Skripsi
APLIKASI NANOPARTIKEL BESI (FeNP) DARI EKSTRAK TIGA JENIS DAUN LALAPAN PADA PEMPEK KULIT
This study aimed to determine the effect of FeNP application as iron fortification on the physicochemical characteristics of pempek kulit. This study used a factorial completely randomized design with two treatment factors: the type of FeNP (pohpohan leaves, beluntas leaves, and pegagan leaves) and the amount of FeNP added (50 mg and 100 mg). Each treatment was repeated three times. The parameters observed include physical characteristics (color and texture), chemical characteristics (water content, ash content, protein content and iron content, and sensory (color, taste, aroma and texture). The results showed that the amount of added iron nanoparticles (FeNP) significantly affected the physical characteristics of color (lightness) and texture (hardness), chemical characteristics (ash content and iron content). The water content value of pempek kulit in all treatments has met the quality requirements according to SNI 7661:2019 for pempek in general, which is a maximum of 65%. The physical characteristics of pempek kulit with the addition of FeNP showed a lightness value of 49.95 - 54.30, redness 4.55 - 6.18, yellowness 10.34 - 13.51, hardness 2.42 - 3.16 N, spiringness 3.260 - 3.509, cohesiveness 0.7793 - 0.8627 and adhesiveness 1.7003 - 1.8667 mJ. Chemical characteristics of water content 27.90 – 31.16%, ash content 1.97 – 2.63%, protein content 0.26 – 0.46%, and iron content 34.57 – 38.16 ppm. Sensory characteristics of color 3.40 – 3.60%, taste 3.00 – 3.97%, aroma 3.43 – 3.70%, and texture 2.93 – 3.95%. The results of sensory tests showed that the taste, aroma and texture of pempek kulit with an amount of 50 mg and 100 mg did not reduce the level of panelist acceptance of the attributes of color, aroma, taste and texture of pempek kulit. This shows that FeNP fortification is still organoleptically acceptable without reducing the sensory quality of pempek kulit. Keywords: pempek kulit, FeNP, pohpohan, beluntas, pegagan
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