Abstract:
Survival period of the fruits after harvest is relatively
short. The main objective of this research is to measure the freshness
of fruits by observing their CO2 release, water vapor release, and
O2 absorption after harvesting for the papaya and watermelon. They
were categorized into the three groups (500g-1kg, 1kg-1.5kg, 1.5kg-
2kg) and tested in 4 selected days including the harvested day, three
days after harvest, a week after, and two weeks after to observe
the changes in these three factors (CO2, O2, and humidity). A CO2
sensor, an O2 sensor, and a humidity sensor was set up to detect the
changes. The collected data was used to train the machine learning
model (Keras Sequential Model). After entering the type of the fruit,
weight, the difference of oxygen, and water vapor concentration
after 45 minutes, as inputs for the model, the model will predict
the freshness of the fruit as a percentage. The Accuracy of the
developed model was considered to be 0.989. The results of the
analysis implied that the rate of O2 absorption gradually increases
after harvesting and the water vapor release gradually decreases.
It is suggested to use higher sensitivity sensors to obtain accurate results.
