Mass modelling by dimension attributes for Mango (Mangifera indica cv. Zebdia) relevant to post-harvest and food plants engineering
Keywords:bioprocess technology, fruit sorting, image processing, physical attributes
Mass identification of mango fruits from their dimension attributes remains challenging. This is because of the unregulated shapes of these fruits. Therefore, this research aims at creating mathematical models that can demonstrate the relationship between the fruit’s mass and dimension attributes. Hence, these models can be used in post-harvest engineering systems. The researchers used 100 mango fruits (Mangifera indica cv. Zebdia) to determine the mathematical relationship between the fruits’ weight and dimension attributes. The researcher measured and photographed the dimensions of these fruits and processed the image captured for each fruit using a computer program to find the fruit’s dimensions. The results obtained led to the development of six mathematical models to predict a fruit’s mass from the dimensions. Given these results, the mathematical model based on the fruit’s length shows the best performance in the mass prediction (Pearson’s r=0.87). One can infer that a fruit’s mass could be obtained from its dimensions. This conclusion is not generalizable to other mango cultivars. Thus, the researcher recommends conducting further studies of other cultivars to develop a unified mathematical model. This will be helpful in developing modern post-harvest engineering systems.