An increased need for efficient storage and retrieval of crop performance data is driven by a desire to increase the value of crop performance tests, opportunities in crop modelling, opportunities to facilitate cross planning, opportunities to discover genes that affect economic traits, and data mining applications that require better integration of data from multiple sources. Thus, an increased number of stakeholders need access to crop data that are current, accurate, and complete. There is also a growing sophistication and awareness of the role and capabilities of modern informatics techniques in biological research – an area that has become known as “bioinformatics”. Bioinformatics, in partnership with statistics, can play a vital role in increasing the value of crop performance data. However, much of this role remains to be developed and adopted by the communities that gather and use these data. Part of the challenge is that phenotypic data are complex, and extensive information about the context under which the data were collected is required. This can include information about experimental design, soil and climatic conditions, treatments applied, germplasm tested, plant growth stages, and traits measured. If context is neglected, data are useless, but if context is overly complex, it may be ignored or used improperly. Several solutions have been developed to address these needs. These include commercial software packages, open-source collaborations, and a new application developed by the authors. Each solution has strengths and weaknesses, and each addresses different types of needs. This review will discuss the motivations for developing and using crop information systems, the current status and availability of crop information systems, and the challenges that must be met to achieve future potential. Key words: Bioinformatics, database, software, statistics, ontology, variety trial