A Calibration Equation Between Δ 48 Values of Carbonate and Temperature

Chlorophyll-a measurements are an important factor in the water quality monitoring of surface waters, especially for determining the trophic status and ecosystem management. However, a collection of field samples for extractive analysis in a laboratory may not fully represent the field conditions. Handheld fluorometers that can measure chlorophyll-a in situ are available, but their performance in waters with a variety of potential light-interfering substances has not yet been tested. We tested a handheld fluorometer for sensitivity to ambient light and turbidity and compared these findings with EPA Method 445.0 using water samples obtained from two urban lakes in Tucson, Arizona, USA. Our results suggested that the probe was not sensitive to ambient light and performed well at low chlorophyll-a concentrations (<25 µg/L) across a range of turbidity levels (50–70 NTU). However, the performance was lower when the chlorophyll-a concentrations were >25 µg/L and turbidity levels were <50 NTU. To account for this discrepancy, we developed a calibration equation to use for this handheld fluorometer when field monitoring for potential harmful algal blooms in water bodies.

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In vivo calibration of the T2* cardiovascular magnetic resonance method at 1.5 T for estimation of cardiac iron in a minipig model of transfusional iron overload

Journal of Cardiovascular Magnetic Resonance ◽

10.1186/s12968-021-00715-6 ◽

2021 ◽

Vol 23 (1) ◽

Author(s):

Peter Diedrich Jensen ◽

Asbjørn Haaning Nielsen ◽

Carsten Wiberg Simonsen ◽

Ulrik Thorngren Baandrup ◽

Svend Eggert Jensen ◽

...

Keyword(s):

Rank Correlation ◽

Calibration Data ◽

Iron Loading ◽

Spearman Rank Correlation ◽

Calibration Equation ◽

Spearman Rank ◽

Cardiac Iron ◽

In Vivo Calibration ◽

Spearman Rank Correlation Coefficient

Abstract Background Non-invasive estimation of the cardiac iron concentration (CIC) by T2* cardiovascular magnetic resonance (CMR) has been validated repeatedly and is in widespread clinical use. However, calibration data are limited, and mostly from post-mortem studies. In the present study, we performed an in vivo calibration in a dextran-iron loaded minipig model. Methods R2* (= 1/T2*) was assessed in vivo by 1.5 T CMR in the cardiac septum. Chemical CIC was assessed by inductively coupled plasma-optical emission spectroscopy in endomyocardial catheter biopsies (EMBs) from cardiac septum taken during follow up of 11 minipigs on dextran-iron loading, and also in full-wall biopsies from cardiac septum, taken post-mortem in another 16 minipigs, after completed iron loading. Results A strong correlation could be demonstrated between chemical CIC in 55 EMBs and parallel cardiac T2* (Spearman rank correlation coefficient 0.72, P < 0.001). Regression analysis led to [CIC] = (R2* − 17.16)/41.12 for the calibration equation with CIC in mg/g dry weight and R2* in Hz. An even stronger correlation was found, when chemical CIC was measured by full-wall biopsies from cardiac septum, taken immediately after euthanasia, in connection with the last CMR session after finished iron loading (Spearman rank correlation coefficient 0.95 (P < 0.001). Regression analysis led to the calibration equation [CIC] = (R2* − 17.2)/31.8. Conclusions Calibration of cardiac T2* by EMBs is possible in the minipig model but is less accurate than by full-wall biopsies. Likely explanations are sampling error, variable content of non-iron containing tissue and smaller biopsies, when using catheter biopsies. The results further validate the CMR T2* technique for estimation of cardiac iron in conditions with iron overload and add to the limited calibration data published earlier.

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A Portable Smartphone-Based Sensing System Using a 3D-Printed Chip for On-Site Biochemical Assays

Sensors ◽

10.3390/s18114002 ◽

2018 ◽

Vol 18 (11) ◽

pp. 4002 ◽

Cited By ~ 2

Author(s):

Feiyi Wu ◽

Min Wang

Keyword(s):

