Quality kinetic model and shelf life prediction of green vegetable (Brassica rapa var. chinensis)

Abstract: With widely utilization of kinetic theory in the field of shelf life prediction, and the necessity of shelf life prediction of perishable leafy vegetables, two methods of shelf life prediction of green vegetable (Brassica campestris L. ssp.chinensis) were conducted through a series of experiments and validation. Reduced ascorbic acid content, chlorophyll, color parameters such as L*(lightness), b*(yellowness), ΔE (color difference), and sensory evaluation of green vegetable stored at 5℃, 10℃, 15℃ and 20℃ were determined in this experiment, then a kinetic analysis of those quality indexes and sensory score were studied. The results showed that the lower temperature at which a green vegetable was stored, the slower quality parameters change in the temperature range was concerned, in other words, the kinetics rate constant of quality change was smaller in lower temperature. Kinetic analyses were proposed that zero-order law was more appropriate than first-order reaction kinetics to describe quality determined change, and zero-order law could describe quality degradation very well except b*(yellowness) (R2>0.84). Nonlinear fitting of reaction rate k and temperature T based on Arrhenius law was also studied, from which active energy Ea of Reduced ascorbic acid content, chlorophyll, L* and ΔE were 68.130 kJ/mol, 57.024 kJ/mol, 46.685 kJ/mol, and 42.581 kJ/mol, respectively. As a consequence, the prediction function of green vegetable shelf life based on time, temperature, and quality parameters was obtained (R2>0.87), from which shelf life could be calculated with different thresholds of quality indexes. A sensory score was also determined by zero-order kinetics and Arrhenius law in this paper, which was used for prediction of sensory shelf life. Sensory shelf life is 11.03, 7.11, 4.65, and 3.09 d with a score of 3.5 as the cut point for a green vegetable stored at 5, 10, 15, and 20℃, respectively, while predicted shelf life is 11.06, 7.15, 4.69, and 3.13d, by assuming final chlorophyll decreased by 36%, which was close to sensory shelf life by a small relative prediction error of 1.5%. However, because of lacking unitive standards for final shelf life in the fruit and vegetable industry, there were almost no references defining any accuracy thresholds of qualities to predict certain shelf life as close as possible with sensory shelf life. Based on above situation, shelf life resulted from Arrhenius law and linear-fitting function of dynamic final quality relied on sensory cutting point was tried in this research, the function curve of which corresponded better to the predicted curve of sensory life. The validated experiment proved that former models were a good approach to evaluate the shelf life of a green vegetable corresponding to relatively remained quality value; on the other hand, latter models could predict sensory shelf life via a quality index, of which the relative prediction error was less than 0.3 day. The overall shelf life prediction parameters can be obtained based on the combination of two models. This conclusion is expected to offer a theoretical basis for shelf life prediction of a green vegetable during transportation in circulation.