All measurements are presented as the mean ± SD of 3 replicates (photosynthetic parameters n = 20). The data were input and analyzed by Excel 2010 software and IBM SPSS Statistics 25.0 software (IBM Corp., Armonk, NY, USA). The charts were produced by Excel 2010, Origin 2021 (Origin Lab Inc., San Francisco, CA, USA) and Adobe Photoshop 2020 (Photoshop Software, San Diego, CA, USA). The growth parameters, photosynthetic index, antioxidant system, soluble proteins, sugars, amino acids, hormones and the physical and chemical properties of substrates were analyzed by the general linear model, which is a fixed effect model. Normal distribution and homogeneity test of variance were conducted on samples before ANOVA processing, which all met the above conditions. One-way ANOVA was performed for significance testing (p < 0.05). Duncan’s test was used to compare the means of all paired measurement values. Pearson correlation coefficient was used for correlation analysis. Principal component analysis (PCA) analysis was performed with Origin 2021 (Origin Lab Inc., USA). Kaiser-Meyer-Olkin (KMO) test was conducted on sample variables, and KMO > 0.7, so PCA could be conducted.
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Spss 26, by IBM (13 mentions)
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Prism 8, by GraphPad (9 mentions)
Prism 9, by GraphPad (9 mentions)
Spss statistics 25, by IBM (9 mentions)
Spss 23, by IBM (8 mentions)
Spss statistics 26, by IBM (8 mentions)
Simca 14, by Sartorius (7 mentions)
Spss statistics 23, by IBM (5 mentions)
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Spss statistics 20, by IBM (4 mentions)
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Spss 19, by IBM (3 mentions)
Spss statistics 24, by IBM (3 mentions)
Prism 7, by GraphPad (3 mentions)
Spss 25, by IBM (3 mentions)
Sigmaplot 12, by Grafiti LLC (3 mentions)
Nicolet is50, by Thermo Fisher Scientific (3 mentions)
354 protocols using origin 2021
1
Plant Growth and Photosynthetic Responses
2
Automated Fungal Growth Analysis
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Time-lapse images (used to produce growth and germination videos) as well as time-point large images (used for measuring growth rates) were obtained with two inverted microscopes (Eclipse Ti-U and Eclipse Ti-2, Nikon; ESI† Methods). Microscopy images were processed and analysed with Image J (Fiji).42 (link) To measure hyphal growth, the segmented line and measurement tool were used. The measured lengths were grouped into 5 intervals; 0.1–0.4 mm, 0.5–1.0 mm, 1.1–2.0 mm, 2.1–3.0 mm and >3 mm, and represented as stacked column diagrams using Origin 2021 (OriginLab). To account for the variation in number of spores loaded into the devices, the results were normalised. Therefore, the number of germination sites (instead of the number of spores) was determined and the absolute value of counts divided by the number of germination sites. For the hyphal growth behaviour, we counted sites where a germination within 14 days of inoculation occurred as germination sites. For calculation of the germination rates, we defined any site where usually a germination occurs from, i.e., cut ends of hyphal remnants, as a germination site. Germinations were counted at the last day, day 14, of the experiment. For determining significant differences in the data points for germination rates and spore distribution within devices, 1-way ANOVA was performed in Origin 2021 (OriginLab).![]()
3
Statistical Analysis of Experimental Data
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Data comparisons throughout the manuscript are presented as mean ± standard error of the mean and plotted using Origin 2021(OriginLab, USA). All data sets were analyzed using t‐test or analysis of variance (ANOVA) with Origin 2021(OriginLab, USA). In cases whereby, samples do not meet normality criteria, a nonparametric test was used. A p‐value of less than 0.05 was considered statistically significant (* indicates p < 0.05, ** indicates p < 0.01, n.s. indicates no significant).
