Design of Experiments on Grass Growth in Controlled Environment

Muhammad Adib Uz Zaman, Anup Bharatkumar Parmer and Saman Naghdi

MPRA Paper from University Library of Munich, Germany

Abstract: Most design of experiments in agricultural applications are complex operations in nature because of numerous process variables, feed material attributes, and raw material attributes that can have significant impact on the performance of the process. Design of experiments (DOE)-based approach offers a solution to this conundrum and allows for an efficient estimation of the main effects and the interactions with minimal number of experiments. This study investigates on the most effective factors contributing in grass growth. All the factors are set in two levels to create a full-factorial 2k design. A systematic methodology is proposed for construction of the model and for precise prediction of the responses which is lawn growth. The results indicate that water is the most significant factor that the cultivator can directly control and cheap seeds found to be suitable for the grass growth applications under consideration

Keywords: DOE; Grass Growth; 2^k design; Full factorial; Random Experiments; ANOVA (search for similar items in EconPapers)
JEL-codes: C90 (search for similar items in EconPapers)
Date: 2018-01-04
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:83574

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