Abstract: A method of establishing yield and moisture content maps involves the continuous recording of yield of moisture content of a harvested crop, as a harvesting machine traverses a field. The recorded yield or moisture content is associated with data from a positioning system, in order that a map of yield or moisture content across the field can be generated. The yield or moisture content is compared with a second measurement of yield or moisture content, and a correction factor is determined. The correction factor is applied to the first yield or moisture content data in order to produce a more accurate yield or moisture content map.

Abstract: A tractor includes a cab mounted analysis/display unit (1) connected to a number of on-board sensors for detecting speed, fuel flow, etc and also capable of receiving data input manually or via a data carrier. The unit (1) is also connected to an on-board GPS navigation system (24), and includes means for generating maps of tractor-related parameters and/or parameters derived therefrom. The math usefulness of the system is in derby “on the go” maps of cost related data for a given field operation. Cost maps for cumulative operations and maps of gross profit margin are possible by adding “on the go” generated cost data to previously generated cost and/or yield data as the tractor performs an operation in a field.

Abstract: A method of collecting yield data from a harvesting machine includes the steps of establishing a first data set comprising raw data by continuously recording yield and position data periodically at data points when the harvesting machine is in a harvesting area. Each data point is tagged with a code indicative of a harvesting parameter of the said harvesting machine. A filtering process is applied to the first data set to create a second data set, wherein invalid data is removed by the filtering process. The filtering process includes the step of identifying all data points in the filtering process where the status of at least one harvesting parameter indicates that the harvester is not harvesting.

Abstract: A method of collecting yield data from a harvesting machine includes the steps of establishing a first data set comprising raw data by continuously recording yield and position data periodically at data points when the harvesting machine is in a harvesting area. Each data point is tagged with a code indicative of a harvesting parameter of the said harvesting machine. A filtering process is applied to the first data set to create a second data set, wherein invalid data is removed by the filtering process. The filtering process includes the step of identifying all data points in the filtering process where the status of at least one harvesting parameter indicates that the harvester is not harvesting.

Abstract: A tractor includes a cab mounted analysis/display unit (1) connected to a number of on-board sensors for detecting speed, fuel flow, etc and also capable of receiving data input manually or via a data carrier. The unit (1) is also connected to an on-board GPS navigation system (24), and includes means for generating maps of tractor-related parameters and/or parameters derived therefrom. The math usefulness of the system is in derby “on the go” maps of cost related data for a given field operation. Cost maps for cumulative operations and maps of gross profit margin are possible by adding “on the go” generated cost data to previously generated cost and/or yield data as the tractor performs an operation in a field.

Abstract: A tractor includes a cab mounted analysis/display unit (1) connected to a number of on-board sensors for detecting speed, fuel flow, etc and also capable of receiving data input manually or via a data carrier. The unit (1) is also connected to an on-board GPS navigation system (24), and includes means for generating maps of tractor-related parameters and/or parameters derived therefrom. The main usefulness of the system is in deriving “on the go” maps of cost related data for a given field operation. Cost maps for cumulative operations and maps of gross profit margin are possible by adding “on the go” generated cost data to previously generated cost and/or yield data as the tractor performs an operation in a field.