cassava_CC | R Documentation |

An example germplasm characterisation data of a core collection generated
from 1591 accessions of IITA Cassava collection
\insertCitebenjamin_cassava_2019EvaluateCore using 10 quantitative and 48
qualitative trait data with CoreHunter3
(`corehunter`

). The core set was generated using
distance based measures giving equal weightage to Average
entry-to-nearest-entry distance (EN) and Average accession-to-nearest-entry
distance (AN). Includes data on 26 descriptors for 168 (10 % of
`cassava_EC`

) accessions. It is used to demonstrate
the various functions of `EvaluateCore`

package.

cassava_CC

A data frame with 58 columns:

- CUAL
Colour of unexpanded apical leaves

- LNGS
Length of stipules

- PTLC
Petiole colour

- DSTA
Distribution of anthocyanin

- LFRT
Leaf retention

- LBTEF
Level of branching at the end of flowering

- CBTR
Colour of boiled tuberous root

- NMLB
Number of levels of branching

- ANGB
Angle of branching

- CUAL9M
Colours of unexpanded apical leaves at 9 months

- LVC9M
Leaf vein colour at 9 months

- TNPR9M
Total number of plants remaining per accession at 9 months

- PL9M
Petiole length at 9 months

- STRP
Storage root peduncle

- STRC
Storage root constrictions

- PSTR
Position of root

- NMSR
Number of storage root per plant

- TTRN
Total root number per plant

- TFWSR
Total fresh weight of storage root per plant

- TTRW
Total root weight per plant

- TFWSS
Total fresh weight of storage shoot per plant

- TTSW
Total shoot weight per plant

- TTPW
Total plant weight

- AVPW
Average plant weight

- ARSR
Amount of rotted storage root per plant

- SRDM
Storage root dry matter

Further details on how the example dataset was built from the original data is available online.

data(cassava_CC) summary(cassava_CC) quant <- c("NMSR", "TTRN", "TFWSR", "TTRW", "TFWSS", "TTSW", "TTPW", "AVPW", "ARSR", "SRDM") qual <- c("CUAL", "LNGS", "PTLC", "DSTA", "LFRT", "LBTEF", "CBTR", "NMLB", "ANGB", "CUAL9M", "LVC9M", "TNPR9M", "PL9M", "STRP", "STRC", "PSTR") lapply(seq_along(cassava_CC[, qual]), function(i) barplot(table(cassava_CC[, qual][, i]), xlab = names(cassava_CC[, qual])[i])) lapply(seq_along(cassava_CC[, quant]), function(i) hist(table(cassava_CC[, quant][, i]), xlab = names(cassava_CC[, quant])[i], main = ""))

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