Phosphorus intensity determines short-term P uptake by pigeon pea (Cajanus cajan L.) grown in soils with differing P buffering capacity

Pypers, Pieter; Delrue, Josefien; Diels, Jan; Smolders, Erik; Merckx, Roel

doi:10.1007/s11104-006-0051-y

Cited by 23 publications

(15 citation statements)

References 23 publications

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“…The calculated relative yield after 14 days of growth was plotted against total (labile) P concentrations in soil, soil solution concentrations or DGT-measured concentrations (estimated with the DIFS model). These theoretical curves are in good agreement with the experimental results of Pypers et al [94] who measured P uptake and growth of pigeon pea in response to P fertilisation in soils with different P sorption characteristics. They observed a 50% yield reduction at a soil solution concentration of ∼10 µM in strongly buffered soil and at ∼30 µM in weakly buffered soil.…”

Section: Dgt For Nutrient Deficiency Studiessupporting

confidence: 90%

“…15 shows theoretical relationships between nutrient supply and plant growth for phosphorus. The plant uptake flux was calculated for different P concentrations and different realistic buffer capacities [94] (K d of 10, 100 or 1000 L kg −1 ) with the NST model. The RGR was calculated from the calculated uptake flux and the critical plant concentrations (Eqn 14).…”

Section: Dgt For Nutrient Deficiency Studiesmentioning

confidence: 99%

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Predicting availability of mineral elements to plants with the DGT technique: a review of experimental data and interpretation by modelling

et al. 2009

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Environmental context. Total concentrations of mineral elements in soil bear little relation to their availability for plants. The DGT (diffusive gradients in thin-films) technique has been found to be a good predictor of trace metal uptake and P deficiency, though not consistently in all studies for all elements. This review examines the fundamental basis for the relation between DGT fluxes and plant uptake and assesses under which conditions this relation may break down.Abstract. In the DGT technique, elements are accumulated on a binding gel after their diffusive transport through a hydrogel. In this paper, we explore in more detail why -and under which conditions -DGT correlates with plant uptake. The theoretical considerations are illustrated with experimental results for metal uptake and toxicity, and for phosphorus deficiency. Strong correlations between DGT and plant uptake are predicted if the diffusive transport of the element from soil to the plant roots is rate-limiting for its uptake. If uptake is not limited by diffusive transport, DGT-fluxes and plant uptake may still correlate provided that plant uptake is not saturated. However, competitive cations may affect the plant uptake under these conditions, whereas they have no effect on the DGT flux. Moreover, labile complexes are not expected to contribute to the plant uptake if diffusion is not limiting, but they are measured with DGT. Therefore, if plant uptake is not limited by diffusion, interpretation of the observed correlation in terms of the labile species measured by DGT is inappropriate.

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Section: Dgt For Nutrient Deficiency Studiessupporting

confidence: 90%

Section: Dgt For Nutrient Deficiency Studiesmentioning

confidence: 99%

Predicting availability of mineral elements to plants with the DGT technique: a review of experimental data and interpretation by modelling

et al. 2009

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“…Results from the fertilizer experiments thus confirm that in high P-sorbing soils, such as Ferralsols, additions of P fertilizers may lead to only incremental increases in solution P concentration (Roy et al, 2016). However, this does not necessarily translate to P availability (Pypers et al, 2006). PBC on the field experiments, taken as the slope of P w increase with increasing P budget, was negatively dependent on K m (F = 10.8, p = 0.0047, and R 2 = 0.40; Fig.…”

Section: K M Buffers Fertilizer Application In Long-term Fertilizer Ementioning

confidence: 70%

“…Phosphorus-buffering capacity (PBC) is defined as the ability of soil to moderate changes in the concentration of soil solution P (Pypers et al, 2006;Olsen and Khasawneh, 1980;Beckett and White, 1964). Historically, PBC has been calculated using Eq.…”

