An Empirical Mathematical Model to Describe Plant Root Systems

Gerwitz, A.; Page, E. R.

doi:10.2307/2402227

Cited by 299 publications

(142 citation statements)

References 14 publications

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“…is the rooting width and depth, R istart (m) is the starting rooting width and depth, ∑ given a proper paramerisation, gives a good description of root penetration of crops observed in a number of studies (Thorup-Kristensen, 1998, 2001, 2006ThorupKristensen & Van den Boogaard, 1998Kage et al, 2000;Kristensen & Thorup-Kristensen, 2004 The root length declines logarithmically from the soil surface downwards, as originally proposed by Gerwitz and Page (1974), and also logarithmically laterally from the crop row to the inter-row soil. However, different from Gerwitz and Page's (1974) the module extends the rooting depth by 30% from the calculated penetrating depth where the root density declines from a calculated value at the penetrating depth to zero, i.e.…”

Section: Plant Growthmentioning

confidence: 88%

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Development and critical evaluation of a generic 2-D agro-hydrological model (SMCR_N) for the responses of crop yield and nitrogen composition to nitrogen fertilizer

Zhang

Yang

Greenwood

et al. 2009

Agriculture, Ecosystems & Environment

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C d), T s -base temperature at which f Nmin (t) equals 1 ( o C), T soil -daily mean soil temperature (ºC), U N -potential N uptake (kg ha -1 ), U Nr -potential N demand by fibrous roots (kg ha -1 ), W -dry weight of the entire plant excluding fibrous roots (t ha -1 ), W r -dry weight of fibrous roots (t ha -1 ), Z osmo -soil depth used in the calculation of mean osmotic pressure (cm), Z smin -depth of soil below which no N mineralization is assumed to take place (cm), ΔW r -root dry weight increment (t ha -1 ).

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Section: Plant Growthmentioning

confidence: 88%

“…However, different from Gerwitz and Page's (1974) the module extends the rooting depth by 30% from the calculated penetrating depth where the root density declines from a calculated value at the penetrating depth to zero, i.e. : r is α, a parameter in calculating critical %N in W (Eq.…”

Section: Plant Growthmentioning

confidence: 99%

Development and critical evaluation of a generic 2-D agro-hydrological model (SMCR_N) for the responses of crop yield and nitrogen composition to nitrogen fertilizer

Zhang

Yang

Greenwood

et al. 2009

Agriculture, Ecosystems & Environment

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“…Root biomass distribution is commonly modeled assuming an exponential decrease of root biomass with depth (Gerwitz and Page, 1974). However, data for root biomass measured…”

Section: Vegetationmentioning

confidence: 99%

Differential long-term effects of climate change and management on stocks and distribution of soil organic carbon in productive grasslands

et al. 2012

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Abstract.We studied the impact of climate change on the dynamics of soil organic carbon (SOC) stocks in productive grassland systems undergoing two types of management, an intensive type with frequent harvests and fertilizer applications and an extensive system without fertilization and fewer harvests. Simulations were conducted with a dedicated newly developed model, the Oensingen Grassland Model. It was calibrated using measurements taken in a recently established permanent sward in Central Switzerland, and run to simulate SOC dynamics over 2001-2100 under various climate change scenarios assuming different elements of IPCC A2 emission scenarios. We found that: (1) management intensity dominates SOC until approximately 20 years after grassland establishment. Differences in SOC between climate scenarios become significant after 20 years and climate effects dominate SOC dynamics from approximately 50 years after establishment. (2) Carbon supplied through manure contributes about 60 % to measured organic C increase in fertilized grassland. (3) Soil C accumulates particularly in the top 10 cm of the soil until 5 years after establishment. In the long-term, C accumulation takes place in the top 15 cm of the soil profile, while C content decreases below this depth. The transitional depth between gains and losses of C mainly depends on the vertical distribution of root senescence and root biomass. We discuss the importance of previous land use on carbon sequestration potentials that are much lower at the Oensingen site under ley-arable rotation with much higher SOC stocks than most soils under arable crops. We further discuss the importance of biomass senescence rates, because C balance estimations indicate that these may differ considerably between the two management systems.

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“…Several mathematical models of root growth have been developed over the last 30 years. The simplest models (Gerwitz and Page, 1974;Stone and Taylor, 1983) simulated only rooting depth. A more complex generation of models simulated a root system exploring the soil in two separated processes: downward penetration of the vertical axis and horizontal proliferation of roots into individual layers (Ritchie et al, 1985;Andrew, 1987;Jones et al, 1991;Robertson et al, 1993).…”

Section: Introductionmentioning

confidence: 99%

Modeling root growth and the soil–plant–atmosphere continuum of cotton crops

Coelho

Villalobos

Mateos

2003

Agricultural Water Management

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A simple and functional model to simulate cotton root growth is coupled to models of water balance and leaf water potential to predict the behavior of the soil-plant-atmosphere continuum (SPAC) of cotton crops. The root-growth model takes into account the dry matter partitioning to roots, root depth increase as a function of thermal time, soil mechanical resistance and soil water stress, and allows the inclusion of spatial variability of soil physical properties. The water balance model uses a cascade approach to simulate drainage while soil and plant evaporation are calculated separately following the model of Ritchie. The leaf water potential model (LWPM) is based on Ohm's Law analogy, where water flow resistance to the roots is calculated using an empirical equation and the resistance within the plant is calculated as a function of a threshold leaf water potential. The model simulated correctly the soil resistance and the temporal and spatial distribution of roots in the soil profile. The model simulated total soil water content and midday leaf water potential well, even when a compacted soil layer was present, but the agreement to observed data was poor for the vertical distribution of soil water content, mainly in the zone of greatest root concentration. #

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An Empirical Mathematical Model to Describe Plant Root Systems

Cited by 299 publications

References 14 publications

Development and critical evaluation of a generic 2-D agro-hydrological model (SMCR_N) for the responses of crop yield and nitrogen composition to nitrogen fertilizer

Development and critical evaluation of a generic 2-D agro-hydrological model (SMCR_N) for the responses of crop yield and nitrogen composition to nitrogen fertilizer

Differential long-term effects of climate change and management on stocks and distribution of soil organic carbon in productive grasslands

Modeling root growth and the soil–plant–atmosphere continuum of cotton crops

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