An approach for experiment evaluations for multiple harvests crops based on non-linear regression

Detalhes bibliográficos
Autor(a) principal: Lúcio,Alessandro Dal’Col
Data de Publicação: 2021
Outros Autores: Diel,Maria Inês, Sari,Bruno G
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Horticultura Brasileira
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-05362021000300250
Resumo: ABSTRACT Biologically based growth models can be an alternative in identifying the productive response of multiple harvest vegetables. By interpreting the estimates of the parameters of the models, it is possible to estimate the total production, the rate of fruit production, and the moment when the crop reaches its maximum production potential. Besides, by estimating confidence intervals, these responses can be compared between genotypes or between different treatments. Therefore, the purpose of this manuscript is to present a literature review, and a detailed step-by-step, to interpreting the evolution of the production cycle of vegetables with multiple harvests crops based on non-linear regression. All the requirements that must be met in this type of analysis were presented in detail based on non-linear regression, providing the necessary steps for this type of analysis in details. Demonstration is given using data from strawberry cultivation along with the associated R scripts and interpretation of analysis output in material supplemental. This approach can allow for more relevant inferences than standard means analyses through better examination and modeling of the underlying biological processes.
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spelling An approach for experiment evaluations for multiple harvests crops based on non-linear regressionhorticulturelogistic modelregression modelsnon-linear modelprecocityproductionABSTRACT Biologically based growth models can be an alternative in identifying the productive response of multiple harvest vegetables. By interpreting the estimates of the parameters of the models, it is possible to estimate the total production, the rate of fruit production, and the moment when the crop reaches its maximum production potential. Besides, by estimating confidence intervals, these responses can be compared between genotypes or between different treatments. Therefore, the purpose of this manuscript is to present a literature review, and a detailed step-by-step, to interpreting the evolution of the production cycle of vegetables with multiple harvests crops based on non-linear regression. All the requirements that must be met in this type of analysis were presented in detail based on non-linear regression, providing the necessary steps for this type of analysis in details. Demonstration is given using data from strawberry cultivation along with the associated R scripts and interpretation of analysis output in material supplemental. This approach can allow for more relevant inferences than standard means analyses through better examination and modeling of the underlying biological processes.Associação Brasileira de Horticultura2021-09-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-05362021000300250Horticultura Brasileira v.39 n.3 2021reponame:Horticultura Brasileirainstname:Associação Brasileira de Horticultura (ABH)instacron:ABH10.1590/s0102-0536-20210302info:eu-repo/semantics/openAccessLúcio,Alessandro Dal’ColDiel,Maria InêsSari,Bruno Geng2021-09-28T00:00:00Zoai:scielo:S0102-05362021000300250Revistahttp://cms.horticulturabrasileira.com.br/ONGhttps://old.scielo.br/oai/scielo-oai.php||hortbras@gmail.com1806-99910102-0536opendoar:2021-09-28T00:00Horticultura Brasileira - Associação Brasileira de Horticultura (ABH)false
dc.title.none.fl_str_mv An approach for experiment evaluations for multiple harvests crops based on non-linear regression
title An approach for experiment evaluations for multiple harvests crops based on non-linear regression
spellingShingle An approach for experiment evaluations for multiple harvests crops based on non-linear regression
Lúcio,Alessandro Dal’Col
horticulture
logistic model
regression models
non-linear model
precocity
production
title_short An approach for experiment evaluations for multiple harvests crops based on non-linear regression
title_full An approach for experiment evaluations for multiple harvests crops based on non-linear regression
title_fullStr An approach for experiment evaluations for multiple harvests crops based on non-linear regression
title_full_unstemmed An approach for experiment evaluations for multiple harvests crops based on non-linear regression
title_sort An approach for experiment evaluations for multiple harvests crops based on non-linear regression
author Lúcio,Alessandro Dal’Col
author_facet Lúcio,Alessandro Dal’Col
Diel,Maria Inês
Sari,Bruno G
author_role author
author2 Diel,Maria Inês
Sari,Bruno G
author2_role author
author
dc.contributor.author.fl_str_mv Lúcio,Alessandro Dal’Col
Diel,Maria Inês
Sari,Bruno G
dc.subject.por.fl_str_mv horticulture
logistic model
regression models
non-linear model
precocity
production
topic horticulture
logistic model
regression models
non-linear model
precocity
production
description ABSTRACT Biologically based growth models can be an alternative in identifying the productive response of multiple harvest vegetables. By interpreting the estimates of the parameters of the models, it is possible to estimate the total production, the rate of fruit production, and the moment when the crop reaches its maximum production potential. Besides, by estimating confidence intervals, these responses can be compared between genotypes or between different treatments. Therefore, the purpose of this manuscript is to present a literature review, and a detailed step-by-step, to interpreting the evolution of the production cycle of vegetables with multiple harvests crops based on non-linear regression. All the requirements that must be met in this type of analysis were presented in detail based on non-linear regression, providing the necessary steps for this type of analysis in details. Demonstration is given using data from strawberry cultivation along with the associated R scripts and interpretation of analysis output in material supplemental. This approach can allow for more relevant inferences than standard means analyses through better examination and modeling of the underlying biological processes.
publishDate 2021
dc.date.none.fl_str_mv 2021-09-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-05362021000300250
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-05362021000300250
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/s0102-0536-20210302
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Associação Brasileira de Horticultura
publisher.none.fl_str_mv Associação Brasileira de Horticultura
dc.source.none.fl_str_mv Horticultura Brasileira v.39 n.3 2021
reponame:Horticultura Brasileira
instname:Associação Brasileira de Horticultura (ABH)
instacron:ABH
instname_str Associação Brasileira de Horticultura (ABH)
instacron_str ABH
institution ABH
reponame_str Horticultura Brasileira
collection Horticultura Brasileira
repository.name.fl_str_mv Horticultura Brasileira - Associação Brasileira de Horticultura (ABH)
repository.mail.fl_str_mv ||hortbras@gmail.com
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