Application of response surface methodology for determining optimal factors in maximization of maize grain yield and total microbial count in long term agricultural

Citation:

Wambua, A.M., et al., 2017. Application of response surface methodology for determining optimal factors in maximization of maize grain yield and total microbial count in long term agricultural . Science Journal of Applied Mathematics and Statistics, 5(6), p.200-209.

Recent Publications

Tum, I.K., Koske, J.K. & Mutiso, J.M., 2018. Optimal and efficient production of rose coco beans through twenty four points second order rotatable design. International Journal of Advanced Statistics and Probability, 6(1), p.1-9.

Wambua, A.M., et al., 2017. Optimal slope designs for second degree Kronecker model mixture experiment. International Journal of Mathematics and Theoretical Physics, 3(4), p.86-91.

Okango, A.A., Koske, J.K. & Mutiso, J.M., 2017. Analyzing four factor second order models using response surface methodology with application in germination of Melia volkensii. African Journal of Education, Science and Technology, 4(2), p.71-101.

Tum, I.K., Mutiso, J.M. & Koske, J.K., 2017. Modeling of rose coco beans using twenty four points optimum second order rotatable design. International Journal of Advanced Statistics and Probability, 5(2), p.96-100.

John M. Mutiso

Professor of Statistics

Application of response surface methodology for determining optimal factors in maximization of maize grain yield and total microbial count in long term agricultural

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Recent Publications

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