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Syngenta invites projects that focus on crops and food production to be part of this year’s Crop Challenge in Analytics. The population of Earth is growing daily and our world is running out of land needed to produce food. Meanwhile, the crops farmers plant face escalating challenges due to increasingly variable growing conditions and climate change. Commercial corn is processed into multiple food and industrial products. It is widely known as one of the world’s most important crops. The question that projects need to focus on is: “Given historical hybrid (inbred by the tester) performance data across years and locations, how can we create a model to predict/impute the performance of the crossing of any two inbred and tester parents?”. The objective of the contest is to estimate the yield performance of the cross between inbred and tester combinations in a given holdout set.
Predicted yield values of the cross between inbred and tester combinations in the test set. Additionally, observing the standards for academic publication, entries should include a written report with the following:
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