Organophosphorus Pesticides ◽

Smartphone Apps ◽

Color Channel ◽

Calibration Equation ◽

Sensing System ◽

Biochemical Sensing ◽

Biochemical Assays ◽

Target Analytes ◽

New Strategy ◽

3D Printed

Recently, smartphone-based chromogenic sensing with paper-based microfluidic technology has played an increasingly important role in biochemical assays. However, generally there were three defects: (i) the paper-based chips still required complicated fabrication, and the hydrophobic boundaries on the chips were not clear enough; (ii) the chromogenic signals could not be steadily captured; (iii) the smartphone apps were restricted to the detection of specific target analytes and could not be extended for different assays unless reprogrammed. To solve these problems, in this study, a portable smartphone-based sensing system with a 3D-printed chip was developed. A 3D-printed imaging platform was designed to significantly reduce sensing errors generated during signal capture, and a brand-new strategy for signal processing in downloadable apps was established. As a proof-of-concept, the system was applied for detection of organophosphorus pesticides and multi-assay of fruit juice, showing excellent sensing performance. For different target analytes, the most efficient color channel could be selected for signal analysis, and the calibration equation could be directly set in user interface rather than programming environment, thus the developed system could be flexibly extended for other biochemical assays. Consequently, this study provides a novel methodology for smartphone-based biochemical sensing.

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A Simple Testing Procedure for near Infrared Instruments

Journal of Near Infrared Spectroscopy ◽

10.1255/jnirs.188 ◽

1998 ◽

Vol 6 (A) ◽

pp. A163-A170 ◽

Cited By ~ 1

Author(s):

B. Barabás

Keyword(s):

Error Compensation ◽

Near Infrared ◽

Testing Procedure ◽

Wheat Protein ◽

Calibration Equation ◽

Minimum Number ◽

Mean Square Difference ◽

Infrared Instruments ◽

Protein Measurement

The testing and adjusting procedure of near infrared (NIR) spectrophotometers is based on the measurement of some standards and, if necessary, on the adjustment of the constants in the calibration equation. For this work some use few standards, whereas others use 20 or more. This work was aimed to determine the range of error compensation and the minimum number of standards required. The experiments were applied to wheat protein measurement using two scanning spectrophotometers. The errors in the NIR measurements were characterised as bias, skew, error derived from skew ( Eskew) and standard error of difference corrected for bias and skew ( SEDc) parameters and supposed that errors derived from the change in the wavelength or reflectance of the instrument. The confidence intervals of bias and skew, derived from duplicate measurements of various numbers of wheat standards, were used to determine the minimum number of standards required. The range of error compensation was defined with those bias values, where SEDc was smaller, than an acceptable limit. The range of compensation corresponded to a bias value of ± 8 g kg−1 for wheat protein measurements. The detection of error of measurements required 4 wheat standards. The elimination of errors of bias and skew required 9 standards within the above limits. The developed procedure was tested in case of real instrument error. Diminishing a bias from 5.2 g kg−1 to 0.7 g kg−1 and the root mean square difference ( RMSD) to an acceptable level required the use of 9 standards, similar to the model experiment. The simplicity and rapidity (about 10 min) of the procedure enabled the routine test of NIR instruments. The range of error compensation and the number of standards referred to wheat protein. The simple modelling procedure proved also suitable for the determination of these values for other components and under other measuring conditions.

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Features of сalibration еequations for IR scanners in determining the amino acid composition of soy proteins

Вестник ДВО РАН ◽

10.37102/08697698.2020.212.4.021 ◽

2020 ◽

Author(s):

С.Е. НИЗКИЙ ◽

Г.А. КОДИРОВА ◽

Г.В. КУБАНКОВА

Keyword(s):

Amino Acids ◽

Liquid Chromatography ◽

Amino Acid ◽

Amino Acid Composition ◽

Acid Composition ◽

High Performance ◽

Near Infrared ◽

Soybean Proteins ◽

Calibration Equation ◽

Calibration Equations

Из 20 аминокислот, входящих в состав растительных белков, 17 лучше всего определяются с помощью высокоэффективной жидкостной хроматографии. Но эта технология затратна по времени, в том числе из-за подготовки проб, что делает ее малопригодной при проведении массовых анализов, например при оценке селекционного материала. В этом случае наиболее приемлемы технологии, основанные на сканировании в ближнем инфракрасном диапазоне излучения. Несмотря на то что ИК-сканеры способны по одному калибровочному уравнению выявлять большое количество компонентов, необходима постоянная коррекция при определении состава аминокислот и приведении его в процентное соотношение. В статье рассматриваются варианты создания калибровочных уравнений для расчета аминокислотного состава белков сои с помощью компьютерных программ (Nir 42, ISI), обеспечивающих работу ИК-сканеров типа NIR-4250 или FOSS NIRSystem 5000. Установлено, что при создании калибровочных уравнений содержание каждой аминокислоты наиболее корректно выражать в абсолютных единицах (г на 100 г белка), а не относительных (%). 17 of the 20 amino acids, included in the composition of plant proteins, are most effectively determined using liquid chromatography. The technology of high-performance liquid chromatography is to a certain extent costly in time, among other things because of sample preparation that makes it unsuitable for mass analysis, for example, when evaluating a breeding material. In this case, the technology based on scanning in the near infrared radiation band are the most acceptable. Despite the fact that IR scanners are able to determine a sufficiently large number of components on the basis of one calibration equation, a constant correction is required when determining the composition of amino acids and reducing it to a percentage ratio. The options for creating calibration equations for determining the amino acid composition of soybean proteins for computer programs (Nir 42, ISI), which provide the operation of IR scanners, such as NIR-4250 or FOSS NIRSystem 5000 are considered in the article. It was found that when creating calibration equations, it is most correct to set for each amino acid its mass content (g per 100 g of protein), and not the relative portion (in %).

