF INCUBATION Alkenal (nmol/ml) Initial SD 4 SDD 8 SD 12 SD 20 SD 24 SD 30 SD Raw Almond 78.3 <.05 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A
Almond whole low NA 68.7 <.05 65.4 <.05 34.6 <.05 39.7 <.05 35 <.05 nd <.05 low Almond whole low NA 80.0 <.05 68.7 <.05 43.3 <.05 58.6 <.05 96 <.05 nd <.05 medium
Raw Walnut 115.5 <.05 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A
Walnut whole 135.3 <.05 501.4 <.05 242.3 <.05 580.6 <.05 260 <.05 152 <.05 nd <.05 low Walnut chop low 133.6 <.05 338.0 <.05 235.5 <.05 604.9 <.05 149 <.05 nd <.05 nd <.05
Walnut chop 108.8 <.05 366.2 <.05 264.8 <.05 207 <.05 282 <.05 21 <.05 nd <.05 medium Walnut whole 156.8 <.05 411.3 <.05 237.8 <.05 527.2 <.05 726.8 <.05 nd <.05 nd <.05 medium
150
Overall oxidative stability
Almonds and walnuts, as expected, differ greatly in overall stability. The portion of this study that focused on the nuts alone will be discussed first followed by the nut bar and model system study. In regards to overall oxidative stability almonds are much more stable over time as demonstrated in this 30 week study. There is a much larger delay of onset of both primary and secondary oxidation which was confirmed with sensory testing. Over time both nuts showed indications of oxidation from rancimat, peroxide and alkenal testing. The roast level was important for walnuts in regards to primary oxidation where the medium roast was more stable than low roast (p=0.054). The overall rate of peroxidation was much faster for walnuts vs almonds and also a drop off were seen around week 20 indicating the beginning of secondary oxidation. Secondary oxidation products were much higher for walnuts, as confirmed with sensory data. Nut type was critical in product failure (p=0.001) and roast method also was significant (p=0.052). An increase in alkenals is expected after a drop off in peroxides, but this relationship was not exactly clear in all cases. It held true for the whole medium walnuts but in most cases the alkenal levels spiked intermittently during this study.
Tocopherols in nuts
Tocopherol levels in raw and roasted nuts are presented in Table 24 and the changes over time are shown in Figures 29-31. Several patterns are clear. Almonds have more than double the total tocopherol levels, mostly in - tocopherol with very little - and -tocopherol, and this difference holds over the entire storage period. Walnuts are the
151 reverse, with very low - tocopherol and relatively high levels of - and -tocopherols. -
Tocopherol is the most reactive isomer so is the most preferred for physiological action;
- and -tocopherols react more slowly and, perhaps for this reason, are more effective as antioxidants (Alasalvar, 2009).
Roasting has a more profound impact on walnuts than on almonds. Tocopherol losses were only ~2.0% in alpha and ~10.0% in gamma isomers in roasted almonds, while 43.4-61.3% alpha , 21.5-39.0% gamma, and 27.4-36.5% delta losses were recorded for the various treatments in roasted walnuts.
Table 24. % Tocopherol loss in roasted nuts over 30 week period
Total Almond whole low 21.19 20.76 14.90 Nd Almond whole medium 21.35 20.94 14.57 Nd Walnut whole low 28.14 13.94 28.31 6.41 Walnut whole medium 21.16 8.76 21.24 (+) 1.68 Walnut chop low 14.95 26.04 13.90 (+) 1.78 Walnut chop medium 36.18 37.58 36.56 9.64
As shown in Table 26, on a percentage basis walnuts lost more total (~25%) and individual (23%) tocopherols than did almonds (~21%). Figure 28 shows the changes in gamma tocopherol over time as well.
Tocopherols loss patterns differed in the two nuts (Figures 29-31) indicates that there is a cycling of tocopherols occurring. One potential explanation is that a synergist such as ascorbic acid is acting to regenerate the tocopherol, the primary antioxidant
152 according to the reaction below where A designates tocopherol and B ascorbic acid
(Fennema, 1996):
RO2 + AH→ ROOH + A
A +BH → B + AH
So B, in this case ascorbic acid, regenerates the tocopherol. Ascorbic acid is present in nuts and appreciable levels in walnuts, 0.4 mg/oz (Alasalvar, 2009).
70% Gamma Tocopherol in Walnut Bars 60%
50%
40%
30%
20% Walnut w hole low (%) Tocopherollevel Walnut w hole medium 10% Walnut Chop low 0% Walnut Chop Medium 4 8 12 16 20 24 28 Incubation time (weeks)
Figure 28. Changes in gamma tocopherol in walnut bars. There is evidence of cycling of tocopherol which may be attributed to regeneration of the tocopherol via ascorbic acid.
A plausible reason for this difference is that since the walnuts are more unstable than almonds, the tocopherols play a more major role early in the oxidation cycle.
Tocopherols quench peroxyl and alkoxyl radicals formed in unsaturated fatty acids, so a
153 greater initial reduction in tocopherols is expected for the more oxidizable polyunsaturated walnuts. -Tocopherol was more labile in walnuts while -tocopherol was consumed more in almonds.
Roasting had inconsistent effects in the two nuts. In almonds, roasting decreased tocopherol loss, consistent with lower levels of oxidation due to lipoxygenase inactivation (and hence lower levels of LO from decomposition of LOOH), as discussed in the previous section. In contrast, in walnuts, roasting increased -tocopherol loss in whole nuts and decreased loss of this isomer in chopped nuts, while the opposite was true for -tocopherol, i.e. decreased loss in whole nuts but notable increase in loss in chopped nuts. -Tocopherol, which is often considered to be the most active tocopherol isomer in foods, showed little change in whole walnuts but one-third less loss in medium roasted walnuts.
Perhaps most importantly, tocopherols continually decreased in almonds during the 30 week shelf life study, but in all walnuts, there was an initial decrease followed by a regeneration of tocopherols (Figure 28). These antioxidant loss patterns are not consistent with the oxidation patterns observed in roasted walnuts (Table 24 and 25). One speculative explanation is that some Maillard browning products formed during heating have reducing potential and are able to cycle tocopherols without affecting lipid oxidation. Reaction of lipid aldehydes with amines to form Maillard products could account for the marked decrease in aldehydes in walnuts after Week 12, but this does not account for the all differences given the fact that almonds also contain Maillard browning products. As mentioned previously in a study by Severini (2000) MRP applied to almonds did have lower PV values compared to a non-vacuum packed sample but did not
154 when compared to a vacuum packed sample. Therefore although MRPs may contribute to product stability the extent and impact on various nuts has not been fully explored.
155
Table 25. Tocopherol levels in nuts after 0, 4, 8, 12, 16, 20, 24 and 30 weeks of storage at 25 C. Nut oils samples were tested in duplicate.
Alpha Gamma Delta Total (nmol/g (nmol/g (nmol/g (nmol/g lipid) lipid) lipid) lipid) Stdev
Initial week 0 Raw Almonds 591.48 31.67 <5.00 628.59 <0.05 Almond whole low 579.27 28.67 <5.00 613.38 <0.05 Almond whole medium 578.58 28.57 <5.00 612.58 <0.05 Raw Walnuts 15.39 343.42 29.43 388.25 <0.05 Walnut whole low 6.32 217.64 22.55 246.51 <0.05 Walnut whole medium 5.96 209.41 21.35 236.72 <0.05 Walnut Chop low 7.35 236.57 22.54 266.46 <0.05 Walnut Chop Medium 8.71 269.42 24.80 302.93 <0.05 Week 4 Almond whole low 550.23 24.49 <5.00 574.72 <0.05 Almond whole medium 566.21 25.73 <5.00 591.93 <0.05 Walnut whole low <5.00 138.49 20.88 159.37 <0.05 Walnut whole medium <5.00 147.09 20.40 167.49 <0.05 Walnut Chop low 6.47 189.65 22.78 218.90 <0.05 Walnut Chop Medium 6.51 191.43 22.98 220.92 <0.05 Week 8 Almond whole low 555.86 27.01 <5.00 588.30 <0.05 Almond whole medium 562.88 28.63 <5.00 596.95 <0.05 Walnut whole low < 5.00 162.55 20.84 183.39 <0.05 Walnut whole medium <5.00 191.58 21.35 212.92 <0.05 Walnut Chop low <5.00 204.02 21.33 225.35 <0.05 Walnut Chop Medium < 5.00 198.54 23.01 221.55 <0.05 Week 12 Almond whole low 473.59 22.08 <5.00 495.66 <0.05 Almond whole medium 497.78 24.79 <5.00 522.58 <0.05 Walnut whole low <5.00 129.67 15.35 145.02 <0.05 Walnut whole medium <5.00 104.74 15.12 119.86 <0.05
156
Walnut Chop low <5.00 134.35 16.41 150.76 <0.05 Walnut Chop Medium <5.00 196.64 19.57 216.21 <0.05
Alpha Gamma Delta Total (nmol/g (nmol/g (nmol/g (nmol/g lipid) lipid) lipid) lipid) Stdev Week 16 Almond whole low 596.85 22.93 <5.00 619.78 <0.05 Almond whole medium 564.02 20.22 <5.00 584.24 <0.05 Walnut whole low <5.00 86.74 6.09 92.83 <0.05 Walnut whole medium <5.00 113.59 7.50 121.09 <0.05 Walnut Chop low <5.00 201.74 9.89 211.63 <0.05 Walnut Chop Medium <5.00 149.35 8.15 157.50 <0.05
Week 20 Almond whole low 479.64 25.82 <5.00 505.46 <0.05 Almond whole medium 497.57 24.85 <5.00 522.41 <0.05 Walnut whole low <5.00 93.46 17.87 111.33 <0.05 Walnut whole medium <5.00 168.83 21.34 190.16 <0.05 Walnut Chop low <5.00 152.97 19.18 172.15 <0.05 Walnut Chop Medium <5.00 111.54 18.78 130.33 <0.05 Week 24 Almond whole low 473.70 27.01 <5.00 500.71 <0.05 Almond whole medium 512.67 25.78 <5.00 538.46 <0.05 Walnut whole low <5.00 124.39 19.73 144.12 <0.05 Walnut whole medium <5.00 130.92 19.96 150.88 <0.05 Walnut Chop low <5.00 147.79 19.09 166.88 <0.05 Walnut Chop Medium <5.00 96.72 17.15 113.87 <0.05
Week 30 Almond whole low 459.02 24.40 <5.00 483.42 <0.05 Almond whole medium 457.40 24.40 <5.00 481.80 <0.05 Walnut whole low <5.00 156.03 21.11 177.14 <0.05 Walnut whole medium <5.00 164.92 21.71 186.63 <0.05 Walnut Chop low <5.00 203.68 22.95 226.63 <0.05 Walnut Chop Medium <5.00 170.93 22.41 193.35 <0.05
Figure 29. Total nut tocopherol levels over 30 week shelf life study
Figure 29. Changes in total tocopherol levels over 30 weeks
157
700 Total Nut Tocopherols 600
Figure500 30. Changes in alpha tocopherol levels in nut bars over 30 weeks
Almond w hole low Almond whole Med 400 Walnut w hole low Walnut w hole med 300 Walnut chop low
nmol/g lipid nmol/g Walnut chop med 200
100
0 0 5 10 15 20 25 30 35 Incubation Time (Weeks)
Figure 29. Changes in total tocopherol in nut bars over 30 weeks
700 Alpha Tocopherols 600
500
400 Almond w hole low Almond whole Med
300 Walnut w hole low nmol/glipid Walnut w hole med 200 Walnut chop low
100 Walnut chop med
0 0 5 10 15 20 25 30 35 Incubation time (Weeks)
Figure 30. Changes in alpha tocopherol in nut bars over 30 weeks
158 300 Gamma Tocopherols Almond w hole low Almond whole Med 250 Walnut w hole low Walnut w hole med Walnut chop low Walnut chop med 200
150
nmol/glipid 100
50
0 0 5 10 15 20 25 30 35
Incubation time (Weeks)
Figure 31. Changes in gamma tocopherol in nut bars over 30 weeks
30
Delta Tocopherol 25
20
15
Almond w hole low nmol/glipid Almond whole Med 10 Walnut w hole low Walnut w hole med Walnut chop low 5 Walnut chop med
0 0 5 10 15 20 25 30 35 Incubation Time (Weeks)
Figure 32. Changes in delta tocopherol in nut bars over 30 weeks
159
Proanthocyanidins in nuts
Procyanidins are polymeric flavonoids that, even with solubility changes, retain strong antioxidant activity, at least against hydroxyl radicals. Compared to other products such as cocoa, endogenous procyanidin levels in nuts are extremely low. However, procyanidins form from monomers that polymerize when exposed to heat, light, oxidation, radicals, metals, and other catalysts. Thus, they can provide a mirror of oxidative chemistry occurring in each of the nuts and chocolate products.
Procyanidin levels in both almonds and walnuts changed little until the last week of storage time, when they increased notably (Table 26). Initially the raw walnuts had higher procyanidin levels and there was a reduction after roasting, but the levels seen in these samples are all very low. Results suggest that anthocyanins do not play a major role in protection of either walnuts or almonds during early oxidations when tocopherols are active, but they may becomes important in later storage after tocopherols have been largely consumed. Longer incubation times and additional analyses would be needed to verify this action.
160
Table 26. Proanthocyanidin levels in roasted nuts before and during storage at room temperature for varying times. Values are the average of two replicates and nuts were stored in a vacuum sealed bag. StDev <0.05
Proanthocyanidins (mg/g nut oil) Weeks of incubation Sample Initial 4 8 12 16 20 24 30 Raw Almond 0.51 N/A N/A N/A N/A N/A N/A N/A Almond whole low 0.36 0.46 0.47 0.42 0.45 0.19 0.47 0.91 Almond whole 0.34 0.45 0.48 0.42 0.48 0.22 0.49 0.86 medium Raw Walnut 1.10 N/A N/A N/A N/A N/A N/A N/A Walnut whole low 0.26 0.55 0.48 0.43 0.38 0.22 0.44 0.82 Walnut whole 0.32 0.52 0.55 0.52 0.55 0.22 0.55 0.95 medium Walnut chop low 0.38 0.58 0.53 0.56 0.52 0.26 0.61 0.95 Walnut chop 0.45 0.7 0.61 0.51 0.51 0.21 0.45 0.79 medium
Overall Results for Antioxidants in Nuts
Two antioxidant types were studied in order to gain understanding in the inherent oxidative stability of each nut type and also what role if any each played in mitigating oxidation. Overall almonds have higher total tocopherol levels and are more stable to roasting conditions and time when whole, but are so unstable chopped that they cannot be used in that form. Walnuts have lower levels of antioxidants which also participate actively in oxidation. The initial drop in tocopherols seen early in incubation parallels hydroperoxide formation so is most likely due to utilization in inhibiting propagation steps. Ascorbic acid in walnuts appears to cyclically regenerate tocopherols. Procyanidins were low in both nut types and did not play appear to play a role in stabilization.
161
Sensory Evaluation of Roasted Nuts
Key characteristics detected by the panelists were (Table 27):
onset of rancid flavors in two walnut samples by 4 weeks (walnut chop medium
and low)
significant rancid flavor in chopped walnut samples
by week 12 chopped walnut sample testing was discontinued due to extensive
rancidity
by week 12 whole roasted walnuts demonstrated oxidation
week 16 whole medium roasted walnut testing was discontinued
week 24 whole low roasted walnut testing was discontinued
there was no detection of rancidity in almond samples over the 30 week test
period
slight reduction in roasted notes and texture (less hard) were evident for all
samples over time
When the sensory results are compared to the PV data, the sensitivities and limitations of this testing are obvious. Braddock et al (1995) suggested that a PV value of
8-10 is an end point to shelf life of peanuts. Results of this study agree. Overall when PV values exceeded 8.0, sensory panelists rated the product as unacceptable. The chopped low walnut sample was determined to be unacceptable at week 12 when it had a PV of
8.7. Whole medium walnuts were deemed unacceptable at week 16 with a PV of 9.8. The walnut whole low sample was discontinued at 24 weeks with a PV of 3. At week 12 the
PV was 9.3 and then dropped to 7.6 at week 20. The PV continued to drop and an
162 increase in alkenals was seen. The only nut variety that differed from this pattern was the walnut chop medium which had relatively low PV and alkenal values but was the first sample discontinued in sensory due to rancid flavors.
