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Repeated grading of weed abundance and multivariate methods to improve the efficacy of on‐farm weed control trials
Author(s) -
NKURUNZIZA LIBÈRE,
MILBERG PER
Publication year - 2007
Publication title -
weed biology and management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.351
H-Index - 36
eISSN - 1445-6664
pISSN - 1444-6162
DOI - 10.1111/j.1445-6664.2007.00247.x
Subject(s) - weed , biology , weed control , abundance (ecology) , multivariate statistics , analysis of variance , biomass (ecology) , repeated measures design , multivariate analysis , statistics , agronomy , ecology , mathematics
We evaluated whether new information could be drawn from additional data collection and unconventional statistical analyses of an on‐farm trial. First, we compared a conventional sampling method using a biomass estimate of weed abundance to repeated visual assessment of the percentage ground cover of weeds. The biomass was sampled once after the treatment, whereas the ground cover was repeatedly sampled once before weed control plus several occasions after weed control. Second, we contrasted the outcomes from analysis of variance ( anova ), taking samples from a single point in time with repeated measures (rm) anova and a multivariate method. As the outcomes and conclusions drawn were relatively similar, we conclude that the ground cover estimate of weed abundance was as reliable as the biomass estimate. The rm anova enabled us to follow the temporal trend in response to treatments in the most abundant species, including possible initial differences. Multivariate analysis went even further, by clearly displaying species‐wise responses and treatment selectivity.