U.S. flag

An official website of the United States government

Dot gov

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Https

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

PubAg

Main content area

Replication Concepts for Bioenergy Research Experiments

Author:
Michael D. Casler, Wilfred Vermerris, Richard A. Dixon
Source:
BioEnergy research 2015 v.8 no.1 pp. 1-16
ISSN:
1939-1234
Subject:
agricultural land, bioenergy, biomass, containers, experimental design, feedstocks, field experimentation, greenhouse experimentation, greenhouses, growth chambers, guidelines, issues and policy, laboratory experimentation
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 variation, some of which is unpredictable and unidentifiable (i.e., pure random variation such as variation among plots in an experiment, individuals within a plot, or laboratory samples within an experimental unit) while some is predictable and identifiable (repeatable variation, such as spatial or temporal patterns within an experimental field, a glasshouse or growth chamber, or among laboratory containers). 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 or by completely ignoring the errors associated with growing feedstocks in an agricultural area at a field or farmland (micro- or macro-region) scale. As such, actual random errors inherent in experimental materials are frequently underestimated, with unrealistically low standard errors of statistical parameters (e.g., means), leading to improper inferences. The examples and guidelines set forth in this paper and many of the references cited are intended to form the general policy and guidelines for replication of bioenergy feedstock experiments to be published in BioEnergy Research.
Agid:
62422
Handle:
10113/62422