The present study was conducted in Umfakarin natural forest reserve, South Kordofan, Sudan. The main objective was to investigate the possibility of managing Acacia seyal Del. variety seyal for the production of gum talha. Three stand densities (strata), namely dense, medium, and slight, were distinguished based on the number of trees per hectare. During the sampling phase, the study adopted the method of identifying the competitors (neighboring trees) from the subject one (trees selected for gum production experiments). From the three stand densities, a total of 482 subject trees, covering variable diameter ranges (d= 9-11.5, 13.5-16, 18-20.5 and above 21 cm) were selected, based on the diameter at 0.25 m height (d0.25). In each stratum, competitor trees were identified within a radius equal to the height of subject tree multiplied by a factor (1.25). The diameter at breast height, height to crown base, height, crown radii, and tree coordinates were measured for each of the subject trees and its competitors. Subject trees were exposed to tapping on first of October, the fifteenth of October, and the first of November, using local tools (Sonki and Makmak). Additionally, untapped trees were used as controlling-variables. The initial gum collection was completed fifteen days after the tapping, while the subsequent (7-9 pickings) were done at an interval of fifteen days.
Six stand height functions were tested and the results illustrated that the Michailow stand height function was suitable for predicting the height of Acacia seyal in Umfakarin natural forest. The predictive ability of this height function ranged from 19.3% to 24%. The volume function used in this study was able to predict the volume of standing trees with more than 92 percent accuracy.
Competition among trees of Acacia seyal was assessed in terms of competition indices. Eight competition indices were quantified using the CroCom program. The relationship between these indices and tree dimensions (diameter at breast height, height and crown diameter) was tested using logarithmic models. Among these indices, the Hegyi_2 index is considered a suitable index to be applied for estimating the degree of competition in natural stands of A. seyal of dense stratum when using diameter at breast height as a predictor. About 70% of the total variability is explained by this logarithmic model.
Gum yielded by each subject tree per season was obtained by summing up the gum samples collected from all pickings. Gum production per unit area was also determined. Regression tree, general linear model (GLM) and logistic regression techniques were used for analyzing the obtained data. The results of the study indicated that the gum yield is independent of stand density. Tapping has influence on gum yield. Trees tapped by sonki on the first of October at medium stand density have the highest gum with an average value of about 56 g/tree/season. Significant difference (p = 0.021) was detected between two groups of dates; the first of October and first of November in medium stand density. The results also revealed that the most important variable influencing gum production was found to be diameter at breast height with 23.95 cm threshold. Between 41-53 percent of subject trees produce gum less than 50 g/season. The results indicated that A. seyal species produces a very low quantity of gum talha (3.6-4.8 kg/ha) and for economic reasons, its tapping is not recommended. The findings of the regression analysis revealed to a model which could be used to estimate the yield of gum talha from A. seyal natural stands in the Umfakarin forest, South Kordofan, Sudan. Conducting experiments on the production of gum talha in permanent plot trials in different climatic regions of the Sudan is highly recommended.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:25592 |
| Date | 04 May 2011 |
| Creators | Hamed Mohammed, Mohammed |
| Contributors | Röhle, Heinz, Ballal, Mohamed El Mukhtar, Technische Universität Dresden |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
Page generated in 0.0025 seconds