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pro vyhledávání: '"Lucy, Egan"'
HairNet2: deep learning to quantify cotton leaf hairiness, a complex genetic and environmental trait
Autor:
Moshiur Farazi, Warren C. Conaty, Lucy Egan, Susan P. J. Thompson, Iain W. Wilson, Shiming Liu, Warwick N. Stiller, Lars Petersson, Vivien Rolland
Publikováno v:
Plant Methods, Vol 20, Iss 1, Pp 1-19 (2024)
Abstract Background Cotton accounts for 80% of the global natural fibre production. Its leaf hairiness affects insect resistance, fibre yield, and economic value. However, this phenotype is still qualitatively assessed by visually attributing a Genot
Externí odkaz:
https://doaj.org/article/307372dac3e741bca13f82732c72ebb2
Publikováno v:
Frontiers in Plant Science, Vol 12 (2021)
Determining the performance of white clover cultivars under drought conditions is critical in dry climates. However, comparing the differences in cultivar performance requires equivalent soil water content for all plants, to reduce the water deficit
Externí odkaz:
https://doaj.org/article/9aa89004ab4d4cca81b406ec8e25b11b
Autor:
Lucy, Egan, Rainer, Hofmann, Shirley, Nichols, Jonathan, Hadipurnomo, Valerio, Hoyos-Villegas
Publikováno v:
Frontiers in Plant Science
Determining the performance of white clover cultivars under drought conditions is critical in dry climates. However, comparing the differences in cultivar performance requires equivalent soil water content for all plants, to reduce the water deficit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::9b49912a53c84548c63d4e65c3b1e710
https://pubmed.ncbi.nlm.nih.gov/33815432
https://pubmed.ncbi.nlm.nih.gov/33815432