Materials and Methods
This chapter will describe the rationale behind the models and techniques applied to the work of this thesis. To avoid unnecessary repetition, details specific to technical settings or parameters used are described in the “Materials and Methods” sections of each study in Chapters 4 to 7.
This chapter is split into the following two sections:
Section 3.1: Sample design and chocolate making methods
Section 3.2: Instrumental methods for fat bloom assessment and chocolate property measurement
Development of chocolate samples
Chocolate models and their materials
Chocolate manufacturers supply consumers with an astonishing variety of chocolate products by using differing types and ratios of ingredients. However, as mentioned in Section 2.4.1, the amount and type of ingredients (e.g. lecithin) can influence the crystallisation behaviour of cocoa butter as well as the chocolate’s physical properties.
This project, therefore, uses simple model chocolate systems to identify different fat bloom types and mechanisms, and to analyse the structure-property relationships of chocolate during bloom formation. Compared to commercial chocolate, with its high levels of complexity, the structure of model systems can be more easily controlled during processing; it also has the advantage of being able to have key elements of interest teased out.
In this research, three types of model chocolate were produced using lab-scale facilities.
These were cocoa mass (CM) chocolate, cocoa powder (CP) chocolate and sand chocolate.
The advantages and disadvantages of each type of model are shown in Table 3-1.
The materials of each model were prepared as illustrated in Figure 3-1. This is an overview and comparison of the sample making methods, and more detailed descriptions and specific settings of the apparatus used will be introduced in the relevant “Materials and Methods” sections in the following chapters.
CM chocolate was made from cocoa nibs (Chocolate Brown, Warkworth, New Zealand), which were pre-ground using a coffee grinder, and then further ground in a stone melanger (Spectra 11 stone melanger, Coimbatore, India) for different lengths of time and at different speeds, to obtain cocoa mass of varying particle size distributions (PSDs). The cocoa mass was then used to produce untempered or well-tempered chocolate samples.
CP chocolate was produced by mixing cocoa powder (Nestlé, UK) and cocoa butter (PureNature, Pure Ingredients Ltd, New Zealand). A mechanical stirrer (RW 20 digital, IKA-works Inc. NC, USA) and a water bath (WB-11, WiseBath, South Korea) were used.
Sand chocolate was a mixture of black sand particles and cocoa butter, produced using the above-mentioned mechanical stirrer and water bath. The black sand was collected from Bethells Beach (New Zealand) and was then washed and dried. The clean sand was ball milled to produce varying PSDs. Sand particles and spherical stainless-steel balls (diameter: 0.5cm) with a weight ratio of 1:5 were filled into a vial (diameter: 8cm; height: 20cm). The vial was placed onto a ball milling system (configurations and specifications in Appendix B) rotating at different speeds for varying amounts of time to obtain sand particles with varying PSDs.
Sample making – tempering protocol
Two tempering methods were used to produce well-tempered chocolate.
Tempering Method 1
A tempering machine (Revolation 2, ChocoVision, USA), which has default tempering profiles, was used to temper the CM chocolate and CP chocolate. The cocoa mass or mixture obtained from Section 3.1.1 was melted in a water bath set to 60oC for at least 1 hour to remove any pre-existing crystal history. Then, the molten liquor was poured into the tempering machine following the default tempering profile for dark chocolate, see Figure 3-2. Temperature was brought down from 42.2 to 32.2oC with the addition of cocoa butter seed crystals, promoting formation of polymorphic form V crystals during the cooling stage from 32.2oC to 29.4oC. The cocoa butter seeds were cocoa butter powder (PureNature, Pure Ingredients Ltd, New Zealand) in polymorphic form VI, and the fraction passing through a 100μm sieve was used. Finally the liquor was reheated to 31.5oC to melt unstable crystals before moulding in cylindrical moulds (Figure 3-3, diameter: 4.5cm; depth: 1.2cm).
