Modelo logístico para fitomassa e extração de nutrientes para a cultura de arroz

Translated title of the contribution: Logistic rice model for dry matter and nutrient uptake

Axel García Y García, Durval Dourado-Neto, Maria del Valle Basanta, Ramiro Fernando López Ovejero, José Laércio Favarin

    Research output: Contribution to journalArticlepeer-review

    9 Scopus citations

    Abstract

    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.

    Translated title of the contributionLogistic rice model for dry matter and nutrient uptake
    Original languagePortuguese
    Pages (from-to)481-488
    Number of pages8
    JournalScientia Agricola
    Volume60
    Issue number3
    DOIs
    StatePublished - Jul 1 2003

    Keywords

    • Macronutrients
    • Modeling
    • Sine function

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