NDLI: Domestication potential of Marula (Sclerocarya birrea subsp. caffra) in South Africa and Namibia: 3. Multiple trait selection

Content Provider	Springer Nature Link
Author	Leakey, Roger
Copyright Year	2005
Abstract	An understanding of the inter-relationships between the traits characterising tree-to-tree variation in fruits and kernels is fundamental to the development of selected cultivars based on multiple trait selection. Using data from previously characterised marula (Sclerocarya birrea) trees in Bushbuckridge, South Africa and North Central Region of Namibia, this study examines the relationships between the different traits (fruit pulp, flesh/juice mass, and nut shell and kernel mass) as a means to determine the opportunities to develop cultivars. Strong and highly significant relationships were found between fruit mass and pulp mass in trees from South Africa and Namibia, indicating that size is a good predictor of fruit pulp production. However, fruit size is not a good predictor of nut or kernel production, as there were weak relationships between fruit and nut and/or kernel mass, which varied between sites and landuses. Generally, the relationships between fruit mass and kernel mass were weaker than between fruit mass and nut mass. Relationships between kernel mass and shell mass were generally weak. The lack of strong relationships between fruit and kernel mass does, however, imply that there are opportunities to identify trees with either big fruits/small nuts for pulp production, or trees with large kernels in relatively small fruits for kernel oil production. However, within fruits from the same tree, nuts could contain 0–4 kernels, indicating that even in trees with an inherent propensity for large kernels, improved pollination may be required to maximise kernel mass through an increase in kernel number. Finally, the relationships between percentage kernel oil content and the measured morphological traits were also very weak. The conclusions of these results are that there is merit in identifying different combinations of traits for the selection of trees producing either pulp or kernels. Consequently, fruit and kernel ‘ideotypes’ are presented as guides to the selection of elite trees for cultivar development. These results have important implications for the domestication of the species as a producer of fruits or kernels for food/beverages or cosmetic oils.
Starting Page	51
Ending Page	59
Page Count	9
File Format	PDF
ISSN	01674366
Journal	Agroforestry Systems
Volume Number	64
Issue Number	1
e-ISSN	15729680
Language	English
Publisher	Kluwer Academic Publishers
Publisher Date	2005-01-01
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Cultivar Domestication Ideotype Indigenous fruits Kernel oil Agriculture Forestry
Content Type	Text
Resource Type	Article
Subject	Forestry Agronomy and Crop Science

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Domestication potential of Marula (Sclerocarya birrea subsp caffra) in South Africa and Namibia: 2. Phenotypic variation in nut and kernel traits

Domestication potential of Marula (Sclerocarya birrea subsp caffra)in South Africa and Namibia: 1. Phenotypic variation in fruit traits

Population status and gender imbalance of the marula tree, Sclerocarya birrea subsp. caffra in northern Namibia

A review of the proximate composition and nutritional value of Marula (Sclerocarya birrea subsp. caffra)

Communities and Conservation: Marula Trees (Sclerocarya birrea subsp. caffra) Under Communal Management at Matiyane Village, Limpopo Province, South Africa

Microbial and Chemical Dynamics during Marula Wine Fermentation

Preliminary examination of factors affecting Agrobacterium tumefaciens-mediated transformation of marula, Sclerocarya birrea subsp. caffra (Anacardiacease)

New record of Ganoderma colossum associated with Sclerocarya birrea dieback

Characterisation of phenotypic variation in marula (Sclerocarya birrea) fruits, nuts and kernels in South Africa and Namibia

Domestication potential of Marula (Sclerocarya birrea subsp. caffra) in South Africa and Namibia: 3. Multiple trait selection

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