Abstract
A healthier lifestyle, incorporating the consumption of foods with a low glycemic index, can mitigate the risk of diabetes. Previous research aimed to develop food products with a low glycemic index using high-fiber raw materials such as sweet corn (Zea mays saccharata Sturt) with a glycemic index 36 and red beans (Phaseolus vulgaris L.) with 26. However, these products exhibited weaknesses, including low crunch resistance in milk, lack of consideration for consumer sensory acceptance, and unverified glycemic index values. Therefore, this research aimed to (1) enhance the crunch resistance of instant flakes in milk; (2) evaluate the physical and sensory characteristics of instant flakes products; and (3) determine the glycemic index value of instant flakes products based on the best formula from the sensory tests. Five formulas were developed based on the proportion of red beans to sweet corn (formulas 1 to 5), respectively 80:120, 90:110, 100:100, 110:90, and 120:80. The color of all formulas of flakes tended to be similar (dominant yellow). The crunch resistance in milk exceeded 2 minutes, predominantly influenced by the red bean portion. Sensory profile from consumer preferences indicated that the intensity of the attributes such as yellowish-brown color, sweet aroma, salty taste, savory taste, savory aftertaste, burned taste, sandy texture, hard texture, dry aftertaste, sticky aftertaste needed to be reduced when serving flakes with milk. Formula 3 emerged as the optimal formula based on sensory profile and red bean proportion, exhibiting a low glycemic index value of 28.
Keywords:
Diabetes mellitus; Flakes; Glycemic index; Product development; Red bean; Sensory profile; Sweet corn
Highlights
• Beans and corn were used to develop an instant product with a low glycemic index
• Optimal formula based on sensory profile and red bean proportion exhibited a low glycemic index value of 28
1 Introduction
Diabetes mellitus (DM) is a serious health problem because it accumulates glucose in the blood and high levels can damage the small blood vessels in the kidneys, heart, eyes, and nervous system. Indonesia ranks 7th in the world with the highest number of people living with diabetes (Saeedi et al., 2019Saeedi, P., Petersohn, I., Salpea, P., Malanda, B., Karuranga, S., Unwin, N., Colagiuri, S., Guariguata, L., Motala, A. A., Ogurtsova, K., Shaw, J. E., Bright, D., & Williams, R. (2019). Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the IDF diabetes atlas, 9th edition. Diabetes Research and Clinical Practice, 157, 107843. http://doi.org/10.1016/j.diabres.2019.107843
http://doi.org/10.1016/j.diabres.2019.10...
). DM is a metabolic disease caused by an increase in blood sugar due to insulin resistance or low levels of insulin production by the pancreas.
Previous studies have shown that the consumption of carbohydrates with a low glycemic index (GI) is an alternative dietary option to prevent DM (Sacks et al., 2014Sacks, F. M., Carey, V. J., Anderson, C. A. M., Miller III, E. R., Copeland, T., Charleston, J., Harshfield, B. J., Laranjo, N., McCarron, P., Swain, J., White, K., Yee, K., & Appel, L. J. (2014). Effects of high vs low glycemic index of dietary carbohydrate on cardiovascular disease risk factors and insulin sensitivity: The OmniCarb randomized clinical trial. Journal of the American Medical Association, 312(23), 2531-2541. PMid:25514303. http://doi.org/10.1001/jama.2014.16658
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). The concept of the glycemic index was introduced (Jenkins et al., 1981Jenkins, D. J., Wolever, T. M., Taylor, R. H., Barker, H., Fielden, H., Baldwin, J. M., Bowling, A. C., Newman, H. C., Jenkins, A. L., & Goff, D. V. (1981). Glycemic index of foods: A physiological basis for carbohydrate exchange. The American Journal of Clinical Nutrition, 34(3), 362-366. PMid:6259925. http://doi.org/10.1093/ajcn/34.3.362
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) as a way of evaluating a food by observing its glycemic response, always compared to a reference food, be it pure glucose or pure bread. The grouping of foods based on the glycemic index value is divided into three categories, namely: [1] low GI foods (≤ 55), [2] medium GI foods (56–69), and [3] high GI foods (≥70).
