Plants (Mar 2023)

Important Medicinal and Food Taxa (Orders and Families) in Kenya, Based on Three Quantitative Approaches

  • Fredrick Munyao Mutie,
  • Yuvenalis Morara Mbuni,
  • Peninah Cheptoo Rono,
  • Elijah Mbandi Mkala,
  • John Mulinge Nzei,
  • Methee Phumthum,
  • Guang-Wan Hu,
  • Qing-Feng Wang

DOI
https://doi.org/10.3390/plants12051145
Journal volume & issue
Vol. 12, no. 5
p. 1145

Abstract

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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 p p 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.

Keywords