Quality Detection of Litchi Stored in Different Environments Using an Electronic Nose

Abstract

The purpose of this paper was to explore the utility of an electronic nose to detect the quality of litchi fruit stored in different environments. In this study, a PEN3 electronic nose was adopted to test the storage time and hardness of litchi that were stored in three different types of environment (room temperature, refrigerator and controlled-atmosphere). After acquiring data about the hardness of the sample and from the electronic nose, linear discriminant analysis (LDA), canonical correlation analysis (CCA), BP neural network (BPNN) and BP neural network-partial least squares regression (BPNN-PLSR), were employed for data processing. The experimental results showed that the hardness of litchi fruits stored in all three environments decreased during storage. The litchi stored at room temperature had the fastest rate of decrease in hardness, followed by those stored in a refrigerator environment and under a controlled-atmosphere. LDA has a poor ability to classify the storage time of the three environments in which litchi was stored. BPNN can effectively recognize the storage time of litchi stored in a refrigerator and a controlled-atmosphere environment. However, the BPNN classification of the effect of room temperature storage on litchi was poor. CCA results show a significant correlation between electronic nose data and hardness data under the room temperature, and the correlation is more obvious for those under the refrigerator environment and controlled-atmosphere environment. The BPNN-PLSR can effectively predict the hardness of litchi under refrigerator storage conditions and a controlled-atmosphere environment. However, the BPNN-PLSR prediction of the effect of room temperature storage on litchi and global environment storage on litchi were poor. Thus, this experiment proved that an electronic nose can detect the quality of litchi under refrigeratored storage and a controlled-atmosphere environment. These results provide a useful reference for future studies on nondestructive and intelligent monitoring of fruit quality.

Classification for Penicillium expansum Spoilage and Defect in Apples by Electronic Nose Combined with Chemometrics

“…The electronic nose detection has the advantages of being fast, simple and non-destructive [8]. Ying [9] and Xu [10] respectively used e-nose to evaluate the freshness of litchi and measured the storage time of litchi under three different conditions. Dai [11] combined electronic nose with headspace solid phase microextraction (HS-SPME)-GC-MS to analyze the volatile components in the fermentation process of Tremella aurantialba.…”

Effect of high‐pressure carbon dioxide on the quality of cold‐ and hot‐break tomato pulps

“…Electronic nose, simulated sense of smell in mammals, has been widely used in research field of food flavor, such as mushroom (Yang et al, ), beef fillets (Papadopoulou, Panagou, Mohareb, & Nychas, ), and edible oils (Xu, Yu, et al, ) and has become an important method for its feasibility and sensitivity. Responses of ten sensors of electronic nose to fresh tomato pulp are presented in Figure .…”

Survey on Applications of Electronic Nose

“…They found that LDA provides better performance with an accuracy of 98.21% and discriminate the different stages of incubation and invasion. Xu et al (2016) used PEN3 E-nose predicts to litch quality. Litch quality was detected in different environments (normal temperature, refrigerator, controlled condition).…”