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Devin pratama
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foodscientia@ecampus.ut.ac.id
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Jl. Pd. Cabe Raya, Pd. Cabe Udik, Kec. Pamulang, Kota Tangerang Selatan, Banten 15418
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INDONESIA
Food Scientia: Journal of Food Science and Technology
Published by Universitas Terbuka
ISSN : -     EISSN : 28071549     DOI : https://doi.org/10.33830/fsj
Core Subject : Science,
Biochemistry, Genetics & Molecular Biology Chemistry Decision Sciences, Operations Research & Management Energy
Food Scientia : Journal of Food Science and Technology is a publication published by the Food Technology Study Program of Universitas Terbuka. This journal is published biannually in January-June and July-December.
Arjuna Subject : Ilmu Pertanian dan Biologi (Semua) - Ilmu Makanan
Articles 42 Documents
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Karakteristik Mutu Produk Susu Kedelai Tanpa Merek yang Beredar di Kota Mataram Komalasari, Husnita; Manurung, Nancy Eka Putri; Yoga, Wahyu Krisna
Food Scientia : Journal of Food Science and Technology Vol 4 No 1 (2024): January - June
Publisher : LPPM Universitas Terbuka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33830/fsj.v4i1.6492.2024

Abstract

Soy milk is a food product made from processed soybeans which has a high source of nutrition and as a source of vegetable protein. The aim of this study is to determine the quality characteristics of unbranded soy milk products marketed in Mataram City and the influence of storage methods and time. The method used was a descriptive and experimental method with a completely randomized design (3 treatments and 3 replications). Data were analyzed using ANOVA a=5% with Tukey and Dunnet further tests. The test results showed that the quality characteristics of unbranded soy milk marketed in Mataram city have several parameters that are and are’nt in accordance with SNI. Parameters that comply with SNI are pH (6.9), normal color and aroma. Meanwhile, what does not comply with SNI is the number of microbes. In addition, several parameters do not yet have standards such as viscosity (1.18 cP), color L* (74.45), a* (-6.14), b* (7.46), °hue (-50.56 ), TPT (15.5), appearance (homogeneous) and texture (liquid). Storage time and method have a significant differences on the physicochemical properties of the product except for the color parameter b*. It is known that storage at room temperature for 48 hours (SK2) results in soy milk not comply with SNI standards, and cold storage (SK2D) is able to maintain the quality of soy milk better than at room temperature. The best quality and treatment characteristics are SK0, but microbial contamination still exceeds the SNI threshold.
Hubungan antara Panjang Rantai Amilopektin dan Indeks Glikemik Pangan Karbohidrat: Review Afandi, Frendy
Food Scientia : Journal of Food Science and Technology Vol 3 No 2 (2023): Juli - Desember
Publisher : LPPM Universitas Terbuka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33830/fsj.v3i2.6503.2023

Abstract

The relationship between starch characteristics and the glycemic index (GI) of carbohydrate foods is interesting to study. One of the advances in analytical techniques in characterizing starch is measuring the degree of polymerization of amylopectin chains. Amylopectin is the main component of carbohydrate starch granules. There have been many publications regarding long chain fractions of amylopectin. The aim of this research is to analyze the relationship between amylopectin chain length and the glycemic index of carbohydrate foods. The method used was to tabulate various studies related to data on amylopectin chain length and the glycemic index of carbohydrate foods. Then a regression analysis was carried out between the degree of polymerization of the amylopectin chain and the Pearson correlation between the degree of polymerization and the glycemic index value. The research results showed that there was a strong correlation between the amylopectin chain length with degree of polymerization (DP) 6-12, 13-24, and 25-36 with the glycemic index value of carbohydrate foods. The degree of polymerization of the amylopectin chain is the number of glucose units that make up the chain. The resulting regression equation is y=0.3123x-0.6256 with a value of r2=0.991. The chain length of amylopectin influences starch properties, including the glycemic index. Starches with shorter amylopectin chains have a lower glycemic index, while starches with longer amylopectin chains have a higher glycemic index. The results of this research provide a new perspective for the field of food chemistry that the characteristics of amylopectin influence the glycemic index value of carbohydrate foods.

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