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Phenomic data-facilitated rust and senescence prediction in maize using machine learning algorithms.
- Published in:
- Scientific Reports, 2022, v. 12, n. 1, p. 1, doi. 10.1038/s41598-022-11591-0
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Phenomic data-facilitated rust and senescence prediction in maize using machine learning algorithms.
- Published in:
- Scientific Reports, 2022, v. 12, n. 1, p. 1, doi. 10.1038/s41598-022-11591-0
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- Article
Prediction of regrowth and biomass of perennial sorghum using unoccupied aerial systems.
- Published in:
- Crop Science, 2022, v. 62, n. 6, p. 2107, doi. 10.1002/csc2.20758
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- Article
Validation of functional polymorphisms affecting maize plant height by unoccupied aerial systems discovers novel temporal phenotypes.
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- G3: Genes | Genomes | Genetics, 2021, v. 11, n. 6, p. 1, doi. 10.1093/g3journal/jkab075
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- Article
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.
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- Remote Sensing, 2021, v. 13, n. 11, p. 2141, doi. 10.3390/rs13112141
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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.
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- PLoS ONE, 2023, v. 17, n. 1, p. 1, doi. 10.1371/journal.pone.0277804
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- Article
Simulations of Non-linear Spin Dynamics in Spin Polarized Dilute He-He Mixtures.
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- Journal of Low Temperature Physics, 2013, v. 171, n. 3/4, p. 165, doi. 10.1007/s10909-012-0782-5
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- Article