agridat (version 1.25)

minnesota.barley.yield: Multi-environment trial of barley in Minnesota at 6 sites in 1927-1936.

Description

These data come from barley breeding experiments conducted in Minnesota during the years 1893-1942. During the early years, the experiments were conducted only at StPaul. By the late 1920s, the experiments had expanded to 6 sites across the state.

Format

A data frame with 647 observations on the following 4 variables.

site

site factor, 6 levels

gen_name

genotype name

gen

genotype (CI cereal introduction ID)

year

year

yield

yield in bu/ac

Details

The lattice package contains a smaller version of this data for the years 1931 and 1932.

This is an expanded version of the barley data that is often used to illustrate dot plots.

The following comments are in reference to the mentioned source documents.

----- Notes about Immer (1934) -----

The University Farm location is at Saint Paul.

This source provides the yield data for each of the three blocks at each location in 1931 and 1932. The following registration numbers and names are given:

C.I. number	Variety name
Minn 184	Manchuria
Minn 445	Glabron
Minn 440	Svansota
Minn 447	Velvet
Minn 448	Trebi
Minn 457	Manchuria x Smooth Awn
Minn 462	Smooth Awn x Manchuria
Minn 452	Peatland
Minn 475	Svanhals x Lion
Minn 529	Wisconsin No 38

----- Notes from Harlan et al (1925) -----

The data from these early tests are accurate at some stations, but may have problems at other stations. (p. 14).

Identification of many varieties is inadequate...the chance of their being incorrectly identified is small...Officials of the StPaul station have expressed a desire that conclusions be drawn from the yields only when the limitations of the earlier experiments are taken into full consideration. (p. 72)

The Chevalier and Hanna varieties are not well adapted for StPaul (p. 73).

----- Notes from Harlan et al (1929) -----

----- Notes from Harlan et al (1935) -----

The 1931 yields match the average values of Immer (1934).

The Minnesota 474 and 475 cultivars are both 'Svanhals x Lion' crosses.

No yields are reported at Crookston in 1928 because of a crop failure. (Page 20)

Also, in the report for North Dakota it says "the zero yields at Williston, ND in 1931 were caused by drought". (Page 31)

----- Notes from Wiebe et al (1935) -----

----- Notes from Wiebe et al (1940) -----

The 1932 data generally match the average values from Immer (1934) with the following notes.

The data for Glabron at St Paul in 1932 are missing, but given as 36.8 in Immer (1934). This value is treated as missing in this R dataset.

The data for Svansota at Morris in 1932 are missing, but given as 35.0 in Immer (1934). This value is treated as missing in this R dataset.

The yield for 'Wisconsin 38' at St Paul in 1932 is shown as 3.80, but 38 in Immer (1934). The latter value is used in this R dataset.

The yields for No475 in 1932 are not reported in Wiebe (1940), but are reported in Immer (1934).

No yields are reported at Morris in 1933 and 1934, because of a crop failure owing to drought.

----- Notes from Hayes (1942) -----

This source gives the block-level yield data for 5 cultivars at 4 sites in 1932 and 1935. Cultivar 'Barbless' is the same as 'Wisconsin No38'.

References

Immer, R. F. and H. K. Hayes and LeRoy Powers. (1934). Statistical Determination of Barley Varietal Adaptation. Journal of the American Society of Agronomy, 26, 403-419. https://doi.org/10.2134/agronj1934.00021962002600050008x

Hayes, H.K. and Immer, F.R. (1942). Methods of plant breeding. McGraw Hill.

Kevin Wright. (2013). Revisiting Immer's Barley Data. The American Statistitician, 67, 129-133. https://doi.org/10.1080/00031305.2013.801783

Examples

if (FALSE) {

library(agridat)

data(minnesota.barley.yield)
dat <- minnesota.barley.yield
dat$yr <- factor(dat$year)

# Drop Dryland, Jeans, CompCross, MechMixture because they have less than 5
# year-loc values
dat <- subset(dat, !is.element(gen_name, c("CompCross","Dryland","Jeans","MechMixture")))
dat <- subset(dat, year >= 1927 & year <= 1936)
dat <- droplevels(dat)

# 1934 has huge swings from one loc to the next
libs(lattice)
dotplot(gen_name~yield|site, dat, groups=yr,
        main="minnesota.barley.yield",
        auto.key=list(columns=5), scales=list(y=list(cex=.5)))
}