Refer to previous studies done by the same group, it was found that several food raw materials have a low GI, namely exotic sweet corn (Zea mays saccharata Sturt) has a glycemic index of 36 (Daniels, 2022Daniels, E. (2022). Verification of meta-analysis results of glycemic index of corn products and development of sweet corn-based instant products. Bogor: IPB University.) and red beans (Phaseolus vulgaris L.) has a glycemic index of 26 (Afandi et al., 2021Afandi, F. A., Wijaya, C. H., Faridah, D. N., Suyatma, N. E., & Jayanegara, A. (2021). Evaluation of various starchy foods: A systematic review and meta-analysis on chemical properties affecting the glycemic index values based on in vitro and in vivo experiments. Foods, 10(2), 364. PMid:33567535. http://doi.org/10.3390/foods10020364
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).
The development of products made from these raw materials is in the form of flakes. This product is expected to be a low-GI alternative food option, that is, aiming for mitigate the risk of diabetes. Daniels (2022)Daniels, E. (2022). Verification of meta-analysis results of glycemic index of corn products and development of sweet corn-based instant products. Bogor: IPB University. has developed this flakes product with two formulas based on the proportion of red beans to corn, namely 70:30 and 30:70, but it still needs further development and we want to achieve that in this research, namely, the crunchiness in milk which is low or quickly destroyed and has not considered consumer sensory acceptance and determination of the glycemic index value.
This study aims to: improve the crunch resistance of instant flakes in milk products; study the physical and sensory characteristics of instant flake products; and determine the GI value of instant flake products based on the best formula from the sensory test.
2 Materials and methods
2.1 Materials
Exotic sweet corn was obtained from Kemang Market, Bogor. The red beans used were purchased in dry form from a vegetable trader in Babakan Raya, Dramaga, Bogor. The reference food used for glycemic index analysis is glucose (Dextrose Monohydrate, PT. Brataco, Indonesia). The ingredients used to make instant flakes are salt, skimmed milk powder, as well as tapioca flour obtained from the local market.
Blood glucose levels were measured using a glucometer, glucose strips (OneTouch UltraEasy, Johnson & Johnson Ltd., USA), syringes (OneTouch UltraSoft, Johnson & Johnson Ltd., USA), and 70% alcohol wipes (Onemed, Indonesia). The tools used for sample analysis are TA-XTplus Texture Analyzer and Konica Minolta Chromameter. Tools for making instant flake products include a food processor, oven, and other tools.
2.2 Work procedures
This research consists of four stages. In the first stage, the formulation is carried out. Flakes are made by mixing the main ingredients consisting of steamed sweet corn and red beans in a food processor, molding the dough, and baking for 55 minutes at 150 °C. Flakes are made in 5 different ratios to see product character patterns. Based on the proportion of red beans to sweet corn, formula 1 (F1) to formula 5 (F5) are respectively 80:120, 90:110, 100:100, 110:90, and 120:80. The amounts of each tapioca flour, skimmed milk powder, and salt added to each formula are the same, respectively 50 g, 30 g, and 5 g.