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Field Calibration of TDR to Assess the Soil Moisture of Drained Peatland Surface Layers

Water ◽

10.3390/w10121842 ◽

2018 ◽

Vol 10 (12) ◽

pp. 1842 ◽

Cited By ~ 2

Author(s):

Tomasz Gnatowski ◽

Jan Szatyłowicz ◽

Bogumiła Pawluśkiewicz ◽

Ryszard Oleszczuk ◽

Maria Janicka ◽

...

Keyword(s):

Dielectric Constant ◽

Soil Moisture ◽

Moisture Content ◽

Soil Moisture Content ◽

Mean Squared Error ◽

Time Domain Reflectometry ◽

Calibration Model ◽

Surface Layers ◽

Calibration Equation ◽

North East

The proper monitoring of soil moisture content is important to understand water-related processes in peatland ecosystems. Time domain reflectometry (TDR) is a popular method used for soil moisture content measurements, the applicability of which is still challenging in field studies due to requirements regarding the calibration curve which converts the dielectric constant into the soil moisture content. The main objective of this study was to develop a general calibration equation for the TDR method based on simultaneous field measurements of the dielectric constant and gravimetric water content in the surface layers of degraded peatlands. Data were collected during field campaigns conducted temporarily between the years 2006 and 2016 at the drained peatland Kuwasy located in the north-east area of Poland. Based on the data analysis, a two-slopes linear calibration equation was developed as a general broken-line model (GBLM). A site-specific calibration model (SSM-D) for the TDR method was obtained in the form of a two-slopes equation describing the relationship between the soil moisture content and the dielectric constant and introducing the bioindices as covariates relating to plant species biodiversity and the state of the habitats. The root mean squared error for the GBLM and SSM-D models were equal, respectively, at 0.04 and 0.035 cm3 cm−3.

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The physics of radiochromic process: one calibration equation for all film types

Journal of Instrumentation ◽

10.1088/1748-0221/14/08/p08006 ◽

2019 ◽

Vol 14 (08) ◽

pp. P08006-P08006 ◽

Cited By ~ 1

Author(s):

P. Casolaro ◽

L. Campajola ◽

F. Di Capua

Keyword(s):

Calibration Equation

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Using stable isotopes to estimate migratory connectivity for a patchily distributed, wetland-associated Neotropical migrant

The Condor ◽

10.1093/condor/duz052 ◽

2019 ◽

Vol 121 (4) ◽

Cited By ~ 2

Author(s):

Jessie Reese ◽

Catherine Viverette ◽

Christopher M Tonra ◽

Nicholas J Bayly ◽

Than J Boves ◽

...

Keyword(s):

Hydrogen Isotope ◽

Isotope Analysis ◽

Distribution Model ◽

Migratory Connectivity ◽

Calibration Equation ◽

Abundance Data ◽

Assignment Model ◽

Breeding Distribution ◽

Stable Hydrogen Isotope ◽

Species Specific

Abstract Estimates of migratory connectivity are needed for full annual cycle population models of migratory bird species experiencing rapid declines in abundance. One technique to determine migratory connectivity is through stable isotope analysis. This low-resolution method may be influenced by how data are calibrated between isotopes measured in precipitation and those measured in feathers, and can be informed by incorporating relative abundance into the assignment model. eBird abundance maps are a new tool combining citizen science data into a predictive species distribution model. In the Prothonotary Warbler (Protonotaria citrea), a wetland-associated songbird with a patchy breeding distribution, we sought to use stable-hydrogen isotope analysis informed by a species-specific calibration equation and eBird abundance data to determine the strength of migratory connectivity. We developed a species-specific calibration equation using known-origin samples from the breeding grounds and found that stable-hydrogen isotope values measured in precipitation explained 50% of the variation in stable-hydrogen isotope values among feathers. We found that the assignment model incorporating eBird abundance data correctly identified the true origins of 66% of individuals, and that the average assignment area (as a measure of precision) was 64% of the breeding distribution. These results represented a 7% increase in precision and a 3% decrease in accuracy when compared to a model that was not informed by abundance. Based on these models, wintering populations from 6 countries represented a mix of likely breeding origins, suggesting low migratory connectivity for Prothonotary Warblers. We found evidence that wintering latitude was related to likely breeding origin, with individuals at western wintering locations more likely to have southern breeding origins, but this relationship was weak. These results corroborate studies using archival light-level geolocators and high-resolution genetic markers, which also demonstrated weak migratory connectivity in this species. For patchily distributed species, eBird abundance data may not provide a useful increase in precision and accuracy for isotope assignments.

