Optimization of vacuum cooling treatment of postharvest broccoli using response surface methodology combined with genetic algorithm technique

In this paper, the effects of vacuum cooling factors on the weight loss of postharvest broccoli were initially investigated. In sequence, the vacuum cooling treatment conditions were optimized using the response surface methodology (RSM) combined with the genetic algorithm (GA) technique. Fresh broccoli samples were harvested from a Chinese farm, and the green heads of selected samples were cut into smaller pieces, with diameters approximately 3-4 cm, and sequentially equilibrated to room temperature. Pressure (200-600 Pa), broccoli weight (200-500 g), water volume (2-6%, v/v) and time (20-40 min) were used as factors, and weight loss and end temperature were recorded as responses. The GA was employed to find the optimal condition for processing broccoli, and its initial solution was obtained from the RSM. The results demonstrate a good performance of the GA for the optimization of the broccoli cooling process. The best conditions of vacuum cooling process were as follows: a weight between 273.5 g and 278.0 g, a water volume of 3.0% v/v, a processing time of 40 min, a pressure of 200 Pa, and a weight loss and end temperature of 0.34 ± 0.01% and 2.0 ± 0.0 °C, respectively, leading to a percentage of profit of 99.66 ± 0.01%.