163
Table 27. Sensory ratings of nuts after 0, 4, 8, 12,16, 20, 24 and 30 weeks of storage at room temperature. Nut Sensory (Scale 0-15) 1 to 15 increase rancidity and roast 1 to 15 decrease in fracturability
Week 0 (Initial reading) Sample Roast Level Off Notes Rancidity Fracturability Comments Almond Whole Low 3.5 0 0 5 Almond Whole Medium 10 0 0 3 more crunchy slightly bitter Walnut Whole Low 4 0 0 8 vegetable oil flavor Walnut Whole Medium 8.5 0 0 7 higher in roast lower in vegetable oil flavor Walnut Chop Low 2.5 0 0 6 less bitter more sweet than whole roast then dice Walnut Chop Medium 6 0 0 6
Week 4 Almond Whole Low 3.5 0 0 5.5 Almond Whole Medium 10 0 0 3.5 Walnut Whole Low 4 0 0 9 Walnut Whole Medium 8 0 0 8 Walnut Chop Low 1.5 3 3 6 Walnut Chop Medium 3.5 3.5 3.5 6
Week 8 Almond Whole Low 3 0 0 6 slight reduction in roast and sl less fracturable Almond Whole Medium 9.5 0 0 5 Walnut Whole Low 3.5 0 3.5 8.5 painty flavor in chopped Walnut Whole Medium 7.5 3.5 4 7.5 off flavor more obvious in paste Walnut Chop Low 1 7.5 9 5.5 even control oxid in chopped less obvious Walnut Chop Medium 3 6.5 8 5.5
164
Table 27, continued. Sensory evaluation after 0, 4, 8, 12,16, 20, 24 and 30 weeks of storage at room temperature. Nut Sensory (Scale 0-15).
Sample Roast Level Off Notes Rancidity Fracturability Comments Week 12 Almond Whole Low 3 0 0 6 Almond Whole Medium 8 0 0 5 reduction in roast level Walnut Whole Low 3 4 4 8.5 Walnut Whole Medium 7.5 3.5 6 7.5 Walnut Chop Low 1 15 15 5 done - extensive rancidity Walnut Chop Medium 3 15 15 5 done - extensive rancidity
Week 16 Almond Whole Low 2.5 0 0 6 sl reduction in nut roast Almond Whole Medium 7 0 0 5 Walnut Whole Low 2.5 7.5 7.5 8.5 Walnut Whole Medium 7 15 15 7.5 discontinued Walnut Chop Low N/A N/A N/A N/A discontinued Walnut Chop Medium N/A N/A N/A N/A discontinued
Week 20 Almond Whole Low 2 0 0 6.5 sl reduction in nut roast Almond Whole Medium 6 0 0 5.5 sl reduction in nut roast Walnut Whole Low 2.5 9 9 8.5 sl reduction in nut roast Walnut Whole Medium N/A N/A N/A N/A discontinued Walnut Chop Low N/A N/A N/A N/A discontinued Walnut Chop Medium N/A N/A N/A N/A discontinued
165
Table 27, continued. Sensory evaluation after 0, 4, 8, 12,16, 20, 24 and 30 weeks of storage at room temperature. Nut Sensory (Scale 0-15). Week 24 Almond Whole Low 2 0 0 6.5 sl less almond flavor Almond Whole Medium 1.5 0 0 5.5 sl less almond flavor Walnut Whole Low 2.5 12 12 8.5 discontinued Walnut Whole Medium N/A N/A N/A N/A discontinued Walnut Chop Low N/A N/A N/A N/A discontinued Walnut Chop Medium N/A N/A N/A N/A discontinued
Week 30 Almond Whole Low 2 0 0 6 sl reduction in nut roast Almond Whole Medium 1.5 0 0 5.5 sl reduction in nut roast Walnut Whole Low N/A N/A N/A N/A discontinued Walnut Whole Medium N/A N/A N/A N/A discontinued Walnut Chop Low N/A N/A N/A N/A discontinued Walnut Chop Medium N/A N/A N/A N/A discontinued
166
Summary of Sensory Results for Nuts
In sensory testing, almonds were stable throughout this study; no off flavors were detected. Walnuts, on the other hand, displayed off notes by week 8 and began to be eliminated from testing at week 12 due to excessive rancid notes. By week 20 only one walnut variety remained in testing (walnut whole low) and by week 24 it also was eliminated from testing. The almonds remained acceptable throughout the study with slight reduction in nut roast character as the only noticeable defect.
2. Stability of chocolate bars with almond and walnut inclusions
Lipid oxidation products
Hydroperoxides for finished chocolate bars (chocolate and nuts)
Almonds were more stable than walnuts in chocolate bars, just as for the nuts alone; even though peroxide values of almonds began to rise at 8 weeks, they were still well below 1 after 30 weeks of storage (Figure 35, Table 28). In contrast, walnuts started the shelf life incubations with peroxide values already close to the 12 week value for almonds (Table 28). Except for walnut whole in chocolate plus milk fat, PVs for all the walnut samples showed the typical pattern of increasing to a peak and then decreasing
(Figures 33 and 34 comparing with and without milk fact versions. Figures 36 and 37 compare whole and chopped nut varieties. Peaks for the walnut samples ranged from 12 to 20 weeks; PVs of chopped walnuts peaked in shorter times than whole walnuts, reflecting lower stability when high surface area is available for oxidation.
Milk fat had a complex effect on lipid oxidation. It did not change on oxidation during early stages, but tended to suppress PVs as incubation progressed. It shortened the
167 peak PV time to 8 in whole walnuts but delayed the peak PV until 20 weeks in chopped walnuts. Since aldehyde levels were higher for most treatments when milk fat was present (next section), some component in the milk fat may be enhancing the LOOH decomposition. According to Beckett (1999) the main causes of product failure for milk fat are oxidation and lipolysis. Exposure to oxygen and temperature can lead to oxidation.
The chocolate bars in this study were stored at ambient sealed in a film, typical for chocolate bars, which is a minimum oxygen barrier. Although milk fat contains a large amount of saturated fatty acids there are also appreciable levels of unsaturated fats which are susceptible to oxidation (Ranken et. al, 1997).
168
Table 28. Lipid hydroperoxides in chocolate bars with nut inclusions, stored for 30 weeks at room temperature. Values are averages of duplicates.
Peroxide values (meq/kg oil) Weeks of incubation PV (meq/kg) 0 Stdev 4 Stdev 8 Stdev 12 Stdev 20 Stdev 30 Stdev Dark chocolate Almond whole low low N/A low N/A 0.11 <0.05 0.53 <0.05 0.3 <0.05 0.79 <0.05
Almond whole med low N/A low N/A 0.22 <0.05 0.91 <0.05 0.71 <0.05 0.15 <0.05
Walnut whole low 0.62 <0.05 2.13 <0.05 4.14 <0.05 4.93 <0.05 7.5 <0.05 5.12 <0.05
Walnut whole med 0.49 <0.05 1.96 <0.05 2.86 <0.05 5.18 <0.05 6.8 <0.05 5.62 <0.05
Walnut chopped low 0.51 <0.05 1.53 <0.05 3.66 <0.05 5.26 <0.05 5.2 <0.05 3.85 <0.05
Walnut chopped med 0.41 <0.05 1.27 <0.05 3.35 <0.05 4.09 <0.05 4.7 <0.05 4.57 <0.05
Dark chocolate + milkfat
Almond whole low low N/A low N/A 0.27 <0.05 0.76 <0.05 0.4 <0.05 0.18 <0.05
Almond whole med low N/A low N/A 0.15 <0.05 0.74 <0.05 0.3 <0.05 0.45 <0.05
Walnut whole low 0.55 <0.05 2.02 <0.05 4.91 <0.05 5.79 <0.05 5.51 <0.05 4.46 <0.05
Walnut whole med 0.6 <0.05 1.53 <0.05 2.85 <0.05 3.69 <0.05 6 <0.05 4.55 <0.05
Walnut chopped low 0.18 <0.05 1.01 <0.05 2.51 <0.05 4.25 <0.05 3.4 <0.05 1.34 <0.05
Walnut chopped med 0.59 <0.05 1.33 <0.05 2.93 <0.05 5.37 <0.05 2.65 <0.05 2.21 <0.05
169
8 Peroxide Values 7 6 5 4 3 Walnut whole low
2 Walnut whole med PV (meg/kg fat) PV(meg/kg Walnut chopped low 1 Walnut chopped med 0 0 5 10 15 20 25 30 Incubation time (weeks)
Figure 33. Effect of chop and roast treatments on peroxide values for dark chocolate bars with walnut inclusions, no milk fat.
7 PV: Dark choc + milkfat
6
5
4
3
PV (meq/kg fat) PV(meq/kg 2 Walnut whole low Walnut whole med 1 Walnut chopped low Walnut chopped med 0 0 5 10 15 20 25 30 Incubation time (weeks)
Figure 34. Effect of chop and roast treatments on peroxide values for dark chocolate bars with walnut inclusions, plus milk fat.
170
1 PV: Chocolate w/ Whole Roasted Almonds 0.9 0.8 Almond whole low w/MF 0.7 Almond whole low w/o MF Almond whole med w/MF 0.6 Almond whole med w/o MF 0.5 0.4
0.3 PV(Meq/kg fat) 0.2 0.1 0 0 4 8 12 20 30 Incubation time (weeks)
Figure 35. Changes in peroxide values for almond bars with and without milk fat. The peroxide levels for almonds are much lower than walnuts and evolve much later in the shelf life.
8
7 PV: Chocolate w/ Whole Roasted Walnuts
6
5
4
3 Walnut whole low w/MF
PV(Meq/kg fat) 2 Walnut whole low w/o MF Walnut whole med w/MF 1 Walnut whole med w/o MF 0 0 4 8 12 20 30 Incubation time (weeks)
Figure 36. Peroxide values for chocolate bars with nut inclusions stored for various periods at room temperature. (whole)
171
6 PV: Chocolate w/ Chopped Walnuts
5
4
3
2 Walnut chop low w/MF PV(Meq/kg fat) Walnut chop low w/o MF 1 Walnut chop med w/MF Walnut chop med w/o MF 0 0 4 8 12 20 30 Incubation time (weeks)
Figure 37. Peroxide values for chocolate bars with nut inclusions stored for various periods at room temperature (chopped).
Aldehydes. Secondary products of lipid oxidation similarly showed that the walnut bars oxidized at a much faster rate than almond bars (Table 29, Figure 38). The aldehyde data makes several interesting points.
Aldehydes accumulated to higher levels with whole walnuts in the chocolate than chopped walnuts, despite lower surface area, lack of cellular disruption, etc., and thus presumably were less stable. However, whole nuts retain structure to trap volatile aldehydes as they are formed while chopped nuts have large areas of cut surface from which volatiles can be released. Thus, the values measured represent aldehydes remaining in the finished chocolate bar (chocolate and nuts) rather than aldehydes actually formed.
172
Except in walnut chop medium samples, milk fat markedly reduced aldehyde levels in the bar. A plausible explanation for this effect is that the high content of saturated fatty acids in milk fat suppress oxidation both in the chocolate and in the nuts, where the saturated fat can form a film around the nuts. The increase in aldehydes in the walnut chop medium samples may results from increased solubilization of oxidation products and facilitation of migration from nuts to chocolate.
The high levels of aldehydes in walnuts and chocolate with walnuts was consistent with sensory perceptions of rancidity, so presumably these are the compounds being tasted.
Finally, the presence of detectable levels of aldehydes even in the almonds points out one of the problems in using only hydroperoxides for monitoring lipid oxidation – because hydroperoxides break down under many conditions, low peroxide values is not a certain indicator of low or no oxidation and must be supplemented with measures of other products.
173
Table 29. Aldehydic secondary lipid oxidation products from chocolate with nut inclusions stored at room temperature for eight weeks. Values are averages of duplicates.
StDev <0.05
Alkenal (nmol/ml)
Week Week Week Week Week Week 0 4 8 12 20 30 Dark chocolate
Almond whole low 41.83 low 54.73 41.23 low 62.00
Almond whole med 38.82 low 58.50 33.30 93.00 46.00
Walnut whole low 66.63 146.64 223.46 330.17 522.82 542.00
Walnut whole med 63.63 67.61 221.66 296.48 419.15 403.00
Walnut chop low 65.13 46.29 217.18 338.10 360.56 387.00
Walnut chop med 62.12 48.96 185.81 229.10 324.51 434.00
Dark chocolate + milkfat
Almond whole low 41.83 low 63.52 54.11 low 69.00
Almond whole med 37.32 low 49.71 45.19 low 85.00
Walnut whole low 60.62 122.66 254.84 193.43 172.00 426.00
Walnut whole med 60.62 73.82 259.32 221.18 356.05 403.00
Walnut chop low 53.10 36.52 243.00 270.72 202.82 139.00
Walnut chop med 58.37 59.61 160.71 373.77 581.00 294.00
174
600 Aldehydes - dark chocolate Almond w hole low 500 Almond whole med Walnut w hole low Walnut w hole med 400 Walnut chop low Walnut chop med
300 nmol/ml 200
100
0 0 5 10 15 20 25 30 Incubation time (weeks)
700 Aldehydes - dark chocolate + milk fat Almond w hole low 600 Almond whole med Walnut w hole low 500 Walnut w hole med Walnut chop low 400 Walnut chop med
300 nmol/ml
200
100
0 0 5 10 15 20 25 30 Incubation time (weeks)
Figure 38. Aldehyde levels in dark chocolate plus almonds or walnuts stored at room temperature for varying periods. Top.Dark chocolate base. Bottom. Dark chocolate plus anhydrous milk fat base.
175
SAFE results: products of lipid oxidation in walnuts
In order to gain more information about lipid oxidation products in chocolate, a
SAFE analysis of an oxidized walnut sample. The whole bar was used for testing and contained oxidized walnuts (chopped medium without milk fat) as determined through sensory testing and PV analysis. This test allows the investigator to gain insight into the major contributing compounds to the oxidized flavors being detected by the sensory panel. The major compounds detected were pyrazine, n-hexanal, 2,3,5 trimethyl, acetic acid and 3-methyl butyric acid (Table 30).
Pyrazines, the major products, are typical Strecker degradation products from carbonyl-amine reactions (Figure 39). Pyrazines are formed from the interaction of dicarbonyl compounds, intermediate products from Maillard browning, and amino acids.
The amino group is transferred to the dicarbonyl which can then go on to condensation reactions (Fenemma, 1996). Various amino acids can serve as precursors but usually threonine is preferred for production of pyrazines.
O O 2,5-Dimethyl-3-Ethyl-Pyrazine Browning Sugars + + Methionine →
CH3
CH2 –CH3 Strecker Reaction CH3
O O α-dicarbonyls
Figure 39. Reaction for the formation of alkyl pyrazines during roasting of nuts.
176
Table 30. SAFE analyses of volatiles released from an oxidized walnut sample.
Peak Number Peak ID Sample ppm 3 n-Hexanal 7505
12 2,3,5-Trimethyl pyrazine 6011
13 Acetic acid 3919
19 3-Methyl butyric acid 2862
4 Undecane 1967
10 2-Ethylmethyl pyrazine 1774
5 Hydrocarbon* 1421
20 Hexanoic acid 1178
8 1-Chloro-2-propanol 1086
2 Decane 1010
14 Tetramethyl pyrazine 934
7 Pentanol 897
6 Dodecane 844
18 Isobutyric acid 732
1 Pentane 492
9 2 Heptanal 459
11 2-(2-Methyl propyl) pyrazine 444
15 3,5 Octadien-2-one 419
17 Benzaldehyde 306
16 Propanoic acid 146
*a specific hydrocarbon not specified
177
The odor type and threshold of the various pyrazines depends on their substituent side groups and position in the ring. For example, 2-methyl-pyrazine has an odor threshold of 105 ug/l and a characteristic odor of roasted peanuts, while 2,6-dimethyl- pyrazine has a threshold of 104 ug/l and has the characteristic odor of chocolate (Belitz and Grosch, 1986). Benzaldehyde and butyric acid derivatives are also typical chocolate volatiles. Decane, undecane, and dodecane are chain scission products formed from saturated fatty acids during roasting of cocoa beans (Figure 40). The only clear oxidation products were hexanal and pentane, formed via and cleavage, respectively, of the
C13 alkoxyl radical of linoleic acid (Figure 40).
CH3(CH2)7-CH2-CH2-CH2-CH2-CH2-(CH2)4COOH Decane Dodecane Undecane O CH3(CH2)4-CH -CH=CH-CH=CH-(CH2)7COOH RC Pentane H 2 HexanalC H Figure 40. Formation= of oxidation products from nut oils via cleavage of fatty acids. C H- C H Both nuts and= the chocolate have significant levels of pyrazines. Over time in a C product containing nutsH- and chocolate two things can potentially occur, one is there is C flavor fade or reductionH in the roasted notes and the other is that the development of off R1 flavors masks the roasted notes hence suppressing them and also resulting in a product with less roasted notes (Braddock, 1995). Through the SAFE analysis, it is possible to see if the pyrazines are actually decreasing through degradation reactions from lipid oxidation or if instead the off notes (i.e. aldehydes and ketones) are masking the roasted
178 notes. Since there was no reduction in pyrazine levels over the shelf life of the product i.e. the oxidized bars had similar pyrazine levels compared to the unoxidized bar (850-
900 ppm), while the oxidation products ( hexanal, etc.) increased dramatically (345 ppm vs 7505 ppm), it seems that the off notes generated from oxidizing lipids are covering up the roasted notes of the nuts (Figure 41). Overtime it would be of interest to track pyrazine levels to see how much flavor fade is occurring, but 20 weeks into the study the pyrazine levels remained quite constant (~850-900 ppm) while the oxidation products greatly increased.
