Important Medicinal and Food Taxa (Orders and Families) in Kenya, Based on Three Quantitative Approaches
Issued Date
2023-03-01
Resource Type
eISSN
22237747
Scopus ID
2-s2.0-85149989538
Journal Title
Plants
Volume
12
Issue
5
Rights Holder(s)
SCOPUS
Bibliographic Citation
Plants Vol.12 No.5 (2023)
Suggested Citation
Mutie F.M., Mbuni Y.M., Rono P.C., Mkala E.M., Nzei J.M., Phumthum M., Hu G.W., Wang Q.F. Important Medicinal and Food Taxa (Orders and Families) in Kenya, Based on Three Quantitative Approaches. Plants Vol.12 No.5 (2023). doi:10.3390/plants12051145 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/81447
Title
Important Medicinal and Food Taxa (Orders and Families) in Kenya, Based on Three Quantitative Approaches
Other Contributor(s)
Abstract
Globally, food and medicinal plants have been documented, but their use patterns are poorly understood. Useful plants are non-random subsets of flora, prioritizing certain taxa. This study evaluates orders and families prioritized for medicine and food in Kenya, using three statistical models: Regression, Binomial, and Bayesian approaches. An extensive literature search was conducted to gather information on indigenous flora, medicinal and food plants. Regression residuals, obtained using LlNEST linear regression function, were used to quantify if taxa had unexpectedly high number of useful species relative to the overall proportion in the flora. Bayesian analysis, performed using BETA.INV function, was used to obtain superior and inferior 95% probability credible intervals for the whole flora and for all taxa. To test for the significance of individual taxa departure from the expected number, binomial analysis using BINOMDIST function was performed to obtain p-values for all taxa. The three models identified 14 positive outlier medicinal orders, all with significant values (p < 0.05). Fabales had the highest (66.16) regression residuals, while Sapindales had the highest (1.1605) R-value. Thirty-eight positive outlier medicinal families were identified; 34 were significant outliers (p < 0.05). Rutaceae (1.6808) had the highest R-value, while Fabaceae had the highest regression residuals (63.2). Sixteen positive outlier food orders were recovered; 13 were significant outliers (p < 0.05). Gentianales (45.27) had the highest regression residuals, while Sapindales (2.3654) had the highest R-value. Forty-two positive outlier food families were recovered by the three models; 30 were significant outliers (p < 0.05). Anacardiaceae (5.163) had the highest R-value, while Fabaceae had the highest (28.72) regression residuals. This study presents important medicinal and food taxa in Kenya, and adds useful data for global comparisons.