The second stage is the process of physical characterization and sensory evaluation and determining the best formula. The physical test consists of a crunch resistance test in milk (Papunas et al., 2013Papunas, M. E., Gregoria, S. S. D., & Judith, S. C. M. (2013). Karakteristik fisikokimia dan sensoris flakes berbahan baku tepung jagung (Zea mays L.), tepung pisang goroho (Musa acuminafe sp.) dan tepung kacang hijau (Phaseolus radiates). Jurnal Universitas Sam Ratulangi, 3(5), 2-10.) which shows the time flakes remain in the milk until they are palatable to consumption and until they crumble, a color test using the Konica Minolta Chromameter CR-400, and a texture test using the TA-XTplus Texture Analyzer. The sensory test was carried out preceded by a Focus Group Discussion by 12 panelists to determine the Check-All-That-Apply (CATA) test parameters and hedonic rating, then the CATA test and hedonic rating were carried out by 78 panelists on five formulas which were carried out with the addition of milk and without milk. This was done to study the character of the flakes themselves and if they were served with milk-like flakes in general. CATA results are in the form of binary data on the presence or absence of attributes according to the panelists. Then the data is processed with XLSTAT to see the differences in attributes between formulas, the relationship between the test formula and the ideal, the relationship between attributes and preferences, and the relationship between need state and satisfaction. The results of the hedonic rating in the form of the percentage of panelists, starting from those who somewhat like the product, will be considered together with the proportion of red beans in a formula in order to determine the selected formula.
The third stage, namely determining the glycemic index with ISO 26642 protocol (International Organization for Standardization, 2010International Organization for Standardization. (2010). ISO 26642:2010E: Food products determination of the Glycaemic Index (GI) and recommendation for food classification. Geneva: ISO.) of the selected formula is preceded by an analysis of water content, ash content, and fat content which is carried out according to SNI 01-2891-1992 (Indonesian National Standard, 2006Indonesian National Standard. (2006). SNI 01-2346-2006: instructions for organoleptic or sensory testing. Jakarta: National Standards Agency.); while protein content and total dietary fiber according to AOAC 960.52-1961 (Association of Official Analytical Chemist, 2010Association of Official Analytical Chemist – AOAC. (2010). AOAC 960.52-1961: Microchemical determination of nitrogen. Gaithersburg: AOAC.); AOAC 985.29 (Association of Official Analytical Chemist, 2005Association of Official Analytical Chemist – AOAC. (2005). AOAC 985.29: Total dietary fiber determination. Gaithersburg: AOAC.). Carbohydrate levels are calculated by difference. The test results are used to determine the portion of flakes consumed by respondents based on 50 g of available carbohydrates.
2.3 Ethics approval of research
This study involves human participants. This research was conducted following the ISO 26642:2010 protocol and was approved by the Ethics Committee IPB University (protocol code: 893/IT3.KEPMSM-IPB/SK/2023).
2.4 Statistical analysis
The results obtained were analyzed by ANOVA using IBM® SPSS® version 26 with a 95% confidence level. Sensory profile calculation was analyzed by using XLSTAT in Microsoft Excel.
3 Results and discussion
3.1 Physical characteristics of flakes products
Determining the quality of a food ingredient often depends on color, because color appears to be the first impression of the product by consumers. Visualization of instant flake products can be seen in Figure 1 and the results of flake color analysis measurements can be seen in Table 1.
Overall, it can be observed that a large proportion of corn in the formula influences the color of the flakes produced, namely increasing L* (lightness), b* (yellowness), C* (chroma), and °Hue (chromatic color). However, the color of the flakes with the five formulations tends to be similar (orange, predominantly yellow).
In previous studies (Daniels, 2022Daniels, E. (2022). Verification of meta-analysis results of glycemic index of corn products and development of sweet corn-based instant products. Bogor: IPB University.) the resulting product was still easily destroyed, in less than 2 minutes. In this study, the texture of the product was improved resulting in greater resistance and crunchiness of the flakes when added to milk. The crunchiness of the milk flakes in this study can be seen in Table 2.
The results of measurements of crunch resistance in milk are in accordance with the statement of Gandhi & Wenk (2014)Gandhi, K., & Wenk, R. S. (2014). Method of forming ready to eat cereal flakes containing legumes. EP Patent No. 2 717 723 B1. that a good breakfast cereal product must be able to maintain its crunchiness for more than two minutes in a bowl of milk. Crunchy resistance in milk can be used as a reference for serving suggestions. Test results also showed an increase in crunchiness in milk as the proportion of beans increased. This is supported by the measurement of the texture parameters of the flakes product (hardness), where the addition of the proportion of red beans causes an increase in product hardness as can be seen in Table 2.
