In this work, we study the freshness and significance of information in an IoT status update system where an Energy Harvesting (EH) device samples an information source and forwards the update packets to a destination node through a direct channel. We introduce and optimize a semantics-aware metric, Query Version Age of Information (QVAoI), in the system alongside other metrics QAoI, VAoI, and AoI. By employing the MDP framework, we formulate the optimization problem and determine the optimal transmission policies at the device, which involve deciding the time slots for updating, subject to the energy limitations imposed by the device's battery and energy arrivals. Through analytical and numerical results, we compare the performance of the semantics-aware QVAoI-Optimal, QAoI-Optimal, VoI-Optimal, and AoI-Optimal policies with a baseline greedy policy. All semantics-aware policies exhibit superior performance compared to the greedy policy. Specifically, the QVAoI-Optimal policy significantly enhances performance by either delivering fresher, more relevant, and valuable updates with the same energy arrivals or reducing transmissions while maintaining comparable freshness and significance of information compared to the QAoI-Optimal and other policies.