Analysis of Vanilla Compounds in Vanilla Extracts and Model Vanilla Ice Cream Mixes Using Novel Technology

Thesis

Presented in Partial Fulfillment of the Requirements for the Degree Masters of Science in the Graduate School of The Ohio State University

By

Michael Dennis Sharp, B.S.

Graduate Program in Food Science and Technology

The Ohio State University

2009

Thesis Committee:

W James Harper, Advisor

Mike Mangino

David Min

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Copyright by

Michael Dennis Sharp

2009

Abstract

Vanilla is an important flavor for many foods. Vanilla beans have been shown to

contain over 200 compounds, which can vary in concentration depending on the region

where the beans are harvested. Several compounds including vanillin, p- hydroxybenzaldehyde, guaiacol, and anise alcohol have been found to be important for the aroma profile of vanilla. Because of the complexity of the vanilla aroma profile there are many gaps in the current understanding of how vanilla compounds are volatilized in food systems. Several novel analytical technologies are under investigation for their ability to aid in analyzing compounds in vanilla extracts and in model ice cream mixes.

Although several methods are currently available, a need exists for a more rapid

and sensitive method to analyze the concentration of important compounds in vanilla

beans and extracts. Selected ion flow tube mass spectroscopy (SIFT-MS) and fourier

transform infrared (FTIR) spectroscopy are two methods that have potential for rapid

discrimination and characterization of vanilla extracts. Vanilla extracts made with beans

from different countries of origin including Uganda, Indonesia, Papua New Guinea,

Madagascar, and India were analyzed using both methods of analysis. Pirouette

statistical software, a multivariate data analysis tool, was utilized to determine the

differences between samples. Differentiation between samples was observed for all

extracts, with Papua New Guinea and Indonesian samples differing the most from other

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samples. The top 5 compounds found to be most responsible, based on discriminating

power, for the differentiation between samples were vanillin, anise alcohol, methylguaiacol, p-hydroxybenzaldehyde, and p-cresol. The top wavenumbers found to

be most responsible, based on discriminating power, for the differentiation between

samples were 1523, 1573, 1516, and 1292 cm-1. These wavenumbers have been

associated with vanillin and vanillin derivatives in previous studies. Both methods have

shown to be quick and reliable methods for analyzing vanilla extracts which could be

utilized as a quality assurance tool in the fragrance, flavoring, and food industries.

Flavor-food interactions have been shown to be important to the overall flavor

profile of many foods including ice cream. Vanilla flavor, being the top flavor of ice

cream, has been shown to be reduced in intensity due to protein and fat in ice cream. A

research gap exists in understanding how vanilla compounds besides vanillin, the most

abundant vanilla compound, and other ingredients besides protein and oil interact. A

3x3x2x2x2 full factorial design with oil, protein, sugar, stabilizer, and corn syrup as

factors was conducted. Each mixture of ice cream ingredients was analyzed for

headspace concentration of vanilla compounds using a selected ion flow tube mass

spectrometry (SIFT-MS) technique. Although the most amount of compounds were

statistically significantly effected by protein and oil, other ingredient and interactions

between ingredients effected the headspace concentration of a variety of vanilla compounds. By changing the formulation of an ice cream mix, the vanilla flavor profile is clearly altered.

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Acknowledgements

This work would not have been possible without the tremendous help, advise, encouragement, and trust from many kind individuals. Firstly my advisor Dr. Harper for all of his support and expertise as well as the freedom he gave me to explore my interests.

I would also like to thank all of the research associates and lab mates for advise and help working through problems. I couldn’t have done the research I did without the help of

Virginia Dare for providing all the samples I needed, or the many knowledgeable and skilled people at Syft technologies. I mostly would like to thank my wife and daughter for being so supportive, trusting, sacrificing and willing to allow me this opportunity.

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Vita

2001………………………………..…………………………….West Jordan High School

2006-2008……………….…………………….………Food Scientist, Casper’s Ice Cream

2007………………………….…..B.S. Food Science and Nutrition, Utah State University

2008-2009……………………Graduate Research Assistant, Department of Food Science

and Technology, The Ohio State University

2009-Present………………………………………..Product Scientist, Dreyer’s Ice Cream

Publications

Sharp MD, McMahon DJ, Broadbent J. Comparative evaluation of yogurt and low-fat

Cheddar cheese as delivery media for probiotic Lactobacillus casei. J Food Sci

73(7):M375-M377

Field of Study

Major Field: Food Science and Technology

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Table of Contents

Abstract……………………………………………………………………………..……..ii

Acknowledgements……………………………………………………………………….iv

Vita………………………………………………………………………………………...v

Chapter 1: Literature Review……………………………………………………………...1

Chapter 2: Rapid Discrimination and Characterization of Vanilla Extracts Made From

Countries of Different Origin by FTIR-ATR and SIFT-MS………………………….…49

Chapter 3: Flavor-Ingredient Interactions Between Vanilla Compounds and a model Ice

Cream Mix……………………………………………………………………………….80

Appendix A: Vanilla Compound Concentrations In Vanillas Of Unique Countries Of

Origin………………………………………………………………….. …………...…109

Appendix B: Estimates and P-Values For Measured Parameters For All Ingredients And

Ingredient Interactions………………………………………………………………….115

References……………………………………………………………………………....153

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CHAPTER 1

Literature Review

1.1 Vanilla

1.1.1 Vanilla Overview

Although vanilla is the second most expensive spice, next to saffron, it is still the

most widely used (Ranadive 2005). Vanilla has a very versatile flavor that is acceptable

at almost any concentration (Korthou and Verpoorte 2007). Because vanilla is such a

versatile and well accepted flavoring it is used readily in the food, beverage, cosmetic,

and tobacco industries (Korthou and Verpoorte 2007). In the United States alone 1350

metric tons of cured vanilla beans are imported yearly and over 2100 metric tons are

imported globally per year (Ranadive 2005).

Natural vanilla flavorings are extracted from the plant genus Vanilla (Rao and

Ravishanker 2000). Two species from this genus have been used and approved in most countries to create vanilla flavoring including Vanilla planifolia and Vanilla tahitensus, however Vanillus planifolia is more widely used because of its pod quality and yield

(Sinha and others 2008). V. planifolia was originally cultivated in Mexico by the Aztecs

(Sinha and others 2008). After the arrival of the Spaniards in Mexico and the discovery of artificial pollination techniques, V. planifolia is now cultivated in many tropical climates that fall between 25˚ above and below the equator (Havkin-Frenkel and Dorn

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1997). Today the principle vanilla cultivating country is Madagascar which exports

1000-1200 tons of cured vanilla beans per year (Ranadive 2005). Other countries that

export a significant amount of vanilla include Indonesia, the Comoro Islands, Uganda,

India, Tonga, Mexico and Tahiti (Ranadive 2005).

Vanilla planifolia is grown on large looping vine fields with about 2000 vines per hectare (Ranadive 2005). Vanilla thrives in warm moist tropical climates, but also needs plenty of shade and support. Vanilla also has shallow roots that require well drained soils

(Ranadive 2005). At about 8 to 9 months post pollination, Vanilla beans are harvested.

At the time of harvest however, green vanilla beans are flavorless and only contain glucosides of flavor compounds (Havkin-Frenkel and Belanger 2007). Vanilla’s characteristic flavor is developed during a process called curing as glucosides are released.

Curing is the process in which the vanilla aroma develops in the pods or beans.

This process for aroma development is carried out in dried vanilla beans and allows chemical and enzymatic reactions to occur (Dignum and others 2001). Although most vanilla cultivating countries have developed their own curing process, all processes

generally consist of four steps: scalding, sweating, drying and conditioning (Dignum and

others 2001). During these curing processes glycosides are hydrolyzed, and other

compounds undergo oxidation or polymerization (Havkin-Frenkel and others 2005).

Although cured vanilla pods themselves are sometimes used for flavoring, it is much more common that vanilla be used for flavoring as an extract. Vanilla extracts are prepared by either percolating cured beans with a water and ethyl alcohol, or by

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macerating whole beans and then circulating ethanol over the pods under vacuum (Sinha

and Others 2008). The latter method is able to increase the concentration or “fold” of the

extract. Each fold of a vanilla extract is defined as 13.35 oz of extractable material per

gallon of solvent (CFR 169.3). The Code of Federal Regulations (169.175) further

defines a vanilla extract as having at least 35% ethanol, and contains one or more of the

following ingredients: Glycerin, Propylene Glycol, Sugar, Dextrose, or Corn Syrup.

Vanilla flavoring is defined as an extract that meets the same requirements as vanilla

extract, but does not contain at least 35% ethanol (CFR 169.177).

1.1.2 Vanilla Flavor Compounds

Over 200 compounds have been found to be responsible for the flavor profile of

vanilla, with vanillin being by far the most abundant (Sinha and others 2008). Some

vanilla beans have shown concentrations of up to 2% vanillin. The other top vanilla

compounds by concentration are p-hydroxybenzaldehyde, p-hydroxybenzyl methyl ether,

and acetic acid (Dignum and others 2001). Perez-Silva and others (2006) showed that several other compounds in low concentration including acetovanillone, vanillyl alcohol,

and p-hydroxybenzyl alcohol have high intensity vanilla-like sensory notes. They also showed in the same paper that at least 20 other compounds, without vanilla-like sensory notes, are responsible for the overall aroma of the vanilla bean. Since each cultivating

region occupies different curing methods, the concentrations of these flavor compounds

varies by region, and is thus responsible for the distinct aroma that accompanies beans

from each region (Ranadive 1992).

Since the demand for vanillin, the chief compound in vanilla, is over 12,000 tons

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per year, and natural vanillin production can only produce around 1800 tons per year,

artificial vanillin production has become important (Dignum and others 2001). Synthetic

vanillin production is traditionally accomplished through a reaction with guaiacol and

glyoxylate, although other methods involving cell cultures or microorganisms are being

used as a way to preserve a “natural” additive claim (Dignum and others 2001).

1.1.3 Vanilla Analysis

Because natural vanilla is so costly and has a limited supply, and as synthetic

vanillin is readily available, efforts are being made to both better synthetically match

natural vanilla, and also to find ways of detecting adulteration. For both purposes it is

vital that reliable and practical analytical techniques for determining chemical

compounds in vanilla are found (Sinha and others 2008). Several chromatographic

methods for the identification and quantification of chemical compounds have been used

in vanilla research including: Thin layer chromatography (TLC), gas chromatography

(GC), high performance liquid chromatography (HPLC), and capillary electrophoresis

(CE), (Sinha and others 2008).

One of the earliest separation and identification techniques for vanilla compounds was using paper chromatography. TLC is rapid, easy to handle, and economical. Anwar

(1963) identified vanillin and its derivatives using paper chromatography. Rao and

Ravishankar (1999) successfully identified vanilla flavor metabolites using silica plates.

Recently Gerasimov and others (2003) used TLC to identify vanillin and ethyl vanillin in food flavorings. High performance TLC (HPTLC), however, has largely replaced TLC as an analytical method (Sinha and others 2008).

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GC has advantages over other chromatographic techniques for separating volatile

mixtures such as high efficiency and high resolution. It can also be used for quantitative

analysis. GC complemented with mass spectrometry (MS) allows for better quantitation

and analysis of vanilla volatiles and has been the means of identifying more than 150

compounds (Sinha and others 2008). Galetto and Hoffman (1978) used GC-MS to

identify benzyl ethers in vanilla extracts. Ramaroson-Raonizafinimanana and others

(1997) identified hydrocarbons from several species of vanilla, and Perez-Silva and

others (2006) identified 65 volatile compounds including 26 odor active compounds

using GC-MS and GC olfactometry. GC-MS has also been used to discriminate between different types of vanilla extracts and flavorings (Sosteric and others 2000).

HPLC is one of the most powerful and preferred techniques for quantifying

organic molecules because of its simplicity, sensitivity, precision and selectivity. HPLC can be made more selective by the use of different stationary phases, mobile phases, and

detectors (Sinha and others 2008). Ranadive (1992), Leprecht and others (1994), Voisine

and others (1995), Negishi and Ozawa (1996), and Dignum and others (2004) all used

HPLC to identify compounds in vanilla samples. Generally when working with vanilla

compounds, a reverse phase column is used with a polar organic solvent as the mobile

phase (Sinha and others 2008). Elution times from literature vary between 7-36 min at

detection wavelengths of 254-340. HPLC has been used successfully in both

compositional analysis as well as adulteration detection (Ehlers 1999).

CE has several advantages over HPLC such as speed, efficiency, reproducibility, small sample volume and low consumption of solvent (Sinha and others 2008). Because

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of these advantages CE is gaining popularity as a technique for analyzing chemical constituents in vanilla. Panossian and others (2001) developed a method using CE to analyze vanillin, syringaldehyde, coniferaldehyde, and sinapaldehyde in brandy and wine with recoveries between 99.9% to 107.7%. A more recent capillary technique is micellar electrokinetic capillary chromatography (MEKC) and has been used to identify nine vanilla constituents and three probable adulterants (Butehorn and Pyell 1996). Pyell and others (2002) showed that MEKC is a better alternative to HPLC because of its shorter analysis time and high resolution.

1.2 Ice Cream

1.2.1 Ice Cream Overview

Over 1.5 billion gallons of ice cream and related frozen desserts were produced in the United States for the year 2007 (IDFA). Ice cream sales and technology have progressed rapidly since the first iced dairy products mentioned in 12th century Chinese literature or the first use of salt to ice by the Portuguese in 1525 (Arbuckle 1986). In

1768 a manuscript entitled, “The Art of Making Frozen Desserts” was written in Paris that proposed formulas for what the authors penned, “food fit for the gods” (Marshall and others 2003). Because ice cream is so desirable the industry gained over 26 billion dollars in sales in 2008 (IDFA).

Ice cream is a complicated colloidal mixture of air, water, milkfat, nonfat milk solids, sweeteners, stabilizers, emulsifiers, and flavors (Marshall and others 2003). An ice cream mix is the blend of ingredients used to supply these constituents before it is frozen and air is incorporated. These constituents are present in ice cream in a wide

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variety of proportions within an acceptable range. The code of federal regulations has defined ice cream to contain “1.6 pounds of solids per gallon, each gallon must weigh at least 4.5 pounds, there must be 20 percent total milk solids, and 10 percent milkfat” (CFR

121.135).

Ice cream is a complex colloidal system in that it is both an emulsion and foam.

(Goff 1997, Rokenkohl and Kohlus 1999). Ice cream displays properties of an emulsion as fat particles are surrounded by the proteins and emulsifiers and dispersed throughout the serum phase. Ice cream displays properties of a foam when frozen as air bubbles are incorporated in the ice cream matrix of partially coalesced and crystallized fat, which is the basis for the foam structure (Goff 1997).

One of the most important sensory aspects of ice cream is texture, which is provided by the ice cream structure (Granger and others 2005). The structure of ice cream also plays a role in the meltdown characteristics, rigidity, and dryness of the product

(Bollinger and others 2000). Fat, air, ice crystals, proteins, sweeteners, emulsifiers and stabilizers help to create the body of the ice cream (Segall and others 2002).

1.2.2 Ice Cream Constituents

Ice Cream is made up of many constituents including milkfat, protein, sweeteners, emulsifiers, stabilizers, and other constituents. Each component plays a specific role in the development of ice cream from mix to frozen product.

1.2.2.3 Milkfat

Milkfat functions in ice cream to provide unique flavor, to carry fat-soluble flavors, to lubricate the mouth, to effect the structure and texture of the ice cream, and to

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aid in lubricating the freezer barrel during processing (Marshal and others 2003). Sources of milkfat in ice cream include, milk, cream, butter, anhydrous milkfat, frozen cream, dry whole milk, liquid and dry buttermilk, and concentrated or condensed milk (Marshall and others 2003). Milkfat is complex and can contain up to 400 different types of fatty acids

(Jensen and others 1991). The fatty acids can be short chain fatty acids such as caproic, caprylic, and butyric (Marshall and others 2003). Milkfat also contains about 27% monounsaturated fatty acids as well as 2.25% diacylglycerols, and 1.11% phospholipids

(Jensen and others 1991). Ice cream must have a minimum fat content of 10% although most premium ice creams contain 14-18% and some light, low fat, or fat free ice creams contain less than 10% fat (Marshall and others 2003). The fat content is an indicator of the perceived quality of the ice cream. Limitations on the amount of milk fat in ice cream include cost, a hindered whipping ability, excessive richness, and a high caloric value (Marshall and others 2003).

Fat is important in order to provide the texture, mouthfeel, and body of the ice cream. Fat also helps with minimizing the rate that the ice cream melts and promotes a more rigid structure (Bolliger and others 2000). Specifically, fat helps to hold the air bubbles within the system by building a network of fat that surrounds the incorporated air

(Bolliger and others 2000). This network of fat is formed through the clumping or clustering of fat that takes place known as partial coalescence. Partial coalescence is described as the irreversible agglomeration of fat globules, joined by a combination of fat crystals and liquid fat (Goff and others 1999). Walstra (1996) described partial coalescence as the process where fat globules come together, with some globules being

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partially crystallized due to rupture caused by added shear, creating a solid “gel like” matrix of partly clumped fat. In order to prevent more clumping, forming larger fat

aggregates, small fat crystals form on the interior of the fat globule and allow for only

partial coalescence or flocculation (Segall and Goff 2002). Initially the fat globules, are not attracted to each other because of their charge. However, during homogenization the globules are forced closer together making them more susceptible to collide with each other (Marshall and others 2003). The fat globules will come together if the liquid portion on the interior of the globules blends with each other (Marshall and others 2003). This partially coalesced fat matrix can then become entrapped between the air bubbles and the ice crystals with help of proteins and emulsifiers that are attached to the air bubble’s outer surface (Goff 1997). Destabilization of the fat globule helps to provide a drier, creamier texture, improves the melting characteristics, and helps to stabilize the air bubbles and prevent shrinkage (Zhang and Goff 2005). Partial coalescence of fat is affected by the emulsifier, shear during whipping, overrun, and amount of ice produced can play a role (Bollinger and others 2000).

1.2.2.2 Protein

Proteins in ice cream generally comes from milk sources which contains whey

proteins and caseins which are comprised of alpha, beta, and gamma caseins as well as

the beta-lactoglobulin, serum albumin, and immune globulin (Marshall and others 2003).

The most common sources of protein in ice cream are from the milk, cream, and non fat

dry milk (NFDM). NFDM can be replaced with dried buttermilk, whey concentrates and

isolates, or other dried and concentrated milk products (Marshall and others 2003).

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Proteins contribute to the development of structure in ice cream including

emulsification, whipping, and water holding capacity (Schmidt 1994). Before

homogenization, protein is critical in the mix because of its emulsification properties, but

after homogenization is replaced by small molecule surfactants in order to promote

partial coalescence (Bolliger and others 2000). Also, proteins, because of their ability to

form foams, are important for stabilizing the air interface in ice cream, and preventing shrinkage from collapsing of air cells (Turan and others 1999). Milk proteins also interact with water, and their hydration is responsible for increased viscosity, ice crystallization, ice crystal stability, and solute mobility (Flores and Goff 1999).

1.2.2.3 Sweeteners

Sweeteners make up 12 to 20% of the mix and are added to ice cream for several

reasons. The most important reason is to supply sweetness, but sweeteners also improve

the overall taste of the product, reduce the freezing point, and lower the number of ice

crystals that form in ice cream (Flores and others 1999, Clarke 2004). Sucrose is the most

often used sweetener in ice cream. It functions to lower the freezing point as well as has

a relatively high amount of sweetness and is made up of 99.9 percent solids (Marshall

and others 2003). Sucrose has two commercial sources, sugarcane or sugar beets, with

most of the sugar used in ice cream coming from sugarcane (BeMiller and others 1996).

Many different types of sweeteners are used in ice cream and include: dextrose, fructose,

sucrose, lactose, maltose, honey, invert sugar, brown sugar, maple syrup, high fructose

corn syrup, corn syrup, and molasses (Marshall and others 2008).

Corn syrup is the second most used sweetener that is added to ice cream, added as

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dried corn syrup solids or corn syrup (80% solids), and also provides sweetness and

lowers the freezing point of the ice cream (Marshall and others 2003). The use of corn

syrup in ice cream adds a cost saving sweetener with high functionality. Corn syrup

contributes to a smoother, firmer, more chewy texture. Corn syrup provides better melt

down characteristics, accentuates fruit flavors, and reduces heat shock which extends

shelf life (Goff and others 1990). The extent to which corn starch is hydrolyzed to make

corn syrup is termed the dextrose equivalent or DE. As the DE of corn syrup is increased

the sweetness increases, the molecular weight decreases, the freezing point of the mix

decreases, as well as the viscosity decreases. The DE of the corn syrup added to ice

cream can be optimized for the intended functionality.

Lactose is also found in ice cream because of the many milk ingredients as lactose

is the main form of sugar found in milk. Lactose does not provide sweetness, but

functions in ice cream to decrease the freezing point to provide added solids (Marshall

and others 2003). However, too high a concentration of lactose will form lactose crystals

as it is freeze concentrated during processing. Lactose crystals are responsible for the sandy defect sometimes found in ice cream with especially high concentrations of whey solids (Marshall and others 2003).

1.2.2.4 Emulsifiers

Emulsifiers in ice cream include natural emulsifiers found in milk, casein and

whey proteins, plus added emulsifiers help to maintain the structure of ice cream (Gelin

and others 1994). The traditional ice cream emulsifier was egg yolk, but has now been

replaced for the most part by mono- and di-glycerides and sorbitan esters (Marshall and

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others 2003). Mono- and di-glycerides are derived from partial hydrolysis of fat and are

more functional at the air interface, while sorbitan esters are fatty acids attached to a

sorbitol molecule and are more active at the fat interface promoting partial coalescence

(Marshall and others 2003).

During homogenization both the protein and added emulsifiers adsorb to the fat

globule interface (Gelin and others 1994). Added emulsifiers are favored because of their increased ability to lower the interfacial tension of the fat/serum emulsion. Because of

this, added emulsifiers are the key components that promote fat destabilization and

minimize proteins on the fat globule (Goff and others 1987). By replacing protein at the

fat/water interface, it reduces the stability of the fat globule, allowing for partial

coalescence of the fat, which can then entrap air bubbles during the whipping process

(Barford and others 1991). The end effects of emulsifiers in ice cream include:

promoting nucleation of fat during aging, thus reducing aging time, improving the whipping quality of the mix, producing a dry and stiff ice cream, increasing resistance to shrinkage and rapid meltdown, increasing the resistance to coarse/icy textures, and providing a smooth texture in the finished product (Marshall and others 2003).

1.2.2.5 Stabilizers

Stabilizers are another ingredient that is commonly used in the ice cream industry

to help improve the properties of ice cream. Stabilizers are used to minimizing the

separation of the serum phase during the meltdown process, adding to the viscosity of the

mix, enhancing the development of the foam structure, to decrease the amount of lactose

and ice crystal growth caused by temperature fluctuation during storage, to reduce

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moisture migration from the product to the package and air, to inhibit shrinkage of the ice

cream volume in storage, and to make the ice cream more resistant to melting (Bollinger

and others 2000, Flores and Goff 1999). Stabilizers’ functionality is based on binding water through hydrogen bonding to many hydroxyl groups (Clarke 2004). Ice creams with stabilizers have denser serum phases providing space between air bubbles and preventing ice crystals from nucleating (Flores and Goff 1999).

Stabilizers used in ice cream include locust bean gum, guar gum, carrageenan,

pectin, sodium carboxymethyl cellulose, and microcrystalline cellulose (Marshall and

others 2003). Guar gum and locust bean gum are both used similarly to add viscosity to

the mix, however locust bean gum has a higher functionality, but at a higher cost

(Marshal and others 2003). Carrageenan in ice creams function to minimize the milk

proteins and polysaccharide separation in the serum phase. This functionality is related

to the three dimensional network that forms with kappa and iota carrageenan and casein

(Clark 2004). Carboxymethyl cellulose or CMC is easily dissolved, binds and holds water

very well, and is best when used synergistically with other gums, such as locust bean,

guar, or carrageenan (Marshall and others 2003). Microcrystalline cellulose is good at

binding water and creates a mouthfeel similar to that of fat (Marshall and others 2003).

1.2.2.6 Other constituents

Water in ice cream comes from fluid dairy ingredients and syrups. Water is the

solvent for the continuous phase. In frozen ice cream it is present as both a liquid and a

solid. The solid to liquid ratio of water in ice cream is an important factor to determine

the firmness of the ice cream (Marshall and others 2003).

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Air is dispersed in ice cream through the fat-in-serum emulsion. The interface

between water and air is stabilized by unfrozen protein, emulsifier, and partially coalesced fat (Marshall and others 2003). The amount of air incorporated into the ice cream is described by the amount of volume increase from the mix, or overrun. The amount of air in the ice cream effects both the quality and profits, which makes monitoring of overrun critical in the ice cream industry (Marshall and others 2003).

Other components that make up the composition of ice cream include minerals, salts, and vitamins. These components can be added or are naturally a component of the milk ingredients such as citrates, phosphates, oxides, and water and oil soluble vitamins

(Marshall and others 2003).

1.2.3 Ice Cream Making Procedure

An ice cream make procedure includes: blending, pasteurization, homogenization,

cool aging, freezing, and hardening. Each step in the make procedure is necessary in order to obtain the right body, consistency, and desired texture needed to meet consumer

demands.

1.2.3.1 Blending

The first step of any make procedure is mixing of the ingredients. In this step

ingredients are mixed together into a vat and shear is applied through stirring as the

product is heated (Arbuckle 1986). Blending is done before high temperature short time

(HTST) pasteurization in order to minimize burn on of unincorporated ingredients.

