Origin 2021

Manufactured by IBM

Sourced in United States

Origin 2021 is a laboratory-grade instrument designed for advanced analytical applications. It provides precise measurements and data processing capabilities for a variety of scientific research and industrial applications. The core function of Origin 2021 is to enable accurate and reliable data collection and analysis.

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Lab products found in correlation

30 protocols using origin 2021

Statistical Analysis of Research Data

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All the data statistical differences were analyzed by using SPSS 26 (IBM Corporation, Armonk, NY, USA) through a one-way analysis of variance (ANOVA) test, and Origin 2021 was used for data analysis and visualization. The differences were considered significant at p < 0.05.

Wu M., He X., Feng D., Li H., Han D., Li Q., Zhao B., Li N., Liu T, & Wang J. (2023). The Effect of High Pressure Homogenization on the Structure of Dual-Protein and Its Emulsion Functional Properties. Foods, 12(18), 3358.

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Comparative Protein Expression Analysis

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Each experiment was performed in three replicates. Experimental results were analysed using GraphPad Prism 8, Origin 2021, IBM SPSS Statistics 23, RStudio, and Cytoscape 3.7.1 software. Error bars denote standard deviations. Different lowercase letters above the bars indicate significant differences (P < 0.05), which were obtained based on one-way ANOVA by LSD and DUNCAN tests using IBM SPSS Statistics 23 software.

Li X., Cheng Y., Wang M., Cui S, & Guan J. (2021). Weighted gene coexpression correlation network analysis reveals a potential molecular regulatory mechanism of anthocyanin accumulation under different storage temperatures in ‘Friar’ plum. BMC Plant Biology, 21, 576.

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Evaluating Plant Responses to Salt Stress

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Data processing was conducted using Excel 2021 and IBM SPSS Statistics 26 software, while Origin 2021 and R4.3.1 was utilized for chart creation. A one-way analysis of variance (ANOVA) was employed to analyze the data of various indicators under different salt stress treatments, providing a robust statistical framework for evaluating the effects of salinity on plant physiology.

Mo Q., Liu Y., Wei H., Jiang L., Wu E., Lin L., Yang Q., Yu X., Yan L, & Li Y. (2024). Salt Tolerance in Machilus faberi: Elucidating Growth and Physiological Adaptations to Saline Environments. Biology, 13(2), 75.

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Statistical Analysis of Experimental Data

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Statistical
analysis was done by using IBM SPSSS Statistics 26, Excel, and ORIGIN
2021 PC Corporation. ANOVA with least significant difference (LSD)
and principle component analysis (PCA) was applied to analyze the
data. The post hoc test was used for significant difference and expressed
in the form alphabetical letters on bars of figures.

Kakar H.A., Ullah S., Shah W., Ali B., Satti S.Z., Ullah R., Muhammad Z., Eldin S.M., Ali I., Alwahibi M.S., Elshikh M.S, & Ercisli S. (2023). Seed Priming Modulates Physiological and Agronomic Attributes of Maize (Zea mays L.) under Induced Polyethylene Glycol Osmotic Stress. ACS Omega, 8(25), 22788-22808.

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Comprehensive Statistical Analysis of Experimental Data

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All tests were performed in triplicate. The experimental data were collated and graphed using Excel 2010. IBM SPSS Statistics, 26, and Origin 2021 were used for graphical plotting. The significance analysis was performed using the Duncan test. P < 0.05 was considered statistically significant. TBtools was used for plotting the heat maps.

Liu W., Luo X., Qiu S., Huang W., Su Y, & LI L. (2023). Determining the changes in metabolites of Dendrobium officinale juice fermented with starter cultures containing Saccharomycopsis fibuligera FBKL2.8DCJS1 and Lactobacillus paracasei FBKL1.3028 through untargeted metabolomics. BMC Microbiology, 23, 67.

