Hyperspectral data comprises the full light spectrum; this dataset of continuous spectral information has many applications including picking out more productive crop cultivars. To help researchers better predict high-yielding crop traits, an international team led by University of Illinois have stacked together six high-powered, machine learning algorithms that are used to interpret hyperspectral data–and they demonstrated that this technique improved the predictive power of a recent study by up to 15%, compared to using just one algorithm.… Login to continue

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