Spectral methods usually produce a large amount of data, and have been greatly applied to food and agricultural products. These products demand several analyses to determine different parameters, that will further indicate their quality. There have been several approaches reported to deal with multi-target regression in recent years, with different applications demanding a specific approach. Multi-target modelling could provide a useful tool for spectral methods, specially when applied to food products, as it could deal with prediction of different parameters from a single data source. This chapter provides an overview of multi-target regression methods, presenting the performance evaluation metrics and discussing its potential application for spectral data. In addition, recent applications to food products are presented, and the future trends discussed.
