The global meeting place for people interested in all things related to SWEETPOTATO

Share your research and experience, ask and answer questions, meet your peers.

USING MAIZEFINDER

MaizeFinder is designed to help maize breeders and other users of information from maize breeding research to find information they need quickly and easily. It provides very powerful search facilities, which enables you to combine different criteria in order to quickly extract the most relevant data. It also permits you to select exactly the types of data you would like to include in the output. MaizeFinderPC includes a simple GIS which enables you to easily visualize the different locations which supplied the information included in your query. It also gives you the possibility to combine the information on the trial sites with other types of information contained in GIS layers such as soil maps or maps with maize mega environments. The GIS tools can help you to quickly determine how relevant the data are for your purposes.

 

MaizeFinderPC can also help you to systematically compare different maize varieties. The tool for this is head-to-head analysis where two materials are compared by collecting all the data from the trials where the materials have been grown at the same time and with the same management. This way you can combine data across different years and statistically test in what aspects two different materials vary. MaizeFinder can provide you with many different answers to a particular question, but do not expect it to provide the answer. Plant breeding is a game of probabilities, and hopefully the easy data access in MaizeFinder can improve your chances of making better decisions, however, it is still based on probabilities and not certainty. For the best use of MaizeFinder try to frame your question in different ways and make sure to obtain different types of outputs. Then use your professional experience to interpret the data.

 

The functionality can be combined in many different ways to answer many different questions like finding varieties to match local conditions and performance assessment of existing varieties.