179
Abundance
SAFE Results for Oxidized Nut Sample vs Non-oxidized Nut bar sample
←n-hexanal 7000000
6000000
5000000
Oxidized vs Control 4000000
3000000
2000000 ←hydrocarbon ↓Tetramethyl pyrazine
↓pentanol ↓3,5 octadien-2-one ↓Hexanoic acid 1000000
0 4.00 6.00 8.00 10.00 12.00 14.00 16.00 18.00 20.00 22.00 24.00 Time
Figure 41. Comparison of oxidized walnut bar sample to control showing the differences in concentration of various flavor compounds from the SAFE method
180
Tocopherols in chocolate bars
Evaluating tocopherols in nuts separated from the dark chocolate bar is much more complicated than nuts alone because chocolate itself contains appreciable amounts of tocopherols (alpha - 10 ppm, gamma - 170 ppm, delta - 17 ppm (Gunstone, 1986)), so even if great care is taken to remove all traces of the chocolate coating (see methods section), traces of chocolate greatly increase variability.
As reported above, stored plain nuts showed marked losses of alpha and gamma tocopherols during storage. However, when nuts were encased in chocolate during storage, tocopherol levels actually increased in both nuts. -Tocopherol increased in almonds (Figure 42), and -tocopherol increased in both walnuts and almonds (Figure 43-
45). Trace contamination could provide a constant background to all nuts and explain gamma tocopherols increase in a single sample, but it cannot explain the continued increase in tocopherols with incubation. The difference between the heat treatments is not consistent with activation of isomerases, so the simplest explanation is migration of tocopherols from the chocolate into the nuts. The -tocopherol is much higher in the cocoa butter than in almonds, thus providing a concentration gradient to drive the migration. The opposite is true for walnuts, which are very high in -tocopherol.
However, walnuts oxidize at a very fast rate and consume tocopherols in the process, so the actual concentrations -tocopherol concentration could be considerably less than in the chocolate, thus establishing a gradient (Figure 42-45).
There is one additional explanation for this increase in tocopherols in nuts. Since chocolate is mostly fat based, it can act as a sink for oxygen and not protect the nuts from oxidation. Fat migrates out of the nuts into the chocolate, reducing the overall fat content
181 of the nuts. The tocopherols are isolated in the nut oil and reported on a proportional basis per volume of oil. The same absolute amounts of tocopherol dissolved in lower volumes of oil will yield an aberrant impression of a concentration increase.
It is worth noting that the different storage of the nuts vs the bars may also play a role. The nuts are stored vacuum sealed kept at 40°F and the bars are wrapped in a minimal oxygen barrier film stored at 70°F. Under vacuum conditions and low temperatures oxidation will occur at a slower rate and therefore most likely the antioxidants will not participate as early or to the same extent in samples that are most likely undergoing oxidation at a faster rate. Also specific isomers of tocopherol are more sensitive to oxygen such as α tocopherol (Belitz and Grosch, 1986).
182
600
Alpha Tocopherol Content of Roasted Almonds in Chocolate Bars
450
300
Almond whole low w/ mf
150 Almond whole low w/o mf
Alpha Tocopherol (ug/g) Tocopherol Alpha Almond whole medium w/ mf
Almond whole medium w/o mf 0 0 5 10 15 20 25 30 Incubation time (weeks) Figure 42. Changes in -tocopherol levels in chocolate bars with almond inclusions stored at room temperature for varying periods.
250 -Tocopherol Content of Roasted Almonds in Chocolate 230 Bars 210 190 170 150
(ug/g) 130 Almond whole low w/ mf 110
GammaTocopherol 90 Almond whole low w/o mf 70 Almond whole medium w/ mf
50 Almond whole medium w/o 0 5 mf10 15 20 25 30 Incubation time (weeks)
Figure 43. Changes in gamma tocopherol in almond inclusions in chocolate bars stored at room temperature for 30 weeks.
183
195 -Tocopherol: Roasted Walnuts in Chocolate Bars w/MF 175
155
135
115 Walnut Whole low w/MF Walnut whole medium w/mf Walnut chop low w/ mf
GammaTocopherol (ug/g) 95 Walnut chop medium w/mf 75 0 5 10 15 20 25 30 Incubation time (weeks)
Figure 44. Changes in gamma tocopherol in walnut bars in chocolate with milk fat during storage.
180 Tocopherol: Roasted Walnuts in Chocolate Bars w/o MF
160
140
120
Walnut whole low w/o MF 100 Walnut whole medium w/o mf Walnut chop low w/o mf
80 GammaTocopherol (ug/g) Walnut chop medium w/o mf
60 0 5 10 15 20 25 30 Incubation time (weeks)
Figure 45. Changes in gamma tocopherol in walnut bars in chocolate without milk fat during storage.
184
Proanthocyanidins in chocolate bars
Proanthocyanidin (PAC) contents in the finished chocolate bars showed no clear connection to nut, treatment, or chocolate formulation (Table 31, Figures 46-47), but in all samples remained constant for the 16-20 weeks, then began increasing. This suggests that PACS are secondary markers of degradation reactions and that the oxidation of monomer anthocyanins to form the PACs was just beginning to be active when the storage experiment ended. If the studies were extended to longer storage periods, greater accumulation PACs might well be observed.
Unlike plain nuts where the PACs increased (albeit small overall total levels) during storage, in the chocolate, when there was change, it was usually loss of the antioxidants followed later by an increase. Proanthocyanidins are effective antioxidants in that they can complex metal as well as act as hydrogen donors. During oxidation they can change structurally this is demonstrated during changes seen in the browning of cocoa and tea leaves for instance. Polymerization occurs in which additional polyphenols such as epitcatechin can attached and extend the chain. PACs can have degrees of polymerization of 50 or greater, they are at times difficult to study due to this complexity and the literature is often contradictory (Bravo1998). Overall the levels of procyanidins seen in this study is quite low in comparison to other nut varieties and food products (i.e. cocoa 12-18 % dry basis and cashews 33.7% fresh basis) and therefore changes in the levels may in fact not be very significant, but overall oxidative polymerization is known to occur in a variety of foods systems and this phenomenon is likely playing a role also especially later in the study where oxidation is occurring at a more rapid rate and an increase in PACs levels is seen.
185
Table 31. Procyanidin levels in nut inclusions from finished chocolate bars.
Procyanidins (mg/g oil) Weeks of incubation
Almond 4 Stdev 8 Stdev 12 Stdev 16 Stdev 20 Stdev 24 Stdev 30 whole low w/MF 1.22 <.05 1.4 <.05 0.82 <.05 1.18 <.05 0.67 <.05 1.49 <.05 2.11 whole low w/o MF 1.2 <.05 1.7 <.05 1.01 <.05 0.89 <.05 1.48 <.05 1.55 <.05 1.74 whole med w/MF 1.14 <.05 1.81 <.05 0.69 <.05 0.67 <.05 1.22 <.05 1.55 <.05 2.39 whole med w/o MF 1.84 <.05 1.56 <.05 1.11 <.05 0.73 <.05 1.53 <.05 1.89 <.05 1.91 Walnut whole low w/MF 1.05 <.05 1.46 <.05 1.16 <.05 1.22 <.05 1.49 <.05 1.77 <.05 2.39 whole low w/o MF 1.32 <.05 1.41 <.05 1.18 <.05 1.14 <.05 1.4 <.05 2.15 <.05 2.03 whole med w/MF 0.96 <.05 1.57 <.05 0.99 <.05 1.24 <.05 1.72 <.05 1.96 <.05 1.64 whole med w/o MF 0.9 <.05 1.68 <.05 1.37 <.05 0.88 <.05 1.28 <.05 1.94 <.05 2.41 chop low w/MF 1.19 <.05 1.62 <.05 1.57 <.05 1.25 <.05 1.47 <.05 1.52 <.05 2.27
186
chop low w/o MF 1.44 <.05 1.5 <.05 1.23 <.05 1.14 <.05 2.91 <.05 1.88 <.05 1.85 chop med w/MF 1.39 <.05 1.97 <.05 1.12 <.05 1.02 <.05 2 <.05 2.29 <.05 2.64 chop med w/o MF 1.36 <.05 2.39 <.05 1.01 <.05 1.09 <.05 1.76 <.05 1.94 <.05 2.06
187
3
2.5 Procyanidins: Chocolate Bars with Roasted Almonds
2
1.5
(mg/g oil) (mg/g Almond whole low w/MF 1 Almond whole low w/o MF Almond whole med w/MF 0.5 Almond whole med w/o MF
0 0 5 10 15 20 25 30 35 Incubation Time (weeks)
3 Procyanidins: Chocolate Bars with Roasted Whole Walnuts
2.5
2
1.5 Walnut whole low w/MF oil) (mg/g 1 Walnut whole low w/o MF Walnut whole med w/MF 0.5 Walnut whole med w/o MF
0 0 5 10 15 20 25 30 35 Incubation time (weeks)
Figure 46. Changes of procyanidin content of chocolate bars with roasted almond (top) and walnut (bottom) inclusions during a 30 day shelf life study at room temperature.
188
Procyanidins: Chocolate Bars with Roasted Chopped Walnuts
3.5
3
2.5 Walnut chop low w/MF 2 Walnut chop low w/o MF Walnut chop med w/MF 1.5
oil) (mg/g Walnut chop med w/o MF 1
0.5
0 0 5 10 15 20 25 30 35
Incubation time (weeks)
Figure 47. Procyanidin levels in chopped walnut bars. Overall the procyanidin levels are low and changes therefore are minimal.
3. Fat Migration from Nuts to Chocolate
GC-FAME analysis was performed to determine the migration of oils from nuts into the chocolate test bars by changes from initial fatty acid profiles. Quantitating the types and actual amounts of oil migrating is critical for understanding fat compatibility and interpreting results of other analyses, particularly DSC and texture profile analyses.
The three fatty acids of cocoa butter are palmitic, stearic, and oleic. Almonds and walnuts both contain high levels of linoleic acid as well as traces of long chain fatty acids. Appearance of any of these in the cocoa butter will indicate oil migration. Nuts are also high in oleic acid, but tracking the migration of this fatty acid which is also in cocoa
189 butter will be more problematic. For simplicity, only 18:1. 18:2, and 18:3 contents are reported in Table 32. For additional clarity, two additional „marker‟ fatty acids present in very low quantities in nuts but not in cocoa butter, C20:1 and C24:0, are included in
Table 32. Results were quantified, using C13 (tridecane) as an internal standard. C13 is a good internal standard because it is not found in the samples, due to its odd number of carbons, and it will behave similarly to the analytes of interest, i.e. it is esterfied. The response of the detector to each of the FAMES including the internal standard is the same. The amount of each ester in the fat can be determined if compared to the integrated areas with the known concentration of the standard. The concentrations of FAMEs responsible for the standard peaks are known, therefore the comparison allows for the calculation of a concentration from the sample peak area. This allows the investigator to address the response factor, or any differences with injection volume, residence time on the column etc.
Over the 30 week storage period, chocolate with walnuts showed a steady loss of oleic acid and gain of linoleic and linolenic acids (Table 32). Almonds lost oleic acid and gained linoleic, but the changes were relatively small. Interestingly, in contrast to walnuts, linolenic acid was lost when almonds were in the chocolate.
These results are consistent with an equilibration process in which excess fatty acids from each phase (cocoa butter and nuts) flow to the other to equalize concen- trations. Walnuts have higher 18:2 and 18:3, hence the flow to chocolate. Chocolate has very little 18:3 but more than almonds hence 18:3 flows from chocolate to almonds (see
FAME results for chocolate, Tables 11 and 12).
