The utility of the predictive decapitation test as a tool for early genetic selection for Hypsipyla tolerance in big-leaf mahogany (Swietenia macrophylla King)
Cornelius, Jonathan P. (2009) The utility of the predictive decapitation test as a tool for early genetic selection for Hypsipyla tolerance in big-leaf mahogany (Swietenia macrophylla King). Forest Ecology and Management, 257 (8). pp. 1815-1821.
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The plantation silviculture of mahogany (Swietenia spp.) has been severely limited by the attack of the mahogany shoot borer (Hypsipyla spp.), which greatly reduces or nullifies the commercial timber value of attacked trees by causing forking low on the stem. Selection for resistance, including tolerance (the capacity to retain apical dominance after attack), is widely considered to have potential as one element in an integrated pest management system. It has been suggested that the response of young seedlings to a predictive decapitation test might be useful as a means of detecting genotypes with high tolerance. This paper describes a pilot provenance/progeny experiment aimed at exploring this hypothesis. The number of shoots produced in response to attacks in the first year of field growth by Costa Rican material was found to be significantly correlated with response to decapitation in the nursery, on both individual tree and family mean bases. It appears, therefore, that the decapitation test could have a role in early selection for tolerance of Hypsipyla in mahogany. However, the presence of within-provenance genetic variation in response to Hypsipyla attack was not established.
|Item Type:||Article (Refereed Research - C1)|
|Keywords:||tropical biology; indirect selection; Meliaceae; insect pests; resistance breeding|
|Date Deposited:||13 May 2010 23:06|
|FoR Codes:||07 AGRICULTURAL AND VETERINARY SCIENCES > 0705 Forestry Sciences > 070507 Tree Improvement (Selection and Breeding) @ 100%|
|SEO Codes:||82 PLANT PRODUCTION AND PLANT PRIMARY PRODUCTS > 8201 Forestry > 820101 Hardwood Plantations @ 100%|
|Citation Count from Web of Science||