Blending is usually done in conjunction with vat pasteurization. The order of addition of the ingredients is important because it affects the overall quality of the ice cream

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(Arbuckle, 1986). Initially, the milk and cream go into the mixing vat first to be heated

and thoroughly mixed (Marshall and others 2003). Dry ingredients are then added, which

include NFDM, sugar, stabilizers, emulsifiers and other desired constituents (Marshall

and others 1995). All dry ingredients must be added to the mixer before the temperature

reaches 50°C to ensure that the ingredients are evenly dispersed throughout the system

and to allow time for the vat to reach proper processing temperatures for each ingredient

(Marshall and others 2003).

Some dry ingredients, especially gums and emulsifier, require that they be mixed

with sugar before being added to the vat in order to allow for better hydration and prevent

clumping when placed with the liquid ingredients (Marshall others 2003). Once all the

ingredients are blended, the mix must remain in the vat until it has reached the temperature to which, the ingredient with the highest melt temperature has been reached, which is most often the emulsifier or the stabilizer (Marshall and others 2003).

1.2.3.2 Pasteurization

The main purpose of pasteurization is to ensure that the ice cream will be safe for consumption. Because pasteurization is critical to the health of the consumer, federal

standards have been set, and are closely monitored by local and federal agencies (21 CFR

135). Pasteurization is the process where heat is used with the purpose of lowering the

health concerns that are associated with pathogenic microorganisms that are commonly

found in milk with minimal amounts of physical, chemical or sensory changes to the food

(Lewis and Heppell 2000). Pasteurization is used to inhibit the growth of vegetative cells

and to destroy pathogenic bacteria. Specifically, pasteurization targets pathogenic

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Mycobacterium tuberculosis, Campylobacter, Salmonella, Listeria monocytogenes, and

Escherichia coli 0157:H7 (Lewis and Heppell 2000). For ice cream, L. monocytogenes is

one of the key pathogens that is targeted, because the added ingredients such as sugars can protect it making it harder to destroy (Lewis and Heppell 2000). Pasteurization has

also been shown to denature hydrolytic enzymes that negatively effect milk quality

(Marshall and others 2003).

The two main types of pasteurization used with ice cram are batch pasteurization

and HTST pasteurization. Batch pasteurization, also known as low temperature long time

(LTLT) is done in a large vat where ingredients are added and heated to a minimum

temperature of 69˚C for thirty minutes (Lewis and Heppell 2000). LTLT pasteurization

requires longer processing times, but can reduce some cooked flavor, and increases

hydration of proteins and stabilizers, which improves body and texture, increases

resistance to heat shock, and reduces the time needed for aging the mix (Marshall and

others 2003). The most commonly used method of pasteurization is the HTST method,

which has advantages of being a continuous method, and by allowing for regeneration

(Lewis and Heppell 2000). HTST pasteurization uses a plate heat exchanger, diversion

valves, and holding tubes, which allows for a larger quantity of liquid that can flow

through the setup (Lewis and Heppell 2000). HTST pasteurization heats the ice cream

mix for at least 15 seconds at 79°C. The main advantage of HTST pasteurization is the ability to heat up and cool down the ice cream mix very quickly, it can handle increased volumes of product, it can be automated, and uses a regeneration process that allows the product to heat and cool itself which reduces energy costs (Lewis and Heppell 2000).

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Although the main purpose of pasteurization is to destroy pathogenic bacteria, there are also other advantages to the ice cream industry for using pasteurization.

Pasteurization also helps bring solids in to solution, aids in blending by melting the fat and decreasing viscosity, improves the flavor of the mix, extends the shelf life of the mix from a few days to a few weeks, and increases the uniformity of the product (Marshall and others 2003).

1.2.3.3 Homogenization

Homogenization is an important part of the ice cream making process for many reasons; however, the main goal of this step is to alter the size of the fat globule (Lucas et and others 2005). Homogenization reduces the size of the globule and makes them more consistent and similar in overall shape (Spreer, 1998). In a review done by Goff (1997), he found that homogenization decreases the mean fat globule diameter from 3.3 to 0.4 micrometers, expands the surface area of the globule from 0.08 to 0.75 m2 mL-1, and increases the number of droplets from 0.015 to 12 micrometers-3.

Homogenizers can either be a single stage or two-stage homogenizer (Lewis and

Heppell 2000). In a single stage homogenizer, the fat globules are forced through a very small valve at about 13.8 MPa and are broken down into the smaller particles. These particles, however, can clump together again and become similar to the size prior to homogenization (Lewis and Heppell 2000). With the second stage which is done at about

3.45 MPa, those fat globules that re-clump are broken again to make a more uniform globule and reduce the viscosity (Lewis and Heppell 2000). Homogenization is most effective at temperatures above 60˚C, and because of this most homogenizers are

17

attached to the pasteurizer so that when the product comes out of the holding tubes, it is

at the right temperature for the breaking down of the globules (Marshall and others

2003). Homogenizing the ice cream mix increases the surface area exposing more of the

fat globule membrane and promoting more destabilization by decreasing the interfacial

tension of the fat globule (Goff 1997).

The advantages of homogenization include that more of the surface area of the

globule is exposed, providing a better texture because the globules are more uniform,

allows for better digestibility of the fat, enhances the destabilization of the fat, promotes

foam stability, and provides an overall softer texture (Goff 1997, Spreer 1998). The

disadvantages of homogenization include that more area is exposed for microbial growth

and enzymatic attack if not properly treated and is more susceptible to light, which can

cause off colors and flavors, and also excessive homogenization can lead to churning of

the fat (Spreer 1998).

1.2.3.4 Cool Aging

After homogenization, the mix is run through a plate cooler to reduce the temperature of the mix to about 4˚C. The mix is then stored and agitated in vats for a minimum of four hours at 2 to 4°C in a process called cool aging (Goff 1997). Cool aging is critical in order to allow the fat to crystallize, which encourages partial coalescence.

Crystallized fat is able to pierce neighboring fat globules allowing their interior liquids to

come together for partial coalescence (Goff 1997). Cool aging also allows for hydration

of the stabilizers and proteins, gives time for the proteins and emulsifiers to adhere to the

fat globules, which make the fat network during the freezing process (Marshall and others

18

2003). Cold temperatures are also important for minimal microbial growth during storage of the mix after pasteurization (Marshall and others 2003).

1.2.3.5 Freezing

Freezing is the process of forming ice crystals, destabilizing the fat, and incorporating air into the ice cream mix. Freezing can either be performed by a continuous freezer or a batch freezer. For both processes, ice cream mix enters a freezing barrel that is chilled with a liquid refrigerant (Marshall and others 2003). The mix is whipped with a dasher that agitates the mix by rotating the blades that are attached to it

(Marshall and others 2003). The dasher provides added shear and the blades are used to scrape the interior sides of the barrel (Marshall and others 2003). Ice crystals are formed and scraped from the side by the dasher blades to help create the texture of the ice cream

(Marshall and others 2003). At this point there is a reduction in the viscosity due to the structure of the ice cream being disrupted and the air is mixed in because of the rotation of the blades (Marshall and others 2003).

The mix enters the freezing step slightly above its freezing point, and so the sensible heat must first be removed in order to begin converting water to ice crystals

(Marshall and others 2003). As ice crystals are formed they are subject to nucleation or the migration of water to form bigger ice crystals (Goff, 1997). As the water begins to freeze the other additives begin to congregate, which help to reduce the overall freezing point of the mix because both the sensible and latent heat are being eliminated (Marshall and others 2003). Because of this there will always be apart of serum phase that will not freeze (Goff 1997). Typically ice cream is drawn from the freezer when 50% of the

19

water is converted to ice (Marshall and others 2003).

During freezing partial coalescence of the fat globules is increased by the shearing

action of the ice cream freezer dasher. Partially coalesced fat globules migrate towards

the air cell interface and provide structure to the unfrozen phase of the mix as they help to stabilize the air cells being incorporated into the ice cream (Marshall and others 2003).

The extent of fat stabilization is dependent on the amount and type of emulsifier, the type of freezer (continuous freezers show more fat destabilization), the time allowed to cool age, and the nature of the fat (Marshall and others 2003). The amount of fat destabilization can be measured by light scattering techniques as in Bollinger and others

(2000).

The principles of air incorporation in to ice cream are generally the same

regardless of the method for freezing. Air cells start out as large entities and are broken

by shearing during freezing (Marshall and others 2003). In continuous freezers air is

injected in the form of small bubbles under pressure, whereas batch freezing operations

rely on the folding and mixing of the ice cream mix to incorporate air. The formation of

ice is crucial for air incorporation in to the mix, because the capacity to reduce air cell

size depends on increased viscosity during freezing (Marshall and others 2003). The size

of the air cells vary from a few microns to over 100 microns (Chang and Hartel 2002).

Factors that determine freezing time include freezer type and setup, wear of the

equipment including blades and dasher, speed of dasher rotation, temperature of coolant,

speed at which the coolant moves throughout the barrel, amount of oil on the machinery,

desired overrun, draw temperature, and speed to which the ice cream is removed from the

20

freezer (Marshall and others 2003). Other factors that affect time also include the

ingredients in the mix, point at which those ingredients freeze, processing of the mix, and

type and quantity of the flavoring (Marshall and others 2003).

1.2.3.6 Hardening

Once the ice cream is removed from the barrel and packaged in the freezing step,

the ice cream is immediately placed into a storage freezer, where it undergoes the

hardening process (Marshall and others 2003). In storage, ice creams are cooled to

temperatures ranging from -18 to -30°C (Marshall and others 2003). This allows for rapid

freezing, which has shown to produce smaller ice crystals, even though nucleation does

not continue to occur once it is pulled from the batch freezer (Marshall and others 2003).

At this point it is very important that there is minimal temperature fluctuation in order to

minimize recrystallization that can occur during a freeze-thaw cycle (Marshall and others

2003).

1.3 Flavor-Food Interactions

1.3.1Flavor-Food Interactions overview

One of the most important factors that influence the consumers’ perception of

foods is flavor. Flavor is defined as the experience of the combined perception of

compounds responsible for taste, aroma, and mouth-feel (Preininger 2006). According to

Lawless (1992) the most important component of perceived flavor is aroma. In order for

aroma compounds to be perceived they must volatilize into the gaseous phase, reach the

nasal cavity and be in high enough concentration to be perceived by the olfactory epithelium (Preininger 2006). In order for flavor compounds to be perceived they must

21

first be released from the food, and the intensity then, is dependent on the amount of flavor released from the food matrix (Frijters 1979). Thus, flavor-food interactions become important as flavor compounds bound to food ingredients no longer are available for perception.

How a food releases flavor is effected by the solid food matrix, hydrophilic liquid

phase, lipophilic liquid phase, and the gas phase. The distribution of the flavor

compound within these phases is controlled by the phase partition coefficient. (Van Ruth

and others 2000). The mass transfer rate of the flavor compound through the phases of

the food matrix is also controlled by viscosity. As a general rule, a flavor in a highly viscous food system is perceived by the sensory panelist as less intense than in a less viscous food system (Druaux and Voilley 1997).

The fact that the food matrix effects the release of flavor compounds and thereby

the perceived flavor of the food is important for the food product developer and

reformulationist. As ingredients and formulations are adjusted in the food industry,

knowledge of how those adjustments will affect the perceived flavor of the food is

imperative. Understanding the interactions between flavor and food ingredients should

support formulating foods with appealing flavors through selection of appropriate

ingredients and processing conditions, or by application of adjusted flavorings

(Preininger 2006). Since most real foods are complex multi-phase systems, an

understanding of flavor interactions requires multiple steps. First there must be a study

with flavor compounds with individual food ingredients in simplified models, followed

by an interaction study using more complicated models and matrix systems. Finally the

22

flavor interactions should be studied in the original food product to evaluate the relative

and sensory relevance of flavor interactions in real foods (Preininger 2006).

Ingredients that have shown to be involved in flavor interactions are lipids and

emulsifiers, proteins, complex and simple carbohydrates, salts, and even packaging

material. Whereas lipids act as a solvent to some flavor compounds, proteins and

carbohydrates bind, absorb, or form complexes with flavor compounds (Hatchwell 1996).

Understanding the flavor changes and release due to these ingredients found in most

foods will help develop foods with desired flavor properties and stabilize food flavor over

shelf life.

1.3.2 Lipid-flavor interactions

Lipids consist of a broad group of compounds that are water-immiscible,

hydrophobic, or lipophilic substances. Lipids comprise fats, oils, fat substitutes, and emulsifiers. Flavor compounds are distributed between the lipid portion of a food and

other portions of a food based on its partition coefficient. Flavor compounds of low polarity, such as long chain fatty acids and aliphatic aldehydes have a higher oil partition coefficient, and are therefore better soluble in oil than in water (Preininger 2006). Most

aroma compounds have been measured to be rather hydrophobic (Piraprez and others

1998).

The main interaction between lipids and flavor compounds is the concentration of

flavor compounds in the lipid phase, which reduces their release into the air, and also reduces their volatility and vapor pressure (Preininger 2006). This effect can be seen by looking at the flavor threshold concentration of flavor compounds of low polarity in oil

23

vs. water. The more hydrophobic a compound is, the more drastically its odor detection threshold differs between a lipid matrix vs. a water matrix (Forss 1969). Hydrophobicity or lipophilicity is a good measure to estimate the retention of aroma compounds by fat. It has been found that increasing the carbon chain length of ethyl esters, alkyl-substituted methoxy pyrazines, and phenols increased the flavor compounds’ odor thresholds by increasing hydrophobicity (Reiners and others 2000).

Because of the hydrophobic nature of most flavor compounds, fat-containing foods have a lower flavor release, but higher flavor capacity than fat-free foods. This aspect of flavor interactions is especially important in the development for reduced fat or fat free products. Full-fat versions of food tend to have a smoother and more lingering flavor profile as compared to fat-free versions that are usually described as having a high initial flavor impact, but fast dissipating aftertastes (Preininger 2006).

The effect of lipids on flavor compounds depends not only on the amount of lipid, but the type of lipid as well. Daget and Vallis (1994) showed that a lower solid-fat index was associated with a more rapid an intense perception of flavor. Maier (1975) also showed that the quantity of retained flavor compounds depends on the chain length of the fatty acids in the triglyceride. Longer chain fatty acids retain less flavor and unsaturated fatty acids retain more flavor.

The emulsion microstructure of oil-in-water emulsions can also have an effect on the release of flavor compounds. Both instrumental studies (Charles and others 2000) and sensory studies (Miettenen and others 2002) have shown that a smaller droplet size increases the release of fat-soluble flavor compounds. This phenomenon may be

24

explained by an increase of the interface between the fat droplets and continuous aqueous

phase as droplet size is reduced. When the interface area is increased, a more rapid

transfer of flavor molecules into the aqueous phase and air for perception is created. This

effect is limited however by the viscosity increase as droplet size is reduced, which can

suppress flavor release (Preininger 2006).

Emulsifiers have the potential for decreasing flavor release by increasing the resistance of mass transfer of flavor molecules (van-Ruth and others 2002). Flavor molecules move more slowly from fat droplets through the emulsifier-occupied droplet interface into the continuous aqueous phase and air. Charles and others (2000) also showed that the type of emulsifier has a large effect on how pronounced the flavor release is decreased. In general protein emulsifiers have a larger effect, where as carbohydrate emulsifiers are more dependent on the droplet size. The effect of emulsifiers on decreasing flavor release has been shown to be minimized due to saliva.

1.3.3 Protein-flavor interactions

Proteins have also been shown to be involved in suppressing flavor release

through binding of the flavor compounds. In general, the binding capacity of a protein for a flavor compound increases from alcohols to ketones and aldehydes (Guichard

2002). Binding of flavor compounds to proteins can occur through reversible hydrophobic interactions, or through irreversible covalent bonding.

Hydrophobic binding of flavor compounds by proteins is thought to occur in,

“hydrophobic pockets” that are made more accessible through unfolding of the protein

during denaturation (Grinberg and others 2002). β-Lactoglobulin has been studied

25

through spectroscopic techniques and found to bind the flavor compounds β-ionone,

retinol, and tetradecanoic acid, in it’s central cavity (Luebke and others 2000). O’Neill

(1996) suggested that the hydrophobic amino acid, L-tryptophan, is an important

component of the hydrophobic binding site of β-Lactoglobulin. In general, an increase in

protein denaturation by heat treatment will cause increased flavor binding. Other

important factors then include water content, salt level, and pH as they change the

conformation of the protein exposing hydrophobic binding sites (Preininger 2006).

Irreversible binding of flavor compounds to proteins happens through covalent

binding of aldehydes by Schiff base formation. Schiff base formations involve aldehyde

flavor compounds with the ε-amino group of the lysine side chains of the protein

(O’Keefe and others 1991). Aldehydes and diacetyl show specific irreversible pH-

dependent binding to proteins high in arginine and lysine.

Milk proteins in particular have been studied for their effect on flavor binding.

Whey proteins and caseins are the main dairy proteins. It has been concluded that

hydrophobic, nonpolar interactions with flavor compounds tend to predominate in casein

vs whey proteins because casein contains more aromatic amino acids, methionine,

arginine, and histidine, but less cysteine and lysine. For the same reason, whey proteins can irreversibly bind aldehydes better than casein (Preininger 2006). The most abundant whey protein is β-Lactoglobulin and as such has been the focus of many flavor binding

studies with milk proteins. A linear correlation was found between the hydrophobicity of

flavor compounds within a series of ketones, aldehydes, alcohols, lactones, or esters, and

their binding to β-Lactoglobulin (Guichard and Langourieux 2000). It was also found

26

that β-Lactoglobulin, when acting as an emulsifier, limits the transfer of hydrophobic

compounds from oil to water and thus induces a lower flavor perception (Guichard and

Langourieux 2000).

1.3.4 Carbohydrate-Flavor Interactions

Carbohydrates including simple sugars, starches, and gums have also been shown to have an effect on flavor perception. Carbohydrates seem to have an effect on flavor perception due to changing the viscosity of the food matrix, complexing with the flavor compounds, or by influencing the volatility of the aroma compounds.

Simple sugars such as mono-, di-, and oligisacharides have been shown to

influence the volatility and release of flavor compounds from aqueous systems. For

example, Wientjes (1968) showed that the headspace concentration of volatile

compounds increased as solutions of glucose, sucrose, and fructose were increased to

40% (w/w). However, in the same study, it was also shown that concentrations above

70% resulted in a decrease in headspace concentration for certain compounds. The effect

of sugars on flavor release is not due entirely to altering viscosity. In a study where

simple sugars and hydrocolloids were used to obtain the same viscosity in an aqueous

system, dissimilar effects on volatile headspace concentration resulted. This effect seems

to depend on the polarity of the volatile compound. The loss of free water by

solubilization of sugar molecules could cause polar volatiles to be driven out of the

solution into the air (salting out effect). Whereas, non-polar compounds could be

entrapped in hydrophobic and amorphous microregions formed by sugar molecules at

high sugar concentrations (Roberts and others 1996).

27

Hydrocolloids such as starches and gums effect flavor volatility by increasing viscosity and in some cases complexing with the flavor compounds. Hydrocolloids are long-chain polymeric materials that thicken or gel in aqueous systems. The impact of hydrocolloids on flavor suppression depends on their concentration. At a specific concentration, called the coil overlap concentration, polysaccharides undergo a transition from a dilute solution behavior to a concentrated solution behavior (Dea 1993). At the coil overlap concentration, carbohydrate polymers begin to form a polymer network by entanglement of molecule chains. At concentrations below the coil overlap concentration, perceived flavor remains relatively constant. In general, the larger the polymer, the lower its concentration is required for flavor suppression (Baines and Morris

1989).

To be tasted flavor compounds must diffuse to the surface of the taste buds.

Intertwined molecular chains of polysaccharides, then, become an obstacle of mixing,

diffusion, and mass transfer of flavor molecules to the taste buds, and thus reduce flavor

release and perception (Morris and Baines 1989). It is also proposed that thickeners

cause flavor suppression by physically coating the taste buds and flavor complex

formation with polysaccharides making the flavor unavailable for aroma perception

(Preininger 2006).

Starches are polysaccharides that consist of amylose and amylopectin, which are

both long chain glucose molecules. The degree of decrease in flavor perception due to

starch is dependent on the conformation of the starch molecule. Native starch undergoes

gelatinization with heat and water. During gelatinization amorphous and crystalline

28

regions of starch are hydrated (Preininger 2006). Gelatinized starch interacts very

differently with flavor compounds compared to native starch. It should be recognized that complete disintegration of the native starch granule is rarely achieved.

Native starch has the potential for adsorbing flavor compounds to the porous

surface of native starch granules (Escher and others 2000). It is thought that the

interactions between native starch and flavor compounds are mainly due to hydrogen

bonding (Boutboul and others 2001). Because of this the affinity of aroma compounds

increases with an increase in polarity. Acids, alcohols, and aldehydes are bound to the

greatest extent by native starch (Hau and others 1996). Gelatinized starch interacts with

flavor compounds a different ways. Linear amylose interacts with ligand molecules by

formation of inclusion complexes (Heinemann and others 2001). In these complexes

flavor ligands can either be embedded in the hydrophobic cavity of the amylose helix or

located between the amylose helices (Helbert and Chanzy 1994).

Gums, which are used as thickeners in foods, decrease volatility of aroma

compounds by increasing the viscosity of the food matrix. Highly volatile compounds

are more affected by an increase in viscosity than less volatile compounds (Roberts and

others 1996). A higher susceptibility to flavor suppression because of gums is also

associated with a decrease in polarity. The degree to which a hydrocolloid decreases

volatility of aroma compounds is effected by its non Newtonian behavior. Gums are

typically shear thinning. During chewing, the apparent viscosity of gum thickened

solutions can decrease, and has an effect on the release of flavor compounds (Cook and

others 2003).

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1.3.5 Ice Cream Ingredient-Flavor Interactions

Ice Cream is a complex colloidal mixture of fat, protein, and carbohydrates. The

ice cream base has been found to be very important for flavor perception (King 1994).

Several studies have focused on the role of ice cream ingredients in altering the flavor

profile of vanilla. Specifically fat and protein have been investigated for their role in

decreasing vanillin perception in ice cream mixes. Li and others (1997) found that fat

significantly decreased free vanillin using HPLC. They also conducted a time-intensity

panel and found that the time to reach maximum vanilla intensity was significantly

different for full fat and low fat ice creams. It was further found through a purge and trap

analysis that as fat decreased vanilla flavor release was slower and at a lower intensity

(Chung and others 2003).

The reduction of vanillin headspace concentration by milk proteins has been

extensively studied. Hansen and Heinis (1991) found that both casein and whey

proteins decrease vanillin flavor intensity. Betalactoglobulin has specifically been linked

with decreasing vanillin odor perception (Reiners and others 2000). The interaction

between milk proteins and vanillin was found to be through hydrogen bonding, and

hydrophobic interactions (Chobpattana and others, 2002). Specifically Schiff base formations have been attributed for the binding of vanillin to milk proteins (Graf and de

Roos 1996).

Other components of ice cream and ice cream processing have also been indicated as

important to vanilla flavor perception in ice cream. Namely sugar was shown to increase

vanilla notes (Chantal and others 1996) whereas emulsifiers (Schmidt and Smith 1988),

30

hydrocolloids (Graf and de Roos 1996), and storage time (Dolan and others 2007) have

been linked to decreasing vanilla flavor perception.

1.4 Analytical Instrumentation

1.4.1 SIFT-MS Introduction

Selected ion flow tube mass spectrometry (SIFT-MS) is a relatively new

analytical technique for quantification of volatile organic compounds (VOCs) in whole

air samples. SIFT-MS has been used previously in research involving clinical,

veterinary, and biological samples (Scotter and others 2005, Wang and others 2005,

Dewhurst and others 2001). SIFT-MS has also been under investigation for its use in

studying aroma compounds in foods. Španĕl and Smith (1999) showed the potential for

SIFT-MS to detect aroma compounds in cut onions, crushed garlic, and ripe bananas.

SIFT-MS uses soft chemical ionization of VOCs in headspace samples using H3O+,

NO+, and O2+ precursor ions. Reactions between the precursor ions and VOCs create product ions that are detected and counted by a downstream mass spectrometer. Absolute concentrations of VOCs in whole air samples can be determined by SIFT-MS down to ppb levels (Smith and Španĕl 2005).

1.4.2 Mass spectrometry

Mass spectrometry is an important tool for analyzing chemical compounds.

Traditional mass spectrometry uses electron ionization sources and requires an

interpretation of generally many mass fragments for each compound (Grützmacher

1999). A variation of traditional mass spectrometry used in the analysis of gaseous

samples occupies the use of “soft” chemical ionization. Generally product ions are

31

created from positively charged precursor ions, which greatly reduce fragmentation

(Harrison 1992). One example of soft ionization mass spectrometry is the use of proton

transfer from H3O+ ions in a drift tube and is called proton transfer reaction mass

spectrometry (PTR-MS) and has been used for gas analysis (Lagg and others 1994).

PTR-MS is more appropriately used for real time quantification of VOCs in air samples

than traditional ionization techniques like those used in gas chromatography mass

spectrometry. However, the use of only one precursor ion limits the ability of PTR-MS

to distinguish between, for example, isobaric compounds. For this reason SIFT-MS,

which uses several carefully selected positive precursor ions, has been developed for

rapid (real time) analysis of whole air samples (Smith and Španĕl 2005).

1.4.3 SIFT-MS Principles

Kinetic studies of ion reactions using selected ion flow tubes have been done for

many years (Adams and Smith 1976). A large kinetics database from thousands of ion-

neutral reactions exists as a result from these experiments (Smith and Španĕl 2005).

SIFT-MS utilizes positive ions that are created in an ion source. A current of

these positive ions of specific mass-to-charge ratios are obtained using a quadrupole mass

filter (Smith & Španĕl 1999). The ions are then introduced into the carrier gas through a

Venturi-type orifice (Smith and Španĕl 2005). The ions are then convected along the flow tube and are sampled via a pinhole orifice at the downstream end of the flow tube into a differentially-pumped quadrupole mass spectrometer. After the mass analyzer they are detected by a channeltron multiplier/pulse counting system (Smith and Španĕl 2005).

