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ARS Home » Midwest Area » Madison, Wisconsin » U.S. Dairy Forage Research Center » Dairy Forage Research » Research » Publications at this Location » Publication #312321
Title: Replication concepts for bioenergy research experiments

Author
item Casler, Michael
item VERMERRIS, WILFRED - University Of Florida
item DIXON, RICHARD - University Of North Texas

Submitted to: BioEnergy Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/13/2015
Publication Date: 3/15/2015
Publication URL: https://handle.nal.usda.gov/10113/62422
Citation: Casler, M.D., Vermerris, W., Dixon, R. 2015. Replication concepts for bioenergy research experiments. BioEnergy Research. 8:1-16.

Interpretive Summary: While there are some large and fundamental differences among disciplines related to the conversion of biomass to bioenergy, all scientific endeavors involve the use of biological feedstocks. As such, nearly every scientific experiment conducted in this area, regardless of the specific discipline, is subject to random and unpredictable variation. Identifying the scale and sources of this variation relative to the specific hypotheses of interest is a critical component of designing good experiments that generate meaningful and believable hypothesis tests and inference statements. Many bioenergy feedstock experiments are replicated at an incorrect scale, typically by sampling feedstocks to estimate laboratory error, completely ignoring the errors and inferences associated with growing feedstocks in an agricultural landscape. As such, conclusions are often faulty. The examples and guidelines set forth in this paper are intended as guidelines for authors to design better experiments.

Technical Abstract: While there are some large and fundamental differences among disciplines related to the conversion of biomass to bioenergy, all scientific endeavors involve the use of biological feedstocks. As such, nearly every scientific experiment conducted in this area, regardless of the specific discipline, is subject to random and unpredictable variation. Identifying the scale and sources of this variation relative to the specific hypotheses of interest is a critical component of designing good experiments that generate meaningful and believable hypothesis tests and inference statements. Many bioenergy feedstock experiments are replicated at an incorrect scale, typically by sampling feedstocks to estimate laboratory error, completely ignoring the errors and inferences associated with growing feedstocks in an agricultural landscape. As such, errors are frequently underestimated, with unrealistically low standard errors, leading to improper conclusions. The examples and guidelines set forth in this paper and many of the references cited are intended as author guidelines for replication of bioenergy feedstock experiments to be published in BioEnergy Research.