Predicting the effect of ozone, chitosan and temperature on acidity content of Mazafati date fruit during storage by using artificial neural network

Mazafati date is one of the most famous and delicious date varieties which has been classified as soft dates. It has a dark red and Soft tissue. This date is third economic variety of our country after Saamaran and Shahani. Regarding to the importance of acidity level the changes of acidity level during storage was predicted by neural network . In doing so , ozone gas , the edible coating of chitosan and different temperatures (5,15,25 oC) were used as strategies to increase durability of Mazafati date during 60 days,
and dates acidity was measured every 3 days . Ozone , chitosan coating and different temperatures were used as in put of network. The results showed that newff artificial network with topology of 1-17-4 , the correlation coefficient of 0.99 and error square mean of 0.0013 by applying hyperbolic sigmoid tangent function and learning pattern of levenberg marquardt is considered as the best neural model in predicting the changes of acidity level. Generally , it can be said that artificial neural network is a reliable method to model and predict the changes of date acidity and similar products .