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Identifying Isoyield Environments for Field Pea Production


This article in CS

  1. Vol. 45 No. 1, p. 106-113
    Received: Jan 27, 2004

    * Corresponding author(s): rong-cai.yang@ualberta.ca
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  1. Rong-Cai Yang *a,
  2. Stanford F. Bladeb,
  3. Jose Crossac,
  4. Daniel Stantona and
  5. Manjula S. Bandarad
  1. a Alberta Agriculture, Food and Rural Development, Room 300, 7000–113 Street, Edmonton, AB, Canada T6H 5T6, and Dep. of Agricultural, Food and Nutritional Science, Univ. of Alberta, Edmonton, AB, Canada T6G 2P5
    b Crop Diversification Centre North, Alberta Agriculture, Food and Rural Development, RR6, 17507 Fort Road, Edmonton, AB, Canada T5B 4K3
    c Biometrics and Statistics Unit, International Maize and Wheat Improvement Center (CIMMYT), Apdo. Postal 6-641, 06600 Mexico D.F., México
    d Crop Diversification Centre South, S.S. #4, Alberta Agriculture, Food and Rural Development, Brooks, AB, Canada T1R 1E6


Cultivars are often recommended to producers based on their averaged yields across sites within a geographic region. However, this geography-based approach gives little regard to the fact that not all sites in a given region have the same level of production capacity. The objective of this paper was to describe a performance-based approach to identifying groups of sites with similar yielding ability (i.e., isoyield groups), but not necessarily contiguous, and its use for analyzing the yield data from field pea (Pisum sativum L.) cultivar trials conducted across the Province of Alberta, Canada, from 1997 to 2001. Of 34 sites tested during the 5 yr, 11 were in 1997, 20 in 1998 and 2000, 22 in 1999, and 21 in 2001. The consecutive use of regression analysis and cluster analysis allowed for classification of test sites in individual years into different isoyield groups: six in 1997; 10 in 1998, 2000, and 2001; and 12 in 1999. However, the most meaningful isoyield groups were those based on the data across the 5 yr through a normalization procedure developed for averaging the multiyear unbalanced data. The use of such averages significantly lessens the impact of random year-to-year variation on the sites, resulting in only seven isoyield groups for the 34 test sites. The identification of isoyield environments (i) facilitates choosing appropriate cultivars for specific environments and (ii) provides a basis for scaling down the cultivar testing program in Alberta.

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