The field of robotic agriculture and tactile sensing is witnessing significant advancements, driven by the need for efficient, sustainable, and precise practices. Researchers are exploring innovative methods for automated fruit handling, including quantitative hardness assessment and adaptive manipulation. Vision-based tactile sensing is emerging as a promising approach for rapid, non-destructive evaluation of fruit properties. Furthermore, the development of adaptive wiping methods and autonomous robotic pruning systems is addressing critical challenges in precision agriculture. Noteworthy papers in this area include the proposal of a novel framework for quantitative hardness assessment utilizing vision-based tactile sensing, which has demonstrated efficacy and robustness in extensive experimental validation. Another notable work is the introduction of an adaptive wiping method that integrates real-time force-torque feedback with pre-trained object representations, achieving 96% accuracy in applying reference forces.