Related Experiment Video
Updated: May 6, 2026

Sampling Soils in a Heterogeneous Research Plot
Published on: January 7, 2019
A method of analyzing cultivar x location x year experiments: a new stability parameter
1Research Branch, Agriculture Canada, Engineering and Statistical Research Centre, K1A OC6, Ottawa, Canada.
Abstract:
Assessment of cultivar performance in a cultivar x location x year experiment is often difficult because of the presence of a location x year interaction. Our objective is to demonstrate a method on separation of environment effects (location x year) into predictable and unpredictabel components. The analysis consists of two parts: (1) a regression analysis based on location effects (averaged over years), assuming that the location means represent predictable environmental variation; and (2) the estimation of stability (denoted type 4) based on the years within location mean squares, assuming that years within location represent unpredictable environmental variation. From the regression analysis in (1), a breeder can determine the optimum range of locations in which a cultivar is well suited, and from (2) he can choose the most stable cultivars. The advantage of type 4 stability is that it is independent of the other cultivars included in the test and of the regression coefficient estimated for predictable variation. Three sets of published data are used to illustrate the analysis. Type 4 stability is compared with type 3 stability (deviation mean square from regression on environmental index) for genetic consistency. The analyses suggest that type 4 stability is consistent and is therefore a potential genetic parameter, but type 3 stability is not.
Related Concept Videos
Variability: Analysis
The range is a simple measure of variability, indicating the difference between the highest and...
Variation
When independent and dependent variables are plotted on a scatter plot, the slope of a line is a value that describes the rate of change between the two...
Methods of Medium Optimization
Multiple Regression
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Regression Analysis
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
Residuals and Least-Squares Property
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...

