General formula of cooling curve for horticultural products on forced air pre‐cooling. (7th March 2022)

• Record Type: Journal Article
• Authors: Wang, Da; Jia, Binguang; Lai, Yanhua; Hu, Shifa
• Is Part Of: Journal of food process engineering. Volume 45:Number 5(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-03-07
• Subjects: Food industry and trade -- Periodicals; Food -- Analysis -- Periodicals; 664.005
• DOI: 10.1111/jfpe.14020
• Languages: English
• ISSNs: 0145-8876

Abstract

Abstract: The air velocity played a key role in controlling the cooling process of forced air pre‐cooling for horticultural products. However, the present general formula of cooling curve for horticultural products on forced air pre‐cooling did not reflect the influence of the air velocity on cooling rate for horticultural products on forced air pre‐cooling. This paper aimed to find the relationships among the air velocity, lag factor and cooling coefficient so as to obtain the general formula of the cooling curve for horticultural products on forced air pre‐cooling by combining the simulation and the experiment. The results showed that the lag factor had a linear relationship with the air velocity, and the cooling coefficient had a quadratic function or power function relationship with the air velocity. These two kinds of general formulas were verified by experimental data of apples, cherries and blueberries, and were also in agreement with the literature values of apples, grapes and Dutch cucumbers. Based on the accuracy and the predictability of the general formulas, the general formula has higher accuracy and predictability when the cooling coefficient had a power function relationship with the air velocity. Practical Applications: This paper attempted to find a general formula to describe the cooling rates of horticultural products for the different air velocities and temperatures. The general formula was only incident the air velocity and the air temperature while the other factors were considered as the unknown variations which was obtained by the functions fitting. This could contribute to reduce the cost and time of experiments and simulations during the analysis of forced air pre‐cooling and to help the operator find the optimal air velocity effectively. To find the suitable general formula, firstly we established the simulated model to find the general formulas by using least square method. Then, the general formulas had been validated by experimental data and literature results. Finally, the predictability of these general formulas had been tested.