Modified atmosphere techniques and preservation technologies, coupling with coldchain have been approved themselves as key tools to prevent spoilage and prolong shelflife for the fruit storage and transportation. Taking table grape as example, modified atmosphere techniques create gaseous microenvironments which usually consist of reduced O2, elevated CO2 concentrations compared to air and fresh keeping agent of sulfur dioxide which commonly used to release SO2 and strongly retard the growth of these pathogenic fungis. Thus, there is an increasing concern about gas monitoring to improve the transparency and traceability during coldchain. However, the existed industrial gas sensor can not meet the demand of coldchain logistics in scale and precision. Then, the paper aimed to extract the static and dynamic response characteristics of gas sensors for table grape cold-chain logistics, which developed the method of characteristic parameter extraction based on time domain, and the carbon dioxide, oxygen and sulfur dioxide were developed as basic parameters. The method of linear regression was used to optimize characteristics of gas sensors, so the best feature parameters were got for gas sensing signal, which contain the response of gas sensor in the air, steady response of gas sensor, the speed of response and response recovery, time of response and response recovery, and response integrated signal respectively. The best feature parameters can be used to analyze the characteristics of gas sensing signal which has a cumulative effect on the quality in coldchain. It is possible to improve the application and monitoring precision, monitoring sensitivity and monitoring stability of gas sensor in the coldchain logistics further more.