Abstract: A crop prediction system performs various machine learning operations to predict crop production and to identify a set of farming operations that, if performed, optimize crop production. The crop prediction system uses crop prediction models trained using various machine learning operations based on geographic and agronomic information. Responsive to receiving a request from a grower, the crop prediction system can access information representation of a portion of land corresponding to the request, such as the location of the land and corresponding weather conditions and soil composition. The crop prediction system applies one or more crop prediction models to the access information to predict a crop production and identify an optimized set of farming operations for the grower to perform.

Abstract: Disclosed is a tray system for use in hydroponic growing, the system including a framework with at least one shelf, a shelf liner sized and configured for placement on the at least one shelf of the framework, a hydroponic grow tray sized and configured for placement on the shelf liner, the grow tray including a first side, a second side and a grow medium portion between the first side and second side, the tray configured in place such that there is a downward slope from the first side to the second side, the tray further comprising: a water receiving surface at the first side of the tray, the water receiving surface positioned to receive water from a source of water mounted to the framework, and sloped such that water received is directed to the grow medium portion of the tray, and a tray drain at the second side of the tray configured to receive water from the grow portion.