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: A current-to-frequency converter in which a succession of small charge feedback pulses is selectively generated to null the input current. The feedback pulses are generated by applying voltage pulses of precisely controlled magnitude to a precision capacitor to produce pulses of precisely-determined charge content. These pulses are then applied to a charge-dividing circuit including a matched pair of bipolar transistors. The charge dividing circuit bypasses the bulk of the charge in each pulse, while applying only a minute fraction of each pulse as the feedback current. The charge division ratio is maintained constant by the circuit in spite of temperature fluctuations.