Temporal phenomic predictions from unoccupied aerial systems can outperform genomic predictions by Alper Adak, Seth C Murray, Steven L Anderson

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Pedigree‐management‐flight interaction for temporal phenotype analysis and temporal phenomic prediction by Alper Adak, Steven L. Anderson, Seth C. Murray

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Cumulative temporal vegetation indices from unoccupied aerial systems allow maize (Zea mays L.) hybrid yield to be estimated across environments with fewer flights. by Sumantra Chatterjee, Alper Adak, Scott Wilde, Shakirah Nakasagga, Seth C Murray

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Cumulative temporal vegetation indices from unoccupied aerial systems allow maize (Zea mays L.) hybrid yield to be estimated across environments with fewer flights by Sumantra Chatterjee, Alper Adak, Scott Wilde, Shakirah Nakasagga, Seth C. Murray

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Assessing Genetic Diversity by Morphological Markers of Bean (Phaseolus vulgaris L.) Germplasm from Northeast Anatolia by Erdal ELKOCA, Faik KANTAR, Kamil HALİLOĞLU, Alper ADAK, Cafer EKEN, Mesude Figen DÖNMEZ

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Phenomic data-facilitated rust and senescence prediction in maize using machine learning algorithms by Aaron J. DeSalvio, Alper Adak, Seth C. Murray, Scott C. Wilde, Thomas Isakeit

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Temporal Vegetation Indices and Plant Height from Remotely Sensed Imagery Can Predict Grain Yield and Flowering Time Breeding Value in Maize via Machine Learning Regression by Alper Adak, Seth C Murray, Sofija Božinović, Regan Lindsey, Shakirah Nakasagga, Sumantra Chatterjee, Steven L. Anderson, Scott Wilde

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Unoccupied aerial systems discovered overlooked loci capturing the variation of entire growing period in maize by Alper Adak, Seth C. Murray, II Steven L. Anderson, Sorin C. Popescu, Lonesome Malambo, M. Cinta Romay, Natalia deLeon

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