Hardness has a positive correlation with amylose levels (Aoki et al., 2012Aoki, N., Umemoto, T., Hamada, S., Suzuki, K., & Suzuki, Y. (2012). The amylose content and amylopectin structure affect the shape and hardness of rice bread. Journal of Applied Glycoscience, 59(2), 75-82. http://doi.org/10.5458/jag.jag.JAG-2011_013
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). Red bean amylose content ranges from 32.0% to 45.4% while corn amylose content generally ranges from 15.3% to 25.1% (Sandhu et al., 2004Sandhu, K. S., Singh, N., & Kaur, M. (2004). Characteristics of the different corn types and their grain fractions: Physicochemical, thermal, morphological, and rheological properties of starches. Journal of Food Engineering, 64(1), 119-127. http://doi.org/10.1016/j.jfoodeng.2003.09.023
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).
3.2 Sensory characteristics of flakes products
3.2.1 Parameters approved by Focus Group Discussion
The results of the Focus Group Discussion (FGD), in the form of 12 sensory attributes and three need state attributes, can be seen in Table 3. The selected attributes were used as the basis for sensory testing of the CATA method and hedonic ratings.
The attributes that have been approved by the FGD participant panelists are then used in the CATA test and hedonic ratings such as the development of small industrial scale coconut chips products (Awaludin et al., 2022Awaludin, M., Andarwulan, N., & Wulandari, N. (2022). Development of coconut chips for small-scale industries. Journal of Food Quality, 9(2), 103-110. ). The CATA test produces binary data from the presence of test attributes such as in the product development of telang lemon drinks with popping boba (Kardinan, 2022Kardinan, S. A. (2022). Physico-chemical characteristics and sensory profile of lemon telang drink with popping boba at PT XYZ. Bogor: IPB Univesity.). The binary data was then analyzed by sensory in XLSTAT to produce differences in attributes between formulas, the relationship between the test formula and the ideal, the relationship between attributes and preferences, and the relationship between need state and satisfaction as in the sensory profile analysis of green tea (Adawiyah et al., 2019Adawiyah, D. R., Azis, M. A., Ramadhani, A. S., & Chueamchaitrakun, P. (2019). Perbandingan profil sensori teh hijau menggunakan metode analisis deskripsi kuantitatif dan CATA (CHECK-ALL-THAT-APPLY). Jurnal Teknologi dan Industri Pangan, 30(2), 161-172. http://doi.org/10.6066/jtip.2019.30.2.161
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). The resulting sensory profile can be seen in the next sub-chapter.
3.2.2 Attribute differences between test product formulas
Differences between samples for each attribute can be seen from the results of Cochran's Q test analysis and multiple pairwise comparisons (Table 4).
In general, the attribute intensity of reddish-brown color, aroma of red bean, and taste of red bean is lower for F1. This is reasonable because F1 is a flakes formula with the lowest proportion of red beans. The same trend was also observed for dry aftertaste attributes. Thus, it can be assumed that increasing the proportion of kidney beans in the formula may cause a dry aftertaste. The reddish-brown color and red bean aroma were not observed when the milk was added. This could be due to the overpowering of the red bean aroma and the white color of the milk which reduces the intensity of the reddish-brown color on the flakes.
3.2.3 Test product and ideal product attributes
Correspondence analysis shows the relationship between samples with each attribute and shows the ideal product position according to the panelists (Adawiyah et al., 2019Adawiyah, D. R., Azis, M. A., Ramadhani, A. S., & Chueamchaitrakun, P. (2019). Perbandingan profil sensori teh hijau menggunakan metode analisis deskripsi kuantitatif dan CATA (CHECK-ALL-THAT-APPLY). Jurnal Teknologi dan Industri Pangan, 30(2), 161-172. http://doi.org/10.6066/jtip.2019.30.2.161
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). In general, the ideal flakes product has the attributes of brownish yellow color, corn taste, corn aroma, sweet taste, sweet aftertaste, roasted aroma, roasted taste, and roasted texture. The dominant attributes possessed by the five samples are different from the ideal product attributes seen from the different points in the quadrants. These results were consistent for both treatments. Product F1 has dominant attributes that tend to be different from F2, F3, F4, and F5 (Figure 2.).
