Logistic rice model for dry matter and nutrient uptake

The temporal variation of cumulative dry matter can be represented by a sigmoidal curve and the temporal variation of nutrient uptake follows this characteristic shape. Therefore, modeling the temporal variation of cumulative dry matter allows estimating nutrient uptake along the crop cycle. The obj...

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Main Authors: Axel García y García, Durval Dourado-Neto, Maria del Valle Basanta, Ramiro Fernando López Ovejero, José Laércio Favarin
Format: Article
Language:English
Published: Universidade de São Paulo 2003-01-01
Series:Scientia Agricola
Subjects:
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162003000300011&tlng=en
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author Axel García y García
Durval Dourado-Neto
Maria del Valle Basanta
Ramiro Fernando López Ovejero
José Laércio Favarin
author_facet Axel García y García
Durval Dourado-Neto
Maria del Valle Basanta
Ramiro Fernando López Ovejero
José Laércio Favarin
author_sort Axel García y García
collection DOAJ
description The temporal variation of cumulative dry matter can be represented by a sigmoidal curve and the temporal variation of nutrient uptake follows this characteristic shape. Therefore, modeling the temporal variation of cumulative dry matter allows estimating nutrient uptake along the crop cycle. The objective of this study was to propose a sine model to estimate dry matter and macronutrient uptake, and to estimate the moments of maximum N and K uptake rates for the rice crop. The field experiment was carried out on a wetland area of Piracicaba, SP, Brazil, consisting of an Humic Haplaquept. The chosen rice variety was IAC 103, a middle season cycle and high yield. Observed variables were dry matter of different plant parts (root, leaf and stem, and panicle) and macronutrient contents per unit dry matter. A sine model was proposed for the cumulative variation of these variables, based on biological events that occurred during the crop cycle. The temporal variation of nutrient uptake was estimated and a lower accuracy was observed for K uptake. The maximum absorption rate for N and K was found at 56% of the relative development of the crop, corresponding to 60 days after emergence in this experiment. The proposed model presented a satisfactory behavior to define the order of magnitude of estimated dry matter and macronutrient uptake by the rice crop and maximum N and K uptake rates.
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spelling doaj.art-11b3c3e6948e4e5f9c7c2d78994333982022-12-21T19:22:36ZengUniversidade de São PauloScientia Agricola1678-992X2003-01-01603481488Logistic rice model for dry matter and nutrient uptakeAxel García y García0Durval Dourado-Neto1Maria del Valle Basanta2Ramiro Fernando López Ovejero3José Laércio Favarin4USPUSPUSPUSPUSPThe temporal variation of cumulative dry matter can be represented by a sigmoidal curve and the temporal variation of nutrient uptake follows this characteristic shape. Therefore, modeling the temporal variation of cumulative dry matter allows estimating nutrient uptake along the crop cycle. The objective of this study was to propose a sine model to estimate dry matter and macronutrient uptake, and to estimate the moments of maximum N and K uptake rates for the rice crop. The field experiment was carried out on a wetland area of Piracicaba, SP, Brazil, consisting of an Humic Haplaquept. The chosen rice variety was IAC 103, a middle season cycle and high yield. Observed variables were dry matter of different plant parts (root, leaf and stem, and panicle) and macronutrient contents per unit dry matter. A sine model was proposed for the cumulative variation of these variables, based on biological events that occurred during the crop cycle. The temporal variation of nutrient uptake was estimated and a lower accuracy was observed for K uptake. The maximum absorption rate for N and K was found at 56% of the relative development of the crop, corresponding to 60 days after emergence in this experiment. The proposed model presented a satisfactory behavior to define the order of magnitude of estimated dry matter and macronutrient uptake by the rice crop and maximum N and K uptake rates.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162003000300011&tlng=enmodelingsine functionmacronutrients
spellingShingle Axel García y García
Durval Dourado-Neto
Maria del Valle Basanta
Ramiro Fernando López Ovejero
José Laércio Favarin
Logistic rice model for dry matter and nutrient uptake
Scientia Agricola
modeling
sine function
macronutrients
title Logistic rice model for dry matter and nutrient uptake
title_full Logistic rice model for dry matter and nutrient uptake
title_fullStr Logistic rice model for dry matter and nutrient uptake
title_full_unstemmed Logistic rice model for dry matter and nutrient uptake
title_short Logistic rice model for dry matter and nutrient uptake
title_sort logistic rice model for dry matter and nutrient uptake
topic modeling
sine function
macronutrients
url http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162003000300011&tlng=en
work_keys_str_mv AT axelgarciaygarcia logisticricemodelfordrymatterandnutrientuptake
AT durvaldouradoneto logisticricemodelfordrymatterandnutrientuptake
AT mariadelvallebasanta logisticricemodelfordrymatterandnutrientuptake
AT ramirofernandolopezovejero logisticricemodelfordrymatterandnutrientuptake
AT joselaerciofavarin logisticricemodelfordrymatterandnutrientuptake