Výsledky vyhledávání - "weed emergence model"

Akademický článek

Analysis of interval‐grouped data in weed science: The binnednp Rcpp package

Autor: Daniel Barreiro‐Ures, Mario Francisco‐Fernández, Ricardo Cao, Basilio B. Fraguela, Ramón Doallo, José Luis González‐Andújar, Miguel Reyes

Publikováno v: Ecology and Evolution, Vol 9, Iss 19, Pp 10903-10915 (2019)

Abstract Weed scientists are usually interested in the study of the distribution and density functions of the random variable that relates weed emergence with environmental indices like the hydrothermal time (HTT). However, in many situations, experi

Externí odkaz: https://doaj.org/article/c846ee26911344138a3695748cd25fc2

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Akademický článek

Predicting Seedling Emergence of Three Canarygrass (Phalaris) Species under Semi-Arid Conditions Using Parametric and Non-Parametric Models

Autor: Carlos Sousa-Ortega, Aritz Royo-Esnal, José María Urbano

Publikováno v: Agronomy, Vol 11, Iss 5, p 893 (2021)

The Phalaris genus includes annual weed species such as short-spiked canarygrass (Phalaris brachystachys Link.), little-seed canarygrass (Phalaris minor Retz.) and hood canarygrass (Phalaris paradoxa L.), which are especially problematic in Spain; as

Externí odkaz: https://doaj.org/article/8cebc5b1be0e4c26b1c14b22e9d8d717

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Akademický článek

Germination Parameters of Selected Summer Weeds: Transferring of the AlertInf Model to Other Geographical Regions

Autor: Valentina Šoštarčić, Roberta Masin, Donato Loddo, Ema Brijačak, Maja Šćepanović

Publikováno v: Agronomy, Vol 11, Iss 2, p 292 (2021)

Effective weed management depends on correct control timing, which depends on seedling emergence dynamics. Since soil temperature and soil moisture are the two main factors that determine weed germination, the hydrothermal time model can be used to p

Externí odkaz: https://doaj.org/article/669a2225359949baacde10251fcb735e

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Predicting Seedling Emergence of Three Canarygrass (Phalaris) Species under Semi-Arid Conditions Using Parametric and Non-Parametric Models

Autor: Aritz Royo-Esnal, Carlos Sousa-Ortega, J. M. Urbano

Publikováno v: Agronomy, Vol 11, Iss 893, p 893 (2021)
Repositorio Abierto de la UdL
Universitad de Lleida
idUS. Depósito de Investigación de la Universidad de Sevilla
instname
idUS: Depósito de Investigación de la Universidad de Sevilla
Universidad de Sevilla (US)
Agronomy
Volume 11
Issue 5

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::04050dd811e4e660648ec6cb3f151486
https://www.mdpi.com/2073-4395/11/5/893

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Analysis of interval‐grouped data in weed science: The binnednp Rcpp package

Autor: Ramón Doallo, Basilio B. Fraguela, José Luis González-Andújar, Mario Francisco-Fernández, Daniel Barreiro-Ures, Ricardo Cao, Miguel Reyes

Publikováno v: Ecology and Evolution
RUC. Repositorio da Universidade da Coruña
instname
Ecology and Evolution, Vol 9, Iss 19, Pp 10903-10915 (2019)
Digital.CSIC. Repositorio Institucional del CSIC

Weed scientists are usually interested in the study of the distribution and density functions of the random variable that relates weed emergence with environmental indices like the hydrothermal time (HTT). However, in many situations, experimental da

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3cfcc5f9ddaae3a1fe494835f1cca1b9
https://hdl.handle.net/2183/24200

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A comparative study between nonlinear regression and nonparametric approaches for modellingPhalaris paradoxaseedling emergence

Autor: J. M. Urbano, Mario Francisco-Fernández, Frank Forcella, Ricardo Cao, José Luis González-Andújar, Fernando Bastida, Miguel Reyes

Publikováno v: Digital.CSIC. Repositorio Institucional del CSIC
instname

Parametric nonlinear regression (PNR) models are used widely to fit weed seedling emergence patterns to soil microclimatic indices. However, such approximation has been questioned, mainly due to several statistical limitations. Alternatively, nonpara

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fc86e4cc16aaf38c0a794ebd52d34286
https://doi.org/10.1111/wre.12216

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Akademický článek

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Modeling seed dormancy release and germination for predicting Avena fatua L. field emergence: A genetic algorithm approach

Autor: Guillermo R. Chantre, Aníbal M. Blanco, Mariela V. Lodovichi, Ramón Gigón, Mario Ricardo Sabbatini, Ricardo L. López, J. Alberto Bandoni, Mario R. Vigna

Avena fatua is a cosmopolite weed species which produces severe yield losses in small-grain production systems in temperate and semiarid climates. In the semiarid region of Argentina, A. fatua field emergence patterns show great year-to-year variabil

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::17841905eb6abddc88111c5d06692c2e
http://www.sciencedirect.com/science/article/pii/S0304380013004808

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