scholarly journals Milk mid-infrared spectra enable prediction of lactation-stage-dependent methane emissions of dairy cattle within routine population-scale milk recording schemes

2016 ◽  
Vol 56 (3) ◽  
pp. 258 ◽  
Author(s):  
Amélie Vanlierde ◽  
Marie-Laure Vanrobays ◽  
Nicolas Gengler ◽  
Pierre Dardenne ◽  
Eric Froidmont ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
High Throughput ◽  
Methane Emissions ◽  
Calibration Coefficient ◽  
Coefficient Of Determination ◽  
Mid Infrared ◽  
First Derivative ◽  
Data Points ◽  
Mir Spectra

Mitigating the proportion of energy intake lost as methane could improve the sustainability and profitability of dairy production. As widespread measurement of methane emissions is precluded by current in vivo methods, the development of an easily measured proxy is desirable. An equation has been developed to predict methane from the mid-infrared (MIR) spectra of milk within routine milk-recording programs. The main goals of this study were to improve the prediction equation for methane emissions from milk MIR spectra and to illustrate its already available usefulness as a high throughput phenotypic screening tool. A total of 532 methane measurements considered as reference data (430 ± 129 g of methane/day) linked with milk MIR spectra were obtained from 165 cows using the SF6 technique. A first derivative was applied to the MIR spectra. Constant (P0), linear (P1) and quadratic (P2) modified Legendre polynomials were computed from each cows stage of lactation (days in milk), at the day of SF6 methane measurement. The calibration model was developed using a modified partial least-squares regression on first derivative MIR data points × P0, first derivative MIR data points × P1, and first derivative MIR data points × P2 as variables. The MIR-predicted methane emissions (g/day) showed a calibration coefficient of determination of 0.74, a cross-validation coefficient of determination of 0.70 and a standard error of calibration of 66 g/day. When applied to milk MIR spectra recorded in the Walloon Region of Belgium (≈2 000 000 records), this equation was useful to study lactational, annual, seasonal, and regional methane emissions. We conclude that milk MIR spectra has potential to be used to conduct high throughput screening of lactating dairy cattle for methane emissions. The data generated enable monitoring of methane emissions and production characteristics across and within herds. Milk MIR spectra could now be used for widespread screening of dairy herds in order to develop management and genetic selection tools to reduce methane emissions.

Determination of actual polymorphisms responsible for economic trait variation in dairy cattle

2015 ◽  
Author(s):  
Joel I. Weller ◽  
Derek M. Bickhart ◽  
Micha Ron ◽  
Eyal Seroussi ◽  
George Liu ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
Quantitative Trait ◽  
Chromosomal Segment ◽  
Coefficient Of Determination ◽  
Causative Mutation ◽  
A Posteriori ◽  
Chromosome 20 ◽  
The U.S ◽  
Holstein Population

The project’s general objectives were to determine specific polymorphisms at the DNA level responsible for observed quantitative trait loci (QTLs) and to estimate their effects, frequencies, and selection potential in the Holstein dairy cattle breed. The specific objectives were to (1) localize the causative polymorphisms to small chromosomal segments based on analysis of 52 U.S. Holstein bulls each with at least 100 sons with high-reliability genetic evaluations using the a posteriori granddaughter design; (2) sequence the complete genomes of at least 40 of those bulls to 20 coverage; (3) determine causative polymorphisms based on concordance between the bulls’ genotypes for specific polymorphisms and their status for a QTL; (4) validate putative quantitative trait variants by genotyping a sample of Israeli Holstein cows; and (5) perform gene expression analysis using statistical methodologies, including determination of signatures of selection, based on somatic cells of cows that are homozygous for contrasting quantitative trait variants; and (6) analyze genes with putative quantitative trait variants using data mining techniques. Current methods for genomic evaluation are based on population-wide linkage disequilibrium between markers and actual alleles that affect traits of interest. Those methods have approximately doubled the rate of genetic gain for most traits in the U.S. Holstein population. With determination of causative polymorphisms, increasing the accuracy of genomic evaluations should be possible by including those genotypes as fixed effects in the analysis models. Determination of causative polymorphisms should also yield useful information on gene function and genetic architecture of complex traits. Concordance between QTL genotype as determined by the a posteriori granddaughter design and marker genotype was determined for 30 trait-by-chromosomal segment effects that are segregating in the U.S. Holstein population; a probability of <10²⁰ was used to accept the null hypothesis that no segregating gene within the chromosomal segment was affecting the trait. Genotypes for 83 grandsires and 17,217 sons were determined by either complete sequence or imputation for 3,148,506 polymorphisms across the entire genome. Variant sites were identified from previous studies (such as the 1000 Bull Genomes Project) and from DNA sequencing of bulls unique to this project, which is one of the largest marker variant surveys conducted for the Holstein breed of cattle. Effects for stature on chromosome 11, daughter pregnancy rate on chromosome 18, and protein percentage on chromosome 20 met 3 criteria: (1) complete or nearly complete concordance, (2) nominal significance of the polymorphism effect after correction for all other polymorphisms, and (3) marker coefficient of determination >40% of total multiple-regression coefficient of determination for the 30 polymorphisms with highest concordance. The missense polymorphism Phe279Tyr in GHR at 31,909,478 base pairs on chromosome 20 was confirmed as the causative mutation for fat and protein concentration. For effect on fat percentage, 12 additional missensepolymorphisms on chromosome 14 were found that had nearly complete concordance with the suggested causative polymorphism (missense mutation Ala232Glu in DGAT1). The markers used in routine U.S. genomic evaluations were increased from 60,000 to 80,000 by adding markers for known QTLs and markers detected in BARD and other research projects. Objectives 1 and 2 were completely accomplished, and objective 3 was partially accomplished. Because no new clear-cut causative polymorphisms were discovered, objectives 4 through 6 were not completed. 

