Fiber is an important nutrient that many Americans do not consume enough of.

Written Report Shelly Davis November 21, 2005 Title: Bene Affects on Fruity Oatmeal Bars Abstract: Fiber is an important nutrient that many Americans do not consume enough of. Bene is a soluble dietary that can be added to food products. Bene is advertised as the clear choice because one consuming the product is not supposed to be able to tell that extra has been added. This project examined the affect of adding different amounts of Bene to fruity oatmeal bars, and examining the changes in flavor, texture, and color. A Stable Micro Systems Texture Analyzer, Hunter Colorimeter, and a taste panel were used to examine the texture, color, and flavor changes in the oatmeal bars. The Texture Analyzer results showed an increase in force as the content increased for the three highest content trials. Both the Hunter Colorimeter and taste panel did not show significant differences between the different levels. Therefore this project mainly enforced Bene s claim that adding Bene to foods will not affect their flavor, texture, or color. Introduction: Many people do not consume the recommended 14-15 grams of dietary per 1000 Kilocalories consumed. Consuming an adequate intake of dietary has shown

to lower blood cholesterol, lower the risk of colon cancer, prevent diverticulosis, normalize blood glucose, and normalize insulin levels. (ADA, 2002) High diets have also shown to decrease the total Kilocalories consumed in a week by 1,071 Kilocalories. (Stevens, J., 1988) Many people do not consume enough of the foods like barley, legumes, fruits, vegetables, oatmeal, oat bran and rice hulls to meet the requirements for dietary intake. (Slavin, J. 1987) Therefore people have turned to other sources of to increase their intakes. These alternatives include products that have gotten the reputation of a gritty texture and bad taste. There are a number of reasons why some high products have these qualities. Some enrichment powders used have larger particle sizes in the size of 100 mesh powder, while products using the 200 mesh powder range have better textures. This is because the powder is less gritty and finer. The effective particle size can dramatically affect the s retention and absorption of water. Fiber s water holding capacity allows it to be a fat replacer. But even the products with high mesh powder ranges can contribute to changes in flavor and color. Processes such as extraction and bleaching processes have been improved to minimize the taste of. ( Prosky, 1988) During the past years, supplementation has been used to increase the content of a variety of foods, and a variety of products have been used to enhance the content without affecting the quality of the product. (Mckee, L.H. 2000) Bene is a soluble dietary that can be added to food products without affecting their natural texture, color, or flavor. Bene is advertised as the clear choice because one consuming the in a product cannot tell that extra has been added. Bene s water solubility means that it is not supposed to change the food s color,

flavor, texture, or even aroma. This project will see if the Bene s claim is true. A taste panel using a 9-point Hedonic Scale will be used to rate the flavor. A Stable Micro Systems Texture Analyzer will be used to measure the texture of the products, and a Hunter Colorimeter will be used to measure the changes in color. The independent variable is going to be the amount of Bene added to the product. The dependent variables measured in this experiment are flavor, texture, and color. Methods: Overall Design The project will have four different levels of Bene added to fruity oatmeal bars and will be carried out for three different trials. The following table shows the different amounts of Bene added to each of the products. There are three samples with added and one with no added which will be the control. The following recipe for Fruity Oatmeal Bars was used for this project. Number 627 725 321 528 % of 0% 1.389% 2.74% 4.05% Bene (in total product) Grams of Bene 0 grams 12 grams 24 grams 36 grams Fruity Oatmeal Bar Recipe Source: Bene.com Ingredients: -96 grams quick-cooking oats -2.3 grams cinnamon -.52 grams cloves -110 grams dried apricots (cut into ¼ inch squares)

