OPTIMASI PROSES PEMBUATAN TEPUNG LABU KUNING MENGGUNAKAN RESPONSE SURFACE METHODOLOGY UNTUK MENINGKATKAN AKTIVITAS ANTIOKSIDANNYA

• Published in: Jurnal Teknologi dan Industri Pangan (Edisi) Vol. 29; no. 1; pp. 29 - 38
• Main Authors: Wahyono, Agung, Kurniawati, Elly, Kasutjianingati, Kasutjianingati, Park, Kang-Hyun, Kang, Woo-Won
• Format: Journal Article
• Language: English
• Published: Bogor Agricultural University; Indonesian Food Technologist Association (IAFT) 01.06.2018
• Subjects: antioxidant; flour; pumpkin; rsm
• ISSN: 1979-7788; 2087-751X
• DOI: 10.6066/jtip.2018.29.1.29

Yellow pumpkin (Cucurbita moscata) is a popular plant in Indonesia, but its utilization is limited. It has been reported that the antioxidant activity of the yellow pumpkin increased by increasing the drying tempe-rature and immersing the pumpkin in bisulfite solution during processing. The aim of this study was to opti-mize the processing conditions for the manufacturing of pumpkin flour using Response Surface Methodo-logy (RSM) to enhance its antioxidant activities. The optimization process was done using a Box-Behnken construction. The factorial treatments consisted of immersion in metabisulfite solution, drying temperature, and drying time. The results showed that the scavenging activity as measured by DPPH and ABTS corres-ponded well to the independent variables based on the multiple regression analysis particularly the multi-variate quadratic regression (MQR). Based on the MQR, the determination coefficients (R2) of DPPH and ABTS were 0.97 and 0.96, respectively. Based on that model, the optimum conditions of pumpkin flour manufacturing were immersion in metabisulfite solution for 23.05 min, drying temperature of 85°C, and drying time of 11.40 h. This optimum condition was predicted to yield pumpkin flour having DPPH and ABTS scavenging activities of 90.12% and 94.38%, respectively. Based on the validation data, the optimum condition resulted in flour with antioxidant activities of 80.23 (DPPH) and 86.67% (ABTS). The quadratic models developed were powerful in predicting the actual values of the antioxidant activity by DPPH and ABTS. The accuracy of the models in predicting the antioxidant activity by DPPH and ABTS were 89.02 and 91.83%, respectively.