scholarly journals Development of Attenuated Total Reflectance Mid-Infrared (ATR-MIR) and Near-Infrared (NIR) Spectroscopy for the Determination of Resistant Starch Content in Wheat Grains

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Rong Wang ◽  
Xia Wei ◽  
Hongpan Wang ◽  
Linshu Zhao ◽  
Cengli Zeng ◽  
...  
Keyword(s):  
Resistant Starch ◽  
Near Infrared ◽  
Coefficient Of Determination ◽  
Attenuated Total Reflectance ◽  
Calibration Model ◽  
Mid Infrared ◽  
Total Reflectance ◽  
Mir Spectroscopy ◽  
Calibration Models

The chemical method for the determination of the resistant starch (RS) content in grains is time-consuming and labor intensive. Near-infrared (NIR) and attenuated total reflectance mid-infrared (ATR-MIR) spectroscopy are rapid and nondestructive analytical techniques for determining grain quality. This study was the first report to establish and compare these two spectroscopic techniques for determining the RS content in wheat grains. Calibration models with four preprocessing techniques based on the partial least squares (PLS) algorithm were built. In the NIR technique, the mean normalization + Savitzky–Golay smoothing (MN + SGS) preprocessing technique had a higher coefficient of determination ( R c 2  = 0.672; R p 2  = 0.552) and a relative lower root mean square error value (RMSEC = 0.385; RMSEP = 0.459). In the ATR-MIR technique, the baseline preprocessing method exhibited a better performance regarding to the values of coefficient of determination ( R c 2  = 0.927; R p 2  = 0.828) and mean square error value (RMSEC = 0.153; RMSEP = 0.284). The validation of the developed best NIR and ATR-MIR calibration models showed that the ATR-MIR best calibration model has a better RS prediction ability than the NIR best calibration model. Two high grain RS content wheat mutants were screened out by the ATR-MIR best calibration model from the wheat mutant library. There was no significant difference between the predicted values and chemical measured values in the two high RS content mutants. It proved that the ATR-MIR model can be a perfect substitute in RS measuring. All the results indicated that the ATR-MIR spectroscopy with improved screening efficiency can be used as a fast, rapid, and nondestructive method in high grain RS content wheat breeding.

Determination of the International Sensitivity Index of a New Near-Patient Testing Device to Monitor Oral Anticoagulant Therapy

1997 ◽  
Vol 78 (02) ◽  
pp. 855-858 ◽  
Author(s):  
Armando Tripodi ◽  
Veena Chantarangkul ◽  
Marigrazia Clerici ◽  
Barbara Negri ◽  
Pier Mannuccio Mannucci
Keyword(s):  
Linear Relationship ◽  
Whole Blood ◽  
Oral Anticoagulant ◽  
Oral Anticoagulant Therapy ◽  
Oral Anticoagulants ◽  
Calibration Model ◽  
Testing Device ◽  
Data Points ◽  
Near Patient Testing

