Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Kyungdahm Yun"'
Autor:
Nicholas T. Glass, Kyungdahm Yun, Eduardo A. Dias de Oliveira, Alina Zare, Roser Matamala, Soo-Hyung Kim, Miquel Gonzalez-Meler
Publikováno v:
Frontiers in Plant Science, Vol 14 (2023)
Roots optimize the acquisition of limited soil resources, but relationships between root forms and functions have often been assumed rather than demonstrated. Furthermore, how root systems co-specialize for multiple resource acquisitions is unclear.
Externí odkaz:
https://doaj.org/article/9c1ac89e251c427b8025ca294e27ac3a
Publikováno v:
Plant Phenomics, Vol 5 (2023)
Root system architecture (RSA) is an important measure of how plants navigate and interact with the soil environment. However, current methods in studying RSA must make tradeoffs between precision of data and proximity to natural conditions, with roo
Externí odkaz:
https://doaj.org/article/76ee99ac0e634fe49b03f2c1f92f0e81
Publikováno v:
Frontiers in Plant Science, Vol 13 (2022)
We introduce an integrative process-based crop model for garlic (Allium sativum). Building on our previous model that simulated key phenological, morphological, and physiological features of a garlic plant, the new garlic model provides comprehensive
Externí odkaz:
https://doaj.org/article/30f25838e7fa426aab145ad167014487
Publikováno v:
Plants, Vol 9, Iss 10, p 1358 (2020)
Plant simulation models are abstractions of plant physiological processes that are useful for investigating the responses of plants to changes in the environment. Because photosynthesis and transpiration are fundamental processes that drive plant gro
Externí odkaz:
https://doaj.org/article/c5303385836b47b3abd4ce49617b99d1
Autor:
Jig Han Jeong, Jonathan P Resop, Nathaniel D Mueller, David H Fleisher, Kyungdahm Yun, Ethan E Butler, Dennis J Timlin, Kyo-Moon Shim, James S Gerber, Vangimalla R Reddy, Soo-Hyung Kim
Publikováno v:
PLoS ONE, Vol 11, Iss 6, p e0156571 (2016)
Accurate predictions of crop yield are critical for developing effective agricultural and food policies at the regional and global scales. We evaluated a machine-learning method, Random Forests (RF), for its ability to predict crop yield responses to
Externí odkaz:
https://doaj.org/article/cda00ac80c774dc2a532e5a38c823804
Autor:
Kyungdahm Yun1 kdyun@uw.edu, Soo-Hyung Kim1 soohkim@uw.edu
Publikováno v:
In Silico Plants. 2023, Vol. 5 Issue 1, p1-16. 16p.
Autor:
Kyungdahm Yun, Soo-Hyung Kim
Publikováno v:
in silico Plants. 5
We introduce Cropbox, a novel modelling framework that supports various aspects of crop modelling in a unique yet concise style. Building a crop model can be easily riddled with technical details looking trivial at first but later becoming major obst
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5f5af76ad403c50d1b7af1ff2bf1a375
https://doi.org/10.1093/insilicoplants/diac021
https://doi.org/10.1093/insilicoplants/diac021
Autor:
Glass, Nicholas T., Kyungdahm Yun, de Oliveira, Eduardo A. Dias, Zare, Alina, Matamala, Roser, Soo-Hyung Kim, Gonzalez-Meler, Miquel
Publikováno v:
Frontiers in Plant Science; 3/17/2023, Vol. 14, p1-12, 12p
Publikováno v:
Frontiers in plant science. 13
We introduce an integrative process-based crop model for garlic (
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::42d3d95ae54d49f868e1e2125d94c900
https://pubmed.ncbi.nlm.nih.gov/35371114
https://pubmed.ncbi.nlm.nih.gov/35371114
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::71b8a72fc1a62055cba25885d4083ef5
https://doi.org/10.2139/ssrn.3989444
https://doi.org/10.2139/ssrn.3989444