Maize dry matter production and macronutrient extraction model as a new approach for fertilizer rate estimation
Autor(a) principal: | |
---|---|
Data de Publicação: | 2017 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Anais da Academia Brasileira de Ciências (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652017000200705 |
Resumo: | ABSTRACT Decision support for nutrient application remains an enigma if based on soil nutrient analysis. If the crop could be used as an auxiliary indicator, the plant nutrient status during different growth stages could complement the soil test, improving the fertilizer recommendation. Nutrient absorption and partitioning in the plant are here studied and described with mathematical models. The objective of this study considers the temporal variation of the nutrient uptake rate, which should define crop needs as compared to the critical content in soil solution. A uniform maize crop was grown to observe dry matter accumulation and nutrient content in the plant. The dry matter accumulation followed a sigmoidal model and the macronutrient content a power model. The maximum nutrient absorption occurred at the R4 growth stage, for which the sap concentration was successfully calculated. It is hoped that this new approach of evaluating nutrient sap concentration will help to develop more rational ways to estimate crop fertilizer needs. This new approach has great potential for on-the-go crop sensor-based nutrient application methods and its sensitivity to soil tillage and management systems need to be examined in following studies. If mathematical model reflects management impact adequately, resources for experiments can be saved. |
id |
ABC-1_6a3e3425a3a9f1a64468c1e1c336bae0 |
---|---|
oai_identifier_str |
oai:scielo:S0001-37652017000200705 |
network_acronym_str |
ABC-1 |
network_name_str |
Anais da Academia Brasileira de Ciências (Online) |
repository_id_str |
|
spelling |
Maize dry matter production and macronutrient extraction model as a new approach for fertilizer rate estimationmaizefertilizer rate estimationnutrient contentnutrient partitionABSTRACT Decision support for nutrient application remains an enigma if based on soil nutrient analysis. If the crop could be used as an auxiliary indicator, the plant nutrient status during different growth stages could complement the soil test, improving the fertilizer recommendation. Nutrient absorption and partitioning in the plant are here studied and described with mathematical models. The objective of this study considers the temporal variation of the nutrient uptake rate, which should define crop needs as compared to the critical content in soil solution. A uniform maize crop was grown to observe dry matter accumulation and nutrient content in the plant. The dry matter accumulation followed a sigmoidal model and the macronutrient content a power model. The maximum nutrient absorption occurred at the R4 growth stage, for which the sap concentration was successfully calculated. It is hoped that this new approach of evaluating nutrient sap concentration will help to develop more rational ways to estimate crop fertilizer needs. This new approach has great potential for on-the-go crop sensor-based nutrient application methods and its sensitivity to soil tillage and management systems need to be examined in following studies. If mathematical model reflects management impact adequately, resources for experiments can be saved.Academia Brasileira de Ciências2017-05-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652017000200705Anais da Academia Brasileira de Ciências v.89 n.1 suppl.0 2017reponame:Anais da Academia Brasileira de Ciências (Online)instname:Academia Brasileira de Ciências (ABC)instacron:ABC10.1590/0001-3765201720160525info:eu-repo/semantics/openAccessMARTINS,KARLA V.DOURADO-NETO,DURVALREICHARDT,KLAUSFAVARIN,JOSÉ L.SARTORI,FELIPE F.FELISBERTO,GUILHERMEMELLO,SIMONE C.eng2017-05-26T00:00:00Zoai:scielo:S0001-37652017000200705Revistahttp://www.scielo.br/aabchttps://old.scielo.br/oai/scielo-oai.php||aabc@abc.org.br1678-26900001-3765opendoar:2017-05-26T00:00Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC)false |
dc.title.none.fl_str_mv |
Maize dry matter production and macronutrient extraction model as a new approach for fertilizer rate estimation |
title |
Maize dry matter production and macronutrient extraction model as a new approach for fertilizer rate estimation |
spellingShingle |
Maize dry matter production and macronutrient extraction model as a new approach for fertilizer rate estimation MARTINS,KARLA V. maize fertilizer rate estimation nutrient content nutrient partition |
title_short |
Maize dry matter production and macronutrient extraction model as a new approach for fertilizer rate estimation |
title_full |
Maize dry matter production and macronutrient extraction model as a new approach for fertilizer rate estimation |
title_fullStr |
Maize dry matter production and macronutrient extraction model as a new approach for fertilizer rate estimation |
title_full_unstemmed |
Maize dry matter production and macronutrient extraction model as a new approach for fertilizer rate estimation |
title_sort |
Maize dry matter production and macronutrient extraction model as a new approach for fertilizer rate estimation |
author |
MARTINS,KARLA V. |
author_facet |
MARTINS,KARLA V. DOURADO-NETO,DURVAL REICHARDT,KLAUS FAVARIN,JOSÉ L. SARTORI,FELIPE F. FELISBERTO,GUILHERME MELLO,SIMONE C. |
author_role |
author |
author2 |
DOURADO-NETO,DURVAL REICHARDT,KLAUS FAVARIN,JOSÉ L. SARTORI,FELIPE F. FELISBERTO,GUILHERME MELLO,SIMONE C. |
author2_role |
author author author author author author |
dc.contributor.author.fl_str_mv |
MARTINS,KARLA V. DOURADO-NETO,DURVAL REICHARDT,KLAUS FAVARIN,JOSÉ L. SARTORI,FELIPE F. FELISBERTO,GUILHERME MELLO,SIMONE C. |
dc.subject.por.fl_str_mv |
maize fertilizer rate estimation nutrient content nutrient partition |
topic |
maize fertilizer rate estimation nutrient content nutrient partition |
description |
ABSTRACT Decision support for nutrient application remains an enigma if based on soil nutrient analysis. If the crop could be used as an auxiliary indicator, the plant nutrient status during different growth stages could complement the soil test, improving the fertilizer recommendation. Nutrient absorption and partitioning in the plant are here studied and described with mathematical models. The objective of this study considers the temporal variation of the nutrient uptake rate, which should define crop needs as compared to the critical content in soil solution. A uniform maize crop was grown to observe dry matter accumulation and nutrient content in the plant. The dry matter accumulation followed a sigmoidal model and the macronutrient content a power model. The maximum nutrient absorption occurred at the R4 growth stage, for which the sap concentration was successfully calculated. It is hoped that this new approach of evaluating nutrient sap concentration will help to develop more rational ways to estimate crop fertilizer needs. This new approach has great potential for on-the-go crop sensor-based nutrient application methods and its sensitivity to soil tillage and management systems need to be examined in following studies. If mathematical model reflects management impact adequately, resources for experiments can be saved. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-05-01 |
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=S0001-37652017000200705 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652017000200705 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0001-3765201720160525 |
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 |
Academia Brasileira de Ciências |
publisher.none.fl_str_mv |
Academia Brasileira de Ciências |
dc.source.none.fl_str_mv |
Anais da Academia Brasileira de Ciências v.89 n.1 suppl.0 2017 reponame:Anais da Academia Brasileira de Ciências (Online) instname:Academia Brasileira de Ciências (ABC) instacron:ABC |
instname_str |
Academia Brasileira de Ciências (ABC) |
instacron_str |
ABC |
institution |
ABC |
reponame_str |
Anais da Academia Brasileira de Ciências (Online) |
collection |
Anais da Academia Brasileira de Ciências (Online) |
repository.name.fl_str_mv |
Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC) |
repository.mail.fl_str_mv |
||aabc@abc.org.br |
_version_ |
1754302864469000192 |