SummaryA key issue for the reliable use of new devices for the laboratory control of oral anticoagulant therapy with the INR is their conformity to the calibration model. In the past, their adequacy has mostly been assessed empirically without reference to the calibration model and the use of International Reference Preparations (IRP) for thromboplastin. In this study we reviewed the requirements to be fulfilled and applied them to the calibration of a new near-patient testing device (TAS, Cardiovascular Diagnostics) which uses thromboplastin-containing test cards for determination of the INR. On each of 10 working days citrat- ed whole blood and plasma samples were obtained from 2 healthy subjects and 6 patients on oral anticoagulants. PT testing on whole blood and plasma was done with the TAS and parallel testing for plasma by the manual technique with the IRP CRM 149S. Conformity to the calibration model was judged satisfactory if the following requirements were met: (i) there was a linear relationship between paired log-PTs (TAS vs CRM 149S); (ii) the regression line drawn through patients data points, passed through those of normals; (iii) the precision of the calibration expressed as the CV of the slope was <3%. A good linear relationship was observed for calibration plots for plasma and whole blood (r = 0.98). Regression lines drawn through patients data points, passed through those of normals. The CVs of the slope were in both cases 2.2% and the ISIs were 0.965 and 1.000 for whole blood and plasma. In conclusion, our study shows that near-patient testing devices can be considered reliable tools to measure INR in patients on oral anticoagulants and provides guidelines for their evaluation.

Determination of main raw material source in bar soaps using mid-infrared spectroscopy combined with classification tools

2021 ◽  
Vol 164 ◽  
pp. 106029
Author(s):  
Diego Maciel Gerônimo ◽  
Sheila Catarina de Oliveira ◽  
Frederico Luis Felipe Soares ◽  
Patricio Peralta-Zamora ◽  
Noemi Nagata
Keyword(s):  
Infrared Spectroscopy ◽  
Raw Material ◽  
Material Source ◽  
Mid Infrared ◽  
Mid Infrared Spectroscopy

scholarly journals Modeling Population Spatial-Temporal Distribution Using Taxis Origin and Destination Data

2021 ◽  
Vol 13 (7) ◽  
pp. 3727
Author(s):  
Fatema Rahimi ◽  
Abolghasem Sadeghi-Niaraki ◽  
Mostafa Ghodousi ◽  
Soo-Mi Choi
Keyword(s):  
Regression Analysis ◽  
Mean Squared Error ◽  
Population Distribution ◽  
Temporal Distribution ◽  
Coefficient Of Determination ◽  
Temporal Modeling ◽  
Location Data ◽  
Time Period ◽  
Proposed Model

During dangerous circumstances, knowledge about population distribution is essential for urban infrastructure architecture, policy-making, and urban planning with the best Spatial-temporal resolution. The spatial-temporal modeling of the population distribution of the case study was investigated in the present study. In this regard, the number of generated trips and absorbed trips using the taxis pick-up and drop-off location data was calculated first, and the census population was then allocated to each neighborhood. Finally, the Spatial-temporal distribution of the population was calculated using the developed model. In order to evaluate the model, a regression analysis between the census population and the predicted population for the time period between 21:00 to 23:00 was used. Based on the calculation of the number of generated and the absorbed trips, it showed a different spatial distribution for different hours in one day. The spatial pattern of the population distribution during the day was different from the population distribution during the night. The coefficient of determination of the regression analysis for the model (R2) was 0.9998, and the mean squared error was 10.78. The regression analysis showed that the model works well for the nighttime population at the neighborhood level, so the proposed model will be suitable for the day time population.

High-throughput determination of flavanone-O-glycosides in citrus beverages by paper spray tandem mass spectrometry

2021 ◽  
pp. 130060
Author(s):  
Fabio Mazzotti ◽  
Lucia Bartella ◽  
Ines Rosita Talarico ◽  
Anna Napoli ◽  
Leonardo Di Donna
Keyword(s):  
Mass Spectrometry ◽  
Tandem Mass Spectrometry ◽  
High Throughput ◽  
Tandem Mass ◽  
Paper Spray

scholarly journals A Multimethod Analysis for Average Annual Precipitation Mapping in the Khorasan Razavi Province (Northeastern Iran)

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 592
Author(s):  
Mehdi Aalijahan ◽  
Azra Khosravichenar
Keyword(s):  
Regional Planning ◽  
Interpolation Method ◽  
Absolute Error ◽  
Rain Gauge ◽  
Annual Precipitation ◽  
Coefficient Of Determination ◽  
Distance Weighting ◽  
Average Annual Precipitation ◽  
Inverse Distance

The spatial distribution of precipitation is one of the most important climatic variables used in geographic and environmental studies. However, when there is a lack of full coverage of meteorological stations, precipitation estimations are necessary to interpolate precipitation for larger areas. The purpose of this research was to find the best interpolation method for precipitation mapping in the partly densely populated Khorasan Razavi province of northeastern Iran. To achieve this, we compared five methods by applying average precipitation data from 97 rain gauge stations in that province for a period of 20 years (1994–2014): Inverse Distance Weighting, Radial Basis Functions (Completely Regularized Spline, Spline with Tension, Multiquadric, Inverse Multiquadric, Thin Plate Spline), Kriging (Simple, Ordinary, Universal), Co-Kriging (Simple, Ordinary, Universal) with an auxiliary elevation parameter, and non-linear Regression. Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and the Coefficient of Determination (R2) were used to determine the best-performing method of precipitation interpolation. Our study shows that Ordinary Co-Kriging with an auxiliary elevation parameter was the best method for determining the distribution of annual precipitation for this region, showing the highest coefficient of determination of 0.46% between estimated and observed values. Therefore, the application of this method of precipitation mapping would form a mandatory base for regional planning and policy making in the arid to semi-arid Khorasan Razavi province during the future.

