Common Garden Phenotypic Measurements and Statistics
All the seeds were sterilized and planted into pots under 12:12
light:dark conditions 25 °C/20 °C for 3 months. To obtain sufficient
leaves and flowers, we transplanted the plants to outdoor agricultural
fields at Northeast Normal University. For phenotypic measurement, 7
regenerative traits and 4 vegetative traits of different populations in
the experimental field during the full flowering stage were measured. To
ensure the accuracy of the measurements, we randomly selected 3-5 plants
from each population to measure the number of inflorescences and plant
height; among these plants, 6 flowers and 6 leaves were randomly
selected from each plant, and the corolla diameter, pistil length,
stamen length, leaf area, leaf perimeter and chlorophyll content were
measured and recorded. Among these 6 flowers, we randomly selected 3
petals and calyxes to measure petal length (not including spurs), calyx
length, spur length and calyx length.
To reduce the error caused by different measurement batches, we used a
mixed linear model to evaluate traits in the lme4 (Bates, Mächler,
Bolker, & Walker, 2014) package in R according to the following
regression model equation:
\begin{equation}
Y_{i}=\mu+\beta_{1}+\beta_{2}P+\varepsilon_{i}\nonumber \\
\end{equation}where\(Y_{i}\) represents the traits of different populations, \(\mu\) is the
actual measurement, \(\beta_{1}\) and \(\beta_{2}\) are regression
coefficients, A represents the measurement batches, P is the person
conducting the measurement, and \(\varepsilon_{i}\) is the residual
variance. The evaluation results were used for ANOVA and K-means cluster
analysis in R.