2.7 | Statistical analysis
The effects of three feeding patterns on muscle fatty acid composition
were compared by one-way analysis of variance
(ANOVA)
followed by Duncan’s multiple range test at the 95% confidence level. A
rarefaction curve and Venn diagram based on OTU matrices were generated
using Mothur 1.30.2. Principal co-ordinates analysis (PCoA) and distance
heatmap plots were employed to visualize variation in botanical
community across samples. To examine trends in RRA of items in the sheep
diet, the data set was reduced to RRAs of the twenty most dominant taxa,
which together comprised over 97% of all plant taxa sequences. Then, we
conducted two-way ANOVA using GLM with Duncan’s multiple range test to
identify significant differences in RRA of predominant plant items
between grazing patterns and grazing periods. These statistical analyses
were performed with SPSS Statistics version 17.0 (IBM, Armonk, NY). The
fatty acid and RRA profiles were reported as mean values ± SEM.
Additionally,
multivariate statistical analyses were conducted to interpret the
relationships between variables and treatments using CANOCO for Windows
version 4.56 (Leps, & Smilauer, 2003). The main gradients of variation
in grazing treatments were described by principal component analysis
(PCA). Redundancy analysis (RDA) was performed to determine the
responses of herbage taxa and fatty acids to grazing treatment. The
treatment combinations of herbage taxa (based on RRA metrics) and the
treatment combinations of muscle PUFAs at the end of growing season were
used as response variables for PCA and RDA. Monte Carlo tests were
conducted in the RDA with restricted random permutations of samples. The
correlation matrix was calculated in both PCA and RDA. Pearson
correlation coefficients were also employed to analyze the relationship
between diet taxa and muscle PUFAs. P < 0.05 was
considered statistically
significant.
Figures were generated with OriginPro version 9.5.1 software (OriginLab
Corporation, USA).