Tempering Method 2
The density of black sand particles was determined by the volumetric method, using a measuring cylinder, water and an electronic balance; the weight/volume of the sand was calculated as 3.24g/cm3. Cocoa powder has an approximate bulk density of 0.48g/cm3 , and the true density is close to 1g/cm3 as fine cocoa powder can suspend in water. Therefore, due to the relatively higher density of sand particles compared to that of cocoa ingredients, phase separation could occur during tempering of sand chocolate without proper mixing. As the tempering machine provided low-shear mixing, Tempering Method 1 was not applicable to temper sand chocolate.
This was resolved by Tempering Method 2, following the temperature profile in Figure 3-4. The chocolate mixture was continuously cooled down to a low temperature of 24oC via high-speed mixing (1200rpm) with the mechanical stirrer, which ensured a high viscosity as a large proportion of form V crystals developed. The viscous mixture was poured into moulds and cooled to 2oC to achieve quick crystallisation of the cocoa butter. Finally, the chocolate samples were stabilised at room temperature, 20±0.5oC, for 6 hours. Cocoa butter polymorphism was examined using differential scanning calorimetry (DSC, Section 184.108.40.206); the fat phase was found to be mainly polymorphic form V, confirming that the sand chocolate was well-tempered.
This section introduces the most important techniques used in fat bloom studies with the principles described here.
Particle size distribution – Mastersizer
Particle size is the most commonly measured quality parameter, as it lies at the heart of defining chocolate properties, and can be perceived during chocolate consumption. Particle size measurements are carried out during chocolate manufacturing on raw ingredients as well on intermediate and finished products.
A micrometer and laser diffractometry are commonly used in both laboratories and in the confectionery industry. Other methods like sieving and microscopy coupled with image analysis may be used as well . The micrometer only indicates the size of the largest particles; thus, measurements of PSD by laser diffractometry are more useful.
The laser diffraction technique depends on the fact that light is scattered by particles in all directions . Laser diffraction instruments measure the light intensity scattered (diffracted) at each angle, and the scattering (diffraction) pattern is transformed to PSD, based on the Mie theory . The size of particles influences the intensity and the angle of the light scattered, where larger-sized particles scatter light of a higher intensity at a smaller angle ; the shape of the particles is not often taken into account. The results are usually presented as the relative distribution of volume or number of particles per particle size class.
In this project, a laser diffraction instrument (Mastersizer 2000, Malvern Instruments Ltd., Malvern, U.K.) was used due to its simple operation and the full range of results obtained. It was equipped with a Hydro SM dispersion unit where water was used as the dispersing medium. Alternatively, liquid chocolate could be dispersed in vegetable oil [147, 162] or isobutanol  or isopropanol [20, 164]. However, as an oil-based dispersing unit was not available, and numerous tests were required during grinding of cocoa mass to obtain the desirable PSDs, it was more practical to keep water as the dispersing medium. Therefore, when measuring PSD of non-fat solids in CP and CM chocolate, hexane extraction to remove cocoa butter was necessary prior to measurement. The fat removal method will be described in Section 220.127.116.11. The refractive index values used in the following chapters were determined experimentally by checking the weighted residual values; if the weighted residual is less than or approximately 1%, it indicates good mathematical modelling.
Different particle size parameters  were used to describe a size distribution.
D10, D50 or D90: 10%, 50% or 90% of the particles are less than the size; 10, 50 and 90 percentiles of the cumulative volume distribution.
D32: the surface area moment mean, or the Sauter mean diameter
D43: the mass or volume moment mean, or the DeBroucker mean diameter
The Sauter mean diameter defines the average particle diameter as “the diameter of a sphere that has the same volume-to-surface area ratio as a particle of interest”, and it has advantages when the same sample of particles is measured several times . Meanwhile, the DeBroucker mean diameter is defined as “the diameter of a sphere whose surface area times the total number of particles equals the surface area per unit weight of the assemblage” . In general, the Sauter mean diameter represents the fineness of particles in terms of the specific surface area, while the DeBroucker mean diameter is based on the volume or mass of particles .