190
Table 32. Changes of key fatty acids in chocolate as markers of fat migration between cocoa butter and nuts. (% total fatty acids)
Walnut Whole week week week week week week week Change Low w/o AMF initial Stdev 4 Stdev 8 Stdev 12 Stdev 16 Stdev 20 Stdev 24 Stdev 30 Stdev (%)
C18:1 35.78 0.10 31.15 0.05 29.22 0.25 29.51 0.19 30.44 0.09 27.77 0.00 28.10 0.07 27.84 0.03 -7.94 C18:2 3.52 0.00 3.13 0.01 7.62 0.08 8.01 0.04 8.50 0.12 8.21 0.00 9.04 0.02 8.82 0.00 5.30 C18:3 0.26 0.00 0.20 0.00 1.34 0.01 1.41 0.01 1.51 0.01 1.49 0.00 1.70 0.00 1.62 0.00 1.36 C20:1 0.00 0.00 0.04 0.00 0.00 0.00 0.00 0.04 0.04 0.04 0.94 0.00 0.97 0.00 0.00 0.01 0.00 C24:0 0.00 0.00 0.28 0.00 0.00 0.00 0.00 0.00 0.16 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.10
Walnut Whole week week week week Week week week Change Low w/ AMF initial Stdev 4 Stdev 8 Stdev 12 Stdev 16 Stdev 20 Stdev 24 Stdev 30 Stdev (%) C18:1 34.92 0.05 29.54 0.11 28.70 0.03 28.49 0.18 29.83 0.07 27.30 0.05 27.05 0.09 27.64 0.08 -7.28 C18:2 3.40 0.22 4.26 0.04 8.35 0.02 8.45 0.06 8.84 0.02 8.66 0.01 9.18 0.04 9.06 0.03 5.66 C18:3 0.30 0.00 0.56 0.01 1.56 0.02 1.50 0.02 1.69 0.05 1.63 0.01 1.77 0.01 1.70 0.01 1.40 C20:1 0.00 0.02 0.05 0.00 0.05 0.00 0.00 0.01 0.87 0.01 0.89 0.00 0.92 0.01 0.06 0.00 0.06 C24:0 0.00 0.01 0.33 0.00 0.00 0.00 0.00 0.00 0.13 0.03 0.00 0.00 0.00 0.00 0.10 0.00 0.10
Walnut Whole Medium w/o week week week week Week week week Change AMF initial Stdev 4 Stdev 8 Stdev 12 Stdev 16 Stdev 20 Stdev 24 Stdev 30 Stdev (%) C18:1 35.78 0.13 30.06 0.05 28.87 0.70 28.95 0.01 29.94 0.01 27.82 0.00 28.10 0.01 28.09 0.04 -7.69 C18:2 3.52 0.11 4.69 0.01 7.77 0.18 8.65 0.12 9.06 0.03 8.16 0.00 9.15 0.01 8.92 0.00 5.40 C18:3 0.26 0.00 0.61 0.06 1.37 0.04 1.53 0.02 1.67 0.00 1.48 0.00 1.69 0.00 1.63 0.00 1.37 C20:1 0.00 0.00 0.04 0.00 0.00 0.02 0.00 0.02 0.85 0.03 0.93 0.00 0.98 0.00 0.06 0.01 0.06 C24:0 0.00 0.00 0.24 0.00 0.00 0.00 0.00 0.00 0.22 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Walnut Whole week week week week Week week week Change Medium w/AMF initial Stdev 4 Stdev 8 Stdev 12 Stdev 16 Stdev 20 Stdev 24 Stdev 30 Stdev (%) C18:1 34.92 0.22 29.42 0.01 28.99 0.13 29.01 0.18 29.08 0.07 27.15 0.03 26.81 0.01 27.39 0.04 -7.53
191
C18:2 3.40 0.26 4.62 0.03 7.98 0.07 8.70 0.04 9.70 0.12 9.13 0.02 9.25 0.01 9.23 0.00 5.83 C18:3 0.30 0.03 0.63 0.00 1.49 0.02 1.62 0.00 1.82 0.01 1.74 0.01 1.78 0.00 1.74 0.00 1.44 C20:1 0.00 0.00 0.04 0.00 0.00 0.00 0.00 0.01 0.81 0.02 0.88 0.00 0.92 0.00 0.82 0.00 0.82 C24:0 0.00 0.00 0.25 0.00 0.00 0.00 0.00 0.00 0.11 0.01 0.00 0.00 0.00 0.00 0.11 0.07 0.11
Walnut Chop week week week week Week week week Change Low w/o MF initial Stdev 4 Stdev 8 Stdev 12 Stdev 16 Stdev 20 Stdev 24 Stdev 30 Stdev (%) C18:1 35.78 0.18 30.29 0.15 30.06 0.13 29.67 0.26 30.58 0.08 28.43 0.01 28.54 0.00 27.94 0.84 -7.84 C18:2 3.52 0.15 4.24 0.04 6.51 0.02 6.41 0.05 7.26 0.00 6.39 0.00 7.25 0.00 7.56 0.01 4.04 C18:3 0.26 0.00 0.50 0.01 1.02 0.00 1.00 0.00 1.18 0.00 1.03 0.00 1.23 0.00 1.31 0.04 1.05 C20:1 0.00 0.01 0.04 0.00 0.00 0.01 0.00 0.04 0.89 0.00 0.96 0.00 1.01 0.00 0.85 0.00 0.85 C24:0 0.00 0.00 0.23 0.00 0.00 0.00 0.00 0.00 0.14 0.00 0.00 0.00 0.00 0.00 0.06 0.00 0.06
Walnut Chop week week week week Week week week Change Low w/ MF initial Stdev 4 Stdev 8 Stdev 12 Stdev 16 Stdev 20 Stdev 24 Stdev 30 Stdev (%) C18:1 34.92 0.11 29.54 0.20 29.51 0.06 28.94 0.16 30.11 0.05 28.42 0.00 28.42 0.01 27.43 0.11 -7.49 C18:2 3.40 0.27 4.26 0.01 6.36 0.03 6.80 0.05 7.07 0.01 7.15 0.00 7.15 0.03 7.57 0.03 4.17 C18:3 0.30 0.01 0.56 0.01 1.12 0.01 1.19 0.02 1.19 0.05 1.25 0.01 1.25 0.00 1.34 0.00 1.04 C20:1 0.00 0.03 0.05 0.02 0.00 0.00 0.00 0.01 0.89 0.03 0.94 0.01 0.94 0.01 0.84 0.00 0.84 C24:0 0.00 0.01 0.33 0.00 0.00 0.00 0.00 0.00 0.12 0.00 0.08 0.00 0.08 0.00 0.00 0.00 0.00
Walnut Chop Medium w/o week week week week Week week week Change MF initial Stdev 4 Stdev 8 Stdev 12 Stdev 16 Stdev 20 Stdev 24 Stdev 30 Stdev (%) C18:1 35.78 0.21 30.20 0.20 29.97 0.07 29.66 0.03 30.85 0.05 28.20 0.01 28.93 0.01 28.41 0.06 -7.37 C18:2 3.52 0.10 4.36 0.05 6.29 0.01 7.44 0.02 7.54 0.00 6.57 0.01 7.13 0.00 7.72 0.01 4.20 C18:3 0.26 0.00 0.54 0.01 1.00 0.00 1.22 0.00 1.26 0.00 1.09 0.00 1.19 0.00 1.32 0.01 1.06 C20:1 0.00 0.01 0.04 0.00 0.05 0.00 0.00 0.04 0.91 0.02 0.96 0.00 1.03 0.00 0.88 0.00 0.88 C24:0 0.00 0.00 0.61 0.00 0.07 0.00 0.00 0.00 0.14 0.00 0.00 0.00 0.00 0.00 0.06 0.00 0.06
192
Walnut Chop week week week week Week week week Change Medium w/ MF initial Stdev 4 Stdev 8 Stdev 12 Stdev 16 Stdev 20 Stdev 24 Stdev 30 Stdev (%) C18:1 34.92 0.18 29.47 0.12 29.36 0.50 29.10 0.43 29.08 0.03 27.56 0.01 32.06 0.05 27.79 0.04 -7.13 C18:2 3.40 0.19 4.29 0.00 6.91 0.13 7.11 0.11 9.70 0.01 7.17 0.01 3.92 0.00 8.55 0.01 5.15 C18:3 0.30 0.00 0.56 0.04 1.22 0.03 1.24 0.01 1.82 0.01 1.24 0.00 0.17 0.00 1.57 0.00 1.27 C20:1 0.00 0.02 0.05 0.02 0.00 0.02 0.00 0.05 0.81 0.02 0.91 0.00 1.05 0.00 0.84 0.00 0.84 C24:0 0.00 0.01 0.39 0.01 0.00 0.00 0.00 0.00 0.11 0.00 0.00 0.00 0.00 0.00 0.06 0.00 0.06
Almond Whole Medium w/o week week week week week week week Change MF initial Stdev 4 Stdev 8 Stdev 12 Stdev 16 Stdev 20 Stdev 24 Stdev 30 Stdev (%) C18:1 35.78 0.20 30.93 0.15 32.29 0.24 32.41 0.21 33.80 0.08 31.26 0.00 28.32 0.01 32.28 0.01 -3.50 C18:2 3.52 0.14 3.25 0.06 3.85 0.03 3.97 0.02 4.12 0.01 3.76 0.00 7.70 0.00 4.22 0.00 0.70 C18:3 0.26 0.00 0.20 0.04 0.18 0.00 0.17 0.00 0.18 0.00 0.18 0.00 1.35 0.00 0.18 0.00 -0.08 C20:1 0.00 0.00 0.04 0.00 0.00 0.02 0.00 0.06 0.04 0.02 0.98 0.00 0.98 0.00 0.90 0.00 0.90 C24:0 0.00 0.00 0.56 0.00 0.00 0.00 0.00 0.00 0.16 0.00 0.00 0.00 0.00 0.00 0.07 0.01 0.07
Almond Whole week week week week Week week week Change Medium w/ MF initial Stdev 4 Stdev 8 Stdev 12 Stdev 16 Stdev 20 Stdev 24 Stdev 30 Stdev (%) C18:1 34.92 0.57 30.14 0.42 32.21 0.02 32.48 0.05 33.03 0.10 30.99 0.00 31.06 0.01 31.25 0.03 -3.67 C18:2 3.40 0.52 3.80 0.05 3.92 0.04 4.03 0.02 4.23 0.03 3.90 0.01 3.97 0.00 4.07 0.00 0.67 C18:3 0.30 0.00 0.28 0.00 0.28 0.04 0.26 0.00 0.22 0.00 0.22 0.00 0.21 0.00 0.23 0.00 -0.07 C20:1 0.00 0.02 0.05 0.00 0.00 0.00 0.00 0.00 0.00 0.02 0.93 0.00 0.97 0.00 0.86 0.00 0.86 C24:0 0.00 0.00 0.51 0.01 0.00 0.00 0.00 0.00 0.13 0.00 0.00 0.00 0.00 0.00 0.06 0.00 0.06
Almond Whole week week week week Week week week Change Low w/MF initial Stdev 4 Stdev 8 Stdev 12 Stdev 16 Stdev 20 Stdev 24 Stdev 30 Stdev (%) C18:1 34.92 0.23 30.42 0.24 31.98 0.47 31.76 0.05 32.65 0.07 30.90 0.03 30.97 0.22 31.07 0.02 -3.85 C18:2 3.40 0.22 3.29 0.02 3.81 0.06 3.88 0.03 4.26 0.04 3.87 0.00 3.86 0.03 3.87 0.00 0.47 C18:3 0.30 0.00 0.25 0.02 0.27 0.03 0.24 0.04 0.21 0.01 0.22 0.00 0.22 0.00 0.22 0.00 -0.08
193
C20:1 0.00 0.02 0.04 0.00 0.00 0.02 0.00 0.05 0.76 0.01 0.93 0.00 0.99 0.01 0.87 0.00 0.87 C24:0 0.00 0.01 0.35 0.04 0.00 0.00 0.00 0.00 0.08 0.00 0.00 0.00 0.00 0.00 0.38 0.00 0.38
Almond Whole week week week week Week week week Change Low w/o MF initial Stdev 4 Stdev 8 Stdev 12 Stdev 16 Stdev 20 Stdev 24 Stdev 30 Stdev (%) C18:1 35.78 0.09 30.13 0.46 31.62 0.25 32.41 0.21 32.99 0.36 31.26 0.00 28.32 0.15 30.75 0.18 -5.03 C18:2 3.52 0.10 4.62 0.04 3.62 0.03 3.93 0.02 4.42 0.46 3.76 0.00 7.70 0.04 3.78 0.01 0.26 C18:3 0.26 0.00 0.60 0.01 0.19 0.00 0.17 0.00 0.18 0.00 0.18 0.00 1.35 0.01 0.18 0.02 -0.08 C20:1 0.00 0.00 0.04 0.00 0.04 0.02 0.00 0.06 0.00 0.03 0.98 0.00 0.98 0.01 0.90 0.31 0.90 C24:0 0.00 0.00 0.29 0.04 0.07 0.00 0.00 0.00 0.08 0.00 0.00 0.00 0.00 0.00 0.03 0.00 0.03
194
Texture Analysis for Softening Due to Fat Migration
Texture hardness analyses were conducted on eight replicate bars from each treatment. It was expected that the chocolate bars would soften over time as nut oils migrated into the chocolate. Instead, except for whole walnuts medium roast, hardness values of the chocolate bars increased with storage time up to 12 weeks, then progressively decreased (Figure 48, Table 33).
The initial hardening can be explained by fatty acid migration, but not as envisioned. During the first half of the incubation period, mono-unsaturated oleic acid- rich TAGs migrate out of the chocolate (to the nuts) faster and to a greater extent than polyunsaturated linoleic and linolenic acid-rich TAGS migrate in. TAGs with saturated palmitic and stearic fatty acids become dominant in the chocolate, raising the melting point and the hardness. However, when sufficient polyunsaturated TAGs migrate from the nuts, the net melting point drops and the chocolate begins to soften. This occurred between 24 and 30 weeks in the current study, indicating that the migration equilibrium is a slow process.
The DSC data also is consistent with the early hardening of dark chocolate, showing a shift from two polymorphs into one, more stable form with higher melting point which would increase hardness.
It was expected that bars containing milk fat would be softer then their counterparts without milk fat. This in fact was observed, as all chocolate variations with milk fat had lower average hardness values. Hardening increased then decreased in almonds, as in dark chocolate. However, with milk fat added, the progression of hardening generally increased throughout the incubation period. Table 31 shows that dark
195 chocolate with milk fat had slightly higher levels of linoleic and linolenic acids, which would account for the generalized softening. However, fatty acid migration patterns over
30 weeks were comparable for chocolate with and without milk fat, so this different behavior must arise from different factors. One possibility is that fat incompatibility develops when TAGS from all three fats intermix. To investigate this explanation, differential scanning calorimetry and x-ray diffraction analyses were conducted on the chocolate samples.
Complications to texture analyses can arise from nuts interfering with the testing protocol in which the probe hits a nut and the force to break the bar therefore seems higher. Standard deviations for each were calculated, and based on this data points were eliminated if they are determined to be extreme outliers i.e. 2 standard deviations from the mean. There were very few instances that fell into the extreme outlier category and were the result of the probe hitting a nut, in this case another sample was run as a replacement.
196
Table 33. Texture Analysis hardness values for chocolate bars after storage for 0, 4, 8, 12 and 16 weeks at room temperature
(average of eight analyses).
Weeks storage 0 4 8 12 16 Sample ID Kg Force SD Kg Force SD Kg Force SD Kg Force SD Kg Force SD
Dark chocolate 0 4 8 12 16 Almond Whole Low 7.32 1.36 7.38 1.33 8.15 1.48 9.62 1.86 10.34 2.50 Almond Whole Medium 8.36 1.89 8.44 2.15 8.22 1.83 9.96 1.47 9.55 0.80 Walnut Chop Low 7.72 1.49 7.30 1.27 7.23 1.11 8.14 1.81 9.15 1.75 Walnut Whole Low 7.39 1.24 7.34 1.19 8.33 1.61 8.19 1.83 8.75 0.94 Walnut Chop Medium 7.10 1.73 7.20 1.77 8.62 1.44 10.21 1.84 8.75 1.40 Walnut Whole Medium 8.98 1.51 8.67 1.77 7.66 1.11 10.26 1.86 8.86 1.32
Dark chocolate + milkfat Almond Whole Low 6.99 1.01 6.97 0.97 8.31 1.76 9.09 1.08 8.59 1.83 Almond Whole Medium 6.99 0.79 7.18 0.94 7.48 1.22 8.07 1.88 8.19 1.49 Walnut Whole Low 6.00 1.40 6.07 1.44 6.91 1.27 7.18 0.82 9.12 1.04 Walnut Chop Low 7.30 1.16 7.29 1.12 6.63 1.17 8.58 1.77 8.62 1.52 Walnut Whole Medium 5.67 0.74 5.38 1.08 6.42 1.05 6.06 1.91 7.00 1.11 Walnut Chop Medium 5.62 0.92 5.91 1.09 8.04 1.30 7.30 1.44 7.26 2.24
197
Table 33. Texture Analysis hardness values for chocolate bars after storage for 20, 24 and 30 weeks at room temperature
(average of eight analyses).
Weeks storage 20 24 30 Sample ID Kg Force SD Kg Force SD Kg Force SD
Dark chocolate Almond Whole Low 8.20 1.29 8.71 1.80 8.32 1.94 Almond Whole Medium 8.68 1.48 9.03 2.07 8.43 1.34 Walnut Chop Low 8.03 2.38 7.83 0.49 7.57 1.68 Walnut Whole Low 7.38 1.69 9.11 2.32 7.13 1.87 Walnut Chop Medium 8.63 2.51 9.48 1.78 8.59 1.86 Walnut Whole Medium 7.73 1.71 7.60 1.65 7.26 1.97
Dark chocolate + milkfat Almond Whole Low 9.16 2.12 9.47 2.12 8.22 1.16 Almond Whole Medium 7.17 1.60 7.92 1.50 6.81 1.74 Walnut Whole Low 6.95 1.49 8.26 1.51 7.01 1.51 Walnut Chop Low 7.54 1.50 9.32 1.13 7.68 2.02 Walnut Whole Medium 6.12 1.12 6.44 1.21 6.69 1.35 Walnut Chop Medium 5.97 0.85 7.64 1.12 6.41 1.48
198
12 Hardness – dark chocolate
10 0 4
8
8
6 12 force g force g 16
4 20
2 24 30 0 Almond Almond Walnut Walnut Walnut Walnut Whole Whole Chop Whole Chop Whole Low Medium Low Low Medium Medium
0 10 Hardness -- Chocolate + milkfat 4 8 8 12 16 6 20 24 4 g force g 30 2
0 Almond Almond Walnut Walnut Walnut Walnut Whole Whole Whole Chop Whole Chop Low Medium Low Low Medium Medium
Figure 48. Hardness values in texture analysis of chocolate bars stored for up to
30 weeks at room temperature.
199
Fat compatibility
DSC is a tool used to gain insight into the melting and crystallization profiles of various fat systems. It is used as a directional tool to identify polymorphic transitions through changes of melting point over time, e.g. increase in melting point indicates a transition to a more stable polymorph. Insight into fat compatibility can be gained by tracking changes in melting points with formulation, as was seen with the addition of milk fat to chocolate (Figure 52), or during storage, as was seen in the shelf life study.
The percent of solid material (ΔHc ) can be used in conjunction with texture analysis to determine if transitions are occurring or if fat incompatibility or changes in structural packing of TAGs is potentially responsible for changes in hardness.
DSC evidence for multiple melting point fractions in chocolate formulations.
Melt peak areas in DSC curves were calculated to gain insight into melting profiles of the nut bars with inclusions. Typical DSC curves for cocoa butter, chocolate, milk fat, chocolate plus milk fat, and chocolate bars (without/with AMF) with nuts are shown in
Figures 49-54, respectively.
Key features in the curves and the information they give are:
a) Peak temperature (melting and crystallization): temperature at which the largest
portion of the lipid is either melted or crystallized
c) Onset temperature (melting or crystallization): temperature at which the fat
beings to melt or crystallize
c) Peak area : is proportional to the amount of melted or crystalline material, often
used as an indication of hardness at a specific temperature. Adapted from
Marangoni, 2005)
200
The breadth of the curve reflects the melting point range and is also influenced by the polymorphic structures present. When dealing with pure compounds say cocoa butter alone, the peak melting point is used to determine the polymorphic form. An investigator can consult the literature for the melting point ranges for cocoa butter for each polymorph in order to identify the form, these ranges have been confirmed with XRD. In the case of mixed fat systems such as cocoa butter and nut oil the situation is more complicated. The peak melting temperature is instead monitored and changes in the temperature are used to indicate a change in polymorph which can then be confirmed through DSC. Some binary fat systems have been categorized and therefore XRD can be used to identify polymorphs, but in a complex system such as this DSC is being used to look for shifts in polymorphism, which can then be confirmed with XRD (Marangoni, 2005).
201
6.0
Peak = 21.95 C
4.5 5.0 5.5 5.5 5.0 4.5
w Endo w (mW) Up
3.5 4.0 4.0 3.5
Area=375.8 mJ
3.0 3.0
H=91.86 Jg
Heat flo Heat
2.5 2.5
Onset = 15.34 C
1.5 2.0 2.0 1.5
0 10 20 30 40 50 Temperature (C)
Figure 49. Typical DSC curve of untempered cocoa butter. A single peak with a low melting point (21.55 °C) is typical for untempered samples where crystal forms have not been set. Specific melting points vary with the cocoa butter depending on the polymorphic forms present.