Correspondence analysis and principal component analysis results for sensory attributes of five flake formulas (F1 – F5) (a) without and (b) with the addition of milk.
Principal component analysis (PCA) was carried out to determine the attributes that most influence preference. PCA test results can be seen in Figure 2. Some of the attributes that most influence preference, both without and with the addition of milk, are sweet taste, sweet aroma and sweet aftertaste, corn aroma, and corn taste (Figure 3). Regarding liking, penalty analysis is carried out with the output in the form of a summary of sensory attributes that can reduce or increase the value of liking a product (Adawiyah et al., 2019Adawiyah, D. R., Azis, M. A., Ramadhani, A. S., & Chueamchaitrakun, P. (2019). Perbandingan profil sensori teh hijau menggunakan metode analisis deskripsi kuantitatif dan CATA (CHECK-ALL-THAT-APPLY). Jurnal Teknologi dan Industri Pangan, 30(2), 161-172. http://doi.org/10.6066/jtip.2019.30.2.161
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). A summary of the sensory attribute analysis of flakes without and with the addition of milk based on the results of the penalty analysis can be seen in Table 5.
Correspondence analysis and principal component analysis (PCA) for the need state attribute of five flakes formulas (F1–F5) (a) without and (b) with the addition of milk.
The attributes of corn aroma, corn taste, crunchy texture, and sweet aftertaste were included in the must-have attribute category for both treatments. The sweet attribute is included in the must-have category for treatment without the addition of milk, indicating that in general, the addition of milk can increase the sweet taste in consuming flakes. Hard texture and dry aftertaste attributes are must not have attributes for both treatments. As for both, it can be caused by the excessive proportion of red beans.
Other attributes that are not stated to be significant are not included in the must-have, nice to have, or must not have attribute category so that they are categorized as does not influence and does not harm (Table 5). In general, the attributes of the taste and aroma of corn had a significant effect on increasing preference, while the hard texture and dry aftertaste thought to be contributed by red beans affected decreasing preference. Even so, the proportion of red beans is an important aspect because it can lower the glycemic index and overall product protein (Afandi et al., 2021Afandi, F. A., Wijaya, C. H., Faridah, D. N., Suyatma, N. E., & Jayanegara, A. (2021). Evaluation of various starchy foods: A systematic review and meta-analysis on chemical properties affecting the glycemic index values based on in vitro and in vivo experiments. Foods, 10(2), 364. PMid:33567535. http://doi.org/10.3390/foods10020364
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). Thus, the proportion of corn to red beans becomes an important aspect of product development.
3.2.4 Need state and satisfaction relation
The need state attribute is an attribute that describes consumer needs or expectations for a product (Adawiyah et al., 2019Adawiyah, D. R., Azis, M. A., Ramadhani, A. S., & Chueamchaitrakun, P. (2019). Perbandingan profil sensori teh hijau menggunakan metode analisis deskripsi kuantitatif dan CATA (CHECK-ALL-THAT-APPLY). Jurnal Teknologi dan Industri Pangan, 30(2), 161-172. http://doi.org/10.6066/jtip.2019.30.2.161
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). The results of the correspondence analysis show that the ideal product according to consumers has the need state satiate attribute, which is owned by F4 for both treatments (Figure 3). Flakes are commonly consumed as breakfast cereals so feeling full after consuming the product (satiate) is an ideal attribute. The results of the principal component analysis show that the needs taste attribute that has the most influence on liking is health maintenance, followed by satiate (Figure 3). This can be because nowadays, consumers are demanding products that are not only filling but have positive health benefits (Purwaningsih et al., 2021Purwaningsih, I., Hardiyati, R., Zulhamdani, M., Laksani, C. S., & Rianto, Y. (2021). Current status of functional foods research and development in Indonesia: Opportunities and challenges. Jurnal Teknologi dan Industri Pangan, 32(1), 83-91. http://doi.org/10.6066/jtip.2021.32.1.83
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).
