Mean germination percentage and number of seeds per time interval
Source:R/MeanGermPercent.R
MeanGermPercent.Rd
Compute the following metrics:
MeanGermPercent
Mean/average germination percentage per unit time (\(\overline{GP}\)) (Czabator 1962) .
MeanGermNumber
Number of seeds germinated per unit time (\(\overline{N}\)) (Khamassi et al. 2013) .
Usage
MeanGermPercent(
germinated.seeds,
germ.counts,
total.seeds,
intervals,
partial = TRUE
)
MeanGermNumber(germ.counts, intervals, partial = TRUE)
Arguments
- germinated.seeds
Number of germinated seeds
- germ.counts
Germination counts at each time interval. Can be partial or cumulative as specified in the argument
partial
.- total.seeds
Total number of seeds.
- intervals
The time intervals.
- partial
logical. If
TRUE
,germ.counts
is considered as partial and ifFALSE
, it is considered as cumulative. Default isTRUE
.
Value
The value of mean germination percentage as % \(\mathrm{time^{-1}}\) or mean number of seeds per time interval as \(\mathrm{count \, time^{-1}}\).
Details
Mean germination percentage per unit time (\(\overline{GP}\)) is computed as follows (Czabator 1962) .
\[\overline{GP} = \frac{GP}{T_{k}}\]
Where, \(GP\) is the final germination percentage, \(T_{k}\) is the time at the \(k\)th time interval, and \(k\) is the total number of time intervals required for final germination.
Mean number of seeds germinated per unit time (\(\overline{N}\)) is computed as follows (Khamassi et al. 2013) .
\[\overline{N} = \frac{N_{g}}{T_{k}}\]
Where, \(N_{g}\) is the number of germinated seeds at the end of the germination test, \(T_{k}\) is the time at the \(k\)th time interval, and \(k\) is the total number of time intervals required for final germination.
References
Czabator FJ (1962).
“Germination value: An index combining speed and completeness of pine seed germination.”
Forest Science, 8(4), 386–396.
Khamassi K, Harbaoui K, Jaime ATdS, Jeddi FB (2013).
“Optimal germination temperature assessed by indices and models in field bean (Vicia faba L. var. minor).”
Agriculturae Conspectus Scientificus, 78(2), 131–136.
Examples
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
y <- c(0, 0, 0, 0, 4, 21, 31, 38, 39, 39, 40, 40, 40, 40)
int <- 1:length(x)
# From partial germination counts
#----------------------------------------------------------------------------
MeanGermPercent(germ.counts = x, total.seeds = 50, intervals = int)
#> [1] 5.714286
MeanGermNumber(germ.counts = x, intervals = int)
#> [1] 2.857143
# From cumulative germination counts
#----------------------------------------------------------------------------
MeanGermPercent(germ.counts = y, total.seeds = 50, intervals = int, partial = FALSE)
#> [1] 5.714286
MeanGermNumber(germ.counts = y, intervals = int, partial = FALSE)
#> [1] 2.857143
# From number of germinated seeds
#----------------------------------------------------------------------------
MeanGermPercent(germinated.seeds = 40, total.seeds = 50, intervals = int)
#> [1] 5.714286