Quandong is a native unique tree that is found in Australia. Santalum acuminate is a short tree that has an average height about 6m. The plant is also characterized by light green leaves and red fruits that are edible. Quandong tree bears spherical fruits that measure about 20 to 30mm. Quandong fruits are renowned for their tart taste. The fruits are highly rich in vitamin C and carbohydrates. Quandong is a drought resistant plant that grows well in the southern and western parts of Australia. The tree usually blossoms and flowers from the month of August to November (as reported by Bailey in 2001). Quandong tree has parasitic nature; it depends on a host in order to grow successfully. The trees’ products are well-known for their medical advantage (National Research Council of US 1990). Quandong yields were frozen, dried and eaten in their raw state by the Australian European settlers. The foodstuffs were taken in the form of jam, liquor, or even a pie. Some products are also taken in the form of sweets.
There has been a substantial growth in the Quandong industry due to the extensive market. The industry has not been able to meet all the needs in the Australian market. Quandong trade is very significant in the Australian native food industry. There has been an extensive research done on the Quandong tree and its products. Nutrient oxidation activity for Quandong tree is 6.5 higher than that of the other fruit trees such as blueberry. About 50,000 Quandong trees were used in commercial trade by the end of 1999. This shows growth in Quandong production. The growth led to a higher profitability of about 0.7-1.3 million dollars in the Quandong industry (cited in the Lethbridge & Randell 2003).
There are many hindrances to the growth of the Quandong industry. Most limitations can be attributed to the lack of sufficient scientific information. The growth of the Quandong industry is greatly limited by the trees’ poor fertility (Williams and Adam publishing, 2010). In addition, it is very difficult to graft the Quandong tree. Small yields can also be attributed to the fact that the tree undergoes a juvenile growth period of about 3-5 years (Maiden, 1999).
Although there are various challenges, the researchers have succeeded in running the Quandong orchard effectively. Ferguson and Bailey performed a number of experiments on the Quandong moth for about three years. They observed different types of moth that occur at different times. This was done in comparison to the timing of the pesticide. Lethbridge and Randell studied eight acacia species to determine the best host for the Quandong tree. The Quandong tree has a problem of drying while at the nursery state according to the observation of Warren and Ryder in their experiments. Another realization that was made is that soil-borne pathogens readily reproduce due to the insufficient watering of the Quandong seedlings. In relation to the executed tests, this paper determines the best site for the establishment of an effective Quandong industry using ArcGIS. Some of the constraints used in the study were the gradient of the land and the distance from the sealed roads. These parameters were varied throughout the experiment in order to get the best results. Annual precipitation and soil texture were the constant conditions that were used in the research.
This study was conducted by the school of environmental studies. The GIS study area is about 40km east of Adelaide. The rectangular shaped area measures about 372 square kilometers. The study area has a maximum temperature of 29.3 degrees Celsius and a minimum temperature of 5.4 degrees Celsius. The site hotness was measured by the metrological bureau of Australia (Australian Government Bureau of Metrology). The area is characterized by the wet winter and hot dry summer. The semi arid climate experienced in the selected region favors the growth and production of Quandong. Sandy loam soil forms the greatest percentage in the area i.e. 68.2%; loamy sand soil forms 18.7%, sand soil forms about 10.7%, and there are traces of other soils as shown in table 1. Sandy loam soil is the most ideal for the growth and production of the Quandong tree.
Spatial Analysis method was used to determine the best location for growth and development of the Quandong. This was realized by the use of criteria modeling program (ArcGIS Version 10). Four conditions were focused in this experiment whereas there are other factors that could have improved the accuracy of the results obtained. The conditions considered in the study include the annual precipitation of the region, the slope of the land, soil texture, and accessibility of the preserved roads. Raster data cell size used in the study was 60m. The resultant co-ordinate system that was prepared for the project is ‘GDA 1994 MGA Zone 54’.
This is the first constraint condition that was considered in the study. The Quandong tree can withstand semi arid conditions. However, the tree gets infected by a number of pathogens in dry conditions. Pathogens are more destructive in the areas that have a low or inadequate water supply (Evans, 2006). The most appropriate annual precipitation for this study ranges from 250mm to 500mm. The school of environmental studies prepared a data set of 10 levels in order to make a sensible conclusion.
A good soil texture should have a high rate of water infiltration. For that reason, soil texture is very significant in the growth of the Quandong tree. Soil texture is a factor that should not be disregarded in the determination of the best location for Quandong production. Apart from having sufficient soil moisture, water should be appropriately drained. Therefore, not all soil types can favor the growth of the Quandong. The most ideal soil textures are the sandy loam soils, the loamy sand soils and sand clay ones. TEXT-SURF system developed by the school of Environment was used in the soil texture classification.
