Identifying isoyield environments for field pea production
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...
| Main Authors: | , , , , |
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| Format: | Journal Article |
| Language: | Inglés |
| Published: |
Wiley
2005
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/91856 |
| _version_ | 1855537253204361216 |
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| author | Yang, R. Blade, S. Crossa, J. Stanton, D. Bandara, M. |
| author_browse | Bandara, M. Blade, S. Crossa, J. Stanton, D. Yang, R. |
| author_facet | Yang, R. Blade, S. Crossa, J. Stanton, D. Bandara, M. |
| author_sort | Yang, R. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | 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. |
| format | Journal Article |
| id | CGSpace91856 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2005 |
| publishDateRange | 2005 |
| publishDateSort | 2005 |
| publisher | Wiley |
| publisherStr | Wiley |
| record_format | dspace |
| spelling | CGSpace918562024-05-15T05:12:07Z Identifying isoyield environments for field pea production Yang, R. Blade, S. Crossa, J. Stanton, D. Bandara, M. isoyield groups cultivars genotypes dendrogram clusters nontraditional crops 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. 2005-11 2018-03-23T06:48:54Z 2018-03-23T06:48:54Z Journal Article https://hdl.handle.net/10568/91856 en Limited Access Wiley Yang, R., Blade, S., Crossa, J., Stanton, D. & Bandara, M. (2005). Identifying isoyield environments for field pea production. Crop science, 45(1), 106-113. |
| spellingShingle | isoyield groups cultivars genotypes dendrogram clusters nontraditional crops Yang, R. Blade, S. Crossa, J. Stanton, D. Bandara, M. Identifying isoyield environments for field pea production |
| title | Identifying isoyield environments for field pea production |
| title_full | Identifying isoyield environments for field pea production |
| title_fullStr | Identifying isoyield environments for field pea production |
| title_full_unstemmed | Identifying isoyield environments for field pea production |
| title_short | Identifying isoyield environments for field pea production |
| title_sort | identifying isoyield environments for field pea production |
| topic | isoyield groups cultivars genotypes dendrogram clusters nontraditional crops |
| url | https://hdl.handle.net/10568/91856 |
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