Thermal analysis – Differential Scanning Calorimetry
DSC examines the phase transition of a material by measuring heat capacity, as a function of temperature and time, in a controlled atmosphere. The thermograms provide information about chemical reactions or physical transitions that involve either endothermic (crystallisation) or exothermic (melting) processes . DSC has been widely used to identify the thermal stability of crystalline fats, and gives information about crystallisation temperature (time), melting points, solid fat content, specific heat capacity and polymorphism of fats .
In chocolate studies, a standard DSC method is also frequently applied to investigate the melting behaviours of the fat phase. The scanning speed, or rate of temperature change, plays an important role in determining the peak height and position, as well as the resolution, of measurements . A heating rate ranging from 1oC/min to 10oC/min is often used . The onset temperature (Tonset) and endset temperature (Tendset) of a melting peak indicates the temperature at which a particular polymorphic form starts and ends melting. The peak temperature (Tpeak) corresponds to the crystalline state the fat presents. Hence, the peak temperature and enthalpies help to determine specific polymorphic forms of cocoa butter by comparing the experimental and reported values. However, it has to be noted that the DSC method is indirect and is an estimation of polymorphic forms of fats, which should be confirmed with an X-ray diffractometer (XRD) .
Polymorphism – X-ray diffraction
DSC-XRD coupled techniques are commonly used to identify physical properties of lipids in the fat industry . XRD is a more direct and accurate technique to characterise crystalline structures of cocoa butter than DSC.
Figure 2-4 (Section 18.104.22.168) presents XRD diffraction patterns of different cocoa butter polymorphs. The experimental values of characteristic peak locations can be compared with the reported values of different polymorphs of cocoa butter, as summarised in Table 3-2, to determine cocoa butter polymorphic states.
In chocolate, the existence of sugar crystals complicates the XRD measurements as sugar diffraction peaks overlap with some phases of cocoa butter . Two commonly used methods to overcome this issue are: 1) removal of sugar prior to X-ray diffraction using repeated cold water rinsing, or 2) subtraction of the molten chocolate diffraction pattern from that of the solid chocolate [63, 174, 175]. For the current study, chocolate models were formulated without sugar to avoid this problem.
Surface whiteness measurement
Fat bloom is related to a change in surface appearance, and there are two main approaches used for its assessment. The first approach is performed using panels of testers: chocolate samples are evaluated by people and scored using a whiteness “scale”. However, such semiquantitative visual determination is rather subjective as results can vary due to a different “reference” level . The second approach, measurement of surface whiteness, is more commonly used in chocolate studies [96, 111].
The Whiteness index (WI) is a colour parameter based on the CIELAB colour space (L*a* b*); which is calculated using Equation 3. This system is widely used as it is independent of devices used for measurements . The L* a* b* values represent a spherical colour space and define the axis of a coordinate system, where L* refers to lightness while a* and b* define colour directions. L* has a value from 0 (black) to 100 (white), and a* (green – red) and b* (blue – yellow) range from -120 to +120 .
WI = 100 – [(100 – L*) 2 + (a*2) + (b* 2)] 0.5
In this project, a machine vision system  was used and its configuration is shown in Figure 3-5. It consisted of a digital camera (DFK 31 BF03, Imaging Source, Charlotte, NC, USA) and a lightbox in which front- or back-lighting can be applied. The upper light (front-lighting) in the lightbox was covered with a polarising sheet. The digital camera equipped with a lens (Tamron, 12VM612), which was positioned in the lightbox, took pictures of the samples. The camera was connected to a laptop via an IEEE1394 cable and could be controlled externally. A polarising filter was attached to the camera lens to reduce reflection by turning 90° relative to the polarised light from the upper light source. A Gretag colour checker (X-Rite Inc., Grand Rapids, MI, USA)) was placed in the lightbox to allow colour calibration. To calculate the area of the sample, a black metal square with an area of 1.6cm2 was placed next to the sample.