-110 grams dried apples (cut into ¼ inch squares) -110 grams dried cranberries (whole) -423 grams apple butter -changing gram amounts of Bene (see table 1 above) Instructions: 1. Pre-heat the oven to 177 C (350 F). Use the same oven for each of the four samples and use the same oven for each of the three trials. 2. Weigh all ingredients using a scale. 3. Mix the weighed oats, cinnamon, and cloves in a large bowl. Stir in the dried fruits and nuts. 4. Combine the apple butter and the Bene. Stir for 25 strokes. 5. Spread the mixture evenly into a 9 inch by 13 inch non-stick pan. 6. Bake the product for 20 minutes. Always cook each product for the same amount of time. 7. Immediately cut the bars into 10 1 inch by 1 inch squares for the taste panel, 2 3 inch x 3 inch squares for the Hunter Colorimeter, and 2 2 inch x 2 inch squares for the texture analyzer. The subjective test of a taste panel of 7-9 people were used to rate the four products using a 9-point Hedonic Rating Scale. Random 3-digit numbers were assigned to each of the products to identify the products during the taste panel. The random 3- digit numbers are assigned in the table shown above. The fruity oatmeal bars were cut into 1 inch by 1 inch squares to be tasted. The taste panel was made up of college age students, both male and female. (See scorecard on next page)

The objective test of the Hunter Colorimeter was used to measure the color differences in the four different samples. This machine reported the L, a, and b values. Hunter Colorimeter Procedure (CM Weaver, JR Daniel, 2003) 1. Turn on the Lab Scan XE and make sure the computer and monitor are on. 2. Click on the Universal icon. 3. Standardize the instrument, and then place sample of fruity granola bar at the measuring port covering the Petri dish. 4. Read the Sample, and the color data will be reported in L, a, and b values. 5. Record the data from the Master Color Data window. The objective test of the Stable Micro Systems Texture Analyzer will be used to examine the texture of the four samples. The Texture Analyzer has a moving crosshead that compressed a food sample, and a load cell that measures the force by using different probes. The cone probe will be used to measure the texture of the fruity oatmeal bars. Each sample had two readings taken by the Texture Analyzer. Stable Micro Systems Texture Analyzer Procedure (CM Weaver, JR Daniel, 2003) 1. Make sure the computer, monitor, and texture analyzer are turned on. 2. Put the cone probe on the texture analyzer. 3. Cut all of the samples into 2 inch x 2 inch squares. 4. Choose the granola setting. Set the texture analyzer at the following settings. Pre test Test Post test Rupture Distance Force Time constant speed speed speed test dist. 2 mm/s 3 mm/s 10mm/s 1mm 8mm 2000g 5s 5

5. Perform 2 quick test runs on each of the four sample products. 6. Record the force required to penetrate the fruity oatmeal bar. Replications The experiment will be carried out for three different trials, with each trial containing each of the four different levels. The sample containing no added will be the control. Each trial will use a taste panel, the Texture Analyzer, and the Hunter Colorimeter to measure the dependent variables. During each trial, the 4 sample products were made. The same oven was used to cook each of the samples, and the same time was also used. Discussion: After collecting the data from the Hunter Colorimeter, it was entered into Excel. The averages and standard deviations were calculated for the Hunter Colorimeter values. Table 1 summarizes these values, and Figures 1-3 examines the values L, a, and b. The L values, values, and b values did not have very much variance among the four different levels. The standard deviations were low with 5.20 being the largest. The L values looked at the black and white variance, with 0 being black and 100 being white. The L values varied between 39.04-41.03. The sample containing 36 grams of showed the whitest product. The Bene product was white in color so the product containing the most Bene should have the highest L value. The a values looked at the green to red variance, with green being negative and red being positive. Figure 2 shows that the value