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Fast prediction of quality parameters in whole seeds of oilseed rape (Brassica napus L.)

Plant Soil and Environment ◽

10.17221/4104-pse ◽

2011 ◽

Vol 49 (No. 4) ◽

pp. 141-145 ◽

Cited By ~ 27

Author(s):

V. Míka ◽

P. Tillmann ◽

R. Koprna ◽

P. Nerušil ◽

V. Kučera

Keyword(s):

Prediction Accuracy ◽

Near Infrared ◽

Quality Parameters ◽

Breeding Cycle ◽

Brassica Napus L ◽

Calibration Equation ◽

Whole Seed ◽

Fast Prediction ◽

Short Time ◽

Non Destructive

A calibration equation for NIRSystems 6500 instrument was derived at VSTE Jevíčko using the measurement of broad collection of Czech samples of winter rape, allowing sufficiently accurate prediction of content of dry matter (DM), crude protein (XP), crude fat (XL), glucosinolates (GSL), oleic and linoleic acids in an extremely short time. The prediction accuracy was verified on a validation file (n = 60). The coefficients of determinance (R2) were 0.83 for XP, 0.71 for XL, and 0.84 for GSL. The prediction accuracy according to the VSTE equation was compared to the prediction accuracy according to the VDLUFA calibration equation (Kassel, FRG) used in EU near infrared spectroscopy network. It was stated that the former was not distinctly worse. Non-destructive NIR-analysis of the whole seed also allows sowing selected seeds in the year of harvest and thus accelerates the breeding cycle.

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Feasibility of Determination of Foodborne Microbe Contamination of Fresh-Cut Shredded Cabbage Using SW-NIR

AgriEngineering ◽

10.3390/agriengineering1020018 ◽

2019 ◽

Vol 1 (2) ◽

pp. 246-256

Author(s):

Benjamaporn Matulaprungsan ◽

Chalermchai Wongs-Aree ◽

Pathompong Penchaiya ◽

Phonkrit Maniwara ◽

Sirichai Kanlayanarat ◽

...

Keyword(s):

Quantitative Measurement ◽

Partial Least Squares Regression ◽

Near Infrared ◽

Nir Spectroscopy ◽

Sample Type ◽

Least Squares Regression ◽

Calibration Equation ◽

E Coli ◽

Total Bacteria

Shredded cabbage is widely used in much ready-to-eat food. Therefore, rapid methods for detecting and monitoring the contamination of foodborne microbes is essential. Short wavelength near infrared (SW-NIR) spectroscopy was applied on two types of solutions, a drained solution from the outer surface of the shredded cabbage (SC) and a ground solution of shredded cabbage (GC) which were inoculated with a mixture of two bacterial suspensions, Escherichia coli and Salmonella typhimurium. NIR spectra of around 700 to 1100 nm were collected from the samples after 0, 4, and 8 h at 37 °C incubation, along with the growth of total bacteria, E. coli and S. typhimurium. The raw spectra were obtained from both sample types, clearly separated with the increase of incubation time. The first derivative, a Savitzky–Golay pretreatment, was applied on the GC spectra, while the second derivative was applied on the SC spectra before developing the calibration equation, using partial least squares regression (PLS). The obtained correlation (r) of the SC spectra was higher than the GC spectra, while the standard error of cross-validation (SECV) was lower. The ratio of prediction of deviation (RPD) of the SC spectra was higher than the GC spectra, especially in total bacteria, quite normal for the E. coli but relatively low for the S. typhimurium. The prediction results of microbial spoilage were more reliable on the SC than on the GC spectra. Total bacterial detection was best for quantitative measurement, as E. coli contamination could only be distinguished between high and low values. Conversely, S. typhimurium predictions were not optimal for either sample type. The SW-NIR shows the feasibility for detecting the existence of microbes in the solution obtained from SC, but for a more specific application for discrimination or quantitation is needed, proving further research in still required.

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