scholarly journals Mid-Infrared Spectroscopy as a Rapid Tool to Qualitatively Predict the Effects of Species, Regions and Roasting on the Nutritional Composition of Australian Acacia Seed Species

Molecules ◽  
2021 ◽  
Vol 26 (7) ◽  
pp. 1879
Author(s):  
Oladipupo Q. Adiamo ◽  
Yasmina Sultanbawa ◽  
Daniel Cozzolino
Keyword(s):  
Principal Component ◽  
Nutritional Composition ◽  
Human Consumption ◽  
Mid Infrared ◽  
Mir Spectroscopy ◽  
As Species ◽  
Before And After ◽  
Mir Spectra ◽  
Main Components ◽  
Rapid Tool

In recent times, the popularity of adding value to under-utilized legumes have increased to enhance their use for human consumption. Acacia seed (AS) is an underutilized legume with over 40 edible species found in Australia. The study aimed to qualitatively characterize the chemical composition of 14 common edible AS species from 27 regions in Australia using mid-infrared (MIR) spectroscopy as a rapid tool. Raw and roasted (180 °C, 5, 7, and 9 min) AS flour were analysed using MIR spectroscopy. The wavenumbers (1045 cm−1, 1641 cm−1, and 2852–2926 cm−1) in the MIR spectra show the main components in the AS samples. Principal component analysis (PCA) of the MIR data displayed the clustering of samples according to species and roasting treatment. However, regional differences within the same AS species have less of an effect on the components, as shown in the PCA plot. Statistical analysis of absorbance at specific wavenumbers showed that roasting significantly (p < 0.05) reduced the compositions of some of the AS species. The results provided a foundation for hypothesizing the compositional similarity and/or differences among AS species before and after roasting.

scholarly journals Rapid tannin profiling of tree fodders using untargeted mid-infrared spectroscopy and partial least squares regression

Plant Methods ◽  
2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Jordi Ortuño ◽  
Sokratis Stergiadis ◽  
Anastasios Koidis ◽  
Jo Smith ◽  
Chris Humphrey ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Least Squares ◽  
Partial Least Squares ◽  
Partial Least Squares Regression ◽  
Multivariate Calibration ◽  
Plant Ecology ◽  
Coefficient Of Determination ◽  
Least Squares Regression ◽  
Mid Infrared ◽  
Mid Infrared Spectroscopy

Abstract Background The presence of condensed tannins (CT) in tree fodders entails a series of productive, health and ecological benefits for ruminant nutrition. Current wet analytical methods employed for full CT characterisation are time and resource-consuming, thus limiting its applicability for silvopastoral systems. The development of quick, safe and robust analytical techniques to monitor CT’s full profile is crucial to suitably understand CT variability and biological activity, which would help to develop efficient evidence-based decision-making to maximise CT-derived benefits. The present study investigates the suitability of Fourier-transformed mid-infrared spectroscopy (MIR: 4000–550 cm−1) combined with multivariate analysis to determine CT concentration and structure (mean degree of polymerization—mDP, procyanidins:prodelphidins ratio—PC:PD and cis:trans ratio) in oak, field maple and goat willow foliage, using HCl:Butanol:Acetone:Iron (HBAI) and thiolysis-HPLC as reference methods. Results The MIR spectra obtained were explored firstly using Principal Component Analysis, whereas multivariate calibration models were developed based on partial least-squares regression. MIR showed an excellent prediction capacity for the determination of PC:PD [coefficient of determination for prediction (R2P) = 0.96; ratio of prediction to deviation (RPD) = 5.26, range error ratio (RER) = 14.1] and cis:trans ratio (R2P = 0.95; RPD = 4.24; RER = 13.3); modest for CT quantification (HBAI: R2P = 0.92; RPD = 3.71; RER = 13.1; Thiolysis: R2P = 0.88; RPD = 2.80; RER = 11.5); and weak for mDP (R2P = 0.66; RPD = 1.86; RER = 7.16). Conclusions MIR combined with chemometrics allowed to characterize the full CT profile of tree foliage rapidly, which would help to assess better plant ecology variability and to improve the nutritional management of ruminant livestock.

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