for the 0 grams of sample and 36 grams of sample had the lowest amount of red. Samples containing 12 and 24 grams of showed the highest amounts of red color. The b values reported by the Hunter Colorimeter show the variance in blue and yellow colors with blue being negative and yellow being positive. The b values varied between 12.65-14.17. Figure 3 shows that the 12 gram of sample had the highest yellow value and that the sample containing 36 grams of had the least amount of yellow value. The Hunter Colorimeter did not show much of a change in color, so therefore Bene s claim that it does not change color is shown here. T-tests ran between each of the variables showed no significant difference. Figure 4 shows the results of the t-test: paired two samples for means that was carried out ran between the control sample and the sample containing 36 grams of. The p value for the t-test ran between the 0 grams of added and the 36 grams of added was 0.62, so therefore there was absolutely no significant difference shown in color by the Hunter Colorimeter. The data collected from the Texture Analyzer was also entered into Excel. The averages and standard deviations are summarized in Table 2. Figure 5 shows that it took more force to penetrate the samples containing 12 grams to 36 grams. These values show that the texture did change as the increased. Bene s claim that it does not change the texture of foods is not shown to be true in this experiment. Figure 6 shows the results of the t-test: paired two samples for means that was carried out between the control sample and the sample containing 36 grams of. The t-test ran between the 0 grams of added and the 36 grams of added showed significance. The p value for this test was 0.013. The t-test ran between 12 grams of added and the 36 grams

of added did not show significance though. Figure 7 shows these results. A study carried out on pastas with added soluble and insoluble dietary showed changes in textural characteristics. Results from this study showed that both the type and amount of added influence the overall quality of both raw and cooked pasta. (Tudorica, CM, 2002) The data collected from the taste panel, using the 9-point Hedonic Scale was entered into Excel, and the average was found for each of the four samples. Table 3 shows that there was not a lot of variance between the 4 samples. The product containing 12 grams of scored the highest with 7.14 and the product containing 24 grams of scored the lowest with 6.23. This information is shown in Figure 8. The taste panel data showed that the highest product did not get the lowest rating. The t-test p value was 0.40, for the test ran between 0 grams of and 36 grams of. Therefore the data shows that the taste does not significantly change with the addition of. Therefore Bene s claim that the product does not change taste was shown in this experiment. Sensory analysis of flavor of beef patties with added Z-Trim corn showed slight decreases in beef and fatty flavors. This study also examined replacing fat with Z-Trim corn in a cake-like brownie product, and the sensory analysis of this product showed that this replacement increased the moistness, density, and cohesiveness than the product without the added. (Warner, 1997) This experiment showed that increasing Bene in fruity oatmeal bars did not significantly change the color or taste of foods. Adding more Bene did make the products different in texture, causing a slight increase in the penetrating force as the increased. The change in the texture analysis was significant between the 0 grams of

added product and 36 grams of added product. More trials would have to be carried out with greater of added to see if adding more Bene increased the penetrating force. Therefore they hypothesis of adding Bene to fruity oatmeal bars will not affect their flavor, texture, or color was shown to be true by this experiment. This experiment could be changed to make the results even better. One change would be by adding Bene to another product than fruity oatmeal bars. The fruity oatmeal bars had a variety of fruits in them so therefore their texture and color was not the same throughout all of the products. A more homogeneous product would be better to test for color and texture changes. The 9-point Hedonic scale could also be used to ask more questions of the sensory panel. This experiment only asked them to rate the flavor, but you could also have them rate the texture and compare these results to the Texture Analyzer results. These would be the best changes for this experiment if it were repeated.

Results: Table 1: Hunter Colorimeter Values Fiber(grams) Average L Standard Deviation L Average a Standard Deviation a Average b Standard Deviation b 0 41.03333 3.412657811 6.353333 1.031843011 12.71667 3.315755319 12 39.04333 0.69212234 6.83 0.753591401 14.17 0.455302098 24 41.1 1.496629547 6.73 0.709248429 13.61 0.687895341 36 40.38333 5.201320345 6.28 0.720023148 12.65333 0.445009363 L values 41.5 41 41.03333333 41.1 40.5 40.38333333 40 39.5 39 39.04333333 38.5 0 5 10 15 20 25 30 35 40 (grams) Figure 1: Hunter Colorimeter Average L Values a values 6.9 6.8 6.83 6.7 6.73 6.6 6.5 6.4 6.353333333 6.3 6.28 6.2 0 5 10 15 20 25 30 35 40 (grams) Figure 2: Hunter Colorimeter Average a Values 14.4 14.2 14.17 14 13.8 13.6 13.61 13.4 13.2 13 12.8 12.6 12.71666667 12.65333333 12.4 0 5 10 15 20 25 30 35 40 (grams) b Values Figure 3: Hunter Colorimeter Average b Values 0 grams 36 grams Mean 41.03333 40.38333333 Variance 11.64623 27.05373333 Observations 3 3 Pearson Correlation 0.984294 Hypothesized Mean Difference 0