Section: Introductionmentioning

confidence: 99%

Soil solution phosphorus turnover: derivation, interpretation, and insights from a global compilation of isotope exchange kinetic studies

et al. 2018

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Abstract. The exchange rate of inorganic phosphorus (P) between the soil solution and solid phase, also known as soil solution P turnover, is essential for describing the kinetics of bioavailable P. While soil solution P turnover (K m ) can be determined by tracing radioisotopes in a soil-solution system, few studies have done so. We believe that this is due to a lack of understanding on how to derive K m from isotopic exchange kinetic (IEK) experiments, a common form of radioisotope dilution study. Here, we provide a derivation of calculating K m using parameters obtained from IEK experiments. We then calculated K m for 217 soils from published IEK experiments in terrestrial ecosystems, and also that of 18 long-term P fertilizer field experiments. Analysis of the global compilation data set revealed a negative relationship between concentrations of soil solution P and K m . Furthermore, K m buffered isotopically exchangeable P in soils with low concentrations of soil solution P. This finding was supported by an analysis of long-term P fertilizer field experiments, which revealed a negative relationship between K m and phosphate-buffering capacity. Our study highlights the importance of calculating K m for understanding the kinetics of P between the soil solid and solution phases where it is bioavailable. We argue that our derivation can also be used to calculate soil solution turnover of other environmentally relevant and strongly sorbing elements that can be traced with radioisotopes, such as zinc, cadmium, nickel, arsenic, and uranium.

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“…As a transient model utilizing a numerical solution, NST 3.0 has been used widely to predict uptake of nutrients by various crop species (Sadana and Claassen 2000;Pypers et al 2006). However, no studies on woody species utilizing this model have been conducted.…”

Section: Current Study On Nst 30 Ssand and Pcatsmentioning

confidence: 99%

Nutrient uptake estimates for woody species as described by the NST 3.0, SSAND, and PCATS mechanistic nutrient uptake models

Lin

Kelly

2010

Plant Soil

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With the advent of the personal computer, mechanistic nutrient uptake models have become widely used as research and teaching tools in plant and soil science. Three models NST 3.0, SSAND, and PCATS have evolved to represent the current state of the art. There are two major categories of mechanistic models, transient state models with numerical solutions and steady state models. NST 3.0 belongs to the former model type, while SSAND and PCATS belong to the latter. NST 3.0 has been used extensively in crop research but has not been used with woody species. Only a few studies using SSAND and PCATS are available. To better understand the similarities and differences of these three models, it would be useful to compare model predictions with experimental observations using multiple datasets from the literature to represent various situations for woody species. Therefore, the objectives of this study are to: (i) compare the predictions of uptake by the NST 3.0, SSAND, and PCATS models for a suite of nutrients against experimentally measured values, (ii) compare the behavior of the three models using a one dimensional sensitivity analysis; and (iii) compare and contrast the behavior of NST 3.0 and SSAND using a multiple dimensional sensitivity analysis approach. Predictions of nutrient uptake by the three models when run with a common data set were diverse, indicating a need for a reexamination of model structure. The failure of many of the predictions to match observations indicates the need for further studies which produce representative datasets so that the predictive accuracy of each model can be evaluated. Both types of sensitivity analyses suggest that the effect of soil moisture on simulation can be influential when nutrient concentration in the soil solution (C Li ) is low. One dimensional sensitivity analysis also revealed that I max negatively influenced the uptake estimates from the SSAND and PCATS models.Further analysis indicates that this counter intuitive response of I max is probably related to low soil nutrient supply. The predictions of SSAND under low-nutrient-supply scenarios are generally lower than those of NST 3.0. We suspect that both of these results are artifacts of the steady state models and further studies to improve them, such as incorporating important rhizospheric effects, are needed if they are to be used successfully for the longer growth periods and lower soil nutrient supply situations more typical of woody species.iii Acknowledgements

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Phosphorus intensity determines short-term P uptake by pigeon pea (Cajanus cajan L.) grown in soils with differing P buffering capacity

Cited by 23 publications

References 23 publications

Predicting availability of mineral elements to plants with the DGT technique: a review of experimental data and interpretation by modelling

Predicting availability of mineral elements to plants with the DGT technique: a review of experimental data and interpretation by modelling

Soil solution phosphorus turnover: derivation, interpretation, and insights from a global compilation of isotope exchange kinetic studies

Nutrient uptake estimates for woody species as described by the NST 3.0, SSAND, and PCATS mechanistic nutrient uptake models

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