Monitoring of Fluorescence Characteristic in Tomato Part during Over-ripening Stage Annisa NURULHUDA, Dimas Firmanda AL RIZA , MUHARFIZA, Makoto KURAMOTO , Tetsuhito SUZUKI , Naoshi KONDO
Kyoto University
Abstract
After harvesting, the evaluation of tomato characteristics is essential to decide a correct postharvest handling process, maturity stages, and shelf-life prediction. Recently, fluorescence imaging has been proven to extend the monitoring systems sensitivity after red stages, which is difficult to solve with a conventional imaging system (Konagaya et al. 2019). This sensitivity enhancement of the monitoring system was able to be achieved due to the auto-fluorescence changes of the tomato surface during storage after the red stages (Konagaya et al. 2020). Nevertheless, the auto-fluorescence change of other tomato part has not been discussed well in the previous report. On the other hand, comprehensive monitoring of fluorescence compound changes of tomato tissues from green to red stage has also been reported by Lai et al. (2017). However, no report has been provided on the fluorescence change of various tomato tissues after red stages, which is important since this stage is the critical stage for storage related to quality and shelf life. In this research, tomato tissues have been classified into three parts i.e. skin, flesh, and inner locus liquid. Those three-part have been extracted, and the fluorescence characteristic has been monitored from red-stages to over-ripening. The fluorescence image changes are confirmed during the storages and correlated with the weight loss as a freshness index. The results show that the fluorescence characteristic of tomato skin and flesh is different. The highest fluorescence emission peak for Excitation of 370 nm is 520 nm for the skin and 490 nm for the flesh. Both fluorescence intensity of skin and flesh changed during storage. Although both changes could affect the fluorescence images, confirming the results of Konagaya et al. 2020, the changes of the skin fluorescence are strong enough to be observed with an imaging method. Classification of fresh and spoilage tomato samples using weight loss and images were also conducted using a PLS-DA model with 92% accuracy. These results demonstrate the potential of fluorescence imaging to monitor tomato freshness during storage.