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Statistical Analysis of Experimental Data

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Data were analyzed using Origin 2021, IBM SPSS Statistics 20.0 and Excel 2010. The statistical analyses were performed using one-way analysis of variance (ANOVA) followed by Duncan’s and Least significant difference (LSD) tests. Results were expressed as the mean ± standard deviation of three independent data in the diagram. If the different level was p < 0.05, it was considered to be significant. The Pearson method was used for correlation analysis. The clustering method was inter-group linkage.

Gao Q., Song Y., Liang Y., Li Y., Chang Y., Ma R., Cao X, & Wang S. (2022). Dynamics of Physicochemical Properties, Functional Compounds and Antioxidant Capacity during Spontaneous Fermentation of Lycium ruthenicum Murr. (Qinghai–Tibet Plateau) Natural Vinegar. Foods, 11(9), 1344.

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Comprehensive Statistical Analysis of Experimental Data

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The data are presented as the mean ± standard error of the mean (SEM). Statistical significance was determined by one-way analysis of variance (ANOVA) with Duncan’s comparison tests at P < 0.05. Figures and charts were prepared using Origin 2021. Correlation analysis was performed with SPSS (25.0, IBM Corp., Armonk, NY, USA) and Origin 2021.

Zhang R., Zheng D., Feng N., Qiu Q.S., Zhou H., Liu M., Li Y., Meng F., Huang X., Huang A, & Li Y. (2023). Prohexadione calcium enhances rice growth and tillering under NaCl stress. PeerJ, 11, e14804.

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Phototactic Response Analysis Protocol

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ERG data were examined by Clampex software v. 10.6. The phototactic response was calculated by the following formula:
Analyses of the phototaxis data were performed with Origin 2021 and IBM SPSS Statistics 26 software. ANOVA and Tukey honestly significant difference (HSD) multiple comparisons were used to determine the significant differences between multiple groups. The significant difference between two treatments was determined using the independent-sample T test (Student’s t-test). Figures were produced with GraphPad Prism 8 software.

Fan W.L., Liu X.K., Zhang T.H., Liang Z.L., Jiang L., Zong L., Li C.Q., Du Z., Liu H.Y., Yang Y.X., Wu F.M, & Ge S.Q. (2023). The morphology and spectral characteristics of the compound eye of Agasicleshygrophila (Selman & Vogt, 1971) (Coleoptera, Chrysomelidae, Galerucinae, Alticini). ZooKeys, 1177, 23-40.

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Environmental Factors and Thermal Comfort

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The data from the experiments were imported into excel, including the content of the questionnaires filled out by the subjects and the measured thermal environment parameters. Then the data were classified and sorted. In addition, linear regression was used to analyze the relationship between the environmental parameters and responses to the subjective questionnaire to determine the neutral temperature. All statistical analyses were performed using IBM SPSS Statistics 25 (IBM Inc., Armonk, NY, USA), and Origin 2021 (Origin Lab Corporation, Northampton, MA, USA), including the fitting of linear regression equations and the calculation of linear regression correlation index R² and the independent sample t-tests. When the significance level was less than or equal to 0.05, there was a statistically significant difference between the tested levels. The figures and charts were created using IBM SPSS Statistics 25 and Origin 2021.

Mao Y., Zhu Y., Guo Z., Zheng Z., Fang Z, & Chen X. (2022). Experimental investigation of the effects of personal protective equipment on thermal comfort in hot environments. Building and Environment, 222, 109352.

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Statistical Analysis of Prophage-Chromosome Correlation

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Statistical analysis of the data was performed using the independent samples Mann–Whitney U test for comparisons of two samples or the independent samples Kruskal–Wallis test for comparing multiple variables. The correlation between the integrated putative prophage numbers and the corresponding K. pneumoniae chromosome length was tested using the Spearman correlation coefficient test. The statistical inferences and hypothesis testing were generated using the software Origin 2021 and SPSS version 27 (IBM, Armonk, NY, USA), using a significance level of 95%.

Kang F., Chai Z., Li B., Hu M., Yang Z., Wang X., Liu W., Ren H., Jin Y, & Yue J. (2023). Characterization and Diversity of Klebsiella pneumoniae Prophages. International Journal of Molecular Sciences, 24(11), 9116.

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