A controlled amount of gas is introduced into the carrier gas through a mass flow

32

meter through an entry port in order to determine the rate coefficient and the products

ions for the reaction of the injected ions (Smith and Španĕl 2005). Once the loss of the precursor ion current and the increase of the product ion count rates are observed the rate coefficient for the reaction can be calculated. More than one product ion sometimes results from an ion–molecule reaction, but can be overcome by determining the branching ratios (Smith and Adams 1987).

SIFT-MS is a sophisticated analytical instrument that uses mass selected

precursor ions to ionize the trace gases in complex gas mixtures, including breath. It is

essential that the precursor ions must be relatively unreactive with air components: N2,

O2, H2O,CO2, and Ar, but very reactive with the trace gases to be quantified (Smith and

Španĕl 2005). Ions that fit these criteria have been discovered through studies of ion– molecule reactions that have been carried out for several decades. (Ferguson and others

1969, Adams and Smith 1976). Three precursor ions, namely: H3O+ (Španĕl and Smith

1995) NO+, and O2+ (Španĕl and Smith 1996) are the only suitable precursor ion species for SIFT-MS. One of the great advantages of SIFT-MS is in the use of all three precursor ions in combination. Extensive SIFT studies on the rate coefficients and the product ions of the reactions of H3O+, NO+, and O2+ with volatile organic compounds from many classes form the kinetics database for SIFT-MS and provide the essential understanding of ion–molecule reactions that indicates how to use SIFT-MS for the analysis of whole air samples (Smith and Španĕl 2005).

One example of the usefulness of using multiple precursor ions comes from a

study using H3O+ and NO+ precursor ions simultaneously to study banana emissions. It

33

was found that the major ester emitted by ripe banana is ethyl acetate rather than its

isomer methyl propionate, taking advantage of the fact that the H3O+-ester and NO+-

ester chemistries are different (Španĕl & Smith, 1999d). There are many other examples where this approach is valuable in SIFT-MS analyses and is summarized by Smith and

Španĕl (2005).

1.4.4 Mass Scan vs SIM Scan:

In order to obtain a full mass scan, the detection quadrupole is swept over a

selected mass-charge ratio (m/z) range for a chosen time while a sample is introduced

into the carrier gas at a steady flow rate. The count rates of the ions are then calculated

from the numbers of counts and the total sampling time for each ion. The count rates are

stored, and then displayed by the on-line computer (Smith and Španĕl 2005).

In a SIM scan only the count rates of the precursor ions and those of selected product ions are monitored. SIM scans are achieved by rapidly switching the downstream mass spectrometer between the masses of all the primary ions and the selected product ions and dwelling on each of these masses for a set time interval, approximately 20 ms (Smith and Španĕl 2005). This real-time monitoring is possible because of the fast time response of SIFT-MS, which is due to the fast flow rates of the carrier gas along the flow tube and the sample gas along the inlet tube (Smith and Španĕl

2005). There is no fundamental limit to the number of different ion masses that can be recorded simultaneously using this technique. However, if large numbers of ions need to be monitored it can be more convenient to sequentially record full-scan spectra and construct a table of count rates in the time allowed by the sample volume (Španĕl 2003).

34

1.4.5 Headspace Sampling with SIFT-MS

SIFT-MS is useful in analyzing volatile compounds emitted by aqueous solutions

(Španĕl and others 2002). Headspace sampling can be obtained by offering the

liquid/solid sample up to the entry port of the SIFT-MS when the ambient air is also

sampled simultaneously, by containing the sample in a collapsible bag in which

atmospheric pressure is automatically maintained, or by placing the sample into a fixed

volume container. It has been shown (Španĕl and others, 2002) that the best analytical procedure is to use a fixed volume container. To test the validity of this analytical

approach, the headspace concentrations of acetaldehyde, ethanol, and acetone above aqueous solutions of known concentrations were determined (Španĕl and others 2002).

From this study, the Henry’s Law constants for these compounds were determined and found to agree with their published values.

1.4.6 The use of SIFT-MS to study Foods:

SIFT-MS has great potential in the monitoring of food, especially because of its real-time monitoring capacity. SIFT-MS has been used in pilot studies in several different food applications. First of all, volatile food flavor compounds trans-2- and cis-3- hexenal, menthone, limonene, benzaldehyde, and vanillin were studied (Španĕl and Smith

1999). Some findings from that study include the obvious differences in the products of the reactions of the hexenal isomers with both H3O+ and NO+. The H3O+ ions simply protonate the trans-2-hexenal molecule producing only MH+ whereas the cis-3-hexenal reaction results in both MH+ and (M-OH)+. Both benzaldehyde and vanillin are protonated by H3O+ forming MH+, but their reactions with NO+ are different, hydride

35

ion transfer forming (M-H)+ with benzaldehyde and charge transfer forming M+. with vanillin.

Secondly, emissions from food and food products were detected and quantified by

positioning the food sample at the entry port of the SIFT-MS. In Španĕl and Smith

(1998) ground Colombian coffee was analyzed for pyridine emission. Also, crushed

garlic was analyzed for headspace concentrations of 1–3 dithiane, diallyl disulphide, and

diallyl disulphide-S-oxide. Similarly VOC emissions from cut onion and ripe banana

were observed (Španĕl and Smith 1999).

Thirdly, ethanol and acetaldehyde emitted by yeast/glucose fermentation was

measured (Smith and Wang 2002). This study has important applications in the brewing

industry. A fixed amount of yeast (typically 10 mg) was placed in aqueous glucose

solutions of various concentrations (2–16mg in 5mLof water) in glass bottles sealed with

septa. The fermentations were allowed to proceed at a controlled temperature of 30˚C for varying times, after which the headspace was sampled using the SIM mode to quantify them. Ethanol was the major compounds emitted, but acetaldehyde was also accurately quantified and is seen to be a significant fraction of the headspace VOCs. The kinetics of production of both ethanol and acetaldehyde can be followed closely by this procedure, which has some value in this fermentation process.

1.4.7 Infrared Spectroscopy

Infrared spectroscopy (IR) is a method of analysis that has become very useful for

the identification of the functional properties of many complex systems (Wehling 2003).

This method has shown to be very beneficial in analyzing the structural make-up of

36

foods and has been found to be a practical technique for the analysis of ice cream.

Infrared, in general, is a form of electromagnetic energy in wavelengths (cm-1) that falls on the electromagnetic spectrum between 750 nanometers and 1 millimeter (Wehling

2003). Infrared is heat energy or infrared radiation that when in contact with objects that have a temperature above absolute zero, is soaked up by the matter (Smith 1999). When the matter in contact with the infrared radiation absorbs the energy, the structural bonds begin to vibrate (Smith 1999). Functional groups of a material will absorb the wavelengths of the infrared radiation at the same wave number no matter the type of material that chemical bond is within or near (Smith 1999). This is very beneficial because the chemical bond will absorbs the radiation and produce a specific wavelength that will be the same in different materials (Smith 1999).

Infrared spectroscopy has great potential for the analysis of chemical functional groups. There are many advantages to using IR such as: it is a rapid technique, it is for

the most part non-destructive, this method can analyze several different types of samples

and the spectra that are produced can show the intensities of the groups, peak positions,

width, and shapes of the peaks (Smith 1999). Also IR is relatively easy to learn and conduct experiments with, it requires small sample sizes, and it is a very sensitive analytical method (Smith 1999). The disadvantages to using IR include: that the sample must have chemical bonds that produce dipoles moments or those atoms that are

“monatomic” (Smith 1999). Samples that are too complex also make it more difficult to analyze and samples with too much water can mask the other compounds in the system because water absorb infrared very readily (Smith 1999).

37

IR can be divided into three different regions by the range wave numbers they

look at. These regions consist of near (NIR), mid (MIR), and far (FIR) and fall between

0.8-2.5 μm, 2.5-15 μm, and 15-100 μm, respectively (Wehling 2003). Most commonly

the spectra used for analysis is usually taken from the ranges of 4000 to 400 cm-1, which

is often described as the MIR region (Smith 1999). This region is most commonly used for identification of unknowns in samples due to the functional groups being able to absorb and produce wave numbers at consistent bands (Smith 1999).

A specific kind of MIR spectroscopy is Fourier transform infrared spectroscopy

(FTIR) where Fourier transform is the mathematical equation that produces the result

spectrum (Wehling 2003). In Lerrabee and Choi (1993) they describe the most critical

portion of FTIR, the Michelson interferometer. The interferometer contains two mirrors,

one being fixed while the other is moving, and a beam splitter. In this case, the light from

the infrared source comes into contact with the beam splitter and from there, the beam is

split and part of the light will go directly through the beam splitter and hit the mirror that

is horizontally parallel with it. The light that hits that mirror, which is moving at the

constant velocity, is reflected back, hits the splitter again, and then goes through the sample and into the detector. Simultaneously, the other part of the split infrared beam that doesn’t flow horizontally after it hits the beam splitter moves perpendicular to the beam splitter and hits the constant mirror. The light reflects back again through the beam splitter and goes through the sample and into the detector. Depending on whether or not the splitting of these beams are simultaneous when they return to the detector determines whether the beams are “constructively or destructively” in sync to produce a specific

38

spectrum (Larabee and others 1993). The analysis is determined by the “intensity versus

the path length” and is altered due to the presence of the sample (Wehling 2003). The mathematical equation or FT is what converts the reading into “absorption versus the frequency” (Wehling 2003). The spectra results that are shown are illustrated as wave

number (cm-1) on the x-axis and transmittance or absorption on the y-axis (Wehling

2003).

Attenuated total reflectance (ATR) is often used in order for FTIR to analyze

solids, liquids, semisolids, and thin films (Smith 1996). ATR allows for samples to be

placed directly on a crystal that permits infrared to go through and it has a very good

reflective index (Smith 1996). The ATR crystal, instead of going directly through,

reflects the infrared light after it passes into the sample due to the refractive index and the

light has the correct angle of incidence (Smith 1996). When the light hits the crystal, it

reflects back three times. Inside the crystal an evanescent wave is created that penetrates slightly above and below the crystal and allows the infrared light to go through the sample (Smith 1996). Common crystals that can be used are diamond, zinc selenide, and germanium (Smith 1996).

39

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CHAPTER 2

Rapid Discrimination and Characterization of Vanilla Extracts Made From Countries of Different Origin by FTIR-ATR and SIFT-MS

2.1 Abstract

Vanilla is an important flavor for many foods. Vanilla beans have been shown to

contain over 200 compounds, which can vary in concentration depending on the region

where the beans are harvested. Several compounds including vanillin, p- hydroxybenzaldehyde, guaiacol, and anise alcohol have been found to be important for the aroma profile of vanilla. A need exists for a rapid method to analyze the concentration of important compounds in vanilla beans and extracts. Selected ion flow tube mass spectroscopy (SIFT-MS) and fourier transform infrared (FTIR) spectroscopy are two methods that have potential for rapid discrimination and characterization of vanilla extracts. Vanilla extracts made with beans from different countries of origin including Uganda, Indonesia, Papua New Guinea, Madagascar, and India were analyzed using both methods of analysis. Pirouette statistical software, a multivariate data analysis tool, was utilized to determine the differences between samples. Differentiation between samples was observed for all extracts, with Papua New Guinea and Indonesian samples differing the most from other samples. The top 5 compounds found to be most responsible, based on discriminating power, for the differentiation between samples were vanillin, anise alcohol, methylguaiacol, p-hydroxybenzaldehyde, and p-cresol. The top

49

wavenumbers found to be most responsible, based on discriminating power, for the differentiation between samples were 1523, 1573, 1516, and 1292 cm-1. These wavenumbers might be associated with vanillin and vanillin derivatives based on previous research. Both methods have shown to be quick and reliable methods for analyzing vanilla extracts which could be utilized as a quality assurance tool in the fragrance, flavoring, and food industries.

2.2 Introduction:

Although vanilla is the second most expensive spice, next to saffron, it is still the most widely used (Ranadive 2005). Natural vanilla flavorings are extracted from the seed pods of the plant genus Vanilla (Rao and Ravishanker 2000). Two species from this genus have been used and approved in most countries to create vanilla flavoring including Vanilla planifolia and Vanilla tahitensus, however Vanillus planifolia is much more widely used because of its pod quality and yield (Sinha and others 2008). Today the principle vanilla cultivating country is Madagascar which exports 1000-1200 tons of cured vanilla beans per year (Ranadive 2005). Other countries that export a significant amount of vanilla include Indonesia, the Comoro Islands, Uganda, India, Tonga, Mexico and Tahiti (Ranadive 2005).

Over 200 compounds have been found to be responsible for the flavor profile of vanilla, with vanillin being by far the most abundant (Sinha and others 2008). Other important flavor compounds for the overall vanilla profile include p- hydroxybenzaldehyde, anise alcohol, acetic acid, and guaiacol (Perez-Silva and others

2006). These compounds have been shown to vary in abundance depending on the

50

country of origin where the beans were cultivated (Ranadive 1992, Stosteric and others

2000). Several chromatographic methods for the identification and quantification of

chemical compounds have been used in vanilla research including: Thin layer

chromatography (TLC), gas chromatography (GC), high performance liquid

chromatography (HPLC), capillary electrophoresis (CE), and micellar electrokinetic

chromatography (MECK) (Sinha and others 2008). New methods are needed to rapidly

analyze vanilla extracts for the purpose of differentiation and characterization. Fourier

transform infrared attenuated total reflectance (FTIR-ATR) spectroscopy and selected ion

flow tube mass spectrometry (SIFT-MS) are potential instruments for rapid analysis of

vanilla extracts.

Infrared spectroscopy is an analytical technique that uses infrared radiation to

produce molecular vibrations in order to acquire complex biochemical spectral

fingerprints that are unique and reproducible for a particular product (Smith 1996).

Infrared spectroscopy is a fast, accurate and non-destructive method to obtain

measurements of chemical components and has the ability provide information about

chemical and structural properties of biological materials (Wilson and others 1999).

Novel improvements in Fourier transform infrared instrumentation and pattern

recognition techniques are important advances that have increased the ability to extract

information related to composition and conformation of food components from the

spectra at low-picogram levels (Bjorsvik and others 1992). Specific spectral bands in the

mid- infrared (4000-700 cm-1) region may be assigned to unique chemical entities arising

from group vibrations with known assignments.

51

Selected ion flow tube mass spectrometry (SIFT-MS) is a relatively new

analytical technique for quantification of volatile organic compounds (VOCs) in whole

air samples. Spanel and Smith (1999) showed the potential for SIFT-MS to detect aroma

compounds in cut onions, crushed garlic, and ripe bananas. SIFT-MS uses soft chemical

+ + + ionization of VOCs in headspace samples using H3O , NO , and O2 precursor ions.

Reactions between the precursor ions and VOCs create product ions that are detected and

counted by a downstream mass spectrometer. Absolute concentrations of VOCs in whole

air samples can be determined by SIFT-MS down to ppb levels (Smith and Spanel 2005).

2.3 Materials and Methods:

2.3.1 Vanilla Extracts

Double fold vanilla extracts were obtained from Virginia Dare (Brooklyn, NY,

USA). Extracts were said to have been extracted under similar conditions and were obtained from the following countries: India, Madagascar, Indonesia, Papa New Guinea,

and Uganda.

2.3.2 SIFT-MS

Figure 1 shows a schematic diagram of the analytical process used with the SIFT-

MS technology. In this process reagent ions are generated using a microwave discharge

source and subsequently selected with the quadrupole mass filter. The reagent ions

+ + + generally selected are H3O , NO , and O2 because they don’t react with bulk air

components. These reagent ions are passed into the flow tube where the reaction with the

analyte occurs. Both the reagent ions and products of the reactions move downstream

and are filtered by a second quadrupole mass filter. The ions are then detected with a

52

particle multiplier and the count rate is sent to a computer for processing. The concentration can be obtained in real time as it is proportional to the count of product ions divided by the count of reagent ions.

The Syft Technologies Voice100® SIFT-MS instrument can be operated in two

modes, as follows:

Full mass scans: Mass scans aid identification of unknown compounds but also

allows concentrations to be derived. Full mass scans were obtained using each of the

+ + + three standard SIFT-MS reagent ions (H3O , NO , and O2 ) over the mass range 15 to

200 daltons.

Selected Ion Mode (SIM): SIM targets specific compounds for sensitive

quantitative analysis. Because SIM provides direct quantitation of target compounds at

their specific product masses, it provides significantly better limits of quantitation and

precision than mass scans. Hence the quantitative data presented in this work were

obtained using the SIM approach. Concentrations are shown in parts-per-billion by

volume (ppb).

The SIM method for this study was developed based on 31 compounds,

previously added to the SIFT library, and considered important to the flavor of vanilla.

These compounds, their masses used for calculation of concentrations, and possible conflicts are included in table 1.

Three ml of extract was micropipetted to 150 mm diameter Whatman 42 filter

paper (Fisher Scientific, Florence, KY, USA) and allowed to dry under a hood for two

hours. The filter paper was then transferred to a 500ml pyrex bottle (Fisher Scientific,

53

Florence, KY, USA). The bottles were equilibrated in a 55˚C water bath for 1h and then a SIM scan was run with a Syft v100 mass spectrometer (Syft, Christchurch, New

Zealand). Scan times were set at 90s. Each extract was run in triplicate and the order of analysis was randomized.

In order to account for any interference a 37% ethanol (Sigma Aldrich, St. Louis,

MO, USA )/ddH2O (wt/wt) was prepared as described above and analyzed with the SIFT-

MS in triplicate and the average and standard deviation are reported in appendix A. Air

samples of the room were also analyzed in triplicate and reported in appendix A.

Compounds that were not found to be in concentrations statistically significantly higher than the room air or ethanol control were considered to be in insufficient concentration for detection.

2.3.3 FTIR-ATR

An Excalibur 3100 Fourier-Transform infrared spectrometer (Varian FT-3100;

Varian Inc., Randolph, MA) with a potassium bromide beam splitter and Deuterated

Triglycine Sulfate (DTGS) detector were used for all readings, operating at 4 cm-1

resolution. The ATR accessory used a three-reflection ZnSe crystal plate, providing a 3 fold increase in sample response compared to the standard single-reflection crystal plate

(Pike Tech., Madison, WI). Spectra were collected over the frequency region from 4000-

700 cm-1 and interferograms of 64 scans were co-added followed by Beer-Norton

apodization. The instrument was continuously purged with CO2-free dry air from a

CO2RP140 dryer (Domnick Hunter, Charlotte, USA).

The vanilla extract samples (0.5μL) were placed directly onto the ZnSe crystal

54

and dried under vacuum for five minutes to remove interfering signal from the water

present in the sample. All extracts were analyzed in replicate and 5 independent spectra

were collected for each sample.

2.3.4 Statistical Analysis

The spectra was exported as SPC file format and imported into the multivariate

statistics program Piroutte 3.11 (Infometrix, Bothel, WA). The spectra were derivatized

by using a 5pt polynomial-fit Savitzky-Golay function and normalized using the

maximum normalization function, which normalizes to the most intense band in the

spectrum.

Soft Independent Modeling of Class Analogy (SIMCA) was used to evaluate the

ability of the ATR-IR spectral data to discriminate among the vanilla extracts made from

beans of varying countries of origin. Sample residual and Mahalanobis distance were used for outlier diagnostics (Molfetta and others 2005). The scores plot (a projection of

the original data onto the principal component axes) allowed the visualization of

clustering among samples (sample patterns, groupings or outliers).

Mean comparisons were found to be statistically significant using the Tukey

means comparison method. This statistical analysis was performed using JPM 8.0 (SAS,

Cary, NC).

2.3.5 Model Prediction Ability

Three replicates of each extract were randomly analyzed with the SIFT-MS and

FTIR-ATR methods described above. A predictive analysis based on the SIMCA model

described above was used to test the ability of the model to identify the origin of the

55

extracts.

2.4 Results and Discussion:

2.4.1 Differentiation

Both SIFT-MS and FTIR-ATR clearly differentiated vanilla extracts from the different countries as shown in figures 2 and 3. The SIMCA plots obtained using SIFT-

MS and FTIR-ATR are quite similar to each other. All extracts besides the Indian and

Madagascar are significantly different based on the FTIR-ATR spectra and all extracts are significantly different based on SIFT-SIM compound concentrations. This is shown in the class distances for the FTIR data (Tables 2) and the SIFT data (Table 3). Interclass distance values greater than three are considered significant for identification among classes (Kvalheim 1992). Using the data from the FTIR-ATR the extracts made from

Madagascar and Indian vanilla beans had an interclass distance of 2.0, while the

Madagascar and Ugandan extracts had an interclass distance of exactly 3.0. Based on interclass distances, the separation between extracts was generally greater using the

SIFT-MS method than was the FTIR-ATR method. This greater separation was also accomplished with less replication for the SIFT-MS method. This might partly be explained by the SIFT-MS method focusing on specific compounds that have already been shown to be distinguishing among vanillas from different regions, whereas the

FTIR-ATR can only measure functional groups which appear to be less powerful for

discrimination.

There is a pattern, however, in both approaches where there is generally little

difference among the extracts made from Uganda, Indian, and Madagascar beans. These

56

extracts are not surprisingly similar as they all come from beans of the Vanilla planifolia

species, and use similar curing processes (Adedeji and others 1993). The extract made

from beans cultivated in Papua New Guinea, is a hybrid between the Vanilla planifolia

and the Vanilla tahetians species (Adedeji and others 1993) and was very well

differentiated from the other extracts. The Indonesian extract, although cultivated from

the Vanilla planifolia species, is possibly more differentiated because of the widely

varying vanilla cultivation procedures known to occur in Indonesia, including a short

curing process associated with low flavor development (Adedeji and others 1993). This suggests that species and curing process are the factors most responsible for differences between vanilla beans.

The top discriminating compounds that differentiated extracts using the SIFT

method were vanillin, anise alcohol, methylguaiacol, p-

hydroxybenzaldehyde/trimethylpyrazine, p-cresol/anisole, guaiacol, isovaleric acid and

acetic acid. The top discriminating wavenumbers that differentiated extracts using the

FTIR method were 1523,1573, 1516, 1292, 1774, 1670, 1608, and 1431 cm-1 . These

wavenumbers are related to functional group vibrations of the top discriminating

compound from the SIFT-MS data, vanillin (Table 3).

2.4.2 Volatile Compound Characterization

Beyond simply discriminating between extracts, the SIFT-MS technique also has

the ability to characterize the differences between volatile compound concentrations

between the vanilla extracts. This paper will focus on the top discriminating compounds,

57

as discussed earlier. A complete graphical depiction of all the compounds in the SIM

method is provided in appendix A.

Vanillin, which is the most abundant compound in vanilla beans, also happened to

be the top discriminating compound for the extracts in this study. Vanillin gives the

typical sweet, vanilla aroma associated with vanilla beans (Perez-Silva 2006). Table 4

shows a very high headspace concentration, above 1500 ppb, of vanillin in the

Madagascar, Indian, and Ugandan extracts. There is a much lower concentration, around

300 ppb, in the Papua New Guinea samples. The Vanilla tahetians species has been

shown to have a lower concentration of vanillin (Sostaric and others 2000). The

Indonesian extract had such a low concentration of vanillin it was not statistically

significant. This is evidence of an incomplete curing process which did not develop the

vanilla flavor in the Indonesian bean (Adedeji and others 1993).

The concentration of anise alcohol was almost twice as high in the Papua New

Guinea extract than in any other (figure 5). The Vanilla tahetians species has been

associated with a higher concentration of anise compounds, including anise alcohol

(Sostaric and others 2000). Anise alcohol has an herbal sensory perception (Perez-Silva and others). The extract made from beans from India had the second highest concentration of anise alcohol, whereas the Indonesian and Madagascar sample had less, and the Ugandan extract did not have a significant amount.

Methylguaiacol has a sweet woody odor quality. The Indian extract had the highest concentration of methylguaiacol, with the Papua New Guniea, Madagascar,

Indonesian, and Ugandan extracts all varying in methylguaiacol concentration (figure 6).

58

This illustrates that although the Madagscar, Indian, and Ugandan extracts are similar,

and have no significant difference in vanillin concentration, subtle aroma differences

exist that make up the entire aroma profile of the beans.

There was no way to resolve conflicts between p-Hydroxybenzaldehyde and

trimethylpirazine with the SIFT-MS instrumentation as is the case with p-cresol and

anisole. As such the two compounds of necessity are reported jointly. However, it is likely that p-Hydroxybenzaldehyde predominates in the vanilla extracts as it is generally

found in much higher concentrations (Dignum and others 2001). This is also supported

by the fact that the Indonesian extract has the highest concentration of these compounds

(figure 7), which further supports the hypothesis of the Indonesian bean having an

underdeveloped aroma as p-hydroxybenzaldehyde is a precursor of vanillin biosynthesis

(Havkin-Frenkel and Belanger 2007). It’s likely that there is a much larger proportion of

p-hydroxybenzaldehyde to vanillin in the Indonesian beans as the p-

hydroxybenzaldehyde was not fully converted to vanillin during the ineffective curing of

the Indonesian beans.

p-Cresol, which has a balsamic odor quality (Perez-Silva 2006), was high in both the Indian and Madagascar extracts, but was lower in the Ugandan, Indonesian, and

Papua New Guinea samples (figure 8). On the other hand, guaiacol, which gives a sweet spicy odor quality (Perez-Silva 2006), was highest in the Madagascar and Ugandan extracts, and lowest in the Indian, Indonesian and Papua New Guinea samples. These two phenolic aroma compounds give a good illustration of how, although the Indian,

Madagascar, and Ugandan samples were all very similar, they also had significant

59

differences in the headspace concentration of several aroma compounds.

Isovaleric acid and Acetic acid show a similar pattern. The Indian and

Madagascar extract are the only ones to have a statistically significantly higher concentration of the acids (figures 9 and 10). However, acetic acid has a sour/vinegar

aroma as isovaleric acid has a more buttery/oily aroma (Perez-Silva 2006).

