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This paper deals with the problem of purposefully failing or yielding an object by a robotic gripper. We propose a grasp quality measure fabricated for robotic harvesting in which picking a crop from its stem is desired. The proposed metric characterizes a suitable grasp configuration for systematically controlling the failure behavior of an object to break it at the desired location while avoiding damage on other areas. Our approach is based on failure task information and gripper wrench insertion capability. Failure task definition is accomplished using failure theories. Gripper wrench insertion capability is formulated by modeling the friction between the object and gripper. A new method inspired by human pre-manipulation process is introduced to utilize gripper itself as a friction measurement device. The provided friction model is capable of handling the anisotropic behavior of materials which is the case for fruits and vegetables. The evaluation method is formulated as a quasistatic grasp problem. Additionally, the general case of both fully-actuated and under-actuated grippers are considered. As a validation of the proposed evaluation method, experimental results for failing parts using Kuka Light-Weight Robot IV robot are presented.