Prediction And Control Of Nutrient Loss In Asparagus (Asparagus Officinalis L.) During Blanching

With many people's attention to healthy green food, asparagus stand out from conventional vegetables due to its superior nutritional values and officinal values. However, asparagus is an easily perishable vegetable characterized by a limited post-harvest life, mainly because of its high respiratory activity which continues after harvesting. This is a challenge faced by farmers, consumers and food researchers. In order to decrease postharvest decay of asparaguses during storage and increase economic income of farmers, this vegetable was usually produced to other products, such as asparagus can, beverage, asparagus tea, asparagus powder, etc. Blanching is one of the many processes that take place during the preparation of untreated vegetables for preservation processes such as canning and freezing. Moreover, it is often processed to reduce post-harvest losses and prolong the shelf-life of fruits and vegetables. Because blanching can inactivate shelf-life limiting enzymes, kill worm eggs and germs and exhaust gas from the plant tissue, which reduce postharvest decay and insect pest and disease. Blanching, however, has some adverse effects, such as pigment modifications, tissues softening and nutrient losses. Nowadays, many food researchers developed mathematical models to predict and simulate the change of food quality during blanching in an attempt to guide practical processing, but these models can not control the adverse effect of thermal treatments of fruits and vegetables. Thus, many food researchers used pretreatment methods, such as high pressure treatment, preheating and calcium treatment, to reduce the adverse effect of blanching of fruits and vegetables. This study was proposed according to present research situation and shortage, and its objectives were (1) to evaluate the percentage loss of ascorbic acid, total phenols, flavonoid and antioxidant activity of different segments of green asparagus during blanching in water through mathematical modelling based on artificial neuron network, (2) to develop the kinetics of ascorbic acid loss prediction models based on artificial neural networks, and (3) to study the effect of microwave pre-treatment in alleviating ascorbic acid loss and accelerating peroxidase inactivation during water blanching of asparagus.After studying, our results can be listed as follows:(1) In this study, the one-hidden-layer artificial neural networks are used, and the number of neurons in the hidden layer was chosen by trial and error. The input layer consisted of two neurons which corresponded to blanching time and temperature. The output layer had one neuron representing the percentage loss of nutrient (eg, ascorbic acid, total phenols, flavonoid or antioxidant activity). Our results showed that the optimal number of nodes in the hidden layer was 5,5,7 and 5 in the bud segment of asparagus,5,7,5 and 7 in the upper segment,8,4,6 and 7 in the middle segment and 5,5,5 and 7 in the butt segment, for predicting the percentage loss of ascorbic acid, total phenols, flavonoid and antioxidant activity, respectively. Optimized ANN models were then tested against an independent dataset. Our results showed the correlation coefficients between experimental and artificial neural networks predicted values ranged from 0.8166 to 0.9868.(2) This result suggests that bud segment of asparagus has higher ascorbic acid content but more liable to lose ascorbic acid than other segments.(3) Our results showed that a one-hidden-layer artificial neural network has been built able to predict the kinetic parameters (k, t1/2 and D-value) of ascorbic acid loss, and the optimal number of nodes in the hidden layer was 24,26,26 and 18 for bud, upper, middle and butt segments of asparagus, respectively. In addition, the correlation coefficients between experimental k, t1/2 or D-value and artificial neural networks predicted values were greater than 0.99 in all cases.(4) Our results showed that ascorbic acid degradation and peroxidase inactivation in all segments of asparagus for both treatments are well described by first-order models. The degradation rate of ascorbic acid and peroxidase is gradually increased from butt to bud segment of asparagus. In addition, microwaves pre-treatment could increase the activation energy of ascorbic acid degradation and decrease the activation energy of peroxidase inactivation during water blanching of asparagus. Therefore, it is recommended that the different segments of asparagus should be subjected to different blanching times, and microwaves pre-treatment could be applied for alleviating ascorbic acid degradation and accelerating peroxidase inactivation during blanching, cooking and pasteurization in water.In conclusion, we successfully develop a mathematical model based on artificial neural networks to predict the change of nutritional values in asparagus during thermal process. The results expand the usage of artificial neural networks in food research field, and success of this research will provide the food industries with a modelling and simulation for nutrient losses control in vegetables during thermal treatments. In addition, microwaves may be an effective pre-treatment process for use prior to water blanching to reduce the degradation of ascorbic acid and to accelerate the inactivation of peroxidase and thus maintain produce quality, and provide consumers healthier and more nutritive asparagus products.