2.4.3 Prediction Accuracy.

The SIMCA model from the 5 extracts made from beans of different countries of

origin had 100% accuracy in first class prediction for both the FTIR and SIFT data

(tables 4 and 5). This means the use of FTIR-ATR and SIFT-MS is a powerful tool for

identification purposes for differentiating the country of origin of vanilla extracts.

2.5 Conclusion:

FTIR-ATR SIFT-MS have been shown to be a rapid method for the

discrimination and identification of low levels of volatile compounds in vanilla extracts.

Discrimination based on country of origin was observed for both methods. The

compounds most responsible for differentiating between extracts were vanillin, anise

alcohol, methylguaiacol, p-hydroxybenzaldehyde/trimethylpyrazine, p-cresol/anisole,

guaiacol, isovaleric acid, and acetic acid. In general, extracts made from beans from

India, Uganda, and Madagascar were similar. The extract made from beans from Papua

New Guinea showed similarities to the Vanilla tahetians species of beans. The extract

made from beans from Indonesia was underdeveloped in flavor, possibly from under

effective curing. This methodology has potential for being a fast, easy to use, quality

assurance tool for the flavor and fragrance industry.

60

References:

Adedeji J, Hartman T, Ho C-T. 1993. Flavor Characterization of Different Varieties of Vanilla Beans. Perf and Flav 18:25-32

Bjorsvik HR, Martens H. 1992. Data analysis: calibration of NIR instruments by PLS regression.In Burns D, Ciurczak E editors. Handbook of Near-Infrared Analysis. New York, NY. Marcel Dekker p 159-170

Burkard, C. 2006. Synthesis of Vanillin analyzed with IR spectroscopy. Practical of Organic Chemistry. 506-511

Dignum ML, Kerler J, Verpoorte R. 2001. Vanilla Production: Technological, chemical, and biosynthetic aspects. Food Rev Int 17(2):199-219.

Ehlers D, Pfister M, Barholomae S. 1994. Analysis of Tahiti vanilla by high performance liquid chromatography. Z Lebensm Unters Forsch 199:38-42.

Havkin-Frenkel D, Belanger C. 2007 Application of metabolic engineering to vanillin biosynthetic pathways in Vanilla Planifolia. In: Verpoorte R Editor. Application of Plant Metabolic Engineering. Springer. p 175-196.

Kvalheim OM, Karstang TV. 1992. SIMCA- Classification by means of disjoint cross validated principle components models. Pages 209-221 in Multivariate Pattern Recognition in Chemometrics. Brereton RG, ed. Elsevier Science Publishers B.V.: Amsterdam, The Netherlands.

Molfetta FA, Bruni AT, Honório KM, and da Silva ABF. 2005. A structure-activity relationship study of quinone compounds with trypanocidal activity. Eur J Med Chem 40: 329-338.

Perez-Silva A, Odoux E, Brat P, Ribeyre F, Rodriguez-Jimenes G, Robles-Olvera V, Garcia-Alvarado MA, Gunata Z. 2006. GC-MS and GC-olfactometry anaolysis of aroma compounds in a representative organic aroma extract from cured vanilla (Vanilla Planifolia) beans. Food Chem 99: 728-735.

Ranadive AS. 1992. Vanillin and Related Flavor Compounds in Vanilla Extracts Made From Beans of Various Global Origins. J Agric Food Chem 40(10):1922-1924.

Ranadive AS. 2005 Vanilla cultivation. In: Vanilla: The first international congress. Princeton: NJ: Allured, Carol Stream. p 25–32.

Sinha AK, Sharma UK, Sharma N. 2008. A comprehensive review on vanilla flavor: Extraction, isolation and quantification of vanillin and other constituents. Int J Food Sci and Nutr 59(4): 299-326. 61

Smith BC. 1996. Fundamentals of Fourier Transform Infrared Spectroscopy. CRC Press, Inc., Boca Raton, FL.

Smith D, Spanel P. 2005. Selected ion flow tube mass spectrometry (SIFT-MS) for on- line trace gas analysis. Mass Spec Rev 24:661-700.

Sostaric T, Boyce MC, Spickett EE. 2000. Analysis of the volatile components in vanilla extracts and flavorings by solid-phase microextraction and gas chromatography. J Agric Food Chem 48:5802-5807.

Spanel P, Smith D. 1999. Selected Ion Flow Tube – Mass Spectrometry: Detection and Real-time Monitoring of Flavours Released by Food Products. Rapid Commun. Mass Spectrom. 13:585-596.

Wilson RH, Tapp HS. 1999. Mid-infrared spectroscopy for food analysis: recent new applications and relevant developments in sample presentation methods. Trends Anal Chem18: 85-93.

62

Figure 1. A schematic diagram of the analytical process used in a SIFT-MS instrument.

63

Compound (s) Potential Interferences Reagent and product ions used in method + + + H3O NO O2 vanillin 153 (+W) 152 152 ethyl vanillin 167 (+W) 166 166 acetic acid 61 (+W) 90 isovaleric acid 103 (+W) 85, 132 isobutyric acid 71, 118 88 methyl ethyl ketone 102 Diacetyl 87 (+W) 86 Acetoin 89 (+W) 118 acetaldehyde 45 (+W) 43, 61, 79 Ethyl hexanoate 174 ethanol 47 (+W) 45, 63, 81 piperonal 150 150 guaiacol 125 (+W) 124 124 methylguaiacol 139 (+W) 138 138 anise alcohol phenol 94 94 furfural 96, 126 96 phenylacetic acid 91 91 2,3-butylene glycol 89 89 furaneol 129 (+W) 128,158 benzaldehyde 105 106 vanillyl alcohol 154 125, 137, 154 anise alcohol 121 138 138 methylguaiacol p-hydroxybenzaldehyde, 122 trimethylpyrazine 123 (+W) 122 p-anisaldehyde 105 136 136 eugenol 165 (+W) 164 164 methyl cinnamate 163 163 131 163 isosafrole p-cresol, anisole 109 (+W) 108 108 isosafrole 163 (+W) 162 162 methyl cinnamate 1,3-propanediol 58, 77 (+W) 75, 151, 153

Table 1. Reagent and product ions used to quantify target compounds and potential interfering compounds.

(+W) = water clusters a Multiple compounds equal compounds that could not be resolved

64

PC2 Uganda Madagascar Indonesia Indian

PC1

PC3

Papua New Guinea

Figure 2. SIMCA scores plot for vanilla extracts using FTIR-ATR

65

Indonesia PC2

Madagascar

Uganda

PC1

PC3

Indian

Papua New Guinea

Figure 3. SIMCA scores plot for vanilla extracts using SIFT-SIM method.

66

Indian Uganda Madagascar Indonesia Uganda 5.5 Madagascar 2.0 3.0 Indonesia 24.0 18.1 14.7 Papua New Guinea 11.0 11.2 8.8 16.2

Table 2. Interclass Distances for FTIR-ATR data

67

Indian Uganda Madagascar Indonesia Uganda 4.5 Madagascar 10.7 6.2 Indonesia 23.3 20.1 15.5 Papa New Guinea 29.0 30.4 17.7 8.3

Table 3. Interclass Distances SIFT-SIM data.

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SIFT-MS Compounds FTIR Wave Numbers Functional Group Discriminating of Vanillin and Rank Compound Power Discriminating Derivative * cm-1 Power 1 vanillin 7030.659 1523 2019.232 C-C stretching

1573 1876.434 C-C Bending 2 anise alcohol 6908.733

3 methylguaiacol 2868.695 1516 1345.997 Unrelated p-hydroxybenzaldehyde/ 1292 832.272 OH-deformation 4 trimethylpyrazine 471.1586

5 p-cresol/anisole 280.8839 1774 394.061 C=O stretch

6 guaiacol 221.8994 1670 190.743 C-C Bending

7 Isovaleric acid 175.7869 1608 175.620 C-C Bending 1431 145.118 C=C Stretching 8 Acetic acid 152.2457

Table 4. Top discriminating compounds and wave numbers from SIMCA model.

* From Burkard (2006)

69

2500 a

2000 a a

1500 Indian

Uganda

Madagascar

1000 Indonesian Concentration (ppb) Concentration Papa New Guinea

Blank

500 b Air bc c c

0 vanillin

Figure 4. Vanillin Concentration in vanilla extracts based on SIFT-MS SIM scans. Levels not connected by same letter are significantly different.

70

400 a

350

300

250 Indian VJ80 Uganda VI75 Madagascar VA03 200 Indonesian VA79 Papa New Guinea VL12 b Blank

Concentration (ppb) Air 150

100

c 50 cd c d d

0 anise alcohol

Figure 5. Anise alcohol concentration in vanilla extracts based on SIFT-MS SIM scans. Levels not connected by same letter are significantly different.

71

120 a

100

80 Indian VJ80 Uganda VI75 Madagascar VA03 60 Indonesian VA79 b Papa New Guinea VL12 Blank Concentration (ppb) Air 40 bc c

20 c d d

0 methylguaiacol

Figure 6. Methylguaiacol concentration in vanilla extracts based on SIFT-MS SIM scans. Levels not connected by same letter are significantly different.

72

a 25

20

Indian VJ80 15 Uganda VI75 Madagascar VA03 Indonesian VA79 b Papa New Guinea VL12 Blank 10 Concentration (ppb) Concentration Air b b

b

5

c c

0 p-hydroxybenzaldehyde/ trimethylpyrazine

Figure 7. p-Hydroxybenzaldehyde/trimethylpyrazine concentration in vanilla extracts based on SIFT-MS SIM scans. Levels not connected by same letter are significantly different.

73

a 25 a

20

Indian VJ80 15 Uganda VI75 Madagascar VA03 Indonesian VA79 b Papa New Guinea VL12 Blank 10 Air

Concentration (ppb) Concentration b b

5

c c

0 p-cresol/ anisole

Figure 8. p-Cresol/anisole concentration in vanilla extracts based on SIFT-MS SIM scans. Levels not connected by same letter are significantly different.

74

50 a

45

40

35

b Indian VJ80 30 Uganda VI75 Madagascar VA03 25 Indonesian VA79 Papa New Guinea VL12 Blank 20 Air Concentration (ppb) Concentration 15 c 10 c

5 cd e d

0 guaiacol

Figure 9. Guaiacol concentration in vanilla extracts based on SIFT-MS SIM scans. Levels not connected by same letter are significantly different.

75

30

a 25 ab

20 Indian VJ80 Uganda VI75 Madagascar VA03 15 bc Indonesian VA79 bc Papa New Guinea VL12 Blank Air Concentration (ppb) Concentration 10 c c c 5

0 isovaleric acid

Figure 10. Isovaleric acid concentration in vanilla extracts based on SIFT-MS SIM scans. Levels not connected by same letter are significantly different.

76

450 a

400

350 ab

300 Indian VJ80 Uganda VI75 250 Madagascar VA03 Indonesian VA79 200 Papa New Guinea VL12 Blank Concentration (ppb) bc bc Air 150 bc

100 c c 50

0 acetic acid

Figure 11. Acetic acid concentration in vanilla extracts based on SIFT-MS SIM scans. Levels not connected by same letter are significantly different.

77

Actual Extract Predicted Extract 2nd Best Prediction 1st Prediction Accuracy Indonesian Indonesian Papua New Guinea Indonesian Indonesian Papua New Guinea 100% Indonesian Indonesian Papua New Guinea Madagascar Madagascar Uganda Madagascar Madagascar Uganda 100% Madagascar Madagascar Indian Indian Indian Uganda Indian Indian Madagascar 100% Indian Indian Uganda Uganda Uganda Indian Uganda Uganda Indian 100% Uganda Uganda Madagascar Papua New Guinea Papua New Guinea Indonesia Papua New Guinea Papua New Guinea Indonesia 100% Papua New Guinea Papua New Guinea Indonesia

Table 5. Prediction accuracy of SIFT-MS for vanilla extracts using SIMCA model.

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Actual Extract Predicted Extract 2nd Best Prediction 1st Prediction Accuracy Indonesian Indonesian Madagascar Indonesian Indonesian Madagascar 100% Indonesian Indonesian Papua New Guinea Madagascar Madagascar Indian Madagascar Madagascar Indian 100% Madagascar Madagascar Indian Indian Indian Madagascar Indian Indian Madagascar 100% Indian Indian Madagascar Uganda Uganda Indian Uganda Uganda Madagascar 100% Uganda Uganda Madagascar Papua New Guinea Papua New Guinea Madagascar Papua New Guinea Papua New Guinea Madagascar 100% Papua New Guinea Papua New Guinea Madagascar

Table 6. Prediction accuracy of FTIR for vanilla extracts using SIMCA model.

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CHAPTER 3

Flavor-Ingredient Interactions between Vanilla Compounds and a model Ice Cream

Mix

3.1 Abstract:

Flavor-food interactions have been shown to be important to the overall flavor

profile of many foods including ice cream. Vanilla flavor, being the top flavor of ice

cream, has been shown to be reduced in intensity due to protein and fat in ice cream. A

research gap exists in understanding how volatile vanilla compounds besides vanillin, the

most abundant vanilla compound, and other ingredients besides protein and oil interact.

A 3x3x2x2x2 full factorial design with oil, protein, sugar, stabilizer, and corn syrup as

factors was conducted. Each mixture of ice cream ingredients was analyzed for

headspace concentration of vanilla compounds using a selected ion flow tube mass

spectrometry (SIFT-MS) technique. Although the most amount of compounds were

statistically significantly effected by protein and oil, other ingredient and interactions

between ingredients effected the headspace concentration of a variety of vanilla compounds. By changing the formulation of an ice cream mix, the vanilla flavor profile is clearly altered.

3.2 Introduction:

Flavor is one of the most important aspects of consumer acceptance of any food

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product, and aroma is the most important aspect of perceived flavor (Lawless 1992). In

order for aroma compounds to be perceived they must first be released from the food.

The flavor intensity then, is dependent on the amount of flavor released from the food

matrix (Frijters 1979). Thus, flavor-food interactions become important as flavor

compounds bound to food ingredients are no longer available for perception.

Over 200 compounds have been found to be responsible for the flavor profile of

vanilla, with vanillin being by far the most abundant (Sinha and others 2008). The other

top vanilla compounds by concentration are p-hydroxybenzaldehyde, p-hydroxybenzyl methyl ether, and acetic acid (Dignum and others 2001). Perez-Silva and others (2006)

showed that at least 25 compounds are responsible for the overall aroma of the vanilla

bean including compounds like isovaleric acid, p-cresol, and methylguaiacol. Vanilla is

the top flavor of ice cream in the United States in terms of share of the segment (IDFA).

The ice cream mix is a complex colloidal mixture of mainly lipids, protein, and

carbohydrates. The ice cream base has been found to be very important for flavor

perception (King 1994). Several studies have focused on the role of ice cream

ingredients in altering the flavor profile of vanilla. Specifically fat and protein have been

investigated for their role in decreasing vanillin perception in ice cream mixes. Li and

others (1997), found that fat significantly decreased free vanillin using HPLC. It was

further found through a purge and trap analysis that as fat decreased vanillin flavor

release was slower and at a lower intensity (Chung and others 2003).

The reduction of vanillin headspace concentration by milk proteins has been

extensively studied. Hansen and Heinis (1991) found that both casein and whey proteins

81

decrease vanillin flavor intensity. Betalactoglobulin has specifically been linked with

decreasing vanillin odor perception (Reiners and others 2000). The interaction between

milk proteins and vanillin was found to be through hydrogen bonding, and hydrophobic

interactions (Chobpattana and others, 2002). Specifically Schiff base formations have

been attributed for the binding of vanillin to milk proteins (Graf and de Roos 1996).

Selected ion flow tube mass spectrometry (SIFT-MS) is a relatively new

analytical technique for quantification of volatile organic compounds (VOCs) in whole

air samples. Spanel and Smith (1999) showed the potential for SIFT-MS to detect aroma

compounds in cut onions, crushed garlic, and ripe bananas. SIFT-MS uses soft chemical

+ + + ionization of VOCs in headspace samples using H3O , NO , and O2 precursor ions.

Reactions between the precursor ions and VOCs create product ions that are detected and

counted by a downstream mass spectrometer. Absolute concentrations, determined by

reaction rates, of VOCs in whole air samples can be rapidly determined by SIFT-MS

down to ppb levels, without extensive sample preparation (Smith and Spanel 2005).

The Syft Technologies Voice100® SIFT-MS instrument (V-100) can be

operated in two modes, a full mass scan, and a selected ion mode (SIM). Full mass scans

+ + are obtained using each of the three standard SIFT-MS reagent ions (H3O , NO , and

+ O2 ) over the mass range 15 to 200 MW. SIM mode is similar to the SIM mode in gas

chromatography and targets specific compounds for sensitive quantitative analysis. In

this study, SIM was used to quantify the volatile compounds in the headspaces of model

vanilla ice cream mix samples. Because SIM provides direct quantitation of target

compounds at their specific product masses, it provides significantly better limits of

82

quantitation and precision than mass scans. Hence the quantitative data presented in this

work were obtained using the SIM approach. Concentrations are shown in parts-per-

billion by volume (ppb).

Since most real foods are complex multi-phase systems, an understanding of

flavor interactions requires multiple steps. First there must be a study with flavor

compounds with individual food ingredients in simplified models, followed by an

interaction study using more complicated models and matrix systems. Finally the flavor

interactions should be studied in the original food product to evaluate the relative and

sensory relevance of flavor interactions in real foods (Preininger 2006). The objective of

this study was to bridge the gap in current research relating ice cream ingredient flavor interactions. This research focuses on flavor-ingredient interactions in a complex model ice cream mix with a natural vanilla flavoring system using novel SIFT-MS technology.

The hypothesis of this work was that many ingredients and interactions between ingredients are important for the headspace concentration of a variety of compounds that make up vanilla. The purpose of this work was to aid in the understanding of complex ingredient interactions so as to assist in proper adjustment of flavorings in food product development or reformulation.

3.3 Materials and Methods:

The model ice cream mixes in this study were roughly based on a combination of

two studies: Schirle-Keller and others (1994) and Chobpattana and others (2002). A

3x3x2x2x2 full factorial design was used in order to account for all possible ingredient

83

interactions and their effect on flavor compounds. The factors were oil at 0, 10, and 15%

levels; milk protein isolate (MPI) at 0, 3, and 6% levels; sugar at 0 and 14% levels; stabilizer at 0 and 0.3% levels; and corn syrup at 0 and 3% levels. All percentages were based on a wt/wt bases. For each non zero level of oil 0.6% (wt/wt) tween 80 was also used as an emulsifier. Mixes were randomly assigned to the day it was made as well as the order of analysis. The complete experimental design was completed in triplicate.

3.3.1 Ingredients:

The ingredients used to make the model ice cream mixes were as follows:

A .05M buffered water solution (ph 6.5) was made using ddH2O and sodium phosphate

(mono and dibasic) (Sigma Aldrich, St. Louis, MO). Other ingredients included milk protein isolate (Protient, St Paul, MN), Tween 80 (Sigma Aldrich, St. Louis, MO), Crisco oil (JM Smucker, Orville, OH), granulated sugar (Giant Eagle Inc., Pittsburgh, PA), Tic

Pretested Dairyblend Ice Cream stabilizer (ingredients: guar gum, locust bean gum,

carrageenan, and dextrose) (Tic Gums, Belcamp, MD), and corn syrup DE 40 (Tate and

Lyle, Decatur, IL). A natural bourbon vanilla oleoresin was obtained from Virginia Dare

(Brooklyn, New York).

3.3.2 Model Ice Cream Mix:

Model Ice Cream mixes were made by first blending the ingredients for 60s on

low in a warring blender, then heating the mixture to 80˚C while stirring at 600 rpm using an isotemp stirring hotplate (Fisher Scientific, Pittsburgh, PA). Mixes were then kept at

60˚C in a water bath for 1h and then homogenized using a Thelco Model 82 homogenizer

(Precision Scientific, Anna Salai, Teynampet, Chennai, India). At this point 4% (wt/wt)

84

vanilla was added and mixed in to the model ice cream mixtures. The mixes were then

placed in a walk in cooler at 4˚C overnight.

3.3.3 Mix Analysis:

Apparent viscosity for all mixes was measured using a viscometer model DV-II

(Brookfield, Middelboro, MA) at 25˚C using a number 2 probe at 60rpm. Relative vapor pressure for all mixes was measured using a CX-2 water activity meter (Decagon Devices

Inc, Pullman, WA) at 25˚C.

Samples were analyzed with a V-100 selected ion flow tube mass spectrometer

(SYFT Technologies, Christchurch, New Zealand) SIM method that had been developed

using 36 compounds that had been previously added to the SIFT library and were found

important to vanilla. These compounds, and the masses used for their calculation are

included in table 7. It should be noted that several compounds shared conflicting masses.

Samples were equilibrated for 1h in a 37˚C water bath, and then analyzed using a 90s scan time with the V-100.

3.3.4 Statistical Analysis:

All statistical analysis was performed using JPM 8.0 (SAS, Cary, NC).

Interaction plots were created using the full factorial design fit model option in JMP.

Mean comparisons were found to be statistically significant using the Tukey means

comparison method.

Because of the high degree of possible interactions between flavors and

ingredients, only flavor-ingredient interactions that were found to be the most statistically

significant (p<.01) are covered in this chapter. All results discussed in this chapter were

85

based on an alpha level of 0.01 or less. For a complete list of all flavor ingredient

interactions see appendix B.

3.4 Results and Discussion

This investigation looked at the effect of ingredients and ingredient interaction on

the water activity (vapor pressure), viscosity and concentration of 37 volatiles associated

with vanilla flavor. The details of the statistical effect ingredient and ingredient

combinations are shown in Appendix B Tables 12 –46. Primary attention has been given to those interactions affecting flavor compounds that were significant at the 0.01 level.

3.4.1 Water Activity (Vapour Pressure)

There was no correlation between relative vapor pressure in the mixes and any

compound’s headspace concentration (Table 8). The effect of the ingredients on

increasing or decreasing the headspace concentration of any compound does not seem to

be related to the ingredient’s role in altering the relative vapor pressure of the mix.

3.4.2: Viscosity

Many of the ingredients and ingredient combinations had a significant effect on

the viscosity of the ice cream mix. Especially the stabilizer and interactions between

other ingredients and the stabilizer significantly increased the viscosity of the mix

(Appendix B, Table 11). Viscosity has been shown to effect flavor volatile release of

some volatile compounds, but not others (Roberts and others 1996). As only a few

compounds were significantly (p<.05) decreased in concentration by the addition of

stabilizers, it is unclear how much of an effect viscosity had overall.

3.4.3 Ingredient effects on vanilla Flavor compounds

86

The ingredients generally had an effect on not only the concentration of vanillin,

but many others of the volatile flavor compounds in the vanilla flavor. These effects

were both in response to individual ingredients and to more complex interactions between

combinations of the ice cream ingredients, especially between protein and lipid.

3.4.3.1 Vanillin:

Vanillin is the most abundant compound in vanilla. Most of the research to date

involving flavor-ingredient interactions with vanilla has focused on vanillin. This study

confirms results presented by other research. Protein had the greatest effect on reducing

the headspace concentration of vanillin from 32-17ppb (figure 12). Oil had the next

greatest effect on vanillin headspace concentration; however there was only a statistically

significant (p< 0.01) decrease from 0% oil to 15% oil. This confirms findings by Graf and de Roos (1996). Although the other ingredients did not have statistically significant effects on vanillin headspace concentration, they show trends that have been reported in other research with the stabilizer and corn syrup decreasing headspace concentration

(Graf and de Roos 1996) and sugar slightly increasing vanillin concentration (Chantal and others 1996).

3.4.3.2Protein, Oil and Protein/Oil Interactions:

Protein and oil had by far the greatest impact on headspace concentration of vanilla compounds. In 4 compounds there was a statistically significant (p<0.01) interaction between protein and oil that effected their headspace concentration. These compounds include guaiacol/p-hydroxybenzyl alcohol, methylguaiacol/p-hydroxy benzoic acid, anise alcohol, and anisaldehyde. All four compounds show the same

87

pattern: As the concentration of oil increases the effect of protein decreases (figures 13-

18). A possible explanation for this phenomenon could be that in the absence of oil, these compounds are able to interact with the protein. However, as oil is added these compounds are dispersed in the oil phase and not available for interactions with proteins in the serum phase.

There were 19 other compounds not described previously in this chapter that were

statistically (p<.01) significantly decreased in headspace concentration by either protein

or oil or both. The flavor profile of vanilla ice cream is dramatically changed by the

addition or subtraction of protein and fat (figure 17 and table 9). For example, when fat

is removed from an ice cream mix, not only are certain flavor compounds suppressed by

protein, but other compounds are more pronounced because they are no longer being

suppressed by oil, but do not interact with protein. In consequence the consumer will

have a more immediate and not as long lasting flavor intensity from some compounds,

and a decreased intensity of other compounds.

3.4.3.3 Oil/Stabilizere interactions

Three compounds were affected by a statistically significant interaction between

oil and stabilizer. Diacetyl and vanillic acid show similar interactions. Both compounds

are only decreased in headspace concentration when both ingredients are present (figures

18 and 19). This is probably due to an interaction between oil and stabilizer that dramatically increases the apparent viscosity of the mix (20). Phenylacetic acid shows a different interaction however. When oil is present, stabilizer levels do not effect headspace concentration, but as oil is removed, stabilizer levels have an effect (figure

88

21). This could be explained by phenylacetic acid being reduced significantly enough by

oil levels that the effect of the stabilizer is insignificant, whereas only when the oil is

removed does the effect of the stabilizer show.

4.4.3.4. Protein/Sugar and Protein/Corn Syrup Interactions

Acetaldehyde showed an effect due to a statistically significant (P<0.01)

interaction between protein and both corn syrup and sugar. For both sugar and corn

syrup, as the level of sweetener is increased the headspace concentration of acetaldehyde

is increased, except in the presence of protein, where there is a slight decrease in

headspace concentration (figure 22). There are two possible explanations for this

phenomenon. One explanation would be that sugar and corn syrup interact with the

protein, decreasing their interaction with acetaldehyde. Another explanation is that there is an interaction between protein and acetaldehyde which is enough to counteract the effects of sugar and corn syrup on the compound. It is likely that there is a Schiff base reaction between the aldehyde and the protein as was see by Graf and de Roos (1996).

