Home Articles The monthly production potential in the eastern provinces of Thailand,by using the...

The monthly production potential in the eastern provinces of Thailand,by using the rubber production potential models and geo-informatics

Somjate Pratummintra, Prasart Kesawapitak
Rubber Research Institute, Department of Agriculture Chatuchak, Bangkok. 10990
email: [email protected]

Land evaluation is a basic technique and often use for land-use planing and for estimating land productivity for a selected crop. Different empirical modeling approaches to predict land productivity for crops under the wide range of weather and soil conditions have been described (e.g. FAO 1978; De Wit & Van Keulen, 1987; Thomasson & Jones, 1991; Tang et al. 1992; Daroussin et al., 1993). Most of these models are designed to use available climatic and soil information as statistical average and generalized crop phenology. A production situation is a hypothetical land-use system, with one or only a few relevant land characteristics and/or land qualities and the production calculated is not the actual but the potential production.

Geographic Information Systems (GIS) are a set of computer tools for collecting, storing, retrieving at will, transforming and displaying spatial data from the real world. GIS have become quite popular and their use in all countries and are still growing up. Handling the variability in climate conditions and soil information can be approached through the use of GIS. Using the GIS technique, it is possible to produce thematic maps, as an output, with information on the impact of differences in climate and soils on land productivity for a specific crop.

For rubber information system (RIS), climatic and soil profile data were stored in relational database, where as the spatial distribution of soil series units (polygons) is digitized and also stored in topological vector form by using ARC/INFO ver 7.0.

This paper describes the use of GPS technology together with the GIS, which called Geo-informatic system, were applied to study for the pilot project with the variation of potential crop production at regional scale. This is exemplified by the integration of a GIS and a maximum production potential model, which is used for estimation of rubber production potential under varying climatic and soil conditions in East Thailand.

Materials and Methods

  1. Crop model
  2. The Maximum Production Potential (MPP) as described and developed in Pratummintra (2000) and Pratummintra et al. (2000) was used to predict the production potential for rubber. At first, the model was simulated using daily climatic data to quantify the radiation production potential (RPP) and corrected by the site index (soil index). Then, soil physical approach was applied to quantify some parameters in soil water balance, such as crop coefficient for rubber (Kc), crop evapotranspiration (ETc) (Pratummintra et al. 2000), the easily fraction of available soil water storage (p) (Pratummintra et al.2000). These values were used to validate the RPP and yielded the water limited production potential (WPP) model. Finally, the WPP was validated with the number of loss of tapping day and got the MPP model (Pratummintra et al. 2000). This was evaluated for the monthly yield data together with the site index.

  3. GIS Software
    • ARC/INFO ver 7.0 works on Sun workstation was used to manage the coverage and attribute table;
    • ARCVIEW ver 3.1 was used to produce the production potential map;
    • -MS OFFICE PACKAGE was used to prepare the database and the crop model, and was related to the GIS database by using ARCVIEW ver 3.1
  4. The GIS software, which had been introduced for managing and analyzing the database for this study, are:

  5. GPS System
  6. In this study, the GARMIN Etrex GPS, with the accuracy of 10 m, was used to measure the coordinate of the rubber plantation. Then, the circumference of the rubber tree was measured at the 170 cm height above the ground level and the girth average was done from 40 trees for each plantation.

  7. GIS Database
  8. In this study, the digital map of topography, soil, geology and land-use were produced from the existing base map with the different scale. The scale of topographic map was 1:50,000, soil series map was 1:100,000, and geological were 1:250,000 and the land use map was interpreted form remote sensing data at the scale 1:50,000. The spatial distribution of soil mapping units (polygons) was stored in the topological vector form. The climatic and soil profile data were stored in relational databases or in the attribute table. The rubber plantations were project as a coordinate dot.

    The study area is situated in the eastern province of Thailand and covered the area of 2,273,220 ha or 2,273 km2. The annual rainfall varies from more than 4,000 mm in Trad province to about 1,000 mm in Chachoengsao Province.

Result and Discussion

  1. Digital map
  2. This soil series map and its data in an attribute table was used to matching with the table of crop requirement for rubber (Pratummintra, 2000). The results can be chosen for presenting as a map of problem soil as shown with the problem in soil depth (Fig.5) and soil pH (Fig.8). The suitability index was calculated and related with the characteristics of the soil series, and yielded a suitability map for rubber (Fig. 9).

    Pratummintra et al. (2000) were studied the maximum production potential models and was brought to the GIS. With that models, the monthly production map was interpolated from the planting area, which was located with the GPS. The plantation with the rubber age above 7 year was used to calculate monthly yield (Fig. 2 A-D) .

    Figure 2. The Example of the Monthly Production Potential in Muang District, Chantha Buri Province, which show the increasing yield during the exploiting season.
  3. Soil Problem for Rubber Interpretation
  4. The site index of the rubber plantation was was calculated by applying the parametric approach (Pratummntra et al. 2000). Then, the soil characteristics can be defined as the limitation for rubber production, which can be adapted to increase the actual production close to the maximum production (Figure 3 A-D).

    Figure 3 The Limiting Parameter for Rubber Production in Muang District, Chantha Buri Province


  1. Sys, C., Van Ranst, E. and Debaveye, J. and Beernaert, F. 1993. Land Evaluation Part I: Principles in Land Evaluation and Crop Production Calculations. Agricultural Publication No. 7. General Administration for Development Cooperation. Brussel. Belgium. 274 pp.
  2. Pratumminra, S. Van Ranst, E., Verplancke, H., Shamshuddin, J., Z. Sauya and Yew, F.K. 2000. Maximum Production Potential Model for Rubber. International Symposium of Sustainable Soil Management. Mine Resource Hotel, Serdang. 8-10 September, 2000. 15 pp.
  3. Pratummintra, S. 2000. Dynamic Approach in Predicting Production Potential for Rubber: A Case Study in East and Northeast Thailand. The Ph.D. Thesis, Twining Program Ghent University and UPM, Malaysia.