Báo cáo nghiên cứu khoa học " Data collection Guidelines for collecting and checking data " ppt

who plant and use their tree species, to find out which traits are most important to the users z Examples : ¾ stem straightness is not very important for trees grown for pulpwood, but i

Data collection

Guidelines for collecting and

checking data

• wood density, colour

• timber strength, stiffness

Choosing traits for measurement and

assessment

z Breeders aim to achieve genetic improvement in traits of economic

importance

z Breeders need to talk to the people (industry managers, farmers,

etc.) who plant and use their tree species, to find out which traits are most important to the users

z Examples :

¾ stem straightness is not very important for trees grown for pulpwood,

but important for trees grown for sawlogs (bends in the stem reduce the recovery of sawn wood and therefore the value of the log)

¾ dry biomass/hectare, not volume/hectare is important for biomass

energy users

Selecting and breeding for a single

trait, or for multiple traits

z Breeding for a single trait is straightforward - we just rank the trees for the trait and choose the better trees for breeding and propagation

z When breeding for two or more traits we must make

“trade-offs” between traits The tree with the largest stem volume may have very poor stem straightness - should we select this tree, if both traits are important

to the user?

Assessing traits

z Objective or subjective scoring systems?

z Objective - e.g 1 = no flowering

2 = flowering

z Subjective - e.g stem straightness

1 = worst 2% of trees in trial

2 = next best 15% of trees in trial

3 = next best 33% of trees in trial

4 = next best 33% of trees in trial

5 = next best 15 % of trees in trial

6 = best 2 % of trees in trial

Assessing stem straightness - subjective scoring system

worst

Prior to scoring, inspect trial and set proportions of scoring categories to

approximate normal distribution - improves heritability of trait

Stem straightness

1

2

4 3

5 6

⇐ ? ⇒

Axis persistence - objective scoring system

1 = stem axis forks

Forking defined as two or more leaders, stem diameter of smaller leader

is more than 50% of diameter of larger leader just above fork

Data collection

z Indexing information on the field data sheets

treatment information included: replicate number, plot number, tree number, seedlot number, etc.

Indexing in field order - RCB design

Collect data in field order

• Indexing information should be in field order, NOT treatment order

team, to avoid bias

order

z spacing 1.5m between trees within rows

z each seedlot occurs only once in any long column

Latinised row column design for seedling seed orchard with 60 families

Assess the trial

in field order !!!

One line - one tree!

used for each experimental unit (usually

a tree)

diameter are put in columns across the data sheet after the indexing columns

Trees within a plot - same order for each measurement! 1…25

Missing values - enter *

symbol, for correct analysis by Genstat

z If the value is 0 (for example the dbh of a tree which is 1.1 m high) enter 0, not *

Missing trees and variates

repl plot tree seedlot height dbh

Check the data !!!!!!!!!!!!!!!

z Mistakes arise at different stages of the

operation

screen, with somebody checking the field

data sheet against the values which are being read out

General tips for computer analysis of data

z Keep all the files for an experiment in one folder (directory)

z Check to see whether you are operating in the right working

folder/directory

z Keep a back-up copy of important files such as your original data file

z As you will most likely modify the original data file, work with a

copy under a different name e.g benthamii2.xls

z Save your work frequently so it is not lost in a power failure, or if a program crashes

Excel tips

in the block of data you have entered

F2:F4000

Data should make biological

sense! Are these trees OK?

height diameter at diameter at

ground level breast height tree (m) (cm) (cm)