3.4.3 Other Significant (P<0.01) Interactions:

Phenylacetic acid, anisaldehyde, and toluene are all statistically increased by the

increase of sugar (Figure 23). It has long been understood that sugar has a “salting out”

effect in certain circumstances (Wjentes 1968). This is probably the case with these

compounds.

The headspace concentration of furfural was significantly decreased with the

increase in stabilizer concentration (Figure 24). This decrease in headspace concentration

might be due to either the increase in viscosity due to the stabilizer or because of

89

complexing with the stabilizer (Preninger 2006).

3.5 Conclusions

This study confirms the results of other studies that both protein and oil are important factors for the profile of vanilla compounds in ice cream, and that vanillin is decreased in concentration more by protein than by oil. Furthermore, this study shows the complex interactions of ice cream ingredients and interactions between ice cream ingredients that affect a variety of compounds in vanilla ice cream. An understanding of the complex amount of variation in the aroma profile of a flavoring due to variations in ingredient formulation is important for the reformulationist and flavorist in order to provide quality flavor delivery to reformulated food products.

90

References

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Chobpattana W, Jeon IJ, Smith JS, Loughlin TM. 2002. Mechanisms of Interactions Between Vanillin and Milk Proteins in Model Systems. J Food Sci. 67(3): 973-977.

Chung SJ, Heymann H, Grun, IU. 2003. Temporal Release of Flavor Compounds from Low-fat and High-fat Ice Cream during eating. J Food Sci. 68(6):2150-2156.

Dignum ML, Kerler J, Verpoorte R. 2001. Vanilla Production: Technological, chemical, and biosynthetic aspects. Food Rev Int 17(2):199-219.

Frijters JER. 1979. Some psycophsical notes on the use of the odor unit number. In: Land DG, Nursten HE, Eds. Progress in Flavor Research. London. App Sci P- 47-51.

Graf E, de Roos KB. 1996. Performance of vanilla flavor in low-fat ice cream. In: McGorrin RJ, Leland JV, editors. Flavor-food interaction. Washington, DC: American Chemical Society. p 24-35.

Hansen AP, Heinis JJ. 1991. Decrease of Vanillin Flavor perception in the Presence of Casein and Whey Proteins. J Dairy Sci. 74: 2936-2940.

IDFA Just the facts: sales and trends. [Internet] Washington D.C.: International Dairy Food Association; [last updated 2009 Sep 08; Accessed 2009 Sep 10] Available http://www.idfa.org/facts/icmonth/page2.cfm

King BM. 1994. Sensory profiling of vanilla ice-cream: flavour and base interactions. Lebensm.-Wiss u. Technol 27: 450–456.

Lawless HT. 1992. Taste and odor. In: Hui YH. Ed. Encyclopedia of Food Technology. New York: John Wiley and Sons. p 2509-2525.

Li Z, Marshall R, Heymann H, Fernando L. 1997. Effect of Milk Fat Content on Flavor Perception of Vanill Ice Cream. J Dairy Sci. 80(12):3133-3141.

Perez-Silva A, Odoux E, Brat P, Ribeyre F, Rodriguez-Jimenes G, Robles-Olvera V, Garcia-Alvarado MA, Gunata Z. 2006. GC-MS and GC-olfactometry anaolysis of aroma compounds in a representative organic aroma extract from cured vanilla (Vanilla Planifolia) beans. Food Chem 99: 728-735.

Preininger M. 2006. Interactions of Flavor Compounds in Foods. In: Gaonkar AG, McPherson A. Ingredient Interactions Effect on Food Quality 2nd ed. Tayolor and 91

Francis. Boca Raton Fl. p. 476-542.

Reiners J, Nicklaus S, Guichard E.2000. Interactions between beta-lactoglobulin and flavor compounds of different chemical classes. Impact of the protein on the odour perception of vanillin and eugonol. Lait 80:347-360.

Roberts DD, Elmore JS, Langley KR, Bakker J. 1996. Effects of sucrose, guar gum, and caroxymethl cellulose on the release of volatile flavor compounds under dynamic conditions. J Agric Food Chem 44(5):1321-1326.

Schirle-Keller JP, Reineccius GA, Hatchwell LC. 1994. Flavor Interactions with Fat Replacers: Effect of Oil Leve. J Food Sci 59(4): 813-815.

Sinha AK, Sharma UK, Sharma N. 2008. A comprehensive review on vanilla flavor: Extraction, isolation and quantification of vanillin and other constituents. Int J Food Sci and Nutr 59(4): 299-326.

Smith D, Spanel P. 2005. Selected ion flow tube mass spectrometry (SIFT-MS) for on- line trace gas analysis. Mass Spec Rev 24:661-700.

Spanel P, Smith D. 1999. Selected Ion Flow Tube – Mass Spectrometry: Detection and Real-time Monitoring of Flavours Released by Food Products. Rapid Commun. Mass Spectr 13:585-596.

Thegoodscentcompany: Compound Descriptions [Internet] Milwaukee, WI: The Good Scent Company; c1980-2008 [Last Updated 2009 Aug 28; Accessed 2009 Sep 10] Available http://www.thegoodscentscompany.com/

Wjentes AG. 1968. The influence of sugar concentrations on the vapor pressure of food odor volatiles in aqueous solutions. J Food Sci. 33:1-2.

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Compound(s)a Potential Interferences Reagent and product ions used in method + + + H3O NO O2 vanillin 153 152 152 acetic acid 61 (+W) 90, 108 anisole, p-cresol isovaleric acid 103 85, 132 isobutyric acid 71 88 methyl ethyl ketone 102 Diacetyl 87 (+W) 86 Acetoin 89 (+W) 118 acetaldehyde 45 (+W) 43, 61, 79 Ethyl hexanoate 174 trimethylpyrazine 122 p-hydroxybenzaldehyde ethanol 47 (+W) 45, 63, 81 piperonal 150 150 anisole 108 108 acetic acid, p-cresol guaiacol/p-hydroxybenzyl 124 alcohol 124 phenol 94 94 furfural 96 96 phenylacetic acid 91, 136 p-anisaldehyde 2_3-butylene glycol 89 89 furaneol 129 (+W) 128, 158 benzaldehyde 105 106 vanillyl alcohol 154 137, 154 anise alcohol 121 138 138 p-hydroxy benzoic acid p-anisaldehyde 105 136 136 phenylacetic acid eugenol 164 164 methyl cinnamate 162,163 131, 162, 163 isosafrole p-cresol 109 (+W) 108 108 acetic acid, anisole isosafrole 162 162 methyl cinnamate acetovanillone/ ethyl 166 vanillin 167 (+W) 166, 167 p-hydroxybenzoic acid/methylguaiacol 139 (+W) 138, 139 138, 139 vanillic acid 168 coumarin 147 (+W) 176 toluene 92 92 1,3-propanediol 75, 151, 153 propanal 57 p-hydroxybenzaldehyde 123 (+W)121, 122, 140 122, 140 trimethylpyrazine

Table 7. Reagent and product ions used to quantify target compounds and potential interfering compounds.

(+W) = water clusters a Multiple compounds equal compounds that could not be resolved

93

Correlation* to water Measured parameter activity (R2) aW 1 cP 0.005461 vanillin 0.007379 acetic acid 0.00472 isovaleric acid 0.014042 isobutyric acid 0.001267 methyl ethyl ketone 0.011859 Diacetyl 0.003869 Acetoin 0.024838 acetaldehyde 0.00996 Ethyl hexanoate 3.72E-05 trimethylpyrazine 0.043848 ethanol 0.000172 piperonal 0.008482 anisole 0.001918 guaiacol 6.25E-06 methylguaiacol 0.014835 phenol 0.003003 furfural 0.002611 phenylacetic acid 0.014568 2_3-butylene glycol 6.24E-05 furaneol 0.000009 benzaldehyde 0.000384 vanillyl alcohol; 6.25E-06 anise alcohol 0.007726 anisaldehyde p- 0.005227 eugenol 0.004436 methyl cinnamate 0.008798 p-cresol 0.002735 isosafrole 0.011837 acetovanillone 0.003025 p-hydroxybenzoic acid 0.00035 vanillic acid 0.001918 p-hydroxybenzyl alcohol 0.019994 coumarin 0.004303 ethyl vanillin 0.015426 toluene 9.41E-05 1,3-propanediol 0.004251 propanal 0.000428 p-hydroxybenzaldehyde 0.005461 Table 8. Correlation between water activity and vanilla compounds.

*The correlations are estimated by Pairwise method. 94

35 a a 30 b a a a ab a a a 25 b c 20

15

10

5 Headspace(ppb) Concentration 0 036 01015 00.3 014 03 % Protein % Oil % Stabilizer % Sugar % Corn Syrup

Figure 12. Vanillin Concentration based on ingredient level. Levels not connected by same letter are significantly (p<0.01) different. N=216

95

0% Prot 6% Prot

0% Oil

15% Oil

Figure 13. Interaction Plot of ice cream mix ingredients on headspace concentration of guaiacol/p-hydroxybenzyl alcohol.

96

6% Prot 0% Prot

0% Oil

15% Oil

Figure 14. Interaction Plot of ice cream mix ingredients on headspace concentration of methylguaiacol/p-hydroxybenzoic acid.

97

6% Prot

0% Prot

0% Oil 15% Oil

Figure 15. Interaction Plot of ice cream mix ingredients on headspace concentration of anise alcohol.

98

6% Prot

0% Prot

0% Oil

15% Oil

Figure 16. Interaction Plot of ice cream mix ingredients on headspace concentration of anisaldehyde

99

Compound acid ketone methyl n phenylacetic coumarin Diacetyl furaneol furfural benzaldehyde acid isobutyric cinnamate methyl ethyl alcohol vanillyl anisole trimethylpyrazine acid isovaleric isosafrole hexanoate Ethyl piperonal acid acetic toluene acetovanillone 0

-0.05

-0.1

-0.15

-0.2 Oil -0.25 Protein

ingredient -0.3

-0.35

-0.4

-0.45

-0.5

Decrease in concentration (ppb) per 1% increase i 1% increase per (ppb) concentration Decrease in Figure 17. Decrease in headspace concentration of selected vanilla compounds due to oil and protein as measured by SIFT-SIM.

100

Effect of Effect of Compound Odor * Oil Protein phenylacetic acid sweet honey floral honeysuckle sour waxy civet -0.204 0 coumarin sweet hay tonka new mown hay -0.181 0 Diacetyl strong butter sweet creamy pungent caramel -0.170 0 furaneol sweet cotton candy strawberry sugar -0.145 0 furfural sweet woody almond fragrant baked bread -0.107 0 benzaldehyde roasted almond, cherry -0.091 0 isobutyric acid acidic sour cheese butter -0.076 -0.330 methyl cinnamate sweet balsam strawberry cherry cinnamon -0.059 -0.061 methyl ethyl ketone acetone-like ethereal fruity camphor -0.055 0 vanillyl alcohol sweet creamy phenolic vanilla tonka -0.031 -0.059 anisole phenolic gasoline ethereal anise -0.029 -0.137 trimethylpyrazine nutty musty earthy powdery cocoa roasted peanut -0.026 0 isovaleric acid sour stinky feet sweaty cheese tropical -0.025 -0.170 isosafrole anise, licorice -0.023 -0.020 Ethyl hexanoate sweet fruity pineapple waxy green banana -0.021 0 piperonal heliotrope flower sweet powdery coconut vanilla -0.014 0 acetic acid sharp pungent sour vinegar 0 -3.110 toluene paint thinner 0 -0.150 acetovanillone faint sweet vanillin 0 -0.030

Table 9. Vanilla compounds and their odors with how much their headspace concentration is decreased with a 1% increase in ingredient.

*as of thegoodscentcompany.com

101

0% Stab .3% Stab

0% Oil

15% Oil

Figure 18. Interaction Plot of ice cream mix ingredients on headspace concentration of diacetyl.

102

0% Stab

.3% Stab

0% Oil

15% Oil

Figure 19. Interaction Plot of ice cream mix ingredients on headspace concentration of vanillic acid.

103

15% Oil

0% Oil

.3% Stab

0% Stab

Figure 20. Interaction between stabilizer and oil on apparent viscosity.

104

.3% Stab 0% Stab

0% Oil 15% Oil

Figure 21. Interaction Plot of ice cream mix ingredients on headspace concentration of phenylacetic acid.

105

0% Prot

6% Prot

0% Sug 14% Sug

0% Prot

6% Prot

3% CS

0% CS

Figure 22. Interaction Plot of ice cream mix ingredients on headspace concentration of acetaldehyde. 106

4.5 a 4

3.5 b 3 a

2.5 b 0 2 14% 1.5 a 1 b 0.5 Headspace Concentration (ppb) Concentration Headspace 0 phenyl acetic acid anisaldehyde toluene

Figure 23. Statistically significant effects of sugar on headspace concentration of selected vanilla compounds. Levels not connected by same letter are significantly (p<0.01) different. N=216

107

6 a

5

4 b

0% 3 30% 2

1 Headspace Concentration (ppb) Concentration Headspace 0 furfural

Figure 24. Statistically significant effect of stabilizer on furfural. Levels not connected by same letter are significantly (p<0.01) different. N=216

108

APPENDIX A

Vanilla Compound Concentrations in Vanillas of Unique Countries of Origin

109

2500

2000

1500 Indian VJ80 Uganda VI75 Madagascar VA03 Indonesian VA79 Papa New Guinea VL12 Blank 1000 Concentration (ppb) Concentration Air

500

0 vanillin acetic acid acetaldehyde anise alcohol 2_3-butylene glycol

Figure 25. Concentration of vanilla compounds from SIFT-SIM method in the range of 0- 2500 ppb. Error bars equal plus or minus one standard deviation, n=3.

110

120

100

80

Indian VJ80 Uganda VI75 Madagascar VA03 60 Indonesian VA79 Papa New Guinea VL12 Blank

Concentration (ppb) Concentration Air

40

20

0 Diacetyl methylguaiacol phenylacetic acid vanillyl alcohol isobutyric acid

Figure 26. Concentration of vanilla compounds from SIFT-SIM method in the range of 0- 120 ppb. Error bars equal plus or minus one standard deviation, n=3.

111

50

45

40

35

30 Indian VJ80 Uganda VI75 Madagascar VA03 25 Indonesian VA79 Papa New Guinea VL12 Blank 20

Concentration (ppb) Air

15

10

5

0 isovaleric acid guaiacol Acetoin benzaldehyde furaneol p-cresol/ anisole

Figure 27. Concentration of vanilla compounds from SIFT-SIM method in the range of 0- 50 ppb. Error bars equal plus or minus one standard deviation, n=3.

112

35

30

25 Indian VJ80 Uganda VI75 20 Madagascar VA03 Indonesian VA79 15 Papa New Guinea VL12 Blank

Concentration (ppb) Concentration Air 10

5

0

e e e

yde p- razin h furfural e xanoat d lpy e l hy a yl cinnamat et hyl h h anis rim Et et t m de/ hy e ld a

benz y drox p-hy

Figure 28. Concentration of vanilla compounds from SIFT-SIM method in the range of 0- 35 ppb. Error bars equal plus or minus one standard deviation, n=3.

113

8

7

6

5 Indian VJ80 Uganda VI75 Madagascar VA03 4 Indonesian VA79 Papa New Guinea VL12 Blank

Concentration (ppb) Air 3

2

1

0 methyl ethyl ketone eugenol ethyl vanillin piperonal isosafrole

Figure 29. Concentration of vanilla compounds from SIFT-SIM method in the range of 0- 8 ppb. Error bars equal plus or minus one standard deviation, n=3.

114

APPENDIX B

Estimates and P-Values For Measured Parameters For All Ingredients And Ingredient Interactions

This appendix provides a summation of the statistical analysis of the effects of the different combinations of ingredients on several ice cream mix parameters. Table 10 shows the effects on vapor pressure, Table 11 shows the effects on viscosity and Table 12-46 show the effects on all of the individual volatile organic compounds evaluated in this investigation.

115

Term Estimate Std Error t Ratio Prob>|t| Intercept 1.020376 0.002899 352.03 <.0001 Protein 0.00473 0.043954 0.11 0.9144 Oil -0.01771 0.017257 -1.03 0.306 Stabilizer 0.142656 0.718295 0.2 0.8428 Sugar -0.063 0.015378 -4.1 <.0001 Corn Syrup -0.11902 0.071766 -1.66 0.0989 (Protein-0.03)*(Oil-0.08333) 0.068747 0.704529 0.1 0.9224 (Protein-0.03)*(Stabilizer-0.00149) 2.627989 29.34237 0.09 0.9287 (Oil-0.08333)*(Stabilizer-0.00149) -15.6463 11.50514 -1.36 0.1755 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) 70.49694 469.7161 0.15 0.8809 (Protein-0.03)*(Sugar-0.07) 0.107198 0.627916 0.17 0.8646 (Oil-0.08333)*(Sugar-0.07) 0.262024 0.246531 1.06 0.2892 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) 3.768981 10.06469 0.37 0.7085 (Stabilizer-0.00149)*(Sugar-0.07) -14.3636 10.26136 -1.4 0.1633 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) 90.05592 419.1767 0.21 0.8301 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 229.6898 164.3591 1.4 0.1639 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 1525.807 6710.23 0.23 0.8204 (Protein-0.03)*(Corn Syrup-0.015) -0.06755 2.930272 -0.02 0.9816 (Oil-0.08333)*(Corn Syrup-0.015) 1.109747 1.150478 0.96 0.336 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) 13.66629 46.96858 0.29 0.7714 (Stabilizer-0.00149)*(Corn Syrup-0.015) -14.0055 47.88634 -0.29 0.7703 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 239.8831 1956.158 0.12 0.9025 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 760.8919 767.0092 0.99 0.3225 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 4183.361 31314.4 0.13 0.8939 (Sugar-0.07)*(Corn Syrup-0.015) 0.085218 1.025223 0.08 0.9338 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) 20.24636 41.86103 0.48 0.6292 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -9.36381 16.4354 -0.57 0.5696 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 109.609 670.9796 0.16 0.8704 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 775.8535 684.0906 1.13 0.2582 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 2812.556 27945.11 0.1 0.9199 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -7795.02 10957.27 -0.71 0.4777 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 38913.22 447348.6 0.09 0.9308

Table 10. Effect of Ingredients and ingredient interactions on water activity (Aw)

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Term Estimate Std Error t Ratio Prob>|t| Intercept -64.3925 7.795634 -8.26 <.0001 Protein 489.2893 118.2147 4.14 <.0001 Oil 346.8554 46.41322 7.47 <.0001 Stabilizer 21455.82 1931.858 11.11 <.0001 Sugar 232.0339 41.36011 5.61 <.0001 Corn Syrup 402.9237 193.0138 2.09 0.0382 (Protein-0.03)*(Oil-0.08333) 8101.414 1894.833 4.28 <.0001 (Protein-0.03)*(Stabilizer-0.00149) 320604.4 78916.43 4.06 <.0001 (Oil-0.08333)*(Stabilizer-0.00149) 225717.5 30943.12 7.29 <.0001 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) 5379433 1263303 4.26 <.0001 (Protein-0.03)*(Sugar-0.07) 4005.369 1688.781 2.37 0.0187 (Oil-0.08333)*(Sugar-0.07) 2978.158 663.046 4.49 <.0001 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) 66550.46 27069.04 2.46 0.0149 (Stabilizer-0.00149)*(Sugar-0.07) 149613 27597.97 5.42 <.0001 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) 2662415 1127378 2.36 0.0192 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 1936184 442044.6 4.38 <.0001 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 44218701 18047192 2.45 0.0152 (Protein-0.03)*(Corn Syrup-0.015) 4608.34 7880.98 0.58 0.5594 (Oil-0.08333)*(Corn Syrup-0.015) 3404.63 3094.215 1.1 0.2726 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) 93183.82 126322.2 0.74 0.4617 (Stabilizer-0.00149)*(Corn Syrup-0.015) 276169.8 128790.5 2.14 0.0333 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 2888651 5261095 0.55 0.5836 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 2353300 2062875 1.14 0.2554 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 62142974 84220228 0.74 0.4615 (Sugar-0.07)*(Corn Syrup-0.015) 3380.235 2757.341 1.23 0.2218 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) -46908.1 112585.4 -0.42 0.6774 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 12975.24 44203.07 0.29 0.7694 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -641121 1804603 -0.36 0.7228 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 2354388 1839865 1.28 0.2023 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -3.4E+07 75158503 -0.46 0.6495 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 9644839 29469639 0.33 0.7438 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -4.47E+08 1.20E+09 -0.37 0.7104

Table 11. Effect of ingredient and ingredient interactions on viscosity (cP).

117

Term Estimate Std Error t Ratio Prob>|t| Intercept 42.02553 1.838838 22.85 <.0001 Protein -226.629 27.88454 -8.13 <.0001 Oil -45.6511 10.94797 -4.17 <.0001 Stabilizer -810.706 455.6875 -1.78 0.0769 Sugar -24.9549 9.756041 -2.56 0.0113 Corn Syrup -203.539 45.52819 -0.47 0.015 (Protein-0.03)*(Oil-0.08333) 570.4372 446.954 1.28 0.2035 (Protein-0.03)*(Stabilizer-0.00149) -15378.7 18614.84 -0.83 0.4098 (Oil-0.08333)*(Stabilizer-0.00149) -8008.44 7298.877 -1.1 0.274 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) 448276.7 297988.6 1.5 0.1342 (Protein-0.03)*(Sugar-0.07) 687.0256 398.3505 1.72 0.0863 (Oil-0.08333)*(Sugar-0.07) -196.059 156.3996 -1.25 0.2116 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) -5928.47 6385.057 -0.93 0.3544 (Stabilizer-0.00149)*(Sugar-0.07) -18406.7 6509.822 -2.83 0.0052 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) 351313.6 265926.3 1.32 0.1881 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 51576.65 104269.7 0.49 0.6214 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -4000337 4256980 -0.94 0.3486 (Protein-0.03)*(Corn Syrup-0.015) 4503.84 1858.969 2.42 0.0164 (Oil-0.08333)*(Corn Syrup-0.015) -157.333 729.8648 -0.22 0.8296 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -50591.9 29796.93 -1.7 0.0912 (Stabilizer-0.00149)*(Corn Syrup-0.015) -39996.3 30379.17 -1.32 0.1896 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 1211925 1240990 0.98 0.3301 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 762829.3 486591.8 1.57 0.1187 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 2301042 19865905 0.12 0.9079 (Sugar-0.07)*(Corn Syrup-0.015) 66.768 650.4027 0.1 0.9183 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) 25912.79 26556.7 0.98 0.3305 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 1662.719 10426.64 0.16 0.8735 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 563914.1 425670.5 1.32 0.1869 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 558565.2 433988.1 1.29 0.1997 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -2.4E+07 17728422 -1.35 0.1778 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -1947211 6951312 -0.28 0.7797 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 1.02E+08 2.84E+08 0.36 0.7199

Table 12. Effect of ingredients and ingredient interactions on vanillin concentration

118

Term Estimate Std Error t Ratio Prob>|t| Intercept 27.91758 1.251779 22.3 <.0001 Protein -311.56 18.98225 -16.41 <.0001 Oil 7.081467 7.452773 0.95 0.3433 Stabilizer -370.514 310.2069 -1.19 0.2339 Sugar 16.30472 6.641373 2.46 0.015 Corn Syrup -87.7502 30.99307 -0.83 0.152 (Protein-0.03)*(Oil-0.08333) -643.311 304.2616 -2.11 0.0358 (Protein-0.03)*(Stabilizer-0.00149) -8461.77 12671.95 -0.67 0.5051 (Oil-0.08333)*(Stabilizer-0.00149) -6698.81 4968.672 -1.35 0.1792 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) 143249.2 202854.1 0.71 0.481 (Protein-0.03)*(Sugar-0.07) -19.3154 271.175 -0.07 0.9433 (Oil-0.08333)*(Sugar-0.07) -32.3777 106.4682 -0.3 0.7614 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) -2771.58 4346.594 -0.64 0.5245 (Stabilizer-0.00149)*(Sugar-0.07) -2352.95 4431.526 -0.53 0.5961 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) 92384.73 181027.9 0.51 0.6104 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -87879.8 70981.02 -1.24 0.2173 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 2652709 2897916 0.92 0.3612 (Protein-0.03)*(Corn Syrup-0.015) 3279.987 1265.483 2.59 0.0103 (Oil-0.08333)*(Corn Syrup-0.015) 310.986 496.8515 0.63 0.5321 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -20950.1 20284.1 -1.03 0.303 (Stabilizer-0.00149)*(Corn Syrup-0.015) 9408.603 20680.46 0.45 0.6497 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 199540 844797 0.24 0.8135 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -484477 331244.8 -1.46 0.1453 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 19634933 13523609 1.45 0.1482 (Sugar-0.07)*(Corn Syrup-0.015) 356.5714 442.7582 0.81 0.4217 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) -29649.3 18078.33 -1.64 0.1027 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -2757.09 7097.879 -0.39 0.6981 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 84870.26 289772.9 0.29 0.7699 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 279975.3 295435.1 0.95 0.3445 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -1E+07 12068528 -0.85 0.3946 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -177717 4732068 -0.04 0.9701 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 35456216 1.93E+08 0.18 0.8546

Table 13. Effect of ingredients and ingredient interactions on acetic acid concentration