3.2.5 Recommendations for product improvement
Based on research, treatment with the addition of milk, the intensity of the attributes of yellowish-brown color, sweet aroma, salty taste, savory taste, savory aftertaste, burned taste, sandy texture, hard texture, dry aftertaste, sticky aftertaste was recommended to be reduced.
3.2.6 Selection of the best formula
Selection of flakes with the best formula is determined based on the hedonic test. Table 6 shows the hedonic test results of the five flakes formulas. F3 has a panelist presentation that has the highest somewhat like, like, or very like for the overall and satisfaction attributes of the five flakes formulas. Therefore, F3 was chosen as the best formula and for determining the IG value. F3 is also the midpoint of some formulas. The added corn aims to increase consumer preference for the product, while the addition of red beans aims to reduce the glycemic index of the product produced.
3.3 Glycemic index of selected formulas
The glycemic index of flake products was conducted according to ISO 26642:2010 protocol with the selected formula (F3). The glycemic index of the selected formula was 28 ± 11 (reference food, glucose = 100). The flakes product produced in this research is classified as a food product with a low glycemic index (<55). The resulting glycemic index is low because it uses low GI raw materials, namely red beans (26) (Afandi et al., 2021Afandi, F. A., Wijaya, C. H., Faridah, D. N., Suyatma, N. E., & Jayanegara, A. (2021). Evaluation of various starchy foods: A systematic review and meta-analysis on chemical properties affecting the glycemic index values based on in vitro and in vivo experiments. Foods, 10(2), 364. PMid:33567535. http://doi.org/10.3390/foods10020364
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) and exotic sweet corn (37) (Daniels, 2022Daniels, E. (2022). Verification of meta-analysis results of glycemic index of corn products and development of sweet corn-based instant products. Bogor: IPB University.). The response of blood sugar levels to the consumption of flakes compared to glucose can be seen in Figure 4. The responses of flakes and glucose curves form a similar pattern. However, in general, blood sugar levels after consuming flakes are much lower than after consuming glucose.
When compared to commercial corn-based breakfast cereals with a glycemic index of 87 (Kaur et al., 2016Kaur, B., Quek, Y. R., Camps, S., & Henry, C. J. (2016). The impact of a low glycaemic index (GI) diet on simultaneous measurements of blood glucose and fat oxidation: A whole body calorimetric study. Journal of Clinical & Translational Endocrinology, 4, 45-52. PMid:29159130. http://doi.org/10.1016/j.jcte.2016.04.003
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), the flakes produced in this study have a much lower glycemic index. The addition of sugar is suspected to contribute significantly to the high glycemic index of commercial products. Cahyani & Purbowati (2022)Cahyani, I. D., & Purbowati, P. (2022). The glycemic index value of corn cereal with added mung beans and red beans. Sport and Nutrition Journal, 4(1), 13-19. http://doi.org/10.15294/spnj.v4i1.50521
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produced flakes with a similar glycemic index using mung beans and red beans, confirming that adding red beans significantly lowers the product's glycemic index.
