Abstract: A method according to an embodiment includes receiving, at one or more processors, satellite image data, temperature measurement data, precipitation measurement data, and one or more agronomic parameters, associated with an agricultural land segment. The method also includes predicting, using the one or more processors and a first neural network, a biomass value associated with the agricultural land segment. The method also includes predicting, using the one or more processors and a second neural network, a sugar content value associated with the agricultural land segment. The method also includes predicting, using the one or more processors, a total sugar value associated with the agricultural land segment. Optionally, the method also includes optimizing harvest dates for a plurality of agricultural land segments that includes the agricultural land segment, based on one or more constraints.

Abstract: A system for computational imaging spectroscopy to provide compact and lightweight design, as well as large field of view of an object to be captured. The system includes imaging components, and computational device. The imaging components includes lens assembly, a fixed or variable-diameter aperture, spectral filter array and imaging sensor. The lens assembly provides wide angle of view, image-side telecentricity, and further may correct for longitudinal chromatic aberrations. The lens assembly may not provide correction of lateral chromatic aberrations. Furthermore, the lens assembly provides image-space telecentricity so as to chief rays are incident perpendicular to image sensor. The lens assembly may produce different chromatic aberrations pattern for each wavelength within the spectral range of interest.