We provide an approach to reconstruct spatiotemporal 3D models of aging objects such as fruit containing time-varying shape and appearance using multi-view time-lapse videos captured by a microenvironment of Raspberry Pi cameras. Our approach represents the 3D structure of the object prior to aging using a static 3D mesh reconstructed from multiple photographs of the object captured using a rotating camera track. We manually align the 3D mesh to the images at the first time instant. Our approach automatically deforms the aligned 3D mesh to match the object across the multi-viewpoint time-lapse videos. We texture map the deformed 3D meshes with intensities from the frames at each time instant to create the spatiotemporal 3D model of the object. Our results reveal the time dependence of volume loss due to transpiration and color transformation due to enzymatic browning on banana peels and in exposed parts of bitten fruit.