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All Journal Jurnal Teknologi Dan Industri Pangan agriTECH JITIPARI (Jurnal Ilmiah Teknologi dan Industri Pangan UNISRI)
Henny Krissetiana Hendrasty
Fakultas Teknologi Pertanian, Institut Pertanian (INTAN) Yogyakarta Jln. Magelang, Km 5,6 Yogyakarta
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Industrial & Manufacturing Engineering

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Journal : agriTECH

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Optimasi Kondisi Pengeringan Mie Singkong dengan Response Surface Methodology Terhadap Karakteristik Produknya Henny Krissetiana Hendrasty; Sundari Setyaningsih; Raden Sugiarto
agriTECH Vol 39, No 2 (2019)
Publisher : Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (457.785 KB) | DOI: 10.22146/agritech.43541

Abstract

Wet cassava starch noodles have been developed in Srihardono Village, Pundong-Bantul District. The disadvantage of this noodle is the short shelf life. The objective of this study was to determine the optimum drying conditions to obtain the best quality of dried cassava noodles. The factors, such as temperature and drying time, and noodle layer were evaluated. Dried cassava noodles contain a combination of traditionally processed cassava starch and manufactured cassava starch. The ratio of traditional starch to manufactured starch was 3:2 (w/w). Drying was conducted using a cabinet drier at various temperatures (70, 80 and 90 °C) for 2 h, 2.5 h, 3 h, 3.5 h and 4 h. Noodle layers were 1, 2, 3 and 4. The observed quality parameters were elongation, water content, cooking loss and water absorption. The obtained data were analyzed using a Response Surface Methodology. The range of optimum drying condition was between 76 and 84 °C and drying time between 3.2 and 3.5 h. Noodles were arranged in 2 layers. Dried cassava noodles had an elongation value of 60 to 70%, water content of 8 to 9%, cooking loss of 10 to 12% and water absorption of 140 to 150%. 
Co-Authors Novia Tabahana Rendra Suyanto Suhardi , Sundari Setyaningsih Suyanto, Rendra Umar Santoso Yulius Kiswanto