Principles of Plant Genetics and Breeding

426 CHAPTER 23
Russell Freed
Data management is crucial for a successful plant breeding program. Plant breeders must design and analyze experiments, print
labels and field books, and manage pedigree and other information about different plant populations. As computers came into
use in the early 1980s, there was a need for a standard management and statistical package for plant breeders. Russell Freed at
Michigan State University along with Oivend Nissen from Norway developed a basic program that incorporated the principles of
good plot design and appropriate statistical analysis. As advances in data management and computer technology occurred,
MSTAT became what it is today: a tool to help plant breeders develop successful programs through better data management and
analysis. Over the years, MSTAT has been used by thousands of researchers to facilitate the development and identification of
new plant cultivars in over 110 different countries (http://www.msu.edu/~freed/mstatc.htm).
MSTAT helps plant breeders design, manage, and analyze simple and complex experiments. MSTAT is capable of generating
random block designs with one to five factors (0–4 splits), and square or rectangular lattices; and also prints field books and
labels. It enables plant breeders to quickly and accurately determine the biological and economic significance of their experiments.
It can analyze one-way, two-way, factorial, lattice, hierarchical, and non-orthogonal data sets. Figure 1 is a sample output
from the ANOVA-2 program. MSTAT can also calculate correlations, regression, multiple regression, frequency tables, and basic
statistics. MSTAT can analyze data over multiple years and locations with the STABIL program option. This is very important for
breeders to identify the yield stability of promising lines. The ease and speed of data analysis provides timely results and thereby
facilitates the generation of new plant cultivars.
The BRSERIES program keeps pedigree information for population development and will automatically update generation
information. To prepare next year’s planting book, the BRSERIES will ask how many rows need to be planted from the current
year’s book and then automatically updates the generation information and creates a book with the new row numbers. It can print
field books, maps, and labels. MSTAT can also be used to help select parents for the crossing program. Figure 2 is a sample printout
from the BRSERIES.
Title: BEAN EXPERIMENT
Function: ANOVA-2
Data case 1 to 120
Two-way Analysis of Variance over
variable 2 (REPLICATION) variable 1 (ENTRY) Variable 4: YIELD
A N A L Y S I S O F V A R I A N C E T A B L E
Degrees of Sum of
Source Freedom Squares Mean Square F-value Prob
REPLICATION 3 5.09 1.697 2.20 0.0939
ENTRY 29 75.34 2.598 3.37 0.0000
Error 87 67.16 0.772
Non-additivity 1 0.36 0.358 0.46
Residual 86 66.80 0.777
Total 119 147.59
Industry highlights
MSTAT: a software program for plant breeders
Department of Crop and Soil Science, Michigan State University, East Lansing, MI 48824, USA
Grand Mean = 3.558 Grand Sum = 427.000 Total Count = 120
Coefficient of Variation = 24.69%
The means of the 4 replications and the 30 varieties are also listed.
Figure 1 MSTAT output from analysis of variance for 30 cultivars and four replications using the ANOVA-2
program.