202
Peak = 23.86C
Area=380.8 mJ H=42.7Jg Onset =
15.61 C
flow Endo flow (mW) Up
Heat
5.834 0 10 20 30 40 50 Temperature (C)
Figure 50. Typical DSC curve of untempered dark chocolate without milk fat.
There is one narrow melting peak with melting point 23.86 C, which is dependent on polymorphic forms present. Melting points of tempered samples are higher, reflecting tighter packing.
Heat flow Endo flow (mW) Up Heat
203
Peak = 15.10C
Area=19 Onset 9.7 mJ Peak = 33.51C = 5.5C H=36.0 Jg Area=50.9 mJ H=9.4Jg
Heat flow Endo flow (mW) Up Heat
5.834 0 10 20 30 40 50
Temperature (C)
Figure 51. Typical DSC curve of AMF. The two distinct melting curves for AMF
indicate the presence of low and high melting fractions as expected from milk fat fatty
acid composition. Since milk fat is a natural product, the specific melting points and
distribution between fractions shows seasonal variation.
204
Peak = 20.81C
Area=338.6 mJ H=38.84Jg
Onset=
15.3C
Heat flow Endo flow (mW) Up Heat
5.834 0 10 20 30 40 50 Temperature (C)
Figure 52. Typical DSC curve of chocolate with milk fat. The melting point is lower than dark chocolate due to disruption of cocoa butter TAG packing by milk fat TAGs.
205
Peak = 31.91C
Peak = 26.42 C Area= 24.95mJ H=41.74Jg
Area= 15.68mJ
Peak = 29.07C
Heat flow Endo flow (mW) Up Heat
0 10 20 30 40 50 Temperature (C)
Figure 53. DSC curve of walnut dark chocolate bar with milk fat
206
Figure 54. DSC curve of dark chocolate bar without AMF with walnuts
Peak = 32.03C
Peak = 26.82C Area= 31.87mJ
H=48.95Jg
Area= 15.23mJ
Up (mW) Up H=14.66Jg
Heat flow Endo flow Heat
5.834 0 10 20 30 40 50
Temperature (C)
207
The scan of untempered cocoa butter is shown in Figure 49. Lower melting points are expected in untempered cocoa butter since TAGS are loosely associated and not in one of the more densely packed crystal forms. Cocoa butter has a narrower melting point range than chocolate (Figure 50) because it does not have added substances that interfere with crystallization. Peaks tend to be broader when there is more than one fat or many different TAGs present due to the fact that they each have different melting/crystallization points. Mixed fat systems typically have wider melting points since different lipid species have different melting points for example chocolate with milk fat and nut oil.
The DSC scan of AMF alone (Figure 51) illustrates the fat complexity of milk fat.
Composed of both short chained saturated and long chained unsaturated fatty acids, AMF is often fractionated into low melting, medium melting, and high melting fractions --
LMF, MMF and HMF respectively. At least two distinct melting fractions (mp approximately 15°C and 34°C) are evident in the AMF used in this study (Figure 51).
Milk fat is unique in that it fits into the crystal lattice of cocoa butter without any major disruptions, yet impacts the structure of the lattice enough to slow the structural change from the βV to βVI (Dimick, 1991). Excess milk fat in a chocolate formulation (>20%) dilutes the cocoa butter and impedes formation of proper structure, resulting in a gritty texture (Barna et al.,1992).
DSC scans of chocolate without and with milk fat (Figures 53 and 54, respectively) are also presented untempered to demonstrate the impact of milk fat, i.e. that milk fat reduces the crystallization temperature and slows the polymorphic
208 transitions of chocolate. Interestingly, in chocolate bars with milk fat but no nuts, only one peak was present indicating that the low levels of AMF used were compatible with cocoa butter.
Effect of nuts on DSC curves and mp fractions of chocolate. When nuts were added to chocolate formulations, two peaks from lower and higher melting fractions were present in most chocolate nut bars, indicating lack of nut oil compatibility with chocolate, and these changed during the 30 week storage (see notations in Figures 53 and 54).
In walnut bars without milk fat, the melting point of Peak 1 (lower mp) was 27 C at four weeks, but by eight and twelve weeks, the melting point had dropped to 23 C.
Peak 1 was present in both chocolate formulations, with only slightly greater area with milk fat, so it cannot be attributed solely to short chain fatty acids from milk fat. Rather, the presence of nuts with migrating unsaturated fatty acids in all formulations suggests the possibility that Peak 1 may be a separate crystal form resulting from incorporation or entrainment of TAGs with unsaturated fatty acids. This trend was seen for both almonds and walnut samples.
Over time, the lower melting fraction becomes incorporated into the larger higher melting fraction and the two peaks merge (Figure 55).
209
9.5% of total 2.5% of total
Area Area
Heat flow (mW) Up Endo
Temperature (C) Temperature (C)
Figure 55. Changes in peak areas over time. The area of peak one at week 12 for walnut
whole low with milk fat sample. The second graph shows the same sample at week 16.
The area of peak one has been reduced over time.
Peak 2 was the main chocolate crystal fraction. Over 30 weeks, Peak 2 showed an
initial drop in melting point as Peak 1 became incorporated into it, indicating some
compatibility, (Figure 56 and 57) There is a potential that some of the unsaturated TAGs
from the nuts migrate into the chocolate changing the melting point of peak 2, but leaving
peak 1. However, then the melting point again increases to starting levels likely due to a
change in polymorphism, i.e. the chocolate is becoming more tightly packed and the
liquid fat is being forced out of the cocoa butter matrix. There is an indication that a
second peak appears again at the very end of the study (week 30 see Figure 58). This may
indicate that the cocoa butter matrix can incorporate a certain level or type (e.g.
monounsaturated) of TAGs from nut oil, but too much unsaturation (amount or type)
forces a reassociation of the saturated TAGs of cocoa butter.
210
Milk fat slows this transition somewhat (Figure 58), supporting observations of
Beckett (1999) who found that AMF does not change the polymorphic state of chocolate but slows the transition and alters the temperature at which the crystals form. Samples with milk fat had a slower transition of Peak 1 into Peak 2 initially (week 12), but after that point very little difference could be seen between the samples. Differences between treatments could not be discerned.
Milk fat can help somewhat early on preventing the formation of a tighter packing structure which contributes to formation of cracks and diffusion of oil. The chocolate contracts and assumes denser packing more slowly, so fewer microscopic cracks form in the surface, and therefore it is less likely that liquid fat can migrate to the surface to create bloom. The milk fat aids in prolonging the BV form, but ultimately migration of unsaturated fatty acids reaches a point where two peaks again appear indicating incompatibility. Basically the chocolate matrix starts to become more tightly packed and the unsaturates diffuse and a polymorphic transition occurs.
33.5 DSC Melting Point: Walnut without MF Bars 211
33 Walnut Whole Low Walnut Whole Medium Walnut Chop Low 32.5 Walnut Chop Medium
32 (degrees C) (degrees 31.5
31
30.5 Weeks 4 10 16 22 28
Figure 56. Changes in peak melting temperature for peak 2 (HMF) walnut bars without milk fat
33.5 DSC Melting Point: Walnut with MF Bars 33 Walnut Whole Low Walnut Whole Medium 32.5 Walnut Chop Low Walnut Chop Medium 32
31.5 (degrees C) (degrees
31
30.5
30 4 10 Weeks 16 22 28
Figure 57. Changes in peak melting temperature for peak 2 (HMF) of walnut bars with milk fat
212
Peak 2 increased throughout the storage period in all formulations and at the end of the study there was an increase in melting point and the emergence again of a second small peak. This is an indicator that the chocolate has taken on a more stable form with a higher melting point and has forced out the lower melting point fractions. Since bloom was not evident at the beginning of storage, we speculated that this is the β-V crystal which changes into the β-VI form which would be in line with the bloom seen on bars. Model system studies used XRD to provide a more definitive answer to this question.
In regards to differences among bar types in terms of nut type, chocolate type, roast treatment type and level, it was determined that for nut bars the type of chocolate
(with/without AMF) played a statistically significant (p=0.017) role in DSC changes, as seen in slower incorporation of the lower melting fraction peak into the higher melting fraction peak in bars with milk fat. Surprisingly, nut type and roasting Level (low or medium) had no significant impact on melting point or fraction distribution in DSC peaks. Apparently, almonds and walnuts are both sufficiently different from cocoa butter in fatty acid profile that they have similar impact on crystal compatibility. Excess of either oleic or linoleic acids in TAGS would be unable to align with cocoa butter TAGS, so both oils would be excluded from the cocoa butter matrix.
It must be noted that DSC cannot identify polymorphs directly; instead, XRD is used for a definitive answer. Marangoni (2005) mentions the limitations of DSC, stating that when studying a „real‟ system the „window‟ for phase transitions widens due to complex factors such as the variability in molecular makeup, various melting points and
213 potential for multiple polymorphs in a sample. Hence, XRD is recommended for determination of polymorphs. XRD data is presented in the next section.
214
DSC on Dark Chocolate + Milk Fat 120 100
80
60 Crystal 2 40 Crystal 1 20 Percentage (%) Percentage 0
Week 4 Week 8 Week 12 Week 16 Week 20 Week 24 Week 30
DSC on Dark Chocolate Bars
120 100
80 Crystal 2 60 Crystal 1 40
Percentage (%) Percentage 20
0
Week 4 Week 8 Week 12 Week 16 Week 20 Week 24 Week 30
Figure 58. Changes in proportions of two crystal forms in dark chocolate and dark
chocolate + AMF formulations stored at room temperature for varying periods. Values
shown are averages of all nut variations for each chocolate formulation.
215
Quantification of Bloom
In order to track development of bloom over time, a set of duplicate bars were stored at 20°C and every 4 weeks tested for the appearance of bloom. The colorimeter was used to track the L value or development of lightness (white) on the dark chocolate surface. This method has detection limitations, as noted previously, but it is simple and uses instrumentation likely to be found in most laboratories.
It was expected that L values would increase with the development of bloom.
Instead, L values dropped. For almonds whole without milk fat, L values dropped nearly
15 points during the first week of incubation, then very slightly each week thereafter. L values of whole almonds plus milk fat decreased slightly but steadily over the 30 weeks, although the L values remained close to 25 (Figure 59A, Table 34). Walnuts showed similar small decreases in L values over time, with the L values again staying near 25
(Figure 59B, Table 34). These results indicate that the colorimeter is registering something different than the developing white spots in the chocolate despite bloom visible to the human eye (see Taste Panel results below). Apparently, samples must be extremely bloomed, i.e. completely covered in a white haze, for a difference in color to be detected. Samples that were completely bloomed i.e. completely white were detected to be bloomed using the colorimeter, but in the case with most chocolate that has regions of bloom the colorimeter did not prove to be a useful tool, perhaps the sensitivity is not high enough for these instances.
In attempt to gain additional sensitivity and provide a more accurate indicator of color changes, a whiteness index was calculated from changes in L, a, and b values as according to the equation:
216
From Bricknell et al. (1998): Whiteness Index (WI) = 100 – [(100-L)2 + a2 + b2]0.5
As with L values, whiteness values for the various chocolate treatments decreased continually during incubation, but dropped only two points (Table 35).
Thus, neither L value nor whiteness index were able to detect subtle development of bloom during storage. In fact, the most sensitive discrimination for determining onset of bloom turned out to be the naked eye. As will be discussed in more detail in the sensory evaluation section below, visual scoring of absence/presence of bloom was more sensitive than the colorimeter.
217
40
35
30
25 4 8 20 12 20 15 24 30 10
5
0 Almond Whole Almond whole Almond whole Almond whole low w / low w /o med w / med w /o
35
30
25
20 4 8 15 12 20 10 24 30
5
0 Walnut Walnut Walnut Walnut Walnut Walnut Walnut Walnut Chop lowChop Lowchop MedChop MedWhole Whole low w hole w hole w w /o w w /o Low w w /o med w / med w /o
Figure 59 A and B. Colorimeter L* values for dark chocolate bars with almonds (top) and with walnuts (bottom).
218
Table 34: Colorimeter Quantification of Bloom L* Values (6 samples per variable)
Week Week Week Week Week Week 4 STD 8 STD 12 STD 20 STD 24 STD 30 STD Almond Whole Low w/ MF 26.48 1.78 26.58 0.21 25.49 0.43 25.20 1.85 25.00 0.65 24.70 0.18 Almond Whole Low w/o MF 26.19 0.62 26.37 0.35 26.25 0.48 24.50 1.01 24.50 0.19 24.10 0.39 Almond Whole Medium w/ MF 26.37 0.05 26.74 0.03 26.38 0.04 26.30 1.47 24.50 0.45 24.80 2.22 Almond Whole Medium w/o MF 25.65 0.35 26.16 0.03 25.37 0.14 26.20 1.66 24.50 0.74 24.60 0.53 Walnut Chop Low w/ MF 26.80 0.57 26.63 0.23 25.60 0.57 25.70 0.77 24.80 0.30 25.00 0.42 Walnut Chop Low w/o MF 26.08 0.17 26.21 0.20 25.41 0.36 24.50 0.89 24.30 0.44 24.50 0.21 Walnut Chop Medium w/ MF 26.39 0.01 27.15 0.48 26.17 0.38 25.30 0.34 24.80 0.34 24.70 1.04 Walnut Chop Medium w/o MF 25.39 0.10 26.06 0.04 24.38 0.06 24.00 1.07 25.40 2.15 24.40 0.25 Walnut Whole Low w/ MF 26.18 0.66 26.95 0.06 25.85 0.18 25.20 0.50 24.80 0.58 25.30 2.56 Walnut Whole Low w/o MF 25.52 0.29 26.11 0.04 24.74 0.21 25.00 0.74 25.20 2.62 24.30 0.44 Walnut Whole Medium w/ MF 25.77 0.33 27.01 0.33 25.32 0.57 26.10 2.07 24.90 0.97 25.70 1.64 Walnut Whole Medium w/o MF 25.49 0.74 26.12 0.03 24.79 0.04 25.50 1.87 24.50 0.74 24.90 1.01
219
Table 35. Whiteness values
Week 4 Week 8 Week 12 Week 20 Week 24 Week 30 Almond Whole Low w/ MF 26.14 26.25 25.21 24.95 24.76 24.45 Almond Whole Low w/o MF 25.88 26.07 25.94 24.25 24.25 23.84 Almond Whole Medium w/ MF 26.03 26.41 26.12 26.05 24.24 24.55 Almond Whole Medium w/o MF 25.31 25.84 25.11 25.95 24.25 24.33 Walnut Chop Low w/ MF 26.45 26.27 25.29 25.43 24.52 24.73 Walnut Chop Low w/o MF 25.78 25.92 25.34 24.26 24.06 24.27 Walnut Chop Medium w/ MF 26.02 26.83 25.93 25.03 24.53 24.43 Walnut Chop Medium w/o MF 25.05 25.77 24.15 23.76 25.17 24.15 Walnut Whole Low w/ MF 25.80 26.63 25.65 24.95 24.53 25.04 Walnut Whole Low w/o MF 25.19 25.83 24.46 24.77 24.95 24.03 Walnut Whole Medium w/ MF 25.36 26.65 24.99 25.84 24.61 25.41 Walnut Whole Medium w/o MF 25.15 25.82 24.53 25.27 24.23 24.61
220
Accelerated Chamber Study
In order to gain some insight early on in the study around stability a set of chocolate bars were placed in a cycling chamber that reaches 31°C for 8 hours then 21°C for 8 hours and returns to 31°C for 8 hours to complete one 24 hour cycle. No bloom was seen on any bars until cycle 10 when, surprisingly, the almond whole low roast and the almond whole medium without milk fat demonstrated bloom to the visible eye; this became more extensive on cycle 11. Walnut chop low without milk fat demonstrated bloom on cycle 12 and extensively on cycle 13. On cycle 14 walnut chop medium without milk fat demonstrated bloom and the study was discontinued. Also, this experiment was based solely on visible appearance of bloom, which is a subjective analysis. These bars were not analyzed with the colorimeter instead they served as a benchmark for the study in order to determine how visible bloom would be to the eye and also if any relationships between a nut and chocolate type could be determined. It is difficult to determine early onset of bloom just visually and therefore a more quantitative approach was instead followed for the main study. This data is supplemented with colorimetric analyses to more accurately quantify the appearance of bloom over time, these samples instead were aged in ambient conditions over a thirty week period.
221
Sensory Results
Both the nuts themselves and the bars with inclusions were evaluated by raw material sensory experts and the investigator at each time pull. Overall, the almonds are much more stable than the walnuts in both nut alone and bar samples.