119

Term Estimate Std Error t Ratio Prob>|t| Intercept 2.255783 0.188535 11.96 <.0001 Protein -17.583 2.858983 -6.15 <.0001 Oil -2.57846 1.122488 -2.3 0.0227 Stabilizer 2.69687 46.72134 0.06 0.954 Sugar 0.058112 1.00028 0.06 0.9537 Corn Syrup 2.327107 4.667975 0.5 0.6187 (Protein-0.03)*(Oil-0.08333) -62.6919 45.8259 -1.37 0.173 (Protein-0.03)*(Stabilizer-0.00149) 2526.78 1908.567 1.32 0.1872 (Oil-0.08333)*(Stabilizer-0.00149) -1704.13 748.349 -2.28 0.0239 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) 83393.42 30552.57 2.73 0.007 (Protein-0.03)*(Sugar-0.07) -44.9362 40.84262 -1.1 0.2727 (Oil-0.08333)*(Sugar-0.07) 2.06797 16.03555 0.13 0.8975 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) 319.5366 654.6557 0.49 0.6261 (Stabilizer-0.00149)*(Sugar-0.07) -156.51 667.4477 -0.23 0.8149 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) -2947.24 27265.25 -0.11 0.914 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -21380 10690.7 -2 0.047 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -760952 436465.3 -1.74 0.0829 (Protein-0.03)*(Corn Syrup-0.015) -257.99 190.5989 -1.35 0.1775 (Oil-0.08333)*(Corn Syrup-0.015) 111.6898 74.83255 1.49 0.1373 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -4097.11 3055.06 -1.34 0.1815 (Stabilizer-0.00149)*(Corn Syrup-0.015) 2300.628 3114.756 0.74 0.4611 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 36607.67 127237.8 0.29 0.7739 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -30857.7 49889.94 -0.62 0.537 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -1101253 2036838 -0.54 0.5894 (Sugar-0.07)*(Corn Syrup-0.015) -34.0042 66.68536 -0.51 0.6107 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) 4257.5 2722.841 1.56 0.1196 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -105.932 1069.036 -0.1 0.9212 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 34514.85 43643.71 0.79 0.4301 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 10963.01 44496.51 0.25 0.8057 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 887105.5 1817683 0.49 0.6261 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 448530.8 712713.4 0.63 0.5299 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -4914597 29097687 -0.17 0.8661

Table 14. Effect of ingredients and ingredient interactions on isovaleric acid

120

Term Estimate Std Error t Ratio Prob>|t| Intercept 8.742707 0.606521 14.41 <.0001 Protein -33.9056 9.197422 -3.69 0.0003 Oil -7.64401 3.611074 -2.12 0.0356 Stabilizer -268.941 150.3038 -1.79 0.0752 Sugar 3.423718 3.217928 1.06 0.2887 Corn Syrup 26.61844 15.017 1.77 0.078 (Protein-0.03)*(Oil-0.08333) 224.699 147.4231 1.52 0.1292 (Protein-0.03)*(Stabilizer-0.00149) -4786.48 6139.911 -0.78 0.4366 (Oil-0.08333)*(Stabilizer-0.00149) -4673.63 2407.458 -1.94 0.0537 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) -318670 98288.41 -3.24 0.0014 (Protein-0.03)*(Sugar-0.07) -13.1651 131.3917 -0.1 0.9203 (Oil-0.08333)*(Sugar-0.07) -44.4305 51.58677 -0.86 0.3902 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) -5661.29 2106.044 -2.69 0.0078 (Stabilizer-0.00149)*(Sugar-0.07) 346.5951 2147.196 0.16 0.8719 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) -57295.8 87713.01 -0.65 0.5144 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -39708.2 34392.26 -1.15 0.2498 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 2377329 1404120 1.69 0.0921 (Protein-0.03)*(Corn Syrup-0.015) -613.416 613.1615 -1 0.3184 (Oil-0.08333)*(Corn Syrup-0.015) -103.797 240.7382 -0.43 0.6669 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) 1572.059 9828.207 0.16 0.8731 (Stabilizer-0.00149)*(Corn Syrup-0.015) -5315.18 10020.25 -0.53 0.5964 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -311539 409327.4 -0.76 0.4476 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -50900.8 160497.2 -0.32 0.7515 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 6565533 6552561 1 0.3177 (Sugar-0.07)*(Corn Syrup-0.015) -167.801 214.5285 -0.78 0.4351 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) 9766.117 8759.45 1.11 0.2663 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -2830.95 3439.118 -0.82 0.4115 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 194657.8 140403 1.39 0.1673 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 197666.1 143146.4 1.38 0.169 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -137364 5847534 -0.02 0.9813 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -418373 2292817 -0.18 0.8554 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 7527890 93608009 0.08 0.936

Table 15. Effect of ingredients and ingredient interactions on isobutyric acid concentration

121

Term Estimate Std Error t Ratio Prob>|t| Intercept 7.01304 0.490131 14.31 <.0001 Protein 31.03805 7.432459 4.18 <.0001 Oil -5.47079 2.918117 -1.87 0.0624 Stabilizer 209.4746 121.4608 1.72 0.0863 Sugar 1.346761 2.600415 0.52 0.6051 Corn Syrup 31.3445 12.13527 2.58 0.0106 (Protein-0.03)*(Oil-0.08333) -148.248 119.133 -1.24 0.2149 (Protein-0.03)*(Stabilizer-0.00149) -8077.88 4961.676 -1.63 0.1052 (Oil-0.08333)*(Stabilizer-0.00149) -4949.89 1945.473 -2.54 0.0118 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) 8851.743 79427.09 0.11 0.9114 (Protein-0.03)*(Sugar-0.07) -47.2212 106.178 -0.44 0.657 (Oil-0.08333)*(Sugar-0.07) -93.9493 41.68739 -2.25 0.0254 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) -3097.81 1701.899 -1.82 0.0704 (Stabilizer-0.00149)*(Sugar-0.07) -2180.39 1735.155 -1.26 0.2105 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) -10094.1 70881.09 -0.14 0.8869 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -38932.2 27792.47 -1.4 0.163 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 803607.7 1134673 0.71 0.4797 (Protein-0.03)*(Corn Syrup-0.015) -965.2 495.4972 -1.95 0.0529 (Oil-0.08333)*(Corn Syrup-0.015) -165.521 194.5411 -0.85 0.396 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) 1847.937 7942.197 0.23 0.8163 (Stabilizer-0.00149)*(Corn Syrup-0.015) -2407.65 8097.388 -0.3 0.7665 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -330388 330778.4 -1 0.3192 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 26294.21 129698.2 0.2 0.8396 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 1037688 5295140 0.2 0.8448 (Sugar-0.07)*(Corn Syrup-0.015) -63.7676 173.361 -0.37 0.7134 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) 10256.47 7078.532 1.45 0.1491 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -3311.96 2779.159 -1.19 0.2349 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -65858 113460 -0.58 0.5623 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 75537.44 115677 0.65 0.5146 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 3141132 4725406 0.66 0.5071 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -877803 1852831 -0.47 0.6362 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -7.5E+07 75644852 -0.99 0.3244

Table 16. Effect of ingredients and ingredient interactions on methyl ethyl ketone concentration

122

Term Estimate Std Error t Ratio Prob>|t| Intercept 8.040887 0.532276 15.11 <.0001 Protein 6.069629 8.071551 0.75 0.453 Oil -17.0629 3.169036 -5.38 <.0001 Stabilizer 176.5487 131.9048 1.34 0.1824 Sugar 6.482319 2.824016 2.3 0.0228 Corn Syrup 6.019847 13.17874 0.46 0.6484 (Protein-0.03)*(Oil-0.08333) 36.01082 129.3768 0.28 0.7811 (Protein-0.03)*(Stabilizer-0.00149) -5100.88 5388.315 -0.95 0.3451 (Oil-0.08333)*(Stabilizer-0.00149) -8120.07 2112.757 -3.84 0.0002 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) -104664 86256.77 -1.21 0.2265 (Protein-0.03)*(Sugar-0.07) -320.027 115.3079 -2.78 0.0061 (Oil-0.08333)*(Sugar-0.07) -41.1721 45.27195 -0.91 0.3643 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) 1318.234 1848.24 0.71 0.4766 (Stabilizer-0.00149)*(Sugar-0.07) 4223.791 1884.355 2.24 0.0262 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) 87165.61 76975.92 1.13 0.259 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -46226.9 30182.25 -1.53 0.1273 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 1638969 1232240 1.33 0.1851 (Protein-0.03)*(Corn Syrup-0.015) -152.123 538.1034 -0.28 0.7777 (Oil-0.08333)*(Corn Syrup-0.015) -111.339 211.2691 -0.53 0.5988 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -10681.5 8625.12 -1.24 0.2171 (Stabilizer-0.00149)*(Corn Syrup-0.015) 1346.795 8793.656 0.15 0.8784 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -204911 359221 -0.57 0.5691 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -209818 140850.5 -1.49 0.138 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 3260356 5750451 0.57 0.5714 (Sugar-0.07)*(Corn Syrup-0.015) 202.4678 188.2678 1.08 0.2836 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) 14195.51 7687.192 1.85 0.0664 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -8607.09 3018.13 -2.85 0.0048 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 162798.6 123216 1.32 0.1881 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 162314 125623.7 1.29 0.198 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 1298454 5131728 0.25 0.8005 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -2657207 2012150 -1.32 0.1883 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -2629833 82149305 -0.03 0.9745

Table 17. Effect of ingredients and ingredient interactions on diacetyl concentration

123

Intercept 6.743475 0.378629 17.81 <.0001 Protein -38.8946 5.741617 -6.77 <.0001 Oil -5.05706 2.254262 -2.24 0.0261 Stabilizer -80.1937 93.82919 -0.85 0.3938 Sugar 2.387078 2.008836 1.19 0.2363 Corn Syrup 32.43834 9.374567 3.46 0.0007 (Protein-0.03)*(Oil-0.08333) 47.01502 92.0309 0.51 0.6101 (Protein-0.03)*(Stabilizer-0.00149) -1675.36 3832.924 -0.44 0.6626 (Oil-0.08333)*(Stabilizer-0.00149) -974.791 1502.889 -0.65 0.5174 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) -28487.3 61357.89 -0.46 0.643 (Protein-0.03)*(Sugar-0.07) -197.53 82.02311 -2.41 0.017 (Oil-0.08333)*(Sugar-0.07) 30.90826 32.20375 0.96 0.3384 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) -3364.83 1314.727 -2.56 0.0113 (Stabilizer-0.00149)*(Sugar-0.07) 0.380703 1340.417 0 0.9998 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) 45042.47 54756.05 0.82 0.4118 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 34815.12 21469.84 1.62 0.1066 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 1080397 876541.3 1.23 0.2193 (Protein-0.03)*(Corn Syrup-0.015) -281.668 382.7745 -0.74 0.4628 (Oil-0.08333)*(Corn Syrup-0.015) 88.37396 150.2842 0.59 0.5572 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -2611.09 6135.393 -0.43 0.6709 (Stabilizer-0.00149)*(Corn Syrup-0.015) -12526.4 6255.279 -2 0.0467 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 74682.45 255528.2 0.29 0.7704 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 22813.37 100192.6 0.23 0.8201 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -1399350 4090526 -0.34 0.7327 (Sugar-0.07)*(Corn Syrup-0.015) 72.66825 133.9224 0.54 0.5881 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) -5114 5468.207 -0.94 0.3509 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 402.0292 2146.917 0.19 0.8517 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 58676.08 87648.47 0.67 0.504 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -46580.9 89361.13 -0.52 0.6028 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 3490114 3650404 0.96 0.3403 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -1057116 1431323 -0.74 0.4611 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 1.01E+08 58436088 1.72 0.0868

Table 18. Effect of ingredients and ingredient interactions on acetoin concentration

124

Term Estimate Std Error t Ratio Prob>|t| Intercept 52.86522 7.784984 6.79 <.0001 Protein -476.532 118.0532 -4.04 <.0001 Oil 81.16746 46.34981 1.75 0.0816 Stabilizer 1356.232 1929.219 0.7 0.4829 Sugar 103.938 41.30361 2.52 0.0127 Corn Syrup 2422.588 192.7502 12.57 <.0001 (Protein-0.03)*(Oil-0.08333) -3090.95 1892.244 -1.63 0.1041 (Protein-0.03)*(Stabilizer-0.00149) -10635.7 78808.62 -0.13 0.8928 (Oil-0.08333)*(Stabilizer-0.00149) -39343.1 30900.85 -1.27 0.2046 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) -876211 1261578 -0.69 0.4882 (Protein-0.03)*(Sugar-0.07) -6089.63 1686.474 -3.61 0.0004 (Oil-0.08333)*(Sugar-0.07) -852.367 662.1402 -1.29 0.1996 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) -17180.3 27032.06 -0.64 0.5259 (Stabilizer-0.00149)*(Sugar-0.07) 8815.664 27560.27 0.32 0.7494 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) 162215.1 1125837 0.14 0.8856 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -540311 441440.7 -1.22 0.2225 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 21793932 18022537 1.21 0.2281 (Protein-0.03)*(Corn Syrup-0.015) -39398.5 7870.214 -5.01 <.0001 (Oil-0.08333)*(Corn Syrup-0.015) -341.418 3089.988 -0.11 0.9121 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -44297.1 126149.6 -0.35 0.7259 (Stabilizer-0.00149)*(Corn Syrup-0.015) 18059.82 128614.6 0.14 0.8885 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -5387559 5253908 -1.03 0.3065 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -1295402 2060057 -0.63 0.5302 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -8E+07 84105171 -0.95 0.3421 (Sugar-0.07)*(Corn Syrup-0.015) 5404.375 2753.574 1.96 0.0512 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) -299132 112431.6 -2.66 0.0085 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -80083.6 44142.68 -1.81 0.0713 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -1582453 1802137 -0.88 0.381 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 1865640 1837351 1.02 0.3113 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 87776198 75055825 1.17 0.2437 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -3.4E+07 29429379 -1.16 0.248 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 1.00E+09 1.20E+09 0.83 0.4054

Table 19. Effect of ingredients and ingredient interactions on acetaldehyde concentration

125

Term Estimate Std Error t Ratio Prob>|t| Intercept 1.331618 0.173076 7.69 <.0001 Protein -4.94943 2.624556 -1.89 0.0609 Oil -2.12118 1.030448 -2.26 0.009 Stabilizer -14.8539 42.89035 -0.35 0.7295 Sugar 1.412761 0.918261 1.54 0.1256 Corn Syrup -7.55179 4.285217 -1.76 0.0797 (Protein-0.03)*(Oil-0.08333) 115.952 42.06833 0.76 0.64 (Protein-0.03)*(Stabilizer-0.00149) -626.559 1752.071 -0.36 0.721 (Oil-0.08333)*(Stabilizer-0.00149) -460.286 686.987 -0.67 0.5037 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) -50707.8 28047.36 -1.81 0.0722 (Protein-0.03)*(Sugar-0.07) 64.63867 37.49366 1.72 0.0864 (Oil-0.08333)*(Sugar-0.07) 12.62215 14.72069 0.86 0.3923 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) 150.7675 600.9762 0.25 0.8022 (Stabilizer-0.00149)*(Sugar-0.07) -433.721 612.7193 -0.71 0.4799 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) 29948.4 25029.59 1.2 0.233 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 5492.042 9814.1 0.56 0.5764 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -408122 400676.6 -1.02 0.3097 (Protein-0.03)*(Corn Syrup-0.015) 143.8151 174.9704 0.82 0.4122 (Oil-0.08333)*(Corn Syrup-0.015) 35.33989 68.69654 0.51 0.6076 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -590.344 2804.555 -0.21 0.8335 (Stabilizer-0.00149)*(Corn Syrup-0.015) -2623.6 2859.357 -0.92 0.3601 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -17572.8 116804.8 -0.15 0.8806 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -22315.4 45799.13 -0.49 0.6267 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 1846732 1869824 0.99 0.3246 (Sugar-0.07)*(Corn Syrup-0.015) 73.15822 61.21739 1.2 0.2336 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) 1476.413 2499.577 0.59 0.5555 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -1252.71 981.3791 -1.28 0.2034 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -20533.1 40065.08 -0.51 0.6089 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 2942.933 40847.95 0.07 0.9426 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 1186453 1668639 0.71 0.478 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 692918.3 654273.3 1.06 0.291 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -2.5E+07 26711776 -0.94 0.3498

Table 20. Effect of ingredients and ingredient interactions on ethyl hexanoate concentration

126

Term Estimate Std Error t Ratio Prob>|t| Intercept 1.778182 0.163427 10.88 <.0001 Protein -2.86961 2.478239 -1.16 0.2484 Oil -2.64209 0.973001 -2.72 0.0073 Stabilizer -36.6795 40.49925 -0.91 0.3663 Sugar 1.160424 0.867069 1.34 0.1824 Corn Syrup -8.33124 4.04632 -2.06 0.0409 (Protein-0.03)*(Oil-0.08333) 9.773416 39.72306 0.25 0.8059 (Protein-0.03)*(Stabilizer-0.00149) -3075.84 1654.395 -1.86 0.0646 (Oil-0.08333)*(Stabilizer-0.00149) 711.6851 648.688 1.1 0.274 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) 28041.92 26483.75 1.06 0.2911 (Protein-0.03)*(Sugar-0.07) 3.713906 35.40342 0.1 0.9166 (Oil-0.08333)*(Sugar-0.07) -31.1847 13.90002 -2.24 0.0261 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) -314.549 567.4722 -0.55 0.58 (Stabilizer-0.00149)*(Sugar-0.07) -630.791 578.5607 -1.09 0.277 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) 45263.52 23634.21 1.92 0.057 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -2469.8 9266.972 -0.27 0.7901 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -555023 378339.2 -1.47 0.1441 (Protein-0.03)*(Corn Syrup-0.015) 206.7065 165.216 1.25 0.2125 (Oil-0.08333)*(Corn Syrup-0.015) -16.7641 64.86676 -0.26 0.7964 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) 1099.7 2648.204 0.42 0.6784 (Stabilizer-0.00149)*(Corn Syrup-0.015) -4982.28 2699.95 -1.85 0.0666 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 763.886 110293 0.01 0.9945 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 75012.06 43245.87 1.73 0.0845 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -542368 1765583 -0.31 0.759 (Sugar-0.07)*(Corn Syrup-0.015) 9.305136 57.80457 0.16 0.8723 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) 2654.774 2360.228 1.12 0.2621 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 736.1169 926.668 0.79 0.428 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -9961.28 37831.48 -0.26 0.7926 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -14826.8 38570.71 -0.38 0.7011 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 1448743 1575614 0.92 0.359 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 254448.1 617798.1 0.41 0.6809 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -5217876 25222616 -0.21 0.8363

Table 21. Effect of ingredients and ingredient interactions on trimethylpyrazine concentration

127

Term Estimate Std Error t Ratio Prob>|t| Intercept 2358.15 137.4276 17.16 <.0001 Protein -10231.2 2083.982 -0.91 0.21 Oil 2682.65 818.2087 0.28 0.33 Stabilizer 3411.679 34056.31 0.1 0.9203 Sugar 4146.576 729.1285 0.69 0.43 Corn Syrup 34606.55 3402.6 0.17 0.22 (Protein-0.03)*(Oil-0.08333) -36103.1 33403.6 -1.08 0.2812 (Protein-0.03)*(Stabilizer-0.00149) 396885.2 1391201 0.29 0.7757 (Oil-0.08333)*(Stabilizer-0.00149) -824998 545489.6 -1.51 0.1321 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) -1.9E+07 22270505 -0.85 0.3988 (Protein-0.03)*(Sugar-0.07) -120802 29771.17 -0.06 0.11 (Oil-0.08333)*(Sugar-0.07) 6137.995 11688.7 0.53 0.6001 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) -1035259 477194.3 -2.17 0.0313 (Stabilizer-0.00149)*(Sugar-0.07) -13810.2 486518.7 -0.03 0.9774 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) 4296331 19874297 0.22 0.8291 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -5714742 7792709 -0.73 0.4643 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 7.07E+08 3.18E+08 2.22 0.0275 (Protein-0.03)*(Corn Syrup-0.015) -732972 138932.1 -0.28 0.09 (Oil-0.08333)*(Corn Syrup-0.015) 29322.74 54547.25 0.54 0.5915 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -2446681 2226907 -1.1 0.2733 (Stabilizer-0.00149)*(Corn Syrup-0.015) -1956869 2270421 -0.86 0.3899 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -3.7E+07 92746718 -0.39 0.694 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -3514624 36365975 -0.1 0.9231 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 82732986 1.49E+09 0.06 0.9556 (Sugar-0.07)*(Corn Syrup-0.015) 70355.6 48608.57 1.45 0.1495 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) -1400657 1984744 -0.71 0.4813 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 214914.2 779246.4 0.28 0.783 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -4969548 31812953 -0.16 0.876 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 9144668 32434580 0.28 0.7783 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 8.85E+08 1.33E+09 0.67 0.5048 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 58223934 5.20E+08 0.11 0.9109 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 1.86E+10 2.12E+10 0.88 0.3807

Table 22. Effect of ingredients and ingredient interactions on ethanol concentration

128

Term Estimate Std Error t Ratio Prob>|t| Intercept 0.450127 0.079258 5.68 <.0001 Protein -1.37101 1.201893 -1.14 0.2555 Oil -1.43385 0.471885 -3.04 0.0027 Stabilizer 18.68881 19.64127 0.95 0.3426 Sugar 0.291224 0.42051 0.69 0.4895 Corn Syrup -4.14693 1.962378 -2.11 0.0359 (Protein-0.03)*(Oil-0.08333) -6.3133 19.26483 -0.33 0.7435 (Protein-0.03)*(Stabilizer-0.00149) -485.344 802.346 -0.6 0.546 (Oil-0.08333)*(Stabilizer-0.00149) -2.35151 314.5998 -0.01 0.994 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) 10661.43 12844.05 0.83 0.4076 (Protein-0.03)*(Sugar-0.07) -17.2759 17.1699 -1.01 0.3157 (Oil-0.08333)*(Sugar-0.07) 6.807396 6.741212 1.01 0.3139 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) -52.3506 275.2119 -0.19 0.8493 (Stabilizer-0.00149)*(Sugar-0.07) 459.0518 280.5895 1.64 0.1035 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) 15117.01 11462.09 1.32 0.1889 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -4784.99 4494.282 -1.06 0.2884 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 39546.24 183486.4 0.22 0.8296 (Protein-0.03)*(Corn Syrup-0.015) 217.6185 80.1262 2.72 0.0072 (Oil-0.08333)*(Corn Syrup-0.015) 42.89116 31.45899 1.36 0.1744 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -1356.41 1284.322 -1.06 0.2923 (Stabilizer-0.00149)*(Corn Syrup-0.015) -487.456 1309.418 -0.37 0.7101 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 31678.87 53489.74 0.59 0.5544 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -19400.3 20973.32 -0.93 0.3562 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 1014298 856269.9 1.18 0.2377 (Sugar-0.07)*(Corn Syrup-0.015) 4.827727 28.03398 0.17 0.8635 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) 1291.878 1144.66 1.13 0.2605 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 242.0005 449.4141 0.54 0.5909 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -18938.1 18347.46 -1.03 0.3033 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -3236.08 18705.97 -0.17 0.8628 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 586902.7 764139.1 0.77 0.4434 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 387750.5 299618.8 1.29 0.1972 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -9870379 12232428 -0.81 0.4208

Table 23. Effect of ingredients and ingredient interactions on piperonal concentration

129

Term Estimate Std Error t Ratio Prob>|t| Intercept 1.922949 0.13758 13.98 <.0001 Protein -13.6887 2.086291 -6.56 <.0001 Oil -2.8508 0.819115 -3.48 0.0006 Stabilizer -50.6648 34.09405 -1.49 0.139 Sugar 1.447997 0.729937 1.98 0.0488 Corn Syrup -7.12122 3.406371 -2.09 0.0379 (Protein-0.03)*(Oil-0.08333) -61.194 33.44062 -1.83 0.0689 (Protein-0.03)*(Stabilizer-0.00149) -25.6578 1392.743 -0.02 0.9853 (Oil-0.08333)*(Stabilizer-0.00149) -228.599 546.0942 -0.42 0.676 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) -11935.6 22295.19 -0.54 0.5931 (Protein-0.03)*(Sugar-0.07) 40.24725 29.80416 1.35 0.1785 (Oil-0.08333)*(Sugar-0.07) -15.0421 11.70165 -1.29 0.2002 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) 447.8394 477.7232 0.94 0.3498 (Stabilizer-0.00149)*(Sugar-0.07) -574.828 487.0579 -1.18 0.2394 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) 46469.66 19896.32 2.34 0.0206 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -2354.21 7801.345 -0.3 0.7632 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -649651 318502.7 -2.04 0.0428 (Protein-0.03)*(Corn Syrup-0.015) 311.0731 139.0861 2.24 0.0265 (Oil-0.08333)*(Corn Syrup-0.015) 68.61452 54.6077 1.26 0.2105 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -1301.34 2229.375 -0.58 0.5601 (Stabilizer-0.00149)*(Corn Syrup-0.015) 42.1908 2272.937 0.02 0.9852 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -9801.41 92849.51 -0.11 0.916 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -22789.8 36406.28 -0.63 0.5321 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 1018826 1486346 0.69 0.4939 (Sugar-0.07)*(Corn Syrup-0.015) -31.4725 48.66244 -0.65 0.5186 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) 2309.846 1986.944 1.16 0.2465 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 435.5189 780.11 0.56 0.5773 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -33116.7 31848.21 -1.04 0.2998 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 47534.77 32470.53 1.46 0.1449 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -648412 1326422 -0.49 0.6255 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -674629 520089.7 -1.3 0.1962 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 25970315 21233511 1.22 0.2229

Table 24. Effect of ingredients and ingredient interactions on anisole concentration