4
Evaluation of SARS-CoV-2 Antibody Assays
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The significance of differences between two groups was analyzed using unpaired Student’s t-tests. Pearson’s correlation was performed using Origin2021 software (Origin Lab Corporation) to determine
associations between two continuous variables. To compare the sensitivity of the bead-based IgG antibody assay with that of the ELISA, the LOD and LOQ were calculated using a serially diluted anti-SARS-CoV-2 RBD neutralizing antibody (AcroBIOSYSTEMS). For the determination of the LOD and LOQ values, the limit of blank (LOB) was considered. The LOB was calculated by the mean of the blank + 1.645 (standard deviation of the blank), and the LOD was calculated by LOD = 3.3 × σ / S, where S is the slope of the calibration curve, and σ is the standard deviation of the Y-intercept. The LOQ was calculated by LOQ = 10 × σ / S (16 (link)). Standard dilution series obtained for the ELISA and bead-based IgG antibody analysis were used to determine the LOD and LOQ. For linear regression to obtain a calibration curve, data with a range higher than the LOB were analyzed using Origin2021 software (Origin Lab Corporation). All data are expressed as the mean ± SD. For all statistical tests, P-values ≤ 0.05 were considered significant.
associations between two continuous variables. To compare the sensitivity of the bead-based IgG antibody assay with that of the ELISA, the LOD and LOQ were calculated using a serially diluted anti-SARS-CoV-2 RBD neutralizing antibody (AcroBIOSYSTEMS). For the determination of the LOD and LOQ values, the limit of blank (LOB) was considered. The LOB was calculated by the mean of the blank + 1.645 (standard deviation of the blank), and the LOD was calculated by LOD = 3.3 × σ / S, where S is the slope of the calibration curve, and σ is the standard deviation of the Y-intercept. The LOQ was calculated by LOQ = 10 × σ / S (16 (link)). Standard dilution series obtained for the ELISA and bead-based IgG antibody analysis were used to determine the LOD and LOQ. For linear regression to obtain a calibration curve, data with a range higher than the LOB were analyzed using Origin2021 software (Origin Lab Corporation). All data are expressed as the mean ± SD. For all statistical tests, P-values ≤ 0.05 were considered significant.
5
Data Analysis and Visualization Tools
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Data evaluation were performed using the OriginLab Origin® 2021 (version 9.8.0.200) (OriginLab Corporation, One Roundhouse Plaza, Suite 303, Northampton, MA, USA) and Microsoft Excel (version 2002) (Microsoft Corporation, One Microsoft Way, Redmond, WA, USA) software. The figures were made using OriginLab Origin® 2021 and Microsoft PowerPoint (version 2002) (Microsoft Corporation, One Microsoft Way, Redmond, WA 98052-7329, USA) software.
6
Thermal Denaturation Analysis of SARS-CoV-2 in Human Whole Blood
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Differential scanning calorimetry (DSC) is a thermoanalytical technique to study the thermodynamic properties of biological and non-biological samples [47 (link),48 (link),49 (link),50 (link),51 ]. To investigate the effect of SARS-CoV-2 on the human whole blood, thermal denaturation measurements were performed with SETARAM Micro DSC-III calorimeter. Each measurement was performed in the range of 20–100 °C by using a 0.3 K·min−1 heating rate. The sample and the reference (normal saline) were balanced with a precision of ±0.05 mg to avoid corrections with the heat capacity of the vessels. A second thermal scan of the denatured sample was carried out for baseline correction. The deconvolution of DSC data, the analysis of the melting temperature (Tm), and the calculation of the relative enthalpy change (ΔH) from the area under the deconvolved heat absorption curves were analyzed using the OriginLab Origin® 2021 (version 9.8.5.212) software (OriginLab Corporation, One Roundhouse Plaza, Suite 303, Northampton, MA 01060, USA).
