
Drying Kinetics and Study of Physical Characteristic Using Image Analysis of Dried Salted Striped Catfish (Pangasius hypophthalmus)
Author(s) -
R H Wafa,
Tri Winarni Agustini,
Akhmad Suhaeli Fahmi
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/750/1/012045
Subject(s) - mathematics , catfish , food science , digital image analysis , thermal diffusivity , hue , chemistry , artificial intelligence , fish <actinopterygii> , computer science , biology , thermodynamics , physics , computer vision , fishery
Dried salted striped catfish ( Pangasius hypophthalmus ) is one of dried fish produced by salt fermentation and drying process. Drying temperature, time, and methods cause specific characteristic of the product. Human visualization is limited and the conventional method to analyze the characteristic of the product is time consuming so that accurate method is needed with digital image analysis or image processing. The study aimed to determine mathematic model which show the characteristics of dried salted striped catfish cause by different drying process and to observe the visual transformations which is stated in image parameter of RGB, L*a*b, hue, saturation, intensity, area, and texture (entropy, energy, contrast, and homogeneity). This research did by using the temperature settings of 40, 50, and 60°C for 12 hours. Moisture content was carried out every two hours. The images were taken per hour for accurate results. The mathematical models used are Lewis, Henderson and Pabis, and Page. The mathematical models were obtained from the regression analysis. The research showed that the drying constant (k) was directly proportional to temperature increase. Model Page is more suitable than the other mathematical models because it has the highest R 2 value and the lowest value of SEE ( Standard Error of Estimate ). The result of diffusivity effective for each temperature with the value of 8.776 × 10 −3 ; 31.922 × 10 −3 ; 48.389 × 10 −3 , with the activation energy of 74.34 kJ/g mol. The digital image has a strong correlation with moisture content reduction with R 2 > 0.8. The results of entropy and energy on textures were continued with Multiple Linear Regression (MLR) analysis produce equation of Moisture Content (%) = 188.721 + (Energy x 40.249) + (Entropy × (-25.801)).