The understanding of the genome of different crops and its genetic variability are increasing steadily. However, at the field level, advances in linking genotype and phenotype are limited by the lack of methods for reliable high-throughput phenotyping to allow season-long monitoring of complex traits. Quantitative phenotypic data generated from field trials at the level of individual lines is one of the most expensive components of any cereal breeding program. However, such data is also the key driver of genetic progress for grain yield and adaptation, for instance in water-limited environments. Robust and time-efficient phenotyping is critical for trait based selection of potential parents for crossing blocks and evaluation of the progeny and would better inform analyses of gene expression at different stages of crop development.

 In this paper a series of useful tools for field phenotyping and its applications are presented. In particular, the prediction of crop properties using hyperspectral models, the use of digital imaging to survey crop early vigour and the use of canopy temperature and its relation to water use. In addition we present and discuss the use of crop simulation as a tool to integrate this information and produce rankings of predictions for complex traits, such as water use or water stress indices.