7
Raman Spectroscopy Analysis of Materials
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Raman spectra were taken using an InVia spectrometer (Renishaw, Gloucester, UK) equipped with a DM 2500 M microscope (Leica, Wetzlar, Germany) with a 50X objective. Lasers with the power of 100 mW, wavelengths of 532 nm, and a spectral resolution of 2 cm−1 were used. A spectral range of 500–2500 cm−1 was considered. The Raman spectra were deconvoluted using Gaussian line fitting (Origin 2021, Origin Lab., Northampton, MA, USA). The fitting parameters were used to calculate the Raman parameters, including band position and the spectral intensity ratios ID/IG and Imax/IC.
8
Membrane Crystal Structure Analysis
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The crystal structure of the membranes was investigated using the X-ray diffraction method with an XRD 6000 diffractometer (Shimadzu, Kyoto, Japan). The average size of the crystallites (lc) was calculated using the Debye-Scherrer Equation (1):
where λ is the wavelength of the incident radiation (Cu K-alpha, λ = 1.54056 Å), β is the width of the reflection at a half height (FWHM), θ is the angle of the diffraction, and k = 0.9. The estimation of the FWHM parameter was performed by interpolating the X-ray pattern using a Gauss function (Origin 2021, Origin Lab., Northampton, MA, USA).
where λ is the wavelength of the incident radiation (Cu K-alpha, λ = 1.54056 Å), β is the width of the reflection at a half height (FWHM), θ is the angle of the diffraction, and k = 0.9. The estimation of the FWHM parameter was performed by interpolating the X-ray pattern using a Gauss function (Origin 2021, Origin Lab., Northampton, MA, USA).
9
Grazing Intensity and Soil Position Effects on Microbial Diversity
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To test the interaction effects between grazing intensities (i.e., CK, LG and HG) and soil positions (both in rhizosphere and non-rhizosphere soils) treatments on the microbial diversity and soil chemical properties, we used a two-way ANOVA with grazing treatments as the main-plot effect, and soil position treatments as the sub-plot effect. Microbial diversity was calculated based on OTUs number, including Richness, Shannon-Wiener index and Chao1 index, calculated by the following formula:
Richness = SobsShannon-Wiener index:
Chao1 index: Schao1 = Sobs + n1(n1 − 1)/2(n2 + 1).
Where: Sobs is the OTUs number actually observed; Schao1 is the estimated OTUs number; n1 represents the number of OTUs containing only one sequence; n2 represents the number of OTUs containing only two sequences; ni is the number of sequences contained in the i th OTUs; N represents all the sequence numbers. Besides, spearman correlation analysis was used to assess the relationships between the microbial diversity (i.e., both bacterial and fungal) and soil chemical properties. Data analysis was conducted using SPSS 19.0 (IBM Corp., Armonk, NY, USA), and all figures were prepared using Origin 2021 (OriginLab Corporation, Northampton, MA, USA).
Richness = SobsShannon-Wiener index:
Chao1 index: Schao1 = Sobs + n1(n1 − 1)/2(n2 + 1).
Where: Sobs is the OTUs number actually observed; Schao1 is the estimated OTUs number; n1 represents the number of OTUs containing only one sequence; n2 represents the number of OTUs containing only two sequences; ni is the number of sequences contained in the i th OTUs; N represents all the sequence numbers. Besides, spearman correlation analysis was used to assess the relationships between the microbial diversity (i.e., both bacterial and fungal) and soil chemical properties. Data analysis was conducted using SPSS 19.0 (IBM Corp., Armonk, NY, USA), and all figures were prepared using Origin 2021 (OriginLab Corporation, Northampton, MA, USA).
10
Multivariate Analysis of Metabolite Data
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One-way analysis of variance and Pearson’s correlation tests (p < 0.01) were conducted on IBM SPSS 19.0 statistical software (SPSS Inc., Armonk, NY, USA). The filtered metabolite data was submitted to R 4.1.3 (www.r-project.org , accessed on 29 December 2021, Auckland, New Zealand) for hierarchical cluster analysis and OPLS-DA (Access date: 29 December 2021). Column diagram, line charts, PCA, Venn diagram, correlation analysis, NMDS, and UMAP were conducted using Origin 2021 software (Originlab, Northampton, MA, USA).
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