Key characteristics detected by the panelists, as detailed in Table 36, were:
softer chocolate texture with milk fat present
onset of rancid flavors in two walnut samples by 4 weeks (whole low in dark
chocolate and chopped medium with AMF)
little texture change until week 8, then dark chocolate softens and with milk fat
hardens
detected first bloom in dark chocolate base, all walnut variations, at eight weeks;
parallel bases with milk fat showed no visible bloom at that time
whole walnuts oxidize faster in dark chocolate; chopped walnuts less stable when
milk fat is present
by 12 weeks, notable off-flavors were evident in nearly all products with walnuts,
by 16 weeks, all but one were unacceptable. By week 20 all walnut samples were
rancid.
appearance of sensory flavor problems paralleled development of peroxides and
especially aldehydes detected chemically
at 16 weeks almond products were all still acceptable, but showing some bloom
almond samples remained acceptable regarding bloom throughout the entire study
failure mode was rancidity; bloom and texture modifications from oil migration
were minimal.
222
Table 36a. Sensory ratings of chocolate bars with nuts after 0, 4, 8,12, 16, 20, and 30 weeks of storage at room temperature. Nut Sensory (Scale 0-15) Sample Rancidity/Off Note Snap Bloom/Appearance Comments
Week 0 (Initial reading) Dark chocolate base Almond Whole Low 0 3 0 Chocolate is bitter, flavor of nuts the same both chocolates Almond Whole Medium 0 3 0 Initial roast comes thru more upon chewing Walnut Whole Low 0 3 0 Walnut comes thru more than almond Walnut Whole Medium 0 3 0 Higher roast flavor blends w/ chocolate and actually get less flavor Walnut Chop Low 0 3 0 Vegetable oil taste, borderline cardboard Walnut Chop Medium 0 3 0 Chocolate overpowers nut flavor
Dark chocolate + milkfat Almond Whole low 0 7 0 Less snap Almond Whole Medium 0 7 0 Slightly higher roast comes thru, tooth packing Walnut Whole Low 0 7 0 Walnut comes thru more than almond Walnut Whole Medium 0 7 0 Higher roast flavor blends w chocolate and actual get less flavor Walnut Chop Low 0 7 0 Vegetable oil taste, borderline cardboard Walnut Chop Medium 0 7 0 Chocolate overpowers nut flavor Scale 1-15 increasing in rancidity and bloom, decreasing in snap
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Table 36b. Sensory ratings of chocolate bars with nuts after 0, 4, 8,12,16, 20, and 30 weeks of storage at room temperature.
Nut Sensory (Scale 0-15) Sample Week 4 Rancidity/Off Note Snap Bloom/Appearance Comments Dark chocolate base Almond Whole Low 0 3 0 Almond Whole Medium 0 3 0 Walnut Whole Low 2 3 0 Walnut Whole Medium 0 3 0 Walnut Chop Low 0 2.5 0 Walnut Chop Medium 0 3 0
Dark chocolate + milkfat Almond Whole low 0 7 0 Almond Whole Medium 0 7 0 Walnut Whole Low 0 7 0 Walnut Whole Medium 0 7 0 Walnut Chop Low 0 7 0 Walnut Chop Medium 2 7 0
Scale 1-15 increasing in rancidity and bloom, decreasing in snap
224
Table 36c. Sensory ratings of chocolate bars with nuts after 0, 4, 8,12, 16, 20, and 30 weeks of storage at room temperature.
Nut Sensory (Scale 0-15) Sample Week 8 Rancidity/Off Note Snap Bloom/Appearance Comments Dark chocolate base Almond Whole Low 0 3.5 0 Reduction in almond/roast flavor Almond Whole Medium 0 3 0 Reduction in almond/roast flavor Walnut Whole Low 5 3 3.5 Walnut Whole Medium 3 3 3.5 Bloom on back Walnut Chop Low 0 3 3 Walnut Chop Medium 0 3.5 4.5
Dark chocolate + milkfat Almond Whole low 0 7.5 0 Reduction in almond/roast flavor Almond Whole Medium 0 7 0 Reduction in almond/roast flavor Walnut Whole Low 0 7 0 Walnut Whole Medium 0 3 0 Walnut Chop Low 4 7 0 Walnut Chop Medium 1 6.5 0
Scale 1-15 increasing in rancidity and bloom, decreasing in snap „
225
Table 36d. Sensory ratings of chocolate bars with nuts after 0, 4, 8,12, 16, 20, and 30 weeks of storage at room temperature.
Nut Sensory (Scale 0-15) Sample Week 12 Rancidity/Off Note Snap Bloom/Appearance Comments Dark chocolate base Almond Whole Low 0 3.5 0 Reduction in almond roast flavor Almond Whole Medium 0 3 0 Slight reduction in almond roast flavor Walnut Whole Low 15 3 4 Bloom on test, slight painty Walnut Whole Medium 10 3 13 Extensive bloom Walnut Chop Low 12 3.5 3 Walnut Chop Medium 12 3 2 Very very slight bloom
Dark chocolate + milkfat Almond Whole low w/MF 0 7 0 Reduction in almond roast flavor Almond Whole Medium w/MF 0 7 0 Reduction in almond roast flavor Walnut Whole Low w/MF 5 5 0 Walnut Whole Medium w/MF 10 7 2 Very very slight bloom Walnut Chop Low w/ MF 10 7 0 Walnut Chop Medium w/ MF 15 7 0
Scale 1-15 increasing in rancidity and bloom, decreasing in snap
226
Table 36e. Sensory ratings of chocolate bars with nuts after 0, 4, 8, 12, 16, 20, and 30 weeks of storage at room temperature.
Nut Sensory (Scale 0-15) Sample Week 16 Rancidity/Off Note Snap Bloom/Appearance Comments Dark chocolate base Almond Whole Low 0 3.5 0 Almond Whole Medium 0 3 0 Less roasted almond Walnut Whole Low N/A N/A N/A Discontinued Walnut Whole Medium 15 3 7.5 Discontinued Walnut Chop Low N/A N/A N/A Discontinued Walnut Chop Medium N/A N/A N/A Discontinued
Dark chocolate + milkfat Almond Whole low 0 6 0 Almond Whole Medium 2 7 0 Less roasted almond Walnut Whole Low 13 5 0 Discontinued Walnut Whole Medium 12 7 0 Discontinued Walnut Chop Low N/A N/A N/A Discontinued Walnut Chop Medium N/A N/A N/A Discontinued
Scale 1-15 increasing in rancidity and bloom, decreasing in snap N/A = samples that are no longer tested due to excessive rancidity yielding them inedible
227
Table 36f. Sensory ratings of chocolate bars with nuts after 0, 4, 8, 12, 16, 20, and 30 weeks of storage at room temperature.
Nut Sensory (Scale 0-15) Sample Week 20 Rancidity/Off Note Snap Bloom/Appearance Comments Dark chocolate base Almond Whole Low 0 3.5 0 Almond Whole Medium 0 3 0 Less roasted almond Walnut Whole Low N/A N/A N/A Discontinued Walnut Whole Medium N/A N/A N/A Discontinue Walnut Chop Low N/A N/A N/A Discontinued Walnut Chop Medium N/A N/A N/A Discontinued
Dark chocolate + milkfat Almond Whole low 0 6 0 Almond Whole Medium 2 7 0 Less roasted almond Walnut Whole Low N/A N/A N/A Discontinue Walnut Whole Medium N/A N/A N/A Discontinue Walnut Chop Low N/A N/A N/A Discontinued Walnut Chop Medium N/A N/A N/A Discontinued
Scale 1-15 increasing in rancidity and bloom, decreasing in snap N/A = samples that are no longer tested due to excessive rancidity yielding them inedible
228
Table 36g. Sensory ratings of chocolate bars with nuts after 0, 4, 8, 12, 16, 20, and 30 weeks of storage at room temperature.
Sample Week 30 Rancidity/Off Note Snap Bloom/Appearance Comments Dark chocolate base Almond Whole Low 0 3.5 0 Almond Whole Medium 0 3 0 Less roasted almond Walnut Whole Low N/A N/A N/A Discontinued Walnut Whole Medium N/A N/A N/A Discontinue Walnut Chop Low N/A N/A N/A Discontinued Walnut Chop Medium N/A N/A N/A Discontinued
Dark chocolate + milkfat Almond Whole low 0 6 0 Almond Whole Medium 2 7 0 Less roasted almond Walnut Whole Low N/A N/A N/A Discontinue Walnut Whole Medium N/A N/A N/A Discontinue Walnut Chop Low N/A N/A N/A Discontinued Walnut Chop Medium N/A N/A N/A Discontinued
Scale 1-15 increasing in rancidity and bloom, decreasing in snap N/A = samples that are no longer tested due to excessive rancidity yielding them inedible
229
Model System Results
In order to explore phenomena involved in fat compatibility in more depth, a fat system was created to model food products and allow for direct application to real food matrices while eliminating interferences of chocolate ingredients. The system contained only cocoa butter into which each nut variety was placed and fatty acid migration, DSC and XRD were tracked. The system was temper-cycled under accelerated conditions and tested 4 times over a 12 day cycling period where each cycle equals 8 hours. DSC and
XRD data were applied together to confirm shifts occurring in crystal forms. The cocoa butter system was used to simplify the system make XRD analyses possible. Chocolate bars contain sugar which strongly reflects x-rays, obscuring changes in the fat crystallization. Some research has been done to overcome this complication, but satisfactory methods are not yet available.
FAME analyses of nut oil migration into cocoa butter
Three fatty acids were targeted for tracking: linoleic and linolenic because they are present in walnuts in appreciable amounts, and a marker fatty acid present in chocolate in negligible amounts. This marker did not prove useful due to its presence at minor levels in walnuts as well.
Fatty acid migration in walnut whole low and medium and walnut chop low systems was relatively consistent: 18:2 increases ranged from 0.66-1.09 % and 18:3 increased slightly over the four temper cycles (Table 37). However, no migration of oil from nut into cocoa butter was observed in the walnut chop medium samples where greatest migration was expected. As shown in the bar studies, migration occurs in both directions so it is possible that the walnut chop medium system was just slower in
230 reaching equilibrium. Alternatively, incompatible nut oil TAGs may force more rapid tightening of the cocoa butter crystal matrix to prevent encroachment. DSC and XRD analyses were conducted to gain more detailed information about TAG reorganization in cocoa butter with and without migrated nut oils.
Table 37. FAME results for Model System (Quantified)
DSC analyses of crystal structure transitions
The DSC scans for the model system were much more complex than in the bar study. Since the product was temperature-cycled, nut oil migration was expedited and
DSC changes were much more extreme than in the chocolate bar study. Most model
231 system scans had 3 peaks vs two peaks for the bar study (Figure 60). In one case (walnut whole medium cycle 3), 4 peaks were present.
This increase in the number of peaks indicates an extreme level of fat incompatibility, resulting in formation of separate crystal fractions. Changes in the peak areas for each model system variant were extremely consistent (Figure 61 and Table 38) indicating that except for the chop medium system the migration processes and forces were essentially the same. Since the same samples showed oil migration in fatty acid analyses, it is reasonable to attribute the new fractions to unsaturated TAGs migrating out of the nuts and forming a phase independent of the cocoa butter which has a very narrow defined melting point relative other food systems. This explanation is consistent with scans for all systems except the walnut chop medium samples which showed migration at cycle 3, but at cycle four did not.
232
Peak= 34.52°→
Peak= 30.15°C→
Peak= 25.56°C→
Heat flow Endo flow (mW) Up Heat
0 10 20 30 40 50
Temperature (C)
Figure 60. DSC for Model system containing 13% Walnut chop low and 87% cocoa butter cycle 4.
233
Table 38. DSC results for whole and chopped walnut and cocoa butter model systems.
Cycle 1 Area Area Peak Area % Area Area % Sample Peak 1 Peak 2 3 1 %2 3 mp 1 mp2 mp 3 Walnut Whole Medium 35.61 116.7 N/A 23.38% 76.63% N/A 26.45 33.59 N/A Walnut Whole Low 30.12 99.36 N/A 23.26% 76.73% N/A 26.38 33.55 N/A Walnut Chop Low 43.08 140.1 N/A 23.52% 76.47% N/A 26.49 33.73 N/A Walnut Chop Medium 37.11 116.3 N/A 24.19% 75.81% N/A 26.56 33.78 N/A Cycle 2 Area Area Peak Area % Area Area % Sample Peak 1 Peak 2 3 1 %2 3 mp 1 mp2 mp 3 Walnut Whole Medium 25.58 103.4 N/A 19.84% 80.22% N/A 26.68 34.55 N/A Walnut Whole Low 29.99 107.9 N/A 21.75% 78.25% N/A 25.94 33.78 N/A Walnut Chop Low 34.01 120.9 N/A 21.96% 78.05% N/A 26.17 33.95 N/A Walnut Chop Medium 38.69 115.1 N/A 25.16% 74.84% N/A 26.37 33.91 N/A Cycle 3 Area Area Peak Area Area % Area Area % Area % Sample Peak 1 Peak 2 3 Peak 4 1 %2 3 4 mp 1 mp 2 mp 3 mp 4 Walnut Whole Medium 6.36 35.21 43.48 110.7 3.25% 17.99% 22.22% 56.57% 21.39 26.1 30.42 34.05 Walnut Whole Low 22.82 31.55 86.44 N/A 16.21% 22.41% 61.39% N/A 25.97 31.52 33.99 N/A Walnut Chop Low 24.43 28.91 90.08 N/A 17.04% 20.16% 62.82% N/A 26.48 29.58 34.14 N/A Walnut Chop Medium 29.15 30.62 87.96 N/A 19.74% 20.73% 59.55% N/A 26.1 30.15 33.94 N/A Cycle 4 Area Area Peak Area % Area Area % Sample Peak 1 Peak 2 3 1 %2 3 mp 1 mp2 mp 3 Walnut Whole Medium 20.04 39.65 98.06 12.71% 25.14% 62.18% 25.25 30.05 34 Walnut Whole Low 14.3 40.48 87.11 10.08% 28.53% 61.39% 25.05 30.13 34.1 Walnut Chop Low 19.41 36.55 88.84 13.45% 25.33% 61.57% 25.56 30.15 34.52
234
30 Changes in DSC Peak 1 Area over Cycling 25
20
15 Walnut Whole Medium
change % 10 Walnut Whole Low Walnut Chop Low 5 Walnut Chop Medium 0 0 1 2 3 4 5 Cycles
100 Changes in DSC Peak 2 Area over Cycling 90 80 70
60 50 40 change % Walnut Whole Medium 30 Walnut Whole Low 20 Walnut Chop Low 10 Walnut Chop Medium 0 0 1 2 Cycles 3 4 5
Figure 61. Changes in areas of DSC Peaks 1 (top) and 2 (bottom) during temperature cycling of walnut samples
235
Walnut chop medium samples showed distinctly different behavior where no migration was observed until cycle three and then it was very slight. It is likely that migration is occurring in both directions and the 18:2/18:3 equilibrium between nut and cocoa butter may be constantly in flux. Alternatively, the incompatible unsaturated TAGS may force a reorganization and tightening of cocoa butter crystal fractions to prevent ingress of foreign TAGs. Clearly, there is a change in crystal structure occurring and the nut oil migration is responsible for this change.
Due to the complexity of the system, crystal forms cannot be identified simply from melting point ranges for cocoa butter standards reported in the literature. With pure cocoa butter, a transition from lower to higher melting point is seen when βV transforms to βVI. However, this model system which includes nut oil does not follow the expected melting point pattern. Instead, the melting point of peak 1 decreases somewhat over time.
For example, the melting point of walnut whole medium at cycle 1 was 26.45°C and at cycle 4 it was 25.25°C. This trend was seen for all samples except the walnut chop low sample which was mentioned previously, and is explained by migration of nut oils into the cocoa butter. X-ray diffraction analyses were conducted to provide further clarification of the polymorphic transitions occurring in each model system and to identify specific crystal forms.
Model System: XRD Results
Greater knowledge of molecular organization in mixed TAG systems is critical to the confections industry. Sato et al (1989) noted this information gap and proposed the use of XRD and DSC in order to gain greater insight into mixed systems. Even though
236 they focused primarily on SOS and POP systems, their results coincide well with the data from this study which also takes into account foreign fats from nut oils that further complicate the system. To learn more about the molecular basis of crystal and matrix stability in chocolate bars with nut inclusions, a cocoa butter and nut inclusion model system was created. FAME, DSC and XRD analyses were conducted on the model systems. The samples were cycled for a total of 12 days and each was cycle 3 days.
A typical XRD spectrum for the cocoa butter used in this study is shown in Figure
62. XRD is used to determine short and long spacings between fatty acids in a crystal matrix (Figure 63). The long spacings correspond to the distance between the planes formed by the terminal methyl groups on the fatty acids and reflect double vs triple chain lengths, while the short spacings refer to the cross sectional arrangement of the fatty acids and reflect TAG chain packing density (Dimick, 1991). As the long spacing and short spacing decrease, the melting point increases due to a more tightly packed arrangement which allows for more van der waal‟s interactions. Both long and short spacings can be used to determine polymorphic transitions.
