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Origin 2021b

Manufactured by OriginLab
Sourced in United States

Origin 2021b is a data analysis and graphing software designed for scientific and engineering applications. It provides a comprehensive set of tools for data manipulation, visualization, and analysis. The software supports a wide range of data formats and offers a variety of graphing options to help users create high-quality plots and charts. Origin 2021b is compatible with Windows operating systems.

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59 protocols using origin 2021b

1

ATR-FTIR Spectroscopy Analysis of Samples

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The ATR-FTIR spectra were collected on an IRTracer-100 spectrophotometer. All spectra were measured between 4000 and 400 cm−1 in the absorbance mode. The following spectrometer parameters were used: resolution: 4 cm−1, the number of scans: 400, and apodization: Happ–Genzel. The sample was placed directly on the ATR crystal. Solid samples were pressed against the ATR crystal and the ATR-FTIR spectrum was scanned. LabSolutions IR software (version 1.86 SP2, Shimadzu, Kyoto, Japan) was used to calculate the second derivative of all spectra. The software performed calculations according to the Savitzky–Golay numerical algorithm. The smoothing parameter was 25 points. A derivative spectrum allowed us to identify the peak positions of the original spectrum and to separate multiple peaks, which were adjoining or on the shoulder. The minima of the second derivative corresponded to the extremes of the original ATR-FTIR spectrum. Origin 2021b (OriginLab Corporation, Northampton, MA, USA) was used to analyse the acquired data.
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2

Multivariate Analysis of Fermentation Compounds

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All data from independent triplicate fermentations (n = 3) were recorded as the average value ± standard deviation (SD). One-way ANOVA with Tukey’s post hoc test was conducted by SPSS® 20.0 (Windows version, Chicago, IL, USA) to check the significant differences (p < 0.05) among samples. Heatmap was plotted by Heatmapper [19 (link)]. Principal component analysis (PCA) of selected aromatic compounds was performed by Origin 2021b (OriginLab Corporation, Northampton, MA, USA).
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3

Comparative Statistical Analysis of Experimental Data

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All measurements were repeated at least three times. Data were recorded as mean ± standard deviation and statistically analyzed for a significant difference (p < 0.05) by IBM SPSS statistics 26 (IBM, NY, USA). All curve fittings were applied by the program Origin 2021b (OriginLab Corporation, MA, USA).
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4

One-way ANOVA for Multiple Comparisons

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For multiple comparisons, the statistical analyses were performed using one-way ANOVA test in Origin 2021b (OriginLab, USA). All data points and P-values can be found in Supplemental Data Set 1.
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5

Statistical Data Analysis of Experimental Findings

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All the experimental data were analyzed by IBM SPSS 22.0 statistical software (SPSS Inc., Chicago, USA) and expressed as mean ± standard deviation. Graphs were constructed using Origin 2021b (Origin Lab Inc., MA, USA). The determination of significant differences (p < 0.05) between groups was based on Analysis of variance (ANOVA) and Duncan’s multiple range.
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6

Normalizing and Analyzing Metabolomic Data

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Physiological, biochemical, and serum metabolomics data were Z-score normalized across the six experimental groups. Unsupervised hierarchical clustering was performed on the normalized data with the Polar Heatmap with dendogram v1.0 from Origin 2021b (Origin Lab Corp., Northampton, MA, USA) using average linkage and uncentered similarity metrics. Principal component analysis was performed with the same input data using the multivariate statistics subroutine of Origin 2021b.
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7

Rheological Measurement Data Analysis

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For each measured parameter, the arithmetic mean and standard deviation were calculated from multiple measurements. The error originating from the sample was assumed to be dominant, while the error from the rheological measurement was neglected. Further evaluation was completed with Origin 2021b (OriginLab Corporation, Northampton, MA, USA) and IGOR Pro 6.37 (WaveMetrics, Portland, OR, USA).
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8

Fumonisin Effects on Biological Parameters

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The statistical analysis was performed using Statistica 13.1 (Tibco Software, Palo Alto, CA, USA) and Origin 2021b (OriginLab, Northampton, MA, USA). Normality was assessed by the Shapiro–Wilk test, while the homogeneity of the variance was studied using the Levene test. A one-way ANOVA with the Fumonisin treatment as the main effect was used to assess the changes under the influence of Fumonisin administration. Non-parametric data were analyzed using a Kruskal–Wallis H test. Post hoc tests (Tukey or Dunn’s) were applied to evaluate differences in the analyzed parameters between the control and supplemented groups. For all tests, a p-value < 0.05 was established as statistically significant. All the data are reported as mean ± standard error. Analysis was performed separately for each sex.
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9

Multivariate Analysis of Research Data

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Quantitative data were reported as mean value ± standard deviation (SD). All tables were drawn using Microsoft Office Excel 2021. One-way analysis of variance (ANOVA), Duncan’s multiple-range tests and hierarchical cluster analysis (HCA) were performed by using the IBM SPSS Statistics 26 software; a difference of p < 0.05 was considered as significant. Heatmap were performed by TB tool; origin 2021b (Origin-Lab, Northampton, MA, USA) and SIMCA14.1 was used to draw the radar chart and PCA, respectively.
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10

Soil Heavy Metal Content Analysis

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The differences in the heavy metal contents in soils from different sampling sites were determined via one-way analysis of variance (ANOVA). A Shapiro–Wilk test and Leven’s test were performed to ensure the normality and homogeneity of the data prior to ANOVA (p < 0.05 or p < 0.01). Pearson’s correlation analysis was applied to evaluate the influences of soil factors on the heavy metals in the soils. Statistical analyses were conducted in SPSS 26.0 (IBM, Armonk, NY, USA) and Origin 2021b (OriginLab Corporation, Northampton, MA, USA).
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