130

Term Estimate Std Error t Ratio Prob>|t| Intercept 35.19728 1.136247 30.98 <.0001 Protein -127.035 17.2303 -7.37 <.0001 Oil -127.33 6.764927 -18.82 <.0001 Stabilizer 27.5277 281.5766 0.1 0.9222 Sugar 10.52167 6.028414 1.75 0.0826 Corn Syrup 8.549269 28.1326 0.3 0.7616 (Protein-0.03)*(Oil-0.08333) 1267.393 276.1801 4.59 <.0001 (Protein-0.03)*(Stabilizer-0.00149) 10098.06 11502.41 0.88 0.3811 (Oil-0.08333)*(Stabilizer-0.00149) -7890.96 4510.093 -1.75 0.0819 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) 279976.8 184131.9 1.52 0.1301 (Protein-0.03)*(Sugar-0.07) -237.084 246.1472 -0.96 0.3367 (Oil-0.08333)*(Sugar-0.07) -24.0912 96.64182 -0.25 0.8034 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) -459.205 3945.429 -0.12 0.9075 (Stabilizer-0.00149)*(Sugar-0.07) 1691.013 4022.523 0.42 0.6747 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) 248292.4 164320.1 1.51 0.1325 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -57889.9 64429.9 -0.9 0.3701 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 2870134 2630456 1.09 0.2766 (Protein-0.03)*(Corn Syrup-0.015) -24.4139 1148.687 -0.02 0.9831 (Oil-0.08333)*(Corn Syrup-0.015) -295.071 450.9951 -0.65 0.5138 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -1747.55 18412 -0.09 0.9245 (Stabilizer-0.00149)*(Corn Syrup-0.015) 78.97626 18771.78 0 0.9966 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -1570879 766827.3 -2.05 0.0419 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -308881 300672.9 -1.03 0.3056 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 20074077 12275461 1.64 0.1037 (Sugar-0.07)*(Corn Syrup-0.015) 6.744072 401.8943 0.02 0.9866 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) 19900.59 16409.81 1.21 0.2268 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -4296.81 6442.788 -0.67 0.5057 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 312651.8 263028.6 1.19 0.2361 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 51666.74 268168.2 0.19 0.8474 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 8580332 10954676 0.78 0.4345 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -1920744 4295327 -0.45 0.6553 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -1.50E+08 1.75E+08 -0.86 0.3923

Table 25. Effect of ingredients and ingredient interactions on guaiacol concentration

131

Term Estimate Std Error t Ratio Prob>|t| Intercept 2.872414 0.181924 15.79 <.0001 Protein -11.5423 2.758731 -4.18 <.0001 Oil -12.6312 1.083128 -11.66 <.0001 Stabilizer -13.5711 45.08303 -0.3 0.7637 Sugar -0.57985 0.965205 -0.6 0.5487 Corn Syrup -2.11942 4.50429 -0.47 0.6385 (Protein-0.03)*(Oil-0.08333) 238.8351 44.21899 5.4 <.0001 (Protein-0.03)*(Stabilizer-0.00149) -3370.31 1841.643 -1.83 0.0689 (Oil-0.08333)*(Stabilizer-0.00149) -743.357 722.1078 -1.03 0.3046 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) 34073.71 29481.23 1.16 0.2493 (Protein-0.03)*(Sugar-0.07) -31.4624 39.41045 -0.8 0.4257 (Oil-0.08333)*(Sugar-0.07) 1.60135 15.47325 0.1 0.9177 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) 798.304 631.6999 1.26 0.2079 (Stabilizer-0.00149)*(Sugar-0.07) -818.414 644.0433 -1.27 0.2054 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) -67178.4 26309.18 -2.55 0.0115 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 16271.41 10315.83 1.58 0.1164 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 571787.2 421160.4 1.36 0.1762 (Protein-0.03)*(Corn Syrup-0.015) 172.4793 183.9154 0.94 0.3496 (Oil-0.08333)*(Corn Syrup-0.015) 70.06662 72.20851 0.97 0.3332 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -8042.66 2947.933 -2.73 0.007 (Stabilizer-0.00149)*(Corn Syrup-0.015) -1275.64 3005.536 -0.42 0.6717 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 114618.5 122776.2 0.93 0.3518 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 59096.7 48140.52 1.23 0.2212 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -146472 1965415 -0.07 0.9407 (Sugar-0.07)*(Corn Syrup-0.015) -33.4559 64.34701 -0.52 0.6037 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) 2602.292 2627.363 0.99 0.3233 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 950.6473 1031.55 0.92 0.358 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 2617.354 42113.32 0.06 0.9505 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -34721.3 42936.22 -0.81 0.4197 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 740802.1 1753945 0.42 0.6733 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -68458.7 687721.7 -0.1 0.9208 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -2.8E+07 28077362 -1.01 0.3161

Table 26. Effect of ingredients and ingredient interactions on methylguaiacol concentration

132

Term Estimate Std Error t Ratio Prob>|t| Intercept 4.332285 0.306448 14.14 <.0001 Protein -4.69596 4.647038 -1.01 0.3136 Oil -11.6385 1.824511 -0.38 0.34 Stabilizer 19.98136 75.94163 0.26 0.7928 Sugar 2.363179 1.625872 1.45 0.1478 Corn Syrup 17.84312 7.587403 2.35 0.0197 (Protein-0.03)*(Oil-0.08333) -130.769 74.48616 -1.76 0.0808 (Protein-0.03)*(Stabilizer-0.00149) 9012.026 3102.217 0.91 0.41 (Oil-0.08333)*(Stabilizer-0.00149) -2552.18 1216.379 -2.1 0.0373 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) 12027.73 49660.65 0.24 0.8089 (Protein-0.03)*(Sugar-0.07) 35.2696 66.38625 0.53 0.5959 (Oil-0.08333)*(Sugar-0.07) -81.1452 26.06444 0.11 0.21 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) -681.43 1064.088 -0.64 0.5227 (Stabilizer-0.00149)*(Sugar-0.07) 3167.971 1084.88 0.92 0.39 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) -112.59 44317.38 0 0.998 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -44972.4 17376.84 -2.59 0.0104 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 1497533 709437.8 2.11 0.0361 (Protein-0.03)*(Corn Syrup-0.015) -121.11 309.8025 -0.39 0.6963 (Oil-0.08333)*(Corn Syrup-0.015) 50.66261 121.634 0.42 0.6775 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -7421.12 4965.744 -1.49 0.1368 (Stabilizer-0.00149)*(Corn Syrup-0.015) 1518.029 5062.775 0.3 0.7646 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 88932.83 206814.4 0.43 0.6677 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -97813.7 81091.91 -1.21 0.2293 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 356802.1 3310710 0.11 0.9143 (Sugar-0.07)*(Corn Syrup-0.015) 40.5854 108.3915 0.37 0.7085 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) -1279.56 4425.75 -0.29 0.7728 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -2570.82 1737.629 -1.48 0.1407 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 123737.9 70939.2 1.74 0.0828 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 16664.43 72325.36 0.23 0.818 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 655389.6 2954492 0.22 0.8247 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 341970.8 1158456 0.3 0.7682 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 4755147 47295853 0.1 0.92

Table 27. Effect of ingredients and ingredient interactions on phenol concentration

133

Term Estimate Std Error t Ratio Prob>|t| Intercept 3.29452 0.753335 4.37 <.0001 Protein -3.96577 11.42373 -0.35 0.7289 Oil -10.7596 4.485163 -2.4 0.0174 Stabilizer 512.6538 186.686 2.75 0.0066 Sugar 9.692462 3.996854 2.43 0.0163 Corn Syrup 42.92803 18.65198 2.3 0.0225 (Protein-0.03)*(Oil-0.08333) -30.7942 183.1081 -0.17 0.8666 (Protein-0.03)*(Stabilizer-0.00149) 37.74462 7626.126 0 0.9961 (Oil-0.08333)*(Stabilizer-0.00149) -8556.72 2990.203 -2.86 0.0047 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) -8421.17 122079.9 -0.07 0.9451 (Protein-0.03)*(Sugar-0.07) -40.8765 163.1962 -0.25 0.8025 (Oil-0.08333)*(Sugar-0.07) -129.843 64.07376 -2.03 0.0442 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) -43.3823 2615.829 -0.02 0.9868 (Stabilizer-0.00149)*(Sugar-0.07) 3548.449 2666.943 1.33 0.185 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) -9.73294 108944.7 0 0.9999 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -107374 42717.19 -2.51 0.0128 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 1924454 1743999 1.1 0.2713 (Protein-0.03)*(Corn Syrup-0.015) -107.52 761.5822 -0.14 0.8879 (Oil-0.08333)*(Corn Syrup-0.015) -617.503 299.0109 -2.07 0.0403 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -2313.21 12207.2 -0.19 0.8499 (Stabilizer-0.00149)*(Corn Syrup-0.015) 16847.03 12445.73 1.35 0.1775 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -130619 508408.4 -0.26 0.7975 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -418529 199346.9 -2.1 0.0371 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 1090230 8138661 0.13 0.8936 (Sugar-0.07)*(Corn Syrup-0.015) 589.1873 266.4569 2.21 0.0283 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) -768.829 10879.75 -0.07 0.9437 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -9824.32 4271.584 -2.3 0.0226 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 37506.23 174388.6 0.22 0.8299 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 378141.1 177796.2 2.13 0.0348 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 1468962 7262977 0.2 0.8399 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -6198504 2847812 -2.18 0.0308 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 4285346 1.16E+08 0.04 0.9706

Table 28. Effect of ingredients and ingredient interactions on furfural concentration

134

Term Estimate Std Error t Ratio Prob>|t| Intercept 5.278573 0.391983 13.47 <.0001 Protein -1.82185 5.944122 -0.31 0.7596 Oil -20.4369 2.333769 -8.76 <.0001 Stabilizer -297.029 97.13851 -3.06 0.0026 Sugar 7.529971 2.079687 3.62 0.0004 Corn Syrup -15.008 9.705205 -1.55 0.1237 (Protein-0.03)*(Oil-0.08333) 262.9607 95.2768 2.76 0.0064 (Protein-0.03)*(Stabilizer-0.00149) 1880.718 3968.11 0.47 0.6361 (Oil-0.08333)*(Stabilizer-0.00149) 5994.651 1555.895 3.85 0.0002 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) 16690.18 63521.97 0.26 0.793 (Protein-0.03)*(Sugar-0.07) 26.20856 84.91604 0.31 0.7579 (Oil-0.08333)*(Sugar-0.07) 11.17622 33.33956 0.34 0.7378 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) 1560.156 1361.097 1.15 0.2532 (Stabilizer-0.00149)*(Sugar-0.07) -1598.59 1387.693 -1.15 0.2508 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) 12621.37 56687.28 0.22 0.8241 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 9361.309 22227.08 0.42 0.6741 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 1065812 907456.6 1.17 0.2417 (Protein-0.03)*(Corn Syrup-0.015) 888.6166 396.2748 2.24 0.0261 (Oil-0.08333)*(Corn Syrup-0.015) 268.4247 155.5846 1.73 0.0862 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -8376.38 6351.787 -1.32 0.1889 (Stabilizer-0.00149)*(Corn Syrup-0.015) 4400.299 6475.901 0.68 0.4977 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -484112 264540.6 -1.83 0.0689 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -253247 103726.4 -2.44 0.0156 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 7855064 4234798 1.85 0.0652 (Sugar-0.07)*(Corn Syrup-0.015) 47.44087 138.6458 0.34 0.7326 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) -4224.46 5661.069 -0.75 0.4565 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -1463.7 2222.638 -0.66 0.511 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 8219.985 90739.81 0.09 0.9279 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -80286.2 92512.87 -0.87 0.3866 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 2369540 3779152 0.63 0.5314 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 3994492 1481805 2.7 0.0077 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -9.3E+07 60497110 -1.54 0.1241

Table 29. Effect of ingredients and ingredient interactions on phenylacetic acid concentration

135

Term Estimate Std Error t Ratio Prob>|t| Intercept 5.359103 0.485419 11.04 <.0001 Protein -25.6665 7.360997 -0.49 0.6 Oil 3.882366 2.89006 1.34 0.1808 Stabilizer -62.7428 120.293 -0.52 0.6026 Sugar 2.284683 2.575413 0.89 0.3762 Corn Syrup 9.141707 12.01859 0.76 0.4479 (Protein-0.03)*(Oil-0.08333) -8.60212 117.9875 -0.07 0.942 (Protein-0.03)*(Stabilizer-0.00149) -9473.72 4913.971 -1.93 0.0554 (Oil-0.08333)*(Stabilizer-0.00149) -3318.6 1926.767 -1.72 0.0867 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) 21587.61 78663.42 0.27 0.7841 (Protein-0.03)*(Sugar-0.07) 120.0708 105.1571 1.14 0.255 (Oil-0.08333)*(Sugar-0.07) -29.1003 41.28657 -0.7 0.4818 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) 790.7062 1685.536 0.47 0.6395 (Stabilizer-0.00149)*(Sugar-0.07) -1197.17 1718.471 -0.7 0.4869 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) -82578.8 70199.58 -1.18 0.241 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -18954.3 27525.25 -0.69 0.4919 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -420820 1123763 -0.37 0.7085 (Protein-0.03)*(Corn Syrup-0.015) 299.0253 490.7332 0.61 0.543 (Oil-0.08333)*(Corn Syrup-0.015) -62.8197 192.6707 -0.33 0.7448 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -6891.99 7865.834 -0.88 0.3821 (Stabilizer-0.00149)*(Corn Syrup-0.015) 9173.635 8019.533 1.14 0.2541 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -369509 327598.1 -1.13 0.2608 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 39568.49 128451.2 0.31 0.7584 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -2136070 5244228 -0.41 0.6842 (Sugar-0.07)*(Corn Syrup-0.015) 225.5172 171.6942 1.31 0.1907 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) -12907 7010.474 -1.84 0.0672 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -898.685 2752.438 -0.33 0.7444 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 95704.42 112369.1 0.85 0.3955 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 73570.45 114564.8 0.64 0.5216 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -1202861 4679972 -0.26 0.7974 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -2814434 1835016 -1.53 0.1268 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 1.21E+08 74917544 1.61 0.1091

Table 30. Effect of ingredients and ingredient interactions on 2,3 butylene glycol concentration

136

Term Estimate Std Error t Ratio Prob>|t| Intercept 2.513705 0.245004 10.26 <.0001 Protein 2.819933 3.715287 0.76 0.4488 Oil -14.468 1.458689 -9.92 <.0001 Stabilizer 101.4519 60.71501 1.67 0.0964 Sugar 0.736519 1.299878 0.57 0.5717 Corn Syrup 11.91243 6.066097 1.96 0.0511 (Protein-0.03)*(Oil-0.08333) -29.6055 59.55138 -0.5 0.6197 (Protein-0.03)*(Stabilizer-0.00149) 4296.637 2480.209 1.73 0.0849 (Oil-0.08333)*(Stabilizer-0.00149) -1924.34 972.4897 -1.98 0.0493 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) -85106.4 39703.48 -2.14 0.0334 (Protein-0.03)*(Sugar-0.07) 56.35181 53.07553 1.06 0.2898 (Oil-0.08333)*(Sugar-0.07) -17.1162 20.83841 -0.82 0.4125 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) -760.766 850.7339 -0.89 0.3724 (Stabilizer-0.00149)*(Sugar-0.07) 476.0434 867.3573 0.55 0.5838 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) -49036.8 35431.56 -1.38 0.168 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -28515.3 13892.71 -2.05 0.0415 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 633160 567192.6 1.12 0.2657 (Protein-0.03)*(Corn Syrup-0.015) 354.5092 247.6858 1.43 0.154 (Oil-0.08333)*(Corn Syrup-0.015) -158.19 97.24591 -1.63 0.1055 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -4863.56 3970.092 -1.23 0.2221 (Stabilizer-0.00149)*(Corn Syrup-0.015) 1790.007 4047.668 0.44 0.6588 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 115156.3 165347.3 0.7 0.487 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -142001 64832.65 -2.19 0.0298 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -1144614 2646899 -0.43 0.6659 (Sugar-0.07)*(Corn Syrup-0.015) 15.94275 86.65853 0.18 0.8542 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) -3318.52 3538.369 -0.94 0.3495 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -733.418 1389.227 -0.53 0.5982 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 8238.285 56715.6 0.15 0.8847 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -6003.31 57823.82 -0.1 0.9174 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 838902.8 2362104 0.36 0.7229 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -193901 926180.7 -0.21 0.8344 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -1759483 37812838 -0.05 0.9629

Table 31. Effect of ingredients and ingredient interactions on furaneol concentration

137

Term Estimate Std Error t Ratio Prob>|t| Intercept 2.425754 0.187787 12.92 <.0001 Protein 1.105849 2.847644 0.39 0.6982 Oil -9.12487 1.118036 -8.16 <.0001 Stabilizer -29.349 46.53603 -0.63 0.529 Sugar 1.541476 0.996313 1.55 0.1235 Corn Syrup 15.69999 4.649461 0.38 0.39 (Protein-0.03)*(Oil-0.08333) -55.2161 45.64414 -1.21 0.2279 (Protein-0.03)*(Stabilizer-0.00149) -2463.73 1900.998 -1.3 0.1966 (Oil-0.08333)*(Stabilizer-0.00149) -1361.54 745.3809 -1.83 0.0694 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) 36046.91 30431.39 1.18 0.2377 (Protein-0.03)*(Sugar-0.07) -37.2467 40.68062 -0.92 0.3611 (Oil-0.08333)*(Sugar-0.07) -4.88766 15.97195 -0.31 0.7599 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) -436.708 652.0592 -0.67 0.5039 (Stabilizer-0.00149)*(Sugar-0.07) 421.2261 664.8005 0.63 0.5271 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) 13657.48 27157.11 0.5 0.6156 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -8324.09 10648.3 -0.78 0.4354 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 608172.1 434734.2 1.4 0.1635 (Protein-0.03)*(Corn Syrup-0.015) -365.412 189.8429 -1.92 0.0558 (Oil-0.08333)*(Corn Syrup-0.015) -85.8867 74.53575 -1.15 0.2507 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -2690.98 3042.943 -0.88 0.3777 (Stabilizer-0.00149)*(Corn Syrup-0.015) -1147.99 3102.402 -0.37 0.7118 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 835.0522 126733.2 0.01 0.9947 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 43547.71 49692.06 0.88 0.382 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -244927 2028759 -0.12 0.904 (Sugar-0.07)*(Corn Syrup-0.015) 29.55537 66.42087 0.44 0.6569 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) 2633.531 2712.042 0.97 0.3328 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -152.454 1064.796 -0.14 0.8863 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 60719.97 43470.61 1.4 0.1642 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 21808.56 44320.03 0.49 0.6233 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 1133622 1810474 0.63 0.532 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 20216.21 709886.6 0.03 0.9773 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 2272025 28982278 0.08 0.9376

Table 32. Effect of ingredients and ingredient interactions on benzaldehyde concentration

138

Term Estimate Std Error t Ratio Prob>|t| Intercept 1.011903 0.134859 7.5 <.0001 Protein -5.96723 2.045029 -2.92 0.004 Oil -3.10465 0.802915 -3.87 0.0002 Stabilizer 7.283972 33.41975 0.22 0.8277 Sugar -0.07373 0.7155 -0.1 0.918 Corn Syrup -4.8071 3.339 -1.44 0.1517 (Protein-0.03)*(Oil-0.08333) -5.54652 32.77924 -0.17 0.8658 (Protein-0.03)*(Stabilizer-0.00149) -1067.33 1365.197 -0.78 0.4353 (Oil-0.08333)*(Stabilizer-0.00149) 724.8393 535.2937 1.35 0.1774 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) -9071.06 21854.24 -0.42 0.6786 (Protein-0.03)*(Sugar-0.07) 20.96806 29.2147 0.72 0.4738 (Oil-0.08333)*(Sugar-0.07) -16.3542 11.47022 -1.43 0.1556 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) -337.728 468.2749 -0.72 0.4717 (Stabilizer-0.00149)*(Sugar-0.07) -743.65 477.425 -1.56 0.121 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) 23916.5 19502.82 1.23 0.2216 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -3846.74 7647.052 -0.5 0.6155 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -411673 312203.4 -1.32 0.1889 (Protein-0.03)*(Corn Syrup-0.015) 161.7922 136.3353 1.19 0.2369 (Oil-0.08333)*(Corn Syrup-0.015) -18.9274 53.52768 -0.35 0.724 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -1551.06 2185.283 -0.71 0.4787 (Stabilizer-0.00149)*(Corn Syrup-0.015) -1180.64 2227.983 -0.53 0.5968 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 124173 91013.15 1.36 0.1741 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 16800.66 35686.24 0.47 0.6383 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -700421 1456949 -0.48 0.6313 (Sugar-0.07)*(Corn Syrup-0.015) 9.997183 47.7 0.21 0.8342 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) 43.17925 1947.647 0.02 0.9823 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -513.52 764.6812 -0.67 0.5027 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 24423.69 31218.33 0.78 0.435 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -5455.22 31828.33 -0.17 0.8641 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -69603.6 1300188 -0.05 0.9574 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -115733 509803.5 -0.23 0.8207 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 8885391 20813560 0.43 0.6699

Table 33. Effect of ingredients and ingredient interactions on vanillyl alcohol concentration

139

Term Estimate Std Error t Ratio Prob>|t| Intercept 3.157671 0.184733 17.09 <.0001 Protein -13.3807 2.801329 -4.78 <.0001 Oil -13.6165 1.099852 -12.38 <.0001 Stabilizer -13.4786 45.77916 -0.29 0.7688 Sugar -0.33239 0.980109 -0.34 0.7349 Corn Syrup -4.97522 4.573841 -1.09 0.2781 (Protein-0.03)*(Oil-0.08333) 270.735 44.90178 6.03 <.0001 (Protein-0.03)*(Stabilizer-0.00149) -2915.49 1870.079 -1.56 0.1207 (Oil-0.08333)*(Stabilizer-0.00149) -518.932 733.2579 -0.71 0.48 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) 21690.71 29936.45 0.72 0.4696 (Protein-0.03)*(Sugar-0.07) -39.7881 40.01898 -0.99 0.3214 (Oil-0.08333)*(Sugar-0.07) -3.09301 15.71217 -0.2 0.8442 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) 701.0554 641.4539 1.09 0.2759 (Stabilizer-0.00149)*(Sugar-0.07) -608.018 653.988 -0.93 0.3537 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) -59212.7 26715.42 -2.22 0.0279 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 11279.44 10475.11 1.08 0.283 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 312064 427663.6 0.73 0.4665 (Protein-0.03)*(Corn Syrup-0.015) 180.4178 186.7553 0.97 0.3353 (Oil-0.08333)*(Corn Syrup-0.015) 97.73174 73.32348 1.33 0.1842 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -8110.02 2993.452 -2.71 0.0074 (Stabilizer-0.00149)*(Corn Syrup-0.015) -967.955 3051.944 -0.32 0.7515 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 119925.8 124672 0.96 0.3373 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 47609.85 48883.86 0.97 0.3314 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 932166.3 1995763 0.47 0.641 (Sugar-0.07)*(Corn Syrup-0.015) -51.2067 65.34059 -0.78 0.4342 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) 4214.137 2667.932 1.58 0.1159 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 863.5005 1047.478 0.82 0.4108 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 2028.648 42763.6 0.05 0.9622 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -27310.5 43599.2 -0.63 0.5318 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 271353.9 1781028 0.15 0.8791 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -368309 698340.8 -0.53 0.5985 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -1.3E+07 28510904 -0.45 0.6509

Table 34. Effect of ingredients and ingredient interactions on anise alcohol concentration

140

Term Estimate Std Error t Ratio Prob>|t| Intercept 1.191834 0.137513 8.67 <.0001 Protein -2.20575 2.085282 -1.06 0.2915 Oil -5.70125 0.818719 -6.96 <.0001 Stabilizer -18.2195 34.07756 -0.53 0.5935 Sugar 2.565539 0.729583 3.52 0.0006 Corn Syrup -1.23523 3.404722 -0.36 0.7172 (Protein-0.03)*(Oil-0.08333) 111.5145 33.42444 3.34 0.001 (Protein-0.03)*(Stabilizer-0.00149) -322.394 1392.069 -0.23 0.8171 (Oil-0.08333)*(Stabilizer-0.00149) 152.8742 545.8299 0.28 0.7797 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) -2953.59 22284.4 -0.13 0.8947 (Protein-0.03)*(Sugar-0.07) -1.58574 29.78974 -0.05 0.9576 (Oil-0.08333)*(Sugar-0.07) -25.6954 11.69599 -2.2 0.0293 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) 212.2639 477.492 0.44 0.6572 (Stabilizer-0.00149)*(Sugar-0.07) -395.134 486.8222 -0.81 0.418 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) -8893.76 19886.7 -0.45 0.6552 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 4051.23 7797.571 0.52 0.604 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -432505 318348.6 -1.36 0.1759 (Protein-0.03)*(Corn Syrup-0.015) 22.78536 139.0188 0.16 0.87 (Oil-0.08333)*(Corn Syrup-0.015) 55.77399 54.58128 1.02 0.3082 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -1019.77 2228.296 -0.46 0.6477 (Stabilizer-0.00149)*(Corn Syrup-0.015) -608.315 2271.837 -0.27 0.7892 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -81315.1 92804.58 -0.88 0.3821 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -32008.8 36388.66 -0.88 0.3802 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 418935.2 1485627 0.28 0.7783 (Sugar-0.07)*(Corn Syrup-0.015) -8.83957 48.63889 -0.18 0.856 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) 1100.794 1985.983 0.55 0.5801 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 385.992 779.7325 0.5 0.6212 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 5392.783 31832.8 0.17 0.8657 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -42254.3 32454.82 -1.3 0.1946 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 2443132 1325780 1.84 0.067 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 1166891 519838 2.24 0.026 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -2.1E+07 21223237 -1 0.3183

Table 35. Effect of ingredients and ingredient interactions on anisaldehyde concentration