It takes more time for TAGs to become tightly packed and aligned and this corresponds to more stable polymorphs. Foreign fats such as milk fat can interfere with the packing and hence influence the transition to more stable polymorphs such as from
βV to βVI (Dimick, 1991). The XRD spectrum in Figure 62 shows the d spacings or short spacings of a typical cocoa butter sample. The polymorphic crystal form can be determined for a test sample by comparing its d-spacings with d-spacings of the known crystal forms of cocoa butter.
237
Well tempered chocolate shows 5 peaks with short spacings of 4.58, 4.02, 3.91, 3.79 and
3.68A, which indicates the βV form. This „finger print‟ is used to identify each
polymorph as well as the number and intensity of each peak. An alteration in this profile
indicates that an alternate form has developed, in this case βVI. Reduction of 5 peaks to
4 has been well-documented as an indicator for transition from βV to βVI (Smith et al,
2006, van Langevelde, 2001, and Sato, 1989). Broadening of peaks and loss of definition
are indicators of the most stable crystal form, β-VI, the bloomed state of chocolate (Sato,
1989).
Counts 4.58 Å
3.91 Å 3.08 Å 4.02 Å
5.42 Å 3.79 Å
Degrees 2-Theta
Figure 62. Typical XRD spectrum of cocoa butter
238
↑ L o n g
S p a c i n g ↓ ←Short → Spacing
Figure 63. Figure demonstrating the short and long spacings of two TAGs.
For this study only the bars with walnuts were analyzed by XRD because integrated results of the raw material and bars indicated greater changes were occurring with the walnut samples. Preliminary XRD analyses of almonds indicated no changes would occur in a reasonable length of time for a full study.
In chocolate bars with walnuts, differences were seen in both short spacings and peak definition (Table 39, Figures 64 A-D). At cycle 1, short spacings coincided with the literature values for a basic cocoa butter, thereby giving confidence to the data from this study. The short spacings were 4.61, 4.07, 3.93, 3.82, 3.72, 3.62, 3.55 and 3.52 Å for β2, and 4.61, 4.07, 3.88, 3.82, 3.72 and 3.67 Å for β1. These observations are consistent with a report of Sato et al (1989) who identified five different crystal forms (α, γ, pseudo β‟,
β2, β1) distinguished by short spacings. In POP, β2 and β1 differ between the 4 and 3.5Å region.
239
Surprisingly, the greatest changes in XRD patterns and earliest transition to βVI occurred in the chop medium walnut bars which had shown the greatest stability in oxidation. Peak 5 disappeared in cycle 3 and the remaining peaks were less sharp, in some cases broadened out and forked into two peaks. The same transitions occurred in remaining samples in cycle 4. XRD short spacing analysis using the formula d = λ / (2
Sin θ) where λ = 1.54 Ǻ revealed little variation in the short spacings (Table 37). This phenomenon has been observed previously by Sato et al. (1989) and by van Malssen et al. (1999), and documents clearly a more rapid transition to βVI crystals whose tight packing that prevents migration of unsaturated fatty acids into the cocoa butter.
The long spacings can also be determined, but require different setting on the equipment specifically the distance from the detector to the sample. This requires the samples to be re-run using different settings. For this study the goal was to gain understanding of the polymorphic forms and the d-spacing or short spacing provides this information.
Table 39. XRD short spacings (Å ) of cocoa butter in nut model systems.
Walnut Whole Low Cycle 1 Cycle 2 Cycle 3 Cycle 4 Peak 1 4.58 4.58 4.58 4.58 Peak 2 3.96 3.97 3.96 3.96 Peak 3 3.89 3.89 3.89 3.89 Peak 4 3.74 3.74 3.69 3.69 Peak 5 3.65 3.65 3.65
Walnut Whole Medium Cycle 1 Cycle 2 Cycle 3 Cycle 4 Peak 1 4.58 4.58 4.58 4.58 Peak 2 3.96 3.97 3.96 3.96 Peak 3 3.89 3.89 3.89 3.89 Peak 4 3.74 3.74 3.73 3.68 Peak 5 3.65 3.65 3.68
240
Walnut Chop Low Cycle 1 Cycle 2 Cycle 3 Cycle 4 Peak 1 4.58 4.58 4.58 4.58 Peak 2 3.96 3.96 3.96 3.96 Peak 3 3.89 3.89 3.89 3.89 Peak 4 3.74 3.74 3.73 3.69 Peak 5 3.65 3.65 3.68
Walnut Chop Medium Cycle 1 Cycle 2 Cycle 3 Cycle 4 Peak 1 4.58 4.58 4.58 4.58 Peak 2 3.96 3.96 3.96 3.96 Peak 3 3.89 3.89 3.89 3.89 Peak 4 3.74 3.73 3.69 3.69 Peak 5 3.65 3.65
Sample of CB (Marangoni, 2005) Peak 1 4.58 Peak 2 4.02 Peak 3 3.91 Peak 4 3.79 Peak 5 3.68
241 Figure 64 A. X-ray diffraction spectra of cocoa butter with whole low roasted walnut inclusions undergoing thermal cycling.
XRD Walnut Whole Low Cycle 1 80000 XRD Walnut Whole Low Cycle 2
70000 80000 60000 70000
50000 60000
40000 50000 40000 30000
30000 INTENSITY
20000 INTENSITY 20000
10000 10000 0 0 0 5 10 15 20 25 30 35 0 5 10 15 20 25 30 35 2 Theta 2 Theta
XRD Walnut Whole Low Cycle 3 XRD Walnut Whole Low Cycle 4
80000 80000
70000 70000
60000 60000 50000 50000 40000 40000
INTENSITY 30000 30000 INTENSITY 20000 20000 10000 10000 0 0 0 5 10 15 20 25 30 35 0 5 10 15 20 25 30 35 2 Theta 2 Theta
242
XRD Walnut Whole Medium Cycle 1 XRD Walnut Whole Medium Cycle 2
80000 80000 70000 70000
60000 60000
50000 50000 40000 40000
30000 30000 INTENSITY
Intensity INTENSITY 20000 20000 10000 10000 0 0
0 5 10 15 20 25 30 35 0 5 10 15 20 25 30 35
2 Theta 2 Theta
XRD Walnut Whole Medium Cycle 3 XRD Walnut Whole Medium Cycle 4
80000 80000
70000 70000
60000 60000 50000 50000 40000 40000
INTENSITY 30000 30000 INTENSITY 20000 20000 10000 10000 0 0 0 5 10 15 20 25 30 35 0 5 10 15 20 25 30 35
2 Theta 2 Theta
Figure 64B. X-ray diffraction spectra of cocoa butter with whole medium roasted walnut inclusions undergoing thermal cycling. 243
XRD Walnut Chop Low Cycle 1 Walnut Chop Low Cycle 2
80000 80000 70000 70000
60000 60000
50000 50000
NSITY 40000 40000
30000 30000
INTE INTENSITY 20000 20000 10000 10000 0 0 0 5 10 15 20 25 30 35 0 5 10 15 20 25 30 35 2 Theta 2 Theta
Walnut Chop Low Cycle 3 XRD Walnut Chop Low Cycle 4
80000 100000 70000
80000 60000 50000 60000 40000
INTENSITY 40000
30000 INTENSITY 20000 20000 10000 0 0 0 5 10 15 20 25 30 35 0 5 10 15 20 25 30 35 2 Theta 2 Theta
Figure 64C. X-ray diffraction spectra of cocoa butter with chopped low roasted walnut inclusions undergoing thermal cycling.
244
Figure 64D. X-ray diffraction spectra of cocoa butter with chopped medium roasted walnut inclusions undergoing thermal cycling.
XRD Walnut Chop Medium Cycle 1 XRD Walnut Chop Medium Cycle 2
80000 80000 70000 70000
60000 60000
50000 50000 40000 40000
30000 30000 INTENSITY
20000 INTENSITY 20000 10000 10000 0 0 0 5 10 152 Theta20 25 30 35 0 5 10 15 20 25 30 35 2 Theta
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Summary and Integration of Results
Almonds and walnuts with different treatments were added to chocolate to learn more about how nut oil migration from nuts affects oxidative stability, crystal structures and texture, tendency to bloom, and sensory qualities, and perhaps most importantly, to determine the major failure mode in chocolate with nut inclusions. Revisiting these goals in conjunction with project outcomes shows that the goals and objectives of this study were in fact met, and that behavior of chocolate with nut inclusions is complex and not easily predicted. Some results were quite surprising.
Innate stability of nuts
Almonds and walnuts, as expected, differed greatly in overall stability. With lower levels of unsaturation and high levels of tocopherols and other antioxidants, almonds are much more resistant to oxidation over time than walnuts, as demonstrated in the 30 week study. The much longer delay in onset of both primary and secondary oxidation determined for almonds in chemical analyses was confirmed with sensory testing.
Oxidation was the failure mode in all systems studies. It began earlier, proceeded more rapidly, and developed higher levels of products in walnuts. In general, peroxide values followed the pattern commonly cited in the literature – i.e. peaking and then declining, but with some quirks. Intuitively, one would expect whole nuts to oxidize more slowly than chopped nuts, showing a longer induction period and lower accumulation of peroxides. However, whole walnuts showed a cycling of peroxide peaks and decline, with an initial peak at four weeks and a second higher peak at twenty weeks, while chopped walnuts did not begin oxidizing until after eight weeks and then peroxide values
246 just increased. These results show that factors other than fatty acid composition have a strong influence on oxidation. We speculate that lipoxygenase enzymes remain active in whole nuts and are able to catalyze rapid formation of hydroperoxides, which may account for the first peroxide peak. That peroxide values were unexpectedly and significantly (p=0.054) lower with longer roasting is consistent with increased destruction of lipoxygenase and other catalytic enzymes. Obviously, heat should also decompose hydroperoxides and hence also peroxide values. However, the decomposition yields two radicals -- alkoxyl and hydroxyl -- which are much more reactive than the peroxyl radicals involved in initial stages of oxidation.
LOOH LO + OH.
Thus, the net result of higher heat should be enhanced oxidation, and that was not observed in the duration of this study.
The degree of chop also plays an important and surprisingly complex role in nut stability. It was expected that chopping the nuts would increase surface area and exposure to oxygen, and thus increase oxidation rate and level. This indeed occurred over the long run (by 30 weeks), but not initially. Accumulation of peroxides was delayed relative to whole walnuts, remaining at low levels until twelve weeks. At the same time, however, aldehydes are produced and reach an initial peak at four weeks, followed by decline and then secondary accumulation. This pattern is totally unexpected based on common depiction of lipid oxidation as not producing aldehydes and other products until after hydroperoxides are decomposed.
Lack of early hydroperoxide formation, e.g. by lipoxygenase, in chopped nuts may be explained in part by disruption of the nut tissues and separation of enzyme bodies
247 from oil sources. However, formation of aldehydes without hydroperoxide precursors is more difficult to explain. Clearly, there are hydroperoxide-independent mechanisms of aldehyde formation active in nuts, and these need to be elucidated.
Two classes of antioxidants in nuts – tocopherols and procyanidins -- were studied to better understanding the inherent oxidative stability of each nut type and also what role, if any, each played in mitigating oxidation. Overall, almonds have higher total tocopherol levels, mostly as -tocopherol, and thus are more stable to roasting conditions and storage time. Lower total levels of tocopherols in walnuts are counterbalanced by high proportions of and tocopherols that are more effective antioxidants in foods; these are necessary to protect the high levels of polyunsaturated fatty acids endogenously, but are not sufficient to prevent oxidation during storage. Procyanidins were low in both nut types and did not appear to play a role in stability of either nut.
Whole almonds maintained acceptable sensory quality throughout the study; no off flavors were detected and a slight reduction in nut roast character was the only noticeable defect. Walnuts, on the other hand, began to display off notes by week 8 and samples were eliminated from testing as early as week 12 due to excessive rancid notes.
By week 20 only one walnut variety remained in testing (walnut whole low) and by week
24 it was also eliminated from testing.
Overall, these results indicate that almonds are relatively stable to oxidation as long as they remain whole, and that walnuts are highly susceptible to oxidation so must be protected if they are to be used in chocolate products.
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Effects of nuts in chocolate bars
The nut-chocolate bar system is much more challenging than the nut alone system due to the complexity of the matrix. Although more difficult to interpret, data from bar studies is directly applicable to the production environment.
The first objective was to determine effects of nuts on oxidative stability.
Our hypothesis predicted that nut type and its fatty acid composition would be a major factor affecting performance in chocolate and this was certainly true for oxidation.
Mono-unsaturated almonds were reasonably stable throughout the 30 weeks of incubation, while chocolate with walnuts began to degrade within a few weeks.
Lipid oxidation in chocolate bars was particularly interesting for walnuts where a number of factors were influential in product stability over time and were confirmed through statistical analysis to be significant. Roast level did not significantly influence stability. However, roasting method (whole vs chopped) and chocolate type (+/ milkfat) were key factors controlling product stability, with statistical confirmation of p=0.000 and p=0.009, respectively. Chocolate bars with chopped walnuts demonstrated a slower rate of primary oxidation than did whole nuts, probably because greater heat penetration destroyed lipoxygenases more effectively. Surprisingly, chocolate with milk fat oxidized at a more accelerated rate than dark chocolate alone. This was not expected since milk fat is predominantly saturated. However, milk fat TAGS appear to provide a solvent phase that facilitates migration of unsaturated TAGs from nuts to chocolate, which accelerates oxidation.
Nut type was the major factor controlling production of secondary oxidation products as well: almonds were significantly more stable than walnuts with high levels of
249 secondary products detected chemically in walnut samples were consistent with rancidity detected in sensory testing. Roasting method also seemed to be important in stability, although the heat effects were complex. Whole roasted walnuts were somewhat less stable than chopped walnuts, probably due to intact cell structures where lipids were in contact with lipoxygenases, and lipoxygenases were not inactivated. Conversely, walnuts that were chopped and medium roasted were unexpectedly the form most stable to oxidation. The high surface area increased access to air and facilitated heat transfer which normally enhances hydroperoxide decomposition; both of these effects accelerate oxidation. However, increased heat transfer also inactivated lipoxygenases and produced
Maillard products with antioxidant activity, both of which decrease oxidation, and the surface are plus high heat facilitated volatilization of oxidation products that produce off- flavors. This shows how nuts are complex multifaceted systems that do not behave according to established dogma re oxidation. Many factors besides fatty acid composition must be considered when using nuts in chocolate.
Analysis of tocopherols in nuts within the chocolate bars was much more complicated than the nut analysis alone. Although the nuts were separated from the chocolate and care was taken to remove all chocolate, chocolate contains tocopherols and this complicates analyses and interpretations. Results suggest that tocopherols move towards a sort of equilibrium, migrating both directions between nuts and chocolate.
Whether this is due to tocopherols being carried along during oil migration or to diffusion in a concentration gradient is not clear. Cocoa butter has appreciable amounts of gamma tocopherol, and a concentration gradient could account for migration into the almonds.
Walnuts, on the other hand, are high in gamma tocopherols so migration from chocolate
250 would be less expected. However, these tocopherols are actively consumed protecting against lipid oxidation in the walnuts, so flow from chocolate to nut could be initiated.
Another explanation is that migration of oil out of the nuts reduces the fat content of the nut, which would thus make the tocopherol content (expressed relative to oil weight) appear higher. Either of these scenarios would explain the increase seen in gamma tocopherols for both almonds and walnuts over time. As with procyanidins in nuts alone, procyanidins in chocolate bars were also very low and did not seem to participate in mitigating oxidation.
The second focus of the study was to track fat migration from nuts to chocolate and determine effects of the nut oil on texture and bloom. Five fatty acids were tracked: 18:2 and 18:3, the major fatty acids in nuts; 18:1, a component of both nuts and cocoa butter; and C20:1 and C24:0, „marker‟ fatty acids present in very low quantities in nuts but not in cocoa butter. The process of fatty acid migration is dependent on time and consistent with diffusion principles. Very clear trends in migration were observed.
Almonds and walnuts differed significantly in their oil migration to chocolate (p=
0.000), which makes sense given their drastically different fatty acid profiles. Oil migration in almond systems was minimal. Chocolate with almonds showed less than 4% loss in oleic acid and influx of less than 1% 18:2 and 20:1; and migration was not affected by roasting method or level. This behavior reflects almond fatty acid compositions similar to cocoa butter and is consistent with diffusion equilibration processes.
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Oil migration in walnut systems was more extensive. Oleic acid levels in chocolate decreased by >7%, linoleic acid increased by 4-6%, and linolenic acid increased slightly (<1%) for all walnut samples. These results are consistent with a drive towards diffusional equilibration of fatty acid levels between the two system components.
