Browsing by Author "Safiei, Nor Zanariah"

Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    Progressive freeze concentrator prototype for preservation of phenolic content in grape juice
    (Universiti Teknologi Malaysia, 2016) Safiei, Nor Zanariah
    The preservation of total phenolic content (TPC) and nutritional, sensorial and antioxidant properties during concentration process has become a major challenge in the grape juice industry. Concentration of grape juice is important in order to reduce the cost of storage, handling and shipping. Progressive freeze concentration (PFC), a concentration process where ice crystals are formed as a layer on the cooled surface was investigated focusing in terms of assessment towards benefiting the grape juice industry. A new prototype system for PFC named Progressive Freeze Concentrator Sequence System (PFCSS) was designed with a coil crystallizer as the main component by building a sequence of four major steps which are feeding, crystallization, collection of concentrate and thawed ice processes. The crystallizer was chosen based on its productivity and the economic benefits that it could offer. Subsequent investigation of the system performance and optimization were performed in order to verify the system?s capability by using grape juice. It was found that the TPC increment obtained was high at intermediate coolant temperature, high circulation flowrate, intermediate time and low initial solution concentration. Intermediate coolant temperature of -8 °C resulted in TPC increment of 22.47% and effective partition constant (K) of 0.41. Meanwhile, circulation flowrate of 3000 mL/min gave a high TPC increment and a low K value with 29.55% and 0.33, respectively. For operation time, at 20 minutes, TPC increment and K obtained were 22.47% and 0.41, respectively. Lastly, the initial solution concentration 8 °Brix gave the highest TPC increment of 37.48% and lowest K of 0.26. A comparison was made between the manual set-up and PFCSS, and the results obtained were 56%, 32% and 27% improvement for coolant temperature, circulation flowrate and operation time, respectively. An optimization was also performed using response surface methodology and artificial neural network and genetic algorithm for single and multi-response, respectively. A process optimization was used to produce the optimum conditions to yield the best TPC increment and K, which have been supported with good R-squared and analysis of variance. The highest TPC increment and lowest K were predicted at -9 °C, 2882 mL/min, 17 minutes and 8 °Brix with 40 percent and 0.46 for TPC increment and K, respectively. Finally, mathematical models for ice crystal mass and TPC in concentrate predictions have been successfully developed