Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Samantha Neeno"'
Publikováno v:
Biosystems Engineering. 200:40-54
With the application of hyperspectral imaging systems on high-throughput plant phenotyping, multivariable spectral data modelling methods have been proposed to predict plant physiological features such as biomass. However, most presented modelling me
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3405e2623deae17df84fa8dbb99c6dd3
https://doi.org/10.1016/j.biosystemseng.2020.09.002
https://doi.org/10.1016/j.biosystemseng.2020.09.002
Autor:
Tyler C Field, Samantha Neeno, Sarah Libring, Javier Flores, Mahira M Morris, Allan P Schinckel, Jay S Johnson, Robert M Stwalley
Publikováno v:
2022 Houston, Texas July 17-20, 2022.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::10a775f7424609aae74b74de9f64086f
https://doi.org/10.13031/aim.202200204
https://doi.org/10.13031/aim.202200204
Dissertation/ Thesis
Autor:
Samantha Neeno (8800826)
To support the growing human population, plant phenotyping technologies must innovate to rapidly interpret hyperspectral (HS) data into genetic inferences for plant breeders and managers. While pigment and nutrient concentrations within canopies are
Autor:
Dongdong Ma, Tanzeel U. Rehman, Jialei Wang, Thirawat Bureetes, Libo Zhang, Zhihang Song, Liangju Wang, Jian Jin, Samantha Neeno, Ziling Chen
Publikováno v:
Computers and Electronics in Agriculture. 167:105069
During recent years, portable plant phenotyping instruments have become increasingly important to monitor conditions of plant health non-destructively in the greenhouse and field environments. These devices, such as the Soil Plant Analysis Developmen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::16eaf50f9f9a07969a109d13acc4111e
https://doi.org/10.1016/j.compag.2019.105069
https://doi.org/10.1016/j.compag.2019.105069