Roasting treatment had the strongest effect on migration of walnut oil. Roasting walnuts whole surprisingly significantly increased migration of linoleic and linolenic acids into chocolate (p=0.000). Oleic acid levels in chocolate dropped slowly and slightly over time. This seems counterintuitive since chopped nuts have larger surface area for oil migration. One plausible explanation is that the initial higher formation of hydroperoxides increases component polarity, which in turn would increase repulsion from the hydrophobic cocoa butter and decrease migration forces. Another possibility is that heat denatures proteins that complex TAGs or phospholipids in nuts, facilitating release and migration.
The concentration gradient effect could also be seen with the presence or absence of milk fat. When milk fat was not included in the formulation, greater losses of oleic acid and smaller gains of linoleic acid were seen in the chocolate. This makes sense given the higher concentration of oleic acid in cocoa butter than milk fat (cocoa butter has
~35% oleic vs 25% oleic in milk fat). The opposite was seen with milk fat present, less loss of oleic and greater gains of linoleic, because in addition to influencing fatty acid concentration balances, milk fat facilitates solubilization of the nut oils into the chocolate.
As will be shown, this solubilization has a marked influence on fat crystallization, texture, and bloom in the chocolate.
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The third focus of the study was to investigate effects of nut oils on cocoa butter crystallization properties and susceptibility to bloom.
Fat compatibility plays a major role in product stability and can be explored through DSC and XRD analysis. DSC reveals the number of crystal forms and their melting points. The presence of nuts and their incompatibility with chocolate is evident from the fact there is more than one peak indicating two distinct melting fractions. Raw cocoa butter displays a single narrow DSC peak, milk fat has two peaks reflecting high and low melting fractions, and fresh chocolate samples show a broad single peak that actually encompasses at least three crystal forms, although only two appear at any one time, distinguishable by melting point. In chocolate with walnuts, crystal form 1 began as the dominant polymorph. During storage, this crystal form initially decreased in all formulations, transforming into crystal form 2 with higher melting point, once again indicating a more stable form, i.e. β-VI. By the end of the study (week 30), however, crystal form 1 was again close to starting levels as higher levels of unsaturated TAGs migrated in.
The second crystal form visible in DSC scans throughout the study results from lack of compatibility between the nut oils and chocolate. Introduction of unsaturated fatty acids induces localized TAG reorganization in the cocoa butter with increased associations between saturated TAGs. The chocolate type used significantly impacted this transition (p=0.017), as did roasting method slightly (p=0.06). Milk fat, with short chain saturated fatty acids, is more compatible with cocoa butter TAGs. Milk fat interferes with the formation of tight packing structures which contribute to formation of cracks and diffusion of oil in chocolate. Roasting walnuts whole indirectly enhances
253 transition to crystal 2 by increasing nut oil migration. Xray diffraction verified that this crystal transition was -V to -VI.
These changes in crystallization were directly reflected in chocolate texture hardness and fracturability. Indeed, texture becoming hard or crumbling is often a key mode of failure for chocolate. Texture hardening showed clear differences between chocolate formulations. There were two potential outcomes for textural changes depending on which driving force outweighs the other: softening due to oil migration and hardening due to TAG repacking in the more stable beta VI form over time.
In dark chocolate with either nut, the drive towards tighter crystal packing dominated until week 16 or 20, leading to harder bars. Analyses of nut oil migration showed greatest increases in nut oils in the chocolate between weeks 12 to 16 in and 20 to 24 in for walnut bar samples. Hence, by this time sufficient unsaturated TAGs had accumulated through oil migration to disrupt cocoa butter crystal matrices and the bars began to soften. An overall slight softening was seen with the addition of milk fat, as was to be expected from the short-chain fatty acids, but in this case the chocolate hardened as nut oil migration increased, reaching close to the same hardness as the dark chocolate at the end of the incubation period. There is a drive for the system to go to the
β-VI form but at the same time there is oil migration, two very different forces.
Significant factors affecting texture were nut (p= 0.003) and chocolate type
(p=0.000) The difference was chocolate with milk fat was softer than expected.
Migration of unsaturated fats out of the chocolate into the nuts is faster than initially than the migration of polyunsaturated fats into the chocolate. This results in an initial harder texture followed by softening. Greater textural changes coincide with higher fat
254 migration from the nuts.
Transformations of β-V to β-VI crystals is also associated with development of bloom, the characteristic white haze on surfaces of chocolate. Bloom was found to be poorly identified and quantified by colorimeter due to the non-homogenous distribution of the white haze on the bars. Hence, the colorimeter could only detect cases of extreme blooming. The human eye in sensory analyses was much more sensitive in detecting low levels of bloom. In the accelerated chamber study, the colorimeter first detected bloom on the 10th melt-recrystallize cycle in the almond low roast without milk fat samples.
Dark chocolate with chopped walnuts bloomed at cycle 12 (low roast) and cycle 14
(medium roast). That almond bars apparently bloomed first was surprising considering their general stability in all measures, and was not consistent with sensory evaluation which detected slight bloom as early as week 8 on all walnut samples, extensive bloom on the walnut whole medium bars by week 12, and no bloom on any of the almond bars during the entire 30 week storage. It was also unexpected intuitively to find that bloom appeared on the whole nut samples before chopped nut samples, yet this sensitivity reflects the enhanced nut oil migration and associated stimulation of TAG reorganization in the cocoa butter matrix. The presence of milk fat did protect against development of bloom in walnut samples but was irrelevant on a practical level since walnut bars failed for rancidity before they bloomed. Indeed, although bloom is highly recognized by consumers as a defect in chocolate, it was not the failure mode for any samples in this study.
A fourth focus of this study was to determine the effects of nut processing
(whole vs chopped and raw vs roasted to various extents) and chocolate formulation
255 on nut performance in chocolate. The hypothesis proposed that small piece sizes, although convenient for processing, offer a greater surface area for fat migration and therefore are more likely to lead to fat migration, oxidation, and bloom. Higher roasting levels were predicted to result in greater instability due to expedition of rancidity. The roasting method proved to be an important parameter in chocolate stability while the roasting level proved more important for stability of nuts alone.
Roasting method (chopped then roasted or roasted whole then chopped) and time significantly influenced product stability (p=0.050), both primary and secondary oxidation (p=0.050), and antioxidant levels (p=0.001). Longer rancimat induction times showed that roasting actually increased stability of almonds. In walnuts, there was a slower onset of oxidation and levels of primary and secondary oxidation products were lower for chopped nuts than whole, but ultimately all samples ended with similar levels.
Total tocopherol losses were lowest for chopped, medium roast walnuts, consistent with the lower oxidation and higher destruction of lipoxygenase, followed by whole low and medium and then chopped low.
When nuts were incorporated into chocolate bars, the situation was complicated by migration of oil both ways into and out of the nut, so treatment differences were difficult to discern. Overall, bars with chopped then roasted nuts had greater overall stability which can be attributed to the shorter roasting time (i.e. 3-4 minutes vs 12-17 minutes), increased lipoxygenase destruction, and separation of enzymes and substrates early in the shelf life. This, demonstrates clearly that roasting influences nut and chocolate quality in many ways, many of which are yet unidentified. Recognition of the role of roasting can be applied to real chocolate product development applications. More
256 detailed analyses of effect of heat and further explorations into time/temperature combinations may identify time-temperature combinations that enhance stability and mark roasting limits where sensory aspects are no longer acceptable.
Lastly, the impact of milk fat in combination with nuts on overall stability and product attributes in a dark chocolate formula was evaluated. Milk fat is frequently added to chocolate to modify textures, enrich flavors, and inhibit bloom. The hypothesis predicted that nut bars made with chocolate plus milk fat would have greater bloom stability (not necessarily oxidative stability) than samples without milk fat due to the ability of milk fat to interfere with chocolate crystallization and hence reduce bloom.
Results of this study showed that milk fat has both benefits and drawbacks as an additional ingredient to a chocolate recipe. There are clear advantages in bloom mitigation. Milk fat inhibits bloom in two ways. Since milk fat TAGs co-crystallize with cocoa butter TAGs, they interfere with reorganization of cocoa butter high melting fractions into -VI crystals associated with bloom. In addition, by acting as a solvent for nut oil and some chocolate crystal fractions, milk fat may facilitate movement of TAGs to the surface but it also prevents their crystallization.
Milk fat also presents issues with softening and increased potential for oxidation.
Milk fat has a broad spectrum of fatty acids, ranging from short chain saturated to long chain saturated and unsaturated. The appreciable levels of unsaturated fats increase susceptibility of chocolate to oxidation. Add to this the ability of milk fat to solubilize nut oils and increase their migration into chocolate, and the presence of milk fat becomes a definite detriment to oxidative stability when nuts are present.
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The addition of milk fat also decreases the hardness of chocolate bars due to disruption of the fat matrix and introduction of lower melting point TAGs. When added to cocoa butter alone, this effect is usually desirable in creating a smoother melt in the mouth. However, when combined with the high PUFA TAGs of nut oils, the net effect can be hardening as increased solubilization of incompatible nut oils forces tightening and reorganization of the cocoa butter crystal matrix. Thus, milk fat must be used with care as a chocolate additive when nuts will also be present. This dilemma opens another rich area for research to identify optimum levels or fractions of milk fat that can counteract effects of nut oils and improve stability of chocolate with nut inclusions.
In summary, nut type (fatty acid composition and endogenous antioxidant levels) and roasting treatment are the major determinants of product stability and quality when adding nuts to chocolate. As expected, almonds with high mono-unsaturated fatty acids and tocopherol levels were much more stable than polyunsaturated walnuts. The stability of almonds is probably one reason why they are so extensively used in chocolate products already. The roasting method (chopped vs whole) is more important overall than the roasting level; it impacted oxidation in both nuts and bars, secondary products and tocopherols in nuts, and FAME and DSC for bars. Roasting time was important in all aspects especially with migration, oxidation and texture. Other components of the chocolate formulation also contribute overall performance. Adding milk fat to chocolate has benefits such as delaying onset of bloom and texture changes, but it also has drawbacks such as expediting oxidation and undesirable texture changes.
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Determining the order of the mode of failure for chocolate products with nut inclusions is critical for the confections industry. For dark chocolate bars with nuts, the first mode of failure was rancidity, and this occurred well before development of bloom or textural changes (either excessive hardening or softening). Since roasting decreased oxidation, research with roasting modes and times combined with increased antioxidant protection may identify ways to overcome these oxidation problems, increase utilization of walnuts in chocolate products, and open many areas of opportunity for confectionery scientists.
Overall, this study has provided the following new understanding of the effect of nuts on the molecular level:
When nuts are added to chocolate, an equilibrium is approached between fatty acids
and tocopherols in nuts and chocolate. Hence, TAGs with oleic acid migrate from the
chocolate to the nuts, and TAGs with polyunsaturated linoleic and linolenic acids
migrate from the nuts to the chocolate. Similarly, tocopherols (especially gamma)
exchange between the chocolate and nuts. Migration of oleic acid occurs first and most
rapidly, resulting in an initial hardening of the chocolate. This is reversed when
polyunsaturated TAGs migrate into the chocolate from nuts. These polyunsaturated
TAGS cannot co-crystallize with cocoa butter, so they form a second phase with lower
melting point. The influx lowers the net melting point of the chocolate but also forces
cocoa butter TAGs to reorganize into tighter crystals with higher melting points so the
net effect on chocolate texture depends on the balance between these two forces. At
least part of the reorganized crystals appear in the -VI form normally associated with
bloom. However, bloom is slower than might be expected because the unsaturated
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phase can solubilize high melting crystal fractions, inhibiting their deposition on the
surface.
Significance and Impact of Results
Model systems have been used to investigate the impact of foreign fats on cocoa butter crystallization, i.e. migrating nut oils (Campos, 2010), but intact systems, especially ones that contain inclusions with two very different fatty acid profiles, have not been studied. This study is unique in several ways. It is designed to provide molecular level information that will both shed new light on chocolate matrix formation under different conditions, and also model real world processing in a controlled production environment so as to provide information that will be directly translatable to industrial processes. To accomplish this, it used a complex chocolate bar system rather than simple cocoa butter plus nuts or nut oils. The chocolate base was produced in-house with total control and oversight over history and quality of all raw materials and processing. This project is comprehensive in addressing both modes of failure -- bloom and oxidative rancidity – while considering also oil migration and other sub-bloom changes in the molecular structure of the chocolate matrix in a system with inclusions that have not been previously studied. The complex system of chocolate and nuts used here, unlike those in the literature, allowed tracking of fat migration over time in systematic way.
This study, although fundamental in nature, has several important practical applications. Greater understanding of nut meats in chocolate is an area of considerable interest to the confectionary industry. The ability to extend the shelf life of nut-containing products means real economic savings, longer time on the shelf and less buy-back for the
260 manufacturer, and a fresher product for consumers. Through knowledge of fatty acid profiles and various chocolate formulations, a product development scientist can formulate the most stable bar by taking into account the most active modes of failure.
Finally, this study is unique in its focus on nuts more than chocolate. Walnut and similar high polyunsaturated nuts are not commonly used in chocolate bar products due to their instability. There are industry theories regarding why certain nuts such as walnuts and macadamia are not very stable, based on empirical observations and some consideration of fundamental chemistry. However, there have been no systematic studies of nut composition and associated effects on oil migration, chocolate crystallization, and stability. Nor have there been studies of nut roasting and oxidation effects on chocolate qualities and stability. This study has provided detailed analytical and sensory analyses to elucidate how nut roasting and oxidation alter the chocolate matrix. Providing a scientific basis for understanding nut interactions with chocolate should identify key properties or behaviors that can be used to predict compatibility of different nuts with chocolate and potentially also offer new approaches for using nuts that previously have been avoided in chocolate products. Elucidation of how these nuts interact with chocolate can suggest innovative approaches for stabilization as well as new ways to use them, offering consumers more variety and manufacturers more flexibility. Increased knowledge of nut oil interactions with cocoa butter can be leveraged to create unique products with enhanced stability and high product quality.
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Future Work
From this study and a review of the current literature it is clear that a greater understanding of food microstructure is needed in order to fully elucidate the mechanism of bloom and fat compatibility. This need for further research into food microstructure and study of the intact food system is supported by Narine et al. (1999), Tietz and Hartel
(2000) and Aguilera (2005). These researchers call for greater exploration into lipid based food products intact with specific focus on crystalline matrices and looking at both the micro and macroscopic level. Specifically information regarding mixed fat systems would be a great area to further explore. Much of the research is done on single fatty acid systems or single TAGs species. In reality food systems are much more complex and are composed of many different fats with various melting points and physical properties.
This is echoed by Metin and Hartel (1998) who suggest that there is little work in the area of quantitative analysis of fat crystallization and kinetics of fat blends.
The use of model systems although valuable cannot be directly applied to the actual food matrix. Therefore, future studies that use both a model and real food matrix would be most valuable to the food industry. A decent number of studies have looked at filled chocolate pieces and fat migration as well as model nut oil systems, but systems with nut inclusions have not be fully explored. Although it is a hard system to probe due to the need to separate the chocolate from the nuts as well as ensuring homogenous distribution through the system it is a valuable system to study due to the prevalence of nuts inclusions in chocolate bars throughout the market. This study serves as a model demonstrating the complexity of such a study as well as the ability to translate this knowledge into real world applications.
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CURRICULUM VITA
Andrea Rossi-Olson Education
B.S, Biotechnology with a concentration in Microbial Technology September 1998- May 2003 Cook College, Rutgers University
B.S, Food Science with a concentration in Food Biotechnology September 1998- May 2003 Cook College, Rutgers University
M.S, Food Science The Effect of Processing Parameters on the Texture Properties of Imitation Cheese May 2006 Graduate School of New Brunswick, Rutgers University
Publications:
Rafi MM, Yadav PN, Rossi AO. Glucosamine inhibits LPS induced COX-2 and iNOS in mouse macrophage cells (RAW 264.7) by inhibition of p38-MAP kinase and transcription factor NF-κB. Molecular Nutrition and Food Research, 51: 581-593 (2007).
Professional Experience
Mars Inc., Burr Ridge, IL (October 2010 – present) Senior Product Development Scientist, Ice Cream and Substantial Snacks
Mars Inc., Hackettstown, NJ (2007 – Sept 2010) Product Development Scientist, Seeds of Change and Dove Chocolate
National Starch & Chemical Co., Bridgewater, NJ (2005 - 2007) Sr. Food Technologist, Food Innovation Group
University of Massachusetts, Amherst, MA Teaching Assistant, September 2004-December 2004
Advanced Food Systems, Somerset, NJ Food Technologist, June 2003-August 2004
Firmenich, Plainsboro, NJ Savory Intern, Summer 2002
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Taco Bell, Irvine, CA Food Product Development Intern, Summer 2001
Calvin Klein Cosmetics Company, Mount Olive, NJ Chemistry Intern, Summers 1999 & 2000