Land Slope (a preference and constraint condition)
Plant growth is highly determined by the nature of the sloppy the land. Some plant species grow well on steep slopes, while others flourish on low lands. Slope of a given piece of land affects the drainage system of the given area. The reason is that the speed of water flow is directly proportional to the gradient of the land. The favorable inclination angle ranges from 2 to 20 degrees, i.e. the preference slope condition. A gentle slope was thus selected as the constraint condition. A Digital Elevation Model (DEM) was designed in order to produce a raster slope map. DEM data was processed with the help of a spatial analytical means. With reference to the most suitable slope angles, a correlation linking the inclination angle and the desired value was defined as linear and negative.
Ease of Access From the Sealed Roads
This is a preference condition. The Quandong orchard should be located very close to the sealed roads. The reason is that delivery costs greatly affect the commercial usage of the Quandong tree. Locating the Quandong orchard very far from the prepared roads will lead to the high transport costs that could be avoided. The distance from the sealed roads was calculated by the use of the spatial analysis tool with a vector of the prepared roads data. The Euclidean distance tool was quite helpful in the determination of the raster road distance data. A correlation for the favorite value and the road distance was also done.
A raster calculator tool was used to perform integration for the five layers selected. The digital calculator has two Boolean logic operations: ‘AND’ and ‘OR’. Each of the five layers is assigned to either zero or one, in order to establish whether it is suitable or not. The values for road accessibility and gradient preference were used as variables in the creation of three models. Three verification checks were then conducted for each layer.
The weighting conditions for all the models are specified in table 2. Figure 2 shows the findings of the criteria modeling. From the results obtained, the most favorable site for the production of Quandong stretches from southwest to northeast of the area under study. When the results were analyzed, it was discovered that the road accessibility was a key concern at the northern part of the study area. The effect of slope is not a key factor in the production of the Quandong according to the obtained results. Table 3 shows the criteria and modeled values at three different points used in the study. Location 1 has the most desirable slope condition but a bad road condition. Location 2 is quite accessible to the sealed road but has an unsuitable gradient or slope condition. Location 3 has a very preferable both slope and road condition; this makes it the best site for the production of Quandong.
From the results obtained, the northeastern part of the study area is more vulnerable to the road condition than the southwestern part. It was discovered that the slope condition was insignificant in the production of Quandong. This makes the southwestern region to be the most ideal for the production of Quandong. However, it is worth noting that modeling results are solely dependent on the weights of the slope together with the road preferences. The northeastern part has a good slope for the Quandong production. The three locations can be easily accessible if the sealed roads were built on each site. Therefore, location 1 will become the most favorable site with a preferable road condition. To conclude, one should be very prudent when determining the best location for the production of Quandong; each condition criterion should be thoroughly checked to establish its reasonableness.
The accuracy of the findings may vary when the points of the study area are generated by the modeling. The degree of accuracy is reduced by using many criteria layers. The reason is that more errors are expected to accumulate from conversion, generalization, and other sources. The ‘error of propagation’ is the right term used to refer to the modeling errors that occur (Longley et al. 2011). For that reason, modest results should be verified by manual computation. A comparison between the manually calculated results and the modeled results is shown in table 4. The variance between the model and manual results was less than one percent in this study. This implies that there is a high degree of confidence in the modeling results obtained.
Challenges Faced in the Study
This research was based on four constraints. Actually, there are more conditions that affect the growth of the Quandong such as suitability of the host trees. More conditions should be considered in the study (Rural Industries Research and Development Corporation, 2007). Quandong grafting is also another important aspect that should be considered (Ferguson & Bailey 2001).
With regard to the existing layer, soil texture layer can also serve as a preference layer. Significant rates of infiltration can be obtained from the soil texture information based on the FAQ (1979) empirical data. It is easier and better to use the infiltration data instead of the soil texture data. because the reason is that the infiltration data can be used to do a comparison for one unit. The findings of this modeling do not show the ultimate reality owing to its cell size. More accurate results can be obtained by the use of a smaller cell size. In addition, it is worth noting that the accuracy issue is always inevitable with the use of a GIS tool in the decision making process.
The most suitable site for the production of Quandong is the region between southwest to the northeast of the study area. This is evident according to the results obtained from criteria modeling with the road distance condition, annual precipitation condition, slope condition, and the soil texture condition. The southwestern region is the most favorite for the growth of the Quandong according to the three modeling tests done. Consequently, three virtual production locations were selected for the production of the Quandong on the southwestern part. Location 3 was found to be the most appropriate. Location 1 had the best slope preference; it can be the best location after the construction of an access road in the region. Additional factors should be included in the research in order to obtain accurate results. For that reason, a more extensive research should be done for the production of Quandong with GIS analysis.