Method for prediction of soil and/or plant condition

A system for predicting a soil or plant condition in precision agriculture, the comprising:

• a measurement device with a data acquisition unit for an acquiring measurement data for at least one measurement parcel, the measurement data comprising
• spectral sensor data;
• a classification unit for executing a classification of the measurement data using a classification algorithm for providing an assignment of the at least one measurement parcel to at least one class of interest, based on the measurement data and a classification model made available to the classification unit comprising at least the at least one class of interest;
• a feedback functionality for processing the assignment by a feedback procedure providing feedback data comprising at least one of:
• verification information for the assignment of the measurement parcel to the at least one class of interest,
• change information of the assignment of the measurement parcel to the at least one class of interest,
• a definition of a new class of interest,
• an instruction for removal of a class of interest from the classification model,
• a first selection of the measurement data to be used for the classification, and
• identification of a second selection of the measurement data to be ignored for further processing, and
• wherein the feedback data is provided to a training unit comprising a training procedure, the training procedure being based on a machine learning algorithm and providing update information for the classification model, wherein the feedback data is provided based on implicit feedback, wherein the implicit feedback is based on at least one of:
• an interpretation of a lack of explicit feedback as a confirmation of the assignment, or
• a comparison of an actually executed action on the at least one measurement parcel with a proposal for an action being based on the assignment of the at least one measurement parcel.