141

Term Estimate Std Error t Ratio Prob>|t| Intercept 0.043856 0.045418 0.97 0.3355 Protein 0.540896 0.688726 0.79 0.4333 Oil -0.03499 0.270406 -0.13 0.8972 Stabilizer -17.9981 11.25512 -1.6 0.1115 Sugar 0.389898 0.240967 1.62 0.1074 Corn Syrup 0.110534 1.12451 0.1 0.9218 (Protein-0.03)*(Oil-0.08333) -4.694 11.03941 -0.43 0.6712 (Protein-0.03)*(Stabilizer-0.00149) -929.813 459.7719 -2.02 0.0446 (Oil-0.08333)*(Stabilizer-0.00149) -52.7075 180.2765 -0.29 0.7703 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) 8994.372 7360.083 1.22 0.2233 (Protein-0.03)*(Sugar-0.07) 20.53871 9.838944 2.09 0.0382 (Oil-0.08333)*(Sugar-0.07) 1.113149 3.862946 0.29 0.7735 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) -190.92 157.7059 -1.21 0.2276 (Stabilizer-0.00149)*(Sugar-0.07) -281.277 160.7875 -1.75 0.0819 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) -5408.27 6568.17 -0.82 0.4113 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 1547.111 2575.379 0.6 0.5488 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 42058.67 105144 0.4 0.6896 (Protein-0.03)*(Corn Syrup-0.015) -7.79678 45.91507 -0.17 0.8653 (Oil-0.08333)*(Corn Syrup-0.015) 11.44294 18.02708 0.63 0.5264 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -656.525 735.9608 -0.89 0.3735 (Stabilizer-0.00149)*(Corn Syrup-0.015) 477.3272 750.3415 0.64 0.5255 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 10284.26 30651.46 0.34 0.7376 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 5917.54 12018.43 0.49 0.623 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -100163 490672.2 -0.2 0.8385 (Sugar-0.07)*(Corn Syrup-0.015) 17.95648 16.06443 1.12 0.2651 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) -258.032 655.9296 -0.39 0.6945 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -4.70029 257.5298 -0.02 0.9855 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 1910.572 10513.73 0.18 0.856 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -1082.28 10719.16 -0.1 0.9197 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 97535.28 437878 0.22 0.824 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -109568 171691.9 -0.64 0.5242 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 6369558 7009602 0.91 0.3647

Table 36. Effect of ingredients and ingredient interactions on eugenol concentration

142

Term Estimate Std Error t Ratio Prob>|t| Intercept 1.104569 0.139187 7.94 <.0001 Protein -6.1854 2.110656 -2.93 0.0038 Oil -5.90435 0.828681 -7.12 <.0001 Stabilizer 23.64849 34.49222 0.69 0.4938 Sugar 0.23879 0.738461 0.32 0.7468 Corn Syrup -0.13532 3.446151 -0.04 0.9687 (Protein-0.03)*(Oil-0.08333) 65.7185 33.83115 1.94 0.0536 (Protein-0.03)*(Stabilizer-0.00149) -307.246 1409.008 -0.22 0.8276 (Oil-0.08333)*(Stabilizer-0.00149) -294.614 552.4717 -0.53 0.5945 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) -4672.72 22555.56 -0.21 0.8361 (Protein-0.03)*(Sugar-0.07) 32.97567 30.15223 1.09 0.2755 (Oil-0.08333)*(Sugar-0.07) -17.3279 11.83831 -1.46 0.145 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) -41.8756 483.3022 -0.09 0.931 (Stabilizer-0.00149)*(Sugar-0.07) -1.67586 492.746 0 0.9973 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) -3166.56 20128.68 -0.16 0.8752 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 8541.746 7892.453 1.08 0.2805 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 42080.96 322222.3 0.13 0.8962 (Protein-0.03)*(Corn Syrup-0.015) -66.4326 140.7104 -0.47 0.6374 (Oil-0.08333)*(Corn Syrup-0.015) 71.20875 55.24543 1.29 0.199 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -1823.89 2255.41 -0.81 0.4197 (Stabilizer-0.00149)*(Corn Syrup-0.015) 376.2158 2299.481 0.16 0.8702 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -59313.3 93933.84 -0.63 0.5285 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 13823.17 36831.45 0.38 0.7079 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -321845 1503704 -0.21 0.8308 (Sugar-0.07)*(Corn Syrup-0.015) 5.778652 49.23074 0.12 0.9067 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) 1241.038 2010.148 0.62 0.5377 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -1095.82 789.2204 -1.39 0.1667 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 39318.84 32220.15 1.22 0.2239 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -3197.27 32849.73 -0.1 0.9226 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 1466983 1341912 1.09 0.2757 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 11932.71 526163.5 0.02 0.9819 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -9980126 21481484 -0.46 0.6428

Table 37. Effect of ingredients and ingredient interactions on methyl cinnamate concentration

143

Term Estimate Std Error t Ratio Prob>|t| Intercept 1.873889 0.135028 13.88 <.0001 Protein -13.1865 2.047596 -6.44 <.0001 Oil -2.79331 0.803923 -3.47 0.0006 Stabilizer -49.9195 33.4617 -1.49 0.1375 Sugar 1.55135 0.716398 2.17 0.0316 Corn Syrup -7.38816 3.343191 -2.21 0.0283 (Protein-0.03)*(Oil-0.08333) -58.5005 32.82039 -1.78 0.0763 (Protein-0.03)*(Stabilizer-0.00149) 25.50011 1366.911 0.02 0.9851 (Oil-0.08333)*(Stabilizer-0.00149) -235.172 535.9656 -0.44 0.6613 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) -10403.1 21881.67 -0.48 0.635 (Protein-0.03)*(Sugar-0.07) 37.66583 29.25137 1.29 0.1995 (Oil-0.08333)*(Sugar-0.07) -14.8287 11.48462 -1.29 0.1983 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) 502.0829 468.8627 1.07 0.2856 (Stabilizer-0.00149)*(Sugar-0.07) -579.677 478.0243 -1.21 0.2268 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) 45762.44 19527.3 2.34 0.0202 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -1016.44 7656.651 -0.13 0.8945 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -718315 312595.3 -2.3 0.0227 (Protein-0.03)*(Corn Syrup-0.015) 318.9708 136.5064 2.34 0.0205 (Oil-0.08333)*(Corn Syrup-0.015) 69.24998 53.59487 1.29 0.1979 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -1353.66 2188.026 -0.62 0.5369 (Stabilizer-0.00149)*(Corn Syrup-0.015) 198.7903 2230.78 0.09 0.9291 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -13773.7 91127.39 -0.15 0.88 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -24145.5 35731.04 -0.68 0.5 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 1122950 1458778 0.77 0.4424 (Sugar-0.07)*(Corn Syrup-0.015) -29.5303 47.75988 -0.62 0.5371 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) 2202.999 1950.091 1.13 0.2601 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 490.5884 765.641 0.64 0.5225 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -34436.3 31257.51 -1.1 0.272 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 47233.86 31868.28 1.48 0.14 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -621723 1301820 -0.48 0.6335 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -669551 510443.4 -1.31 0.1913 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 26701631 20839685 1.28 0.2017

Table 38. Effect of ingredients and ingredient interactions on p-cresol concentration

144

Term Estimate Std Error t Ratio Prob>|t| Intercept 0.333811 0.072479 4.61 <.0001 Protein -2.35497 1.099083 -2.14 0.0335 Oil -2.04442 0.43152 -4.74 <.0001 Stabilizer 20.30907 17.96115 1.13 0.2596 Sugar 0.198134 0.384539 0.52 0.607 Corn Syrup -0.73069 1.794516 -0.41 0.6844 (Protein-0.03)*(Oil-0.08333) 32.93442 17.61692 1.87 0.0631 (Protein-0.03)*(Stabilizer-0.00149) -1345.61 733.7133 -1.83 0.0683 (Oil-0.08333)*(Stabilizer-0.00149) -484.577 287.6889 -1.68 0.0938 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) 26918.8 11745.37 2.29 0.023 (Protein-0.03)*(Sugar-0.07) 3.609065 15.70119 0.23 0.8185 (Oil-0.08333)*(Sugar-0.07) -8.62908 6.164568 -1.4 0.1633 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) 46.06989 251.6702 0.18 0.855 (Stabilizer-0.00149)*(Sugar-0.07) -244.541 256.5879 -0.95 0.3418 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) -10453.2 10481.62 -1 0.3199 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 9640.132 4109.841 2.35 0.0201 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 147819.6 167791 0.88 0.3795 (Protein-0.03)*(Corn Syrup-0.015) 26.8049 73.2722 0.37 0.7149 (Oil-0.08333)*(Corn Syrup-0.015) 41.15429 28.76798 1.43 0.1543 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -838.828 1174.461 -0.71 0.476 (Stabilizer-0.00149)*(Corn Syrup-0.015) -235.889 1197.41 -0.2 0.844 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -15092.8 48914.22 -0.31 0.758 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 9167.038 19179.26 0.48 0.6332 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -174525 783024.6 -0.22 0.8239 (Sugar-0.07)*(Corn Syrup-0.015) 11.1973 25.63595 0.44 0.6628 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) 413.2438 1046.746 0.39 0.6935 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -335.037 410.9712 -0.82 0.416 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -10484.5 16778.02 -0.62 0.5328 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 8874.96 17105.86 0.52 0.6045 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 639473.6 698774.6 0.92 0.3613 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -92201.8 273989.4 -0.34 0.7369 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -9013745 11186066 -0.81 0.4214

Table 39. Effect of ingredients and ingredient interactions on isosafrole concentration

145

Term Estimate Std Error t Ratio Prob>|t| Intercept 1.402519 0.209684 6.69 <.0001 Protein -2.56049 3.179693 -0.81 0.4217 Oil -3.04312 1.248405 -2.44 0.0157 Stabilizer 33.97218 51.96237 0.65 0.5141 Sugar 1.157858 1.112488 1.04 0.2993 Corn Syrup 7.18408 5.191611 1.38 0.1681 (Protein-0.03)*(Oil-0.08333) -16.458 50.96648 -0.32 0.7471 (Protein-0.03)*(Stabilizer-0.00149) -821.226 2122.663 -0.39 0.6993 (Oil-0.08333)*(Stabilizer-0.00149) -703.908 832.2961 -0.85 0.3988 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) -7634.5 33979.85 -0.22 0.8225 (Protein-0.03)*(Sugar-0.07) -91.9373 45.42419 -2.02 0.0444 (Oil-0.08333)*(Sugar-0.07) 25.49486 17.83435 1.43 0.1545 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) 835.9331 728.0925 1.15 0.2524 (Stabilizer-0.00149)*(Sugar-0.07) 630.8125 742.3195 0.85 0.3965 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) 18038.92 30323.76 0.59 0.5527 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -19260.5 11889.94 -1.62 0.107 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 279749 485426.4 0.58 0.5651 (Protein-0.03)*(Corn Syrup-0.015) 60.07248 211.9795 0.28 0.7772 (Oil-0.08333)*(Corn Syrup-0.015) -68.3592 83.22699 -0.82 0.4125 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -3987.42 3397.765 -1.17 0.2421 (Stabilizer-0.00149)*(Corn Syrup-0.015) 4296.818 3464.158 1.24 0.2164 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 41264.47 141510.9 0.29 0.7709 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -35007 55486.4 -0.63 0.5289 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 400929.7 2265323 0.18 0.8597 (Sugar-0.07)*(Corn Syrup-0.015) -21.1998 74.16588 -0.29 0.7753 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) 1174.852 3028.279 0.39 0.6985 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 1772.929 1188.957 1.49 0.1376 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 38644.93 48539.5 0.8 0.427 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -45719.1 49487.97 -0.92 0.3568 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 934583.5 2021584 0.46 0.6444 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 821355.2 792662.9 1.04 0.3015 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -1.9E+07 32361757 -0.59 0.5571

Table 40. Effect of ingredients and ingredient interactions on acetovanillone concentration

146

Protein -21.1276 4.25117 -4.97 <.0001 Oil -16.5338 1.669086 -9.91 <.0001 Stabilizer -62.2342 69.47238 -0.9 0.3715 Sugar -0.94922 1.487369 -0.64 0.5241 Corn Syrup -7.52016 6.941054 -1.08 0.28 (Protein-0.03)*(Oil-0.08333) 261.2281 68.1409 3.83 0.0002 (Protein-0.03)*(Stabilizer-0.00149) -3729.65 2837.948 -1.31 0.1904 (Oil-0.08333)*(Stabilizer-0.00149) -66.2259 1112.759 -0.06 0.9526 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) -45679.3 45430.2 -1.01 0.316 (Protein-0.03)*(Sugar-0.07) -99.2035 60.731 -1.63 0.1041 (Oil-0.08333)*(Sugar-0.07) 23.35986 23.84408 0.98 0.3285 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) -431.875 973.4414 -0.44 0.6578 (Stabilizer-0.00149)*(Sugar-0.07) -1403.32 992.4625 -1.41 0.1591 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) -55450 40542.11 -1.37 0.1731 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 18227.86 15896.56 1.15 0.253 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 992564 649002.8 1.53 0.1279 (Protein-0.03)*(Corn Syrup-0.015) 394.4389 283.4113 1.39 0.1657 (Oil-0.08333)*(Corn Syrup-0.015) 72.64998 111.2724 0.65 0.5146 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -11134.5 4542.727 -2.45 0.0152 (Stabilizer-0.00149)*(Corn Syrup-0.015) -774.996 4631.492 -0.17 0.8673 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 129675.6 189196.5 0.69 0.494 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -8960.57 74183.93 -0.12 0.904 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 1915766 3028680 0.63 0.5278 (Sugar-0.07)*(Corn Syrup-0.015) -9.80133 99.15791 -0.1 0.9214 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) 4105.984 4048.733 1.01 0.3118 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 1103.45 1589.606 0.69 0.4885 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 43687.07 64896.1 0.67 0.5017 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -28870.6 66164.17 -0.44 0.6631 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 210533.7 2702807 0.08 0.938 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -206460 1059770 -0.19 0.8458 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -1.6E+07 43266856 -0.36 0.7185

Table 41. Effect of ingredients and ingredient interactions on p-hydroxybenzoic acid concentration

147

Term Estimate Std Error t Ratio Prob>|t| Intercept 0.95703 0.17235 5.55 <.0001 Protein -2.65991 2.613547 -1.02 0.3101 Oil -0.71999 1.026126 -0.7 0.4838 Stabilizer -42.9621 42.71044 -1.01 0.3158 Sugar -0.7664 0.914409 -0.84 0.403 Corn Syrup 5.683907 4.267242 1.33 0.1845 (Protein-0.03)*(Oil-0.08333) 124.9958 41.89187 2.98 0.0032 (Protein-0.03)*(Stabilizer-0.00149) -3036.84 1744.722 -1.74 0.0834 (Oil-0.08333)*(Stabilizer-0.00149) -2183.73 684.1053 -3.19 0.0017 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) -9104.91 27929.71 -0.33 0.7448 (Protein-0.03)*(Sugar-0.07) 4.053109 37.33639 0.11 0.9137 (Oil-0.08333)*(Sugar-0.07) -29.8394 14.65894 -2.04 0.0432 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) 261.8799 598.4553 0.44 0.6622 (Stabilizer-0.00149)*(Sugar-0.07) 539.9459 610.1491 0.88 0.3773 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) -46156.8 24924.6 -1.85 0.0656 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -14396.1 9772.932 -1.47 0.1424 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -400403 398995.9 -1 0.3169 (Protein-0.03)*(Corn Syrup-0.015) 69.5169 174.2365 0.4 0.6904 (Oil-0.08333)*(Corn Syrup-0.015) 69.80041 68.40838 1.02 0.3089 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -3264.9 2792.791 -1.17 0.2439 (Stabilizer-0.00149)*(Corn Syrup-0.015) -3244.97 2847.363 -1.14 0.2559 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 40392.2 116314.8 0.35 0.7288 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 31701.57 45607.02 0.7 0.4879 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -2335528 1861981 -1.25 0.2113 (Sugar-0.07)*(Corn Syrup-0.015) -17.1524 60.9606 -0.28 0.7787 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) -1922.43 2489.092 -0.77 0.4409 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -352.928 977.2625 -0.36 0.7184 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 21254.59 39897.02 0.53 0.5949 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 54353.7 40676.61 1.34 0.1831 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -8212.54 1661640 0 0.9961 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 145769.4 651528.8 0.22 0.8232 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 10389407 26599728 0.39 0.6966

Table 42. Effect of ingredients and ingredient interactions on vanillic acid concentration

148

Term Estimate Std Error t Ratio Prob>|t| Intercept 35.19728 1.136247 30.98 <.0001 Protein -127.035 17.2303 -7.37 <.0001 Oil -127.33 6.764927 -18.82 <.0001 Stabilizer 27.5277 281.5766 0.1 0.9222 Sugar 10.52167 6.028414 1.75 0.0826 Corn Syrup 8.549269 28.1326 0.3 0.7616 (Protein-0.03)*(Oil-0.08333) 1267.393 276.1801 4.59 <.0001 (Protein-0.03)*(Stabilizer-0.00149) 10098.06 11502.41 0.88 0.3811 (Oil-0.08333)*(Stabilizer-0.00149) -7890.96 4510.093 -1.75 0.0819 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) 279976.8 184131.9 1.52 0.1301 (Protein-0.03)*(Sugar-0.07) -237.084 246.1472 -0.96 0.3367 (Oil-0.08333)*(Sugar-0.07) -24.0912 96.64182 -0.25 0.8034 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) -459.205 3945.429 -0.12 0.9075 (Stabilizer-0.00149)*(Sugar-0.07) 1691.013 4022.523 0.42 0.6747 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) 248292.4 164320.1 1.51 0.1325 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -57889.9 64429.9 -0.9 0.3701 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 2870134 2630456 1.09 0.2766 (Protein-0.03)*(Corn Syrup-0.015) -24.4139 1148.687 -0.02 0.9831 (Oil-0.08333)*(Corn Syrup-0.015) -295.071 450.9951 -0.65 0.5138 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -1747.55 18412 -0.09 0.9245 (Stabilizer-0.00149)*(Corn Syrup-0.015) 78.97626 18771.78 0 0.9966 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -1570879 766827.3 -2.05 0.0419 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -308881 300672.9 -1.03 0.3056 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 20074077 12275461 1.64 0.1037 (Sugar-0.07)*(Corn Syrup-0.015) 6.744072 401.8943 0.02 0.9866 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) 19900.59 16409.81 1.21 0.2268 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -4296.81 6442.788 -0.67 0.5057 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 312651.8 263028.6 1.19 0.2361 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 51666.74 268168.2 0.19 0.8474 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 8580332 10954676 0.78 0.4345 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -1920744 4295327 -0.45 0.6553 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -1.50E+08 1.75E+08 -0.86 0.3923

Table 43. Effect of ingredients and ingredient interactions on p-hydroxybenzyl alcohol concentration

149

Term Estimate Std Error t Ratio Prob>|t| Intercept 2.702746 0.560088 4.83 <.0001 Protein 17.79465 8.493297 2.1 0.0375 Oil -18.1181 3.334621 -5.43 <.0001 Stabilizer 68.40856 138.797 0.49 0.6227 Sugar 1.324282 2.971574 0.45 0.6564 Corn Syrup -3.68527 13.86734 -0.27 0.7907 (Protein-0.03)*(Oil-0.08333) -294.378 136.1369 -2.16 0.0319 (Protein-0.03)*(Stabilizer-0.00149) -4592.14 5669.859 -0.81 0.419 (Oil-0.08333)*(Stabilizer-0.00149) -938.055 2223.151 -0.42 0.6736 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) 135875.2 90763.76 1.5 0.1361 (Protein-0.03)*(Sugar-0.07) -29.2069 121.3328 -0.24 0.81 (Oil-0.08333)*(Sugar-0.07) 39.78416 47.63745 0.84 0.4047 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) 749.182 1944.812 0.39 0.7005 (Stabilizer-0.00149)*(Sugar-0.07) -3718.2 1982.814 -1.88 0.0623 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) 24356.1 80997.98 0.3 0.764 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 37351.3 31759.3 1.18 0.2411 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 1135282 1296625 0.88 0.3824 (Protein-0.03)*(Corn Syrup-0.015) 279.1107 566.2198 0.49 0.6226 (Oil-0.08333)*(Corn Syrup-0.015) 52.77448 222.3081 0.24 0.8126 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -15457.5 9075.791 -1.7 0.0902 (Stabilizer-0.00149)*(Corn Syrup-0.015) 352.2686 9253.132 0.04 0.9697 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -187497 377990.6 -0.5 0.6205 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 68633.8 148210.1 0.46 0.6439 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -607779 6050918 -0.1 0.9201 (Sugar-0.07)*(Corn Syrup-0.015) 91.28002 198.1049 0.46 0.6455 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) 3154.541 8088.854 0.39 0.697 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -449.704 3175.83 -0.14 0.8875 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -3081.59 129654.2 -0.02 0.9811 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 80596.19 132187.6 0.61 0.5428 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -343875 5399866 -0.06 0.9493 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -522415 2117287 -0.25 0.8054 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 26814421 86441679 0.31 0.7568

Table 44. Effect of ingredients and ingredient interactions on coumarin concentration

150

Term Estimate Std Error t Ratio Prob>|t| Intercept 2.567499 0.210972 12.17 <.0001 Protein -15.3595 3.199226 -4.8 <.0001 Oil -0.41951 1.256074 -0.33 0.7388 Stabilizer -49.2062 52.28157 -0.94 0.3478 Sugar 3.145053 1.119322 2.81 0.0055 Corn Syrup 9.630751 5.223504 1.84 0.0668 (Protein-0.03)*(Oil-0.08333) -76.8625 51.27957 -1.5 0.1356 (Protein-0.03)*(Stabilizer-0.00149) 4.253303 2135.703 0 0.9984 (Oil-0.08333)*(Stabilizer-0.00149) -396.794 837.4089 -0.47 0.6362 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) -14143.8 34188.59 -0.41 0.6796 (Protein-0.03)*(Sugar-0.07) -95.9448 45.70323 -2.1 0.0372 (Oil-0.08333)*(Sugar-0.07) 9.421492 17.94391 0.53 0.6002 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) -1314.65 732.5653 -1.79 0.0744 (Stabilizer-0.00149)*(Sugar-0.07) 557.6525 746.8796 0.75 0.4562 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) -22736.9 30510.04 -0.75 0.4571 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -10558.1 11962.98 -0.88 0.3786 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 452736.3 488408.4 0.93 0.3552 (Protein-0.03)*(Corn Syrup-0.015) -57.2691 213.2818 -0.27 0.7886 (Oil-0.08333)*(Corn Syrup-0.015) 11.2447 83.73826 0.13 0.8933 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) 1616.148 3418.638 0.47 0.637 (Stabilizer-0.00149)*(Corn Syrup-0.015) -1861.55 3485.438 -0.53 0.5939 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 36439.08 142380.2 0.26 0.7983 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 43442.76 55827.26 0.78 0.4375 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 631610.6 2279239 0.28 0.782 (Sugar-0.07)*(Corn Syrup-0.015) 38.40749 74.62148 0.51 0.6074 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) -2584.44 3046.882 -0.85 0.3974 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) -36.9957 1196.261 -0.03 0.9754 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 25014.14 48837.68 0.51 0.6091 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -4705.35 49791.98 -0.09 0.9248 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -96872.6 2034003 -0.05 0.9621 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -707330 797532.3 -0.89 0.3763 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 13119129 32560558 0.4 0.6875

Table 45. Effect of ingredients and ingredient interactions on toluene concentration

151

Term Estimate Std Error t Ratio Prob>|t| Intercept 5.348037 0.396837 13.48 <.0001 Protein -13.9065 6.017723 -2.31 0.0219 Oil -14.1884 2.362666 -6.01 <.0001 Stabilizer -88.2517 98.34129 -0.9 0.3707 Sugar 1.2676 2.105438 0.6 0.5479 Corn Syrup -23.6252 9.825376 -2.4 0.0172 (Protein-0.03)*(Oil-0.08333) 162.32 96.45652 1.68 0.0941 (Protein-0.03)*(Stabilizer-0.00149) -4475.2 4017.243 -1.11 0.2667 (Oil-0.08333)*(Stabilizer-0.00149) -829.503 1575.161 -0.53 0.5991 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149) 840.4331 64308.5 0.01 0.9896 (Protein-0.03)*(Sugar-0.07) 42.27273 85.96747 0.49 0.6235 (Oil-0.08333)*(Sugar-0.07) -45.0971 33.75238 -1.34 0.1832 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07) -2086.21 1377.95 -1.51 0.1317 (Stabilizer-0.00149)*(Sugar-0.07) -3230.87 1404.876 -2.3 0.0226 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07) -35.858 57389.19 0 0.9995 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) -7396.3 22502.29 -0.33 0.7428 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07) 366172.9 918692.9 0.4 0.6907 (Protein-0.03)*(Corn Syrup-0.015) 440.541 401.1815 1.1 0.2736 (Oil-0.08333)*(Corn Syrup-0.015) 22.1476 157.5111 0.14 0.8883 (Protein-0.03)*(Oil-0.08333)*(Corn Syrup-0.015) -7934.55 6430.435 -1.23 0.2188 (Stabilizer-0.00149)*(Corn Syrup-0.015) 4101.343 6556.086 0.63 0.5324 (Protein-0.03)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 36796.97 267816.2 0.14 0.8909 (Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) -73307.2 105010.7 -0.7 0.486 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Corn Syrup-0.015) 10710611 4287233 2.5 0.0134 (Sugar-0.07)*(Corn Syrup-0.015) 68.46928 140.3625 0.49 0.6263 (Protein-0.03)*(Sugar-0.07)*(Corn Syrup-0.015) 749.9994 5731.165 0.13 0.896 (Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 929.3334 2250.159 0.41 0.6801 (Protein-0.03)*(Oil-0.08333)*(Sugar-0.07)*(Corn Syrup-0.015) 3393.752 91863.36 0.04 0.9706 (Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -126308 93658.37 -1.35 0.1791 (Protein-0.03)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) 2325642 3825946 0.61 0.544 (Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -66328.5 1500153 -0.04 0.9648 (Protein-0.03)*(Oil-0.08333)*(Stabilizer-0.00149)*(Sugar-0.07)*(Corn Syrup-0.015) -9E+07 61246191 -1.47 0.142

Table 46. Effect of ingredients and ingredient interactions on p-hydroxybenzaldehyde concentration

152

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