Topic

# Detection limit

About: Detection limit is a(n) research topic. Over the lifetime, 34379 publication(s) have been published within this topic receiving 644817 citation(s). The topic is also known as: limit of detection & lower detection limit.

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TL;DR: The presented review provides information relating to the calculation of the limit of detection and limit of quantitation.

Abstract: The quality of an analytical method developed is always appraised in terms of suitability for its intended purpose, recovery, requirement for standardization, sensitivity, analyte stability, ease of analysis, skill subset required, time and cost in that order. It is highly imperative to establish through a systematic process that the analytical method under question is acceptable for its intended purpose. Limit of detection (LOD) and limit of quantification (LOQ) are two important performance characteristics in method validation. LOD and LOQ are terms used to describe the smallest concentration of an analyte that can be reliably measured by an analytical procedure. There has often been a lack of agreement within the clinical laboratory field as to the terminology best suited to describe this parameter. Likewise, there have been various methods for estimating it. The presented review provides information relating to the calculation of the limit of detection and limit of quantitation. Brief information about differences in various regulatory agencies about these parameters is also presented here.

1,687 citations

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01 Aug 2008

TL;DR: The Limit of Blank, Limit of Detection, and Limit of Quantitation are terms used to describe the smallest concentration of a measurand that can be reliably measured by an analytical procedure.

Abstract: * Limit of Blank (LoB), Limit of Detection (LoD), and Limit of Quantitation (LoQ) are terms used to describe the smallest concentration of a measurand that can be reliably measured by an analytical procedure. * LoB is the highest apparent analyte concentration expected to be found when replicates of a blank sample containing no analyte are tested. LoB = mean(blank) + 1.645(SD(blank)). * LoD is the lowest analyte concentration likely to be reliably distinguished from the LoB and at which detection is feasible. LoD is determined by utilising both the measured LoB and test replicates of a sample known to contain a low concentration of analyte. * LoD = LoB + 1.645(SD (low concentration sample)). * LoQ is the lowest concentration at which the analyte can not only be reliably detected but at which some predefined goals for bias and imprecision are met. The LoQ may be equivalent to the LoD or it could be at a much higher concentration.

1,326 citations

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TL;DR: The confidence limit of the method here termed EMD/HSA (for empirical mode decomposition/Hilbert spectral analysis) is introduced by using various adjustable stopping criteria in the sifting processes of the EMD step to generate a sample set of intrinsic mode functions (IMFs) as mentioned in this paper.

Abstract: The confidence limit is a standard measure of the accuracy of the result in any statistical analysis. Most of the confidence limits are derived as follows. The data are first divided into subsections and then, under the ergodic assumption, the temporal mean is substituted for the ensemble mean. Next, the confidence limit is defined as a range of standard deviations from this mean. However, such a confidence limit is valid only for linear and stationary processes. Furthermore, in order for the ergodic assumption to be valid, the subsections have to be statistically independent. For non‐stationary and nonlinear processes, such an analysis is no longer valid. The confidence limit of the method here termed EMD/HSA (for empirical mode decomposition/Hilbert spectral analysis) is introduced by using various adjustable stopping criteria in the sifting processes of the EMD step to generate a sample set of intrinsic mode functions (IMFs). The EMD technique acts as a pre‐processor for HSA on the original data, producing a set of components (IMFs) from the original data that equal the original data when added back together. Each IMF represents a scale in the data, from smallest to largest. The ensemble mean and standard deviation of the IMF sample sets obtained with different stopping criteria are calculated, and these form a simple random sample set. The confidence limit for EMD/HSA is then defined as a range of standard deviations from the ensemble mean. Without evoking the ergodic assumption, subdivision of the data stream into short sections is unnecessary; hence, the results and the confidence limit retain the full‐frequency resolution of the full dataset. This new confidence limit can be applied to the analysis of nonlinear and non‐stationary processes by these new techniques. Data from length‐of‐day measurements and a particularly violent recent earthquake are used to demonstrate how the confidence limit is obtained and applied. By providing a confidence limit for this new approach, a stable range of stopping criteria for the decomposition or sifting phase (EMD) has been established, making the results of the final processing with HSA, and the entire EMD/HSA method, more definitive.

1,099 citations

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TL;DR: It is demonstrated that this facile methodology can offer a rapid, reliable, and selective detection of Cu(2+) with a detection limit as low as 6 nM and a dynamic range from 10 to 1100 nM.

Abstract: A novel sensing system has been designed for Cu2+ ion detection based on the quenched fluorescence (FL) signal of branched poly(ethylenimine) (BPEI)-functionalized carbon quantum dots (CQDs) Cu2+ ions can be captured by the amino groups of the BPEI-CQDs to form an absorbent complex at the surface of CQDs, resulting in a strong quenching of the CQDs’ FL via an inner filter effect Herein, we have demonstrated that this facile methodology can offer a rapid, reliable, and selective detection of Cu2+ with a detection limit as low as 6 nM and a dynamic range from 10 to 1100 nM Furthermore, the detection results for Cu2+ ions in a river water sample obtained by this sensing system agreed well with that by inductively couple plasma mass spectrometry, suggesting the potential application of this sensing system

776 citations

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TL;DR: In this paper, the concentration of hydrogen peroxide (H2O2) in distilled water, drinking water and in different types of surface and rain waters can be easily determined by a photometric method in which N,N-diethyl-p-phenylenediamine (DPD) is oxidized by a peroxidase catalyzed reaction.

Abstract: The concentration of hydrogen peroxide (H2O2) in distilled water, drinking water and in different types of surface and rain waters can be easily determined by a photometric method in which N,N-diethyl-p-phenylenediamine (DPD) is oxidized by a peroxidase catalyzed reaction. DPD is available as a commercial reagent. In all waters its oxidation occurs with a stoichiometric factor of 2.0 and leads to an absorbance (at 551 nm) of 21,000 ± 500 M−1cm−1 per H2O2. In the presence of other hydroperoxides H2O2 can be determined by comparison with a blank in which the H2O2 is destroyed with sulfite, and the sulfite residual masked with formaldehyde. The detection limit is 0.2 μg l−1 in distilled water and about 0.3 μg l−1 in most types of natural waters when 10 cm cells and a spectrophometer are used. We consider the DPD method to be a candidate for a standard method for drinking water analysis because it is easy to perform and to calibrate for absolute determinations.

728 citations