It is important when cultivating winter wheat with excellent milling and breadmaking quality not only to choose the best variety, but also to select the optimum combination of agronomic treatments. Principal component analysis was used to group sixteen artificial "microenvironments", formed from the combination of two water supply levels and eight nutrient levels, on the basis of six quality traits measured in the 3-year (1990-1992) yield of three wheat varieties with different qualities. Correlations were calculated between the principal component variables and the mean values of the quality parameters in order to determine the effect of background variables on quality. The 1st principal component variable had a different influence on breadmaking quality in varieties with good and poor quality. Principal component weights and the results of correlations analysis were used to determine the best agronomic treatment combinations for high-quality production.
|Number of pages||10|
|Publication status||Published - Oct 1 1996|
ASJC Scopus subject areas
- Agronomy and Crop Science