The “two-image method”  was used to determine the WI of the samples, as it has the advantage of accurate background segmentation. For each measurement, two pictures were taken, one with front-lighting and one with back-lighting. After processing the two images, the WI was automatically calculated and displayed using the software programme “LensEye” (Version 11.3.4) . Colour and size calibration was carried out during image analysis.
Fat bloom is actually a human, visual perception of chocolate quality. However, as it is directly related to changes in surface microstructure, microscopy was used to identify corresponding changes. Visualisation techniques such as scanning electron microscopy (SEM) [77, 84, 182], atomic force microscopy [78, 100, 101], stereoscopic binocular microscopy  and light microscopy [68, 92] have been used in other studies to examine the changes in chocolate surface microstructure. The observations of fat bloom vary by type, and the microstructure of fat bloom is influenced by processing and storage conditions, as well as the composition of chocolate products.
Light microscopy is a ubiquitous and versatile tool in food science as it magnifies images of very small samples, providing detail unavailable to the naked eye. A light microscope is easy to use and samples can be viewed under ambient conditions. In addition, it preserves full colour information which aids interpretation and visualisation of samples. Sometimes, stains are used to mark different substances. However, light microscopy has limitations, such as fixed magnification lenses in compound microscopes and limited depth of focus . Stereomicroscopes and compound microscopes are the two principle classes of light microscope used in food studies . The stereomicroscope creates stereoscopic image information, and has low to moderate magnifications (5× to 200×). Compound microscopes are able to achieve high resolution with magnifications between 10× and 1000×. However, the working distance of a compound microscope is shorter than that of a stereomicroscope. In this project, a Nikon AZ100 multizoom light microscope and a Nikon Eclipse 80i fluorescence microscope were used to examine the fat bloom on chocolate surfaces.
An SEM uses an electron beam instead of light to create images of sample surfaces at high magnification. The electron column is under high vacuum (10-6Torr or lower) . The electrons can penetrate the samples releasing energy, and some of the energy, in the form of ejected or scattered electrons, is collected by a detector. Therefore, an image can be generated using these signals to reveal the surface morphology. In this study, an environmental SEM (ESEM) and a cryogenic SEM (cryo-SEM) were used. The specimen chamber in a normal ESEM can be maintained under low vacuum (0.1-20Torr ) which allows samples with poor conductivity, like chocolate, to be imaged without coating through a conducting metal layer. This low vacuum makes ESEM suitable for food materials with high vapour pressure which would otherwise have to be treated prior to imaging. Hence, the ESEM has advantages for capturing images of foods in their native state. An ESEM was used to examine the morphology of chocolate surface and the shape of fat bloom. Cryo-SEM is also widely used in food research, as cryo-fixation, by liquid nitrogen, can maintain the structure of a hydrated sample. It has an advantage over ESEM for solid chocolate due to its higher resolution.
TABLE OF CONTENTS
Table of Contents
General Indole Introduction
Mushroom-Derived Natural Products
C2-Substituted Indole Alkaloids from the Tricholoma Genus
First Generation Approach to Sciodole
Proposed Synthesis of (±)-Sciodole
Synthesis of 5-Hydroxy-2,4-dimethylindole (205)
Synthesis of N-linked Dimer 217
Second Generation Approach to Sciodole
Proposed Biomimetic Synthesis of (+)-Sciodole
Proposed Route to Bioinspired Coupling Partner 323
Synthesis of Weinreb Amide 326
Metalation of Pyrroles
Revised Approach to Tetrahydroindole 343
Revised Approach – Heck Cyclisation
SN2 Addition of Indole 185 to Tetrahydroindole 402
SN1 Addition of Indole 185 to Tetrahydroindole 402
Amination by Hydrogen Autotransfer
SN2 Addition of Indoline 317 to Pyrrole 397
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SYNTHETIC STUDIES TOWARDS TRICHOLOMA-DERIVED 2-METHYLINDOLES