The deficiency of the ?economic optimum? application for evaluating models which predict crop yield response to nitrogen fertiliser

Sutherland, R. A.; Wright, C. P. M.; Verstraeten, L. M. J.; Greenwood, D. J.

doi:10.1007/bf01049355

Cited by 10 publications

(6 citation statements)

References 8 publications

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“…This kind of rational function is usually applied in modeling crop yield responses to nitrogen fertilizer [114] and milk yield lactation curves from dairy cattle [115]. Lineshape readout scheme for spin probed HSA samples and the pH-dependent Iabf parameter.…”

Section: Monitoring Global Spectral Changes From Cw Epr Spectra Ofmentioning

confidence: 99%

“…The results from analyses on I abf curves are explicitly discussed in Supplementary Material S5 (see also Table 2). Counterintuitively, it was found that the asymmetric minimum features between about 3 < pH < 6, as well as from about 9 < pH < 12, can be determined by an appropriate Nelder model function [113]: This kind of rational function is usually applied in modeling crop yield responses to nitrogen fertilizer [114] and milk yield lactation curves from dairy cattle [115].…”

Section: 31mentioning

confidence: 99%

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Exploring the pH-Induced Functional Phase Space of Human Serum Albumin by EPR Spectroscopy

et al. 2018

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A systematic study on the self-assembled solution system of human serum albumin (HSA) and paramagnetic doxyl stearic acid (5-DSA and 16-DSA) ligands is reported covering the broad pH range 0.7–12.9, mainly using electron paramagnetic resonance (EPR) methods. It is tested to which extent the pH-induced conformational isomers of HSA reveal themselves in continuous wave (CW) EPR spectra from this spin probing approach in comparison to an established spin-labeling strategy utilizing 3-maleimido proxyl (5-MSL). Most analyses are conducted on empirical levels with robust strategies that allow for the detection of dynamic changes of ligand, as well as protein. Special emphasis has been placed on the EPR spectroscopic detection of a molten globule (MG) state of HSA that is typically found by the fluorescent probe 8-Anilino- naphthalene-1-sulfonic acid (ANS). Moreover, four-pulse double electron-electron resonance (DEER) experiments are conducted and substantiated with dynamic light scattering (DLS) data to determine changes in the solution shape of HSA with pH. All results are ultimately combined in a detailed scheme that describes the pH-induced functional phase space of HSA.

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Section: Monitoring Global Spectral Changes From Cw Epr Spectra Ofmentioning

confidence: 99%

Section: 31mentioning

confidence: 99%

Exploring the pH-Induced Functional Phase Space of Human Serum Albumin by EPR Spectroscopy

et al. 2018

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“…In any case, this paper is about the validation of a subsoil model, RothPC‐1. A t ‐test (as used by Sutherland et al , 1986) was applied separately to each of the three layers. The Mean Sum of Squares was calculated for each profile, excluding the 0–23 cm layer.…”

Section: Rothpc‐1: the Subsoil Version Of Rothc‐263mentioning

confidence: 99%

The turnover of organic carbon in subsoils. Part 2. Modelling carbon turnover

Jenkinson¹,

Coleman²

2008

European J Soil Science

215

127

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A new model, RothPC-1, is described for the turnover of organic C in the top metre of soil. RothPC-1 is a version of RothC-26.3, an earlier model for the turnover of C in topsoils. In RothPC-1 two extra parameters are used to model turnover in the top metre of soil: one, p, which moves organic C down the profile by an advective process, and the other, s, which slows decomposition with depth. RothPC-1 is parameterized and tested using measurements (described in Part 1, this issue) of total organic C and radiocarbon on soil profiles from the Rothamsted long-term field experiments, collected over a period of more than 100 years. RothPC-1 gives fits to measurements of organic C and radiocarbon in the 0-23, 23-46, 46-69 and 69-92 cm layers of soil that are almost all within (or close to) measurement error in two areas of regenerating woodland (Geescroft and Broadbalk Wildernesses) and an area of cultivated land from the Broadbalk Continuous Wheat Experiment. The fits to old grassland (the Park Grass Experiment) are less close. Two other sites that provide the requisite pre-and post-bomb data are also fitted; a prairie Chernozem from Russia and an annual grassland from California. Roth-PC-1 gives a close fit to measurements of organic C and radiocarbon down the Chernozem profile, provided that allowance is made for soil age; with the annual grassland the fit is acceptable in the upper part of the profile, but not in the clay-rich Bt horizon below. Calculations suggest that treating the top metre of soil as a homogeneous unit will greatly overestimate the effects of global warming in accelerating the decomposition of soil C and hence on the enhanced release of CO 2 from soil organic matter; more realistic estimates will be obtained from multi-layer models such as RothPC-1.

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“…Poor estimates of a model's success may result if either of the pure error sum of squares or the sum of squares due to lack of fit contains most of the degrees of freedom. If the error term contains most of the degrees of freedom then the model might be tested best by comparing the individual simulations with means of the measurements using a t-test as described by Sutherland et al (1986).…”

Section: Discussionmentioning

confidence: 99%

“…The t-statistic is calculated as where SEis the standard error of the mean measurement, j j , anddis the mean deviation. Sutherland et al (1986) used the t-statistic to assess the closeness of each simulation to a set of replicated measurements. They recorded the size and sign of each deviation and ranked these against the measurements.…”

Section: Introductionmentioning

confidence: 99%

method for assessing the goodness of computer simulation of soil processes

Whitmore

1991

Journal of Soil Science

151

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Any satisfactory computer simulation model of a soil process must match actual behaviour in the laboratory or field; a model can be evaluated by how well it does so. This paper describes a method for assessing models using anion diffusion and nitrate leaching as examples. The method partitions the sum of squares of the differences between measurement and simulation into two components, one calculated from the differences between the simulation and the mean of replicate measurements (the 'lack of fit'), and the other calculated from the variance within each set of replicate measurements (the 'pure error'). If the former is not significantly larger than the latter than the data present no grounds for rejecting the model. Where a model simulates the change in a process with time the method can also take account of how experimental error in the initial measurements affects the goodness of fit of the simulation of subsequent measurements.The method is particularly valuable where it is difficult or costly to take many replicate measurements, such as often happens in soil science or agriculture; nonetheless, some replicates must be taken.

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The deficiency of the ?economic optimum? application for evaluating models which predict crop yield response to nitrogen fertiliser

Cited by 10 publications

References 8 publications

Exploring the pH-Induced Functional Phase Space of Human Serum Albumin by EPR Spectroscopy

Exploring the pH-Induced Functional Phase Space of Human Serum Albumin by EPR Spectroscopy

The turnover of organic carbon in subsoils. Part 2. Modelling carbon turnover

method for assessing the goodness of computer simulation of soil processes

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