df 2 t Stat 0.580844 P(T<=t) one-tail 0.310039 t Critical one-tail 2.919986 P(T<=t) two-tail 0.620078 t Critical two-tail 4.302653 Figure 4: Hunter Colorimeter T-test Results between 0 grams of and 36 grams of Table 2: Texture Analyzer Results Fiber(grams) Average(grams of force) Standard Deviation(grams of force) 0 226.8556 28.87068 12 192.4444 87.35184 24 266.3 60.8717 36 348.1222 86.7271 force to penetrate(grams) 400 350 300 250 200 150 100 50 0 0 5 10 15 20 25 30 35 40 (grams) Figure 5: Texture Analyzer Results 0 grams 36 grams Mean 226.8556 348.1222 Mean Variance 5298.648 8686.482 Variance Observations 9 9 Observations Pearson Correlation 0.062107 Pearson Correlation Hypothesized Mean Difference 0 Hypothesized Mean Difference df 8 df t Stat -3.1734 t Stat P(T<=t) one-tail 0.006564 P(T<=t) one-tail t Critical one-tail 1.859548 t Critical one-tail P(T<=t) two-tail 0.013127 P(T<=t) two-tail t Critical twotail t Critical two-tail 2.306004 Figure 6: Texture Analyzer T-test Results between 0 grams of and 36 grams of

t-test: Paired Two Sample for Means 12 grams 36 grams Mean 226.8556 192.4444 Variance 5298.648 9043.478 Observations 9 9 Pearson Correlation 0.02012 Hypothesized Mean Difference 0 df 8 t Stat 0.870507 P(T<=t) one-tail 0.204692 t Critical one-tail 1.859548 P(T<=t) two-tail 0.409383 t Critical two-tail 2.306004 Figure 7: Texture Analyzer T-test Results between 12 grams of and 36 grams of Table 3: Taste Panel Results Fiber(grams) Average Result Values (based on 9 point scale) 0 6.851852 12 6.566138 24 7.137566 36 6.227513 7.4 Panel Scale Results (based on a 0-9 point Hedonic Scale) 7.2 7 6.8 6.6 6.4 6.2 6 5.8 5.6 1 2 3 4 (grams) Figure 8: Taste Panel Results

References Stevens, J, 1988. Does dietary affect food intake and body weight? J Am Diet Assoc. Aug; 88(8): 939-42, 945. Prosky L, Asp NG, Schweizer TF, DeVries JW, Furda I, 1988. Determination of insoluble, soluble, and total dietary in foods and food products: interlaboratory study. J Assoc of Anal Chem. Sep-Oct; 71(5):1017-23 Slavin JL. 1987. Dietary : classification, chemical analyses, and food sources. J Am Diet Assoc. Sep; 87(9):1164-71. American Dietetic Association. 2002. Health implications of dietary. J Am Diet Assoc; 1 02:993-1000. Tudorica CM, Kuri V, Brennan CS. 2002. Nutritional and physicochemical characteristics of dietary enriched pasta. J Agric Food Chem; 16;50(2):347-56. Warner K, Inglett, G.E. 1997. Flavor and Texture Characteristics of Foods Containing Z-Trim Corn and Oat Fibers as Fat and Flour Replacers. Cereal Foods World; 42, 10:821-825. McKee L.H., Latner T.A. 2000. Underutilized sources of dietary : A review. Plant Foods for Human Nutrition; 55,4:285-304. Bene.com