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Comparison of soil analytical methods for estimating wheat potassium fertilizer requirements in response to contrasting plant K demand in the glasshouse

Overview of attention for article published in Scientific Reports, September 2017
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Title
Comparison of soil analytical methods for estimating wheat potassium fertilizer requirements in response to contrasting plant K demand in the glasshouse
Published in
Scientific Reports, September 2017
DOI 10.1038/s41598-017-11681-4
Pubmed ID
Authors

Yulin Zhang, Gunasekhar Nachimuthu, Sean Mason, Michael J. McLaughlin, Ann McNeill, Michael J. Bell

Abstract

The traditional soil potassium (K) testing methods fail to accurately predict K requirement by plants. The Diffusive Gradients in Thin-films (DGT) method is promising, but the relationship between the DGT-measured K pool and plant available K is not clear. Wheat (Triticum aestivum L., cv. Frame) was grown in 9 Australian broad acre agricultural soils in a glasshouse trial until the end of tillering growth stage (GS30) with different plant K demands generated by varying plant numbers and pot sizes. Different K concentrations in soils were varied by 4 rates of K fertilizer application. The relative dry matter and K uptake were plotted against the soil K test value (CaCl2, Colwell and NH4OAc and DGT K measurements). To obtain 90% of maximum relative dry matter at low root density (closest to field conditions), the critical value of the NH4OAc K method was 91 (R(2) = 0.56) mg kg(-1). The DGT K method was not able to accurately predict relative dry matter or K uptake due to a weak extraction force for K from soils with high CEC values. Further endeavor on increasing K extraction force of the DGT method is warranted to obtain accurate plant available K results.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 18%
Student > Doctoral Student 4 12%
Student > Master 4 12%
Student > Ph. D. Student 4 12%
Lecturer 3 9%
Other 7 21%
Unknown 5 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 55%
Environmental Science 3 9%
Biochemistry, Genetics and Molecular Biology 1 3%
Computer Science 1 3%
Physics and Astronomy 1 3%
Other 3 9%
Unknown 6 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 September 2017.
All research outputs
#20,447,499
of 23,002,898 outputs
Outputs from Scientific Reports
#106,195
of 124,203 outputs
Outputs of similar age
#276,066
of 316,004 outputs
Outputs of similar age from Scientific Reports
#4,558
of 5,548 outputs
Altmetric has tracked 23,002,898 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 124,203 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.3. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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