Single-shot volumetric fluorescence (SVF) imaging offers a significant advantage over traditional imaging methods that require scanning across multiple axial planes as it can capture biological processes with high temporal resolution across a large field of view. Existing SVF imaging methods often require large, complex point spread functions (PSFs) to meet the multiplexing requirements of compressed sensing, which limits the signal-to-noise ratio, resolution and/or field of view. In this paper, we introduce the QuadraPol PSF combined with neural fields, a novel approach for SVF imaging. This method utilizes a cost-effective custom polarizer at the back focal plane and a polarization camera to detect fluorescence, effectively encoding the 3D scene within a compact PSF without depth ambiguity. Additionally, we propose a reconstruction algorithm based on the neural fields technique that addresses the inaccuracies of phase retrieval methods used to correct imaging system aberrations. This algorithm combines the accuracy of experimental PSFs with the long depth of field of computationally generated retrieved PSFs. QuadraPol PSF, combined with neural fields, significantly reduces the acquisition time of a conventional fluorescence microscope by approximately 20 times and captures a 100 mm$^3$ cubic volume in one shot. We validate the effectiveness of both our hardware and algorithm through all-in-focus imaging of bacterial colonies on sand surfaces and visualization of plant root morphology. Our approach offers a powerful tool for advancing biological research and ecological studies.