Red beans have a low glycemic index, even the lowest within the legume subgroup (Afandi et al., 2021Afandi, F. A., Wijaya, C. H., Faridah, D. N., Suyatma, N. E., & Jayanegara, A. (2021). Evaluation of various starchy foods: A systematic review and meta-analysis on chemical properties affecting the glycemic index values based on in vitro and in vivo experiments. Foods, 10(2), 364. PMid:33567535. http://doi.org/10.3390/foods10020364
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). Cooked red beans have the highest levels of resistant starch and fiber compared to other legumes, at 21.27% and 32.63%, respectively (Reddy et al., 2013Reddy, C. K., Suriya, M., & Haripriya, S. (2013). Physico-chemical and functional properties of Resistant starch prepared from red kidney beans (Phaseolus vulgaris.L) starch by enzymatic method. Carbohydrate Polymers, 95(1), 220-226. http://doi.org/10.1016/j.carbpol.2013.02.060
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). This is due to interactions between carbohydrates, proteins, and phenolic compounds, forming complex compounds with disulfide cross-linking bonds that are difficult or impossible for the body to digest (López-Barón et al., 2017López-Barón, N., Gu, Y., Vasanthan, T., & Hoover, R. (2017). Plant proteins mitigate in vitro wheat starch digestibility. Food Hydrocolloids, 69, 19-27. http://doi.org/10.1016/j.foodhyd.2017.01.015
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). The presence of resistant starch and dietary fiber reduces starch digestibility, leading to a slower increase in blood glucose levels. In other words, resistant starch and dietary fiber lower the glycemic index of the material.
Therefore, the corn-red bean flakes formulated as F3 in this study have the potential to be a breakfast cereal product for people with diabetes, serving as an alternative to commercial products with a high glycemic index.
4 Conclusion
The resulting flakes maintain crunchiness in milk for over 2 minutes, primarily influenced by the red bean portion. Correspondence analysis reveals that ideal flakes exhibit attributes such as a brownish-yellow color, corn taste and aroma, sweet taste and aftertaste, and roasted aroma, taste, and texture. PCA indicates that the most influential attributes on preference, both with and without milk, are sweet taste, sweet aroma, sweet aftertaste, corn aroma, and corn taste. Organoleptic test results suggest that the intensity of yellowish-brown color, sweet aroma, salty taste, savory taste, savory aftertaste, burned taste, sandy texture, hard texture, dry aftertaste, and sticky aftertaste should be reduced when serving flakes with milk. Furthermore, F3 emerges as the optimal formula, receiving the highest ratings (somewhat like it, like it, or very like it) for overall satisfaction among the five tested formulas. Consequently, F3 was selected to determine the product's glycemic index value. The corn-red bean flakes formulated as F3 exhibited a low glycemic index of 28 (< 55), indicating its potential as a breakfast cereal product for people with diabetes.
Acknowledgments
The authors would like to acknowledge the Department of Food Science and Technology, IPB University for providing the facilities for this work. This work was also supported by the Ministry of Research and Technology/National Research and Innovation Agency (Indonesia) as a part of the Leading Basic Research Program for Higher Education Institutions.
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Cite as:
Daniels, E., Faridah, D. N., & Wulandari, N. (2024). Development of sweet corn and red beans-based low-glycemic index flakes. Brazilian Journal of Food Technology, 27, e2023148. https://doi.org/10.1590/1981-6723.014823 -
Funding:
Ministry of Research; Research and Innovation Agency (Indonesia) (001/E5/PG.02.00.PL/2023); Department of Food Science and Technology, IPB University.
References
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» http://doi.org/10.6066/jtip.2019.30.2.161 - Afandi, F. A., Wijaya, C. H., Faridah, D. N., Suyatma, N. E., & Jayanegara, A. (2021). Evaluation of various starchy foods: A systematic review and meta-analysis on chemical properties affecting the glycemic index values based on in vitro and in vivo experiments. Foods, 10(2), 364. PMid:33567535. http://doi.org/10.3390/foods10020364
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» http://doi.org/10.15294/spnj.v4i1.50521 - Daniels, E. (2022). Verification of meta-analysis results of glycemic index of corn products and development of sweet corn-based instant products Bogor: IPB University.
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Associate Editor:
Publication Dates
-
Publication in this collection
07 Oct 2024 -
Date of issue
2024
History
-
Received
10 Dec 2023 -
Accepted
05 July 2024