In this paper, a delay-minimal joint framing and scheduling policy is proposed for cognitive sensor networks, where a secondary sensor node collects measurement samples, combines them together into packets and transmits the packets to a central data fusion center after proper scheduling, when a shared channel is released by primary nodes. The main objective of this study is to minimize the end-to-end delivery time for secondary sensor nodes based on the current input traffic rate, channel availability process and channel bit error probability. The proposed method outperforms conventional constant-length framing policies for any choice of packet length by minimizing the delay and preventing potential queue instability under dynamic channel conditions. This method can be utilized by secondary nodes in a wide variety of wireless sensing applications in order to collect time-sensitive data with minimal delays.