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This article in AJ

  1. Vol. 68 No. 1, p. 63-66
     
    Received: Mar 6, 1975


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doi:10.2134/agronj1976.00021962006800010017x

Diffusion and Mass Flow of Nitrate-Nitrogen to Plant Roots1

  1. R. E. Phillips,
  2. T. NaNagara,
  3. R. E. Zartman and
  4. J. E. Leggett2

Abstract

Abstract

The transport of plant nutrient ions from the soil mass to plant root surfaces is an important phenomenon in mineralnutrition of plants. Nitrate-nitrogen, the most important source of nitrogen of non-leguminous plants, is soluble in soil water and is transported to plant roots by both mass flow and diffusion. It is, therefore, important to understand the relative importance of each of these two mechanisms of transport of NO3-N to plant roots and the environmental conditions under which each is the dominant mechanism of transport.

In order to predict from theory the simultaneous transport of NO3-N to plant root, several soil and plant parameters must be known. These parameters include the volumetric soil water content, concentration of NO3-N in soil solution, porous diffusion coefficient of NO3-N in soil, average macroscopic velocity of soil water at plant root surface, radius of root, transpiration rate and plant root length. These soil and plant parameters must be measured in either the field or greenhouse.

The validity and/or consequences of several assumptions of a previously reported steady-state model describing simultaneous mass flow and diffusion of NO3-N to plant root surfaces are discussed with reference to experimental measurement of plant and soil parameters. The relative importance of diffusion to mass flow of NO3-N is large when the ratio of transpiration rate to the constant of proportionality relating flux into the plant to concentration of NO3-N in the soil solution is less than 0.2 but is negligible when the ratio is greater than unity. The average concentration of NO3-N of the entire soil mass rather than the concentration of NO3-N at the outer radius of the soil cylinder associated with each root can be used in the model with little error for most situations expected to occur in the field.

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