Simulating Agricultural Land Use Changes in Thailand
Results and Discussion:
In the estimation of the agricultural productivity, the value of the harvest index determines the economic yields of the respective crops. The
harvest index depends on a number of factors like the genetic potential of the , crop -whether high yielding or low yielding and water regime -rainfed or irrigated. These are inherent to the crop variety in use and can be referred to as the unconstrained harvest yield index. But then, the level of agricultural inputs along with the soil conditions and topography also contribute to the harvest index at a given location, these can be referred to as the constraint factors. Then the harvest index (Hi) can be said to be a combination of the unconstrained yield index and the constraint factors. The harvest index ranges are given in the Table 1.
Table 1. Harvest Index of high yielding cultivars under rain fed conditions and the average harvest index of the calibrated values.
* Fresh Tuber at 35 percent dry weight
| Crop |
Product |
Harvest Index |
Average Index |
| Phaseolus Bean(inc. Mung Bean) |
Grain |
0.25-0.35 |
0.079 |
| Soybean |
Grain |
0.30-0.40 |
0.151 |
| Rice |
Grain |
0.25-0.35 |
0.259 |
| Cassava |
Tuber |
0.50-0.60 |
0.766 |
| Maize |
Grain |
0.30-0.40 |
0.198 |
| Sorghum |
Grain |
0.20-0.35 |
0.108 |
In the model simulation of the agricultural productivity, the harvest index has been first estimated and then calibrated. The village based point data for Rice and Cassava were obtained for the crop year 1990-91 and these values have been used to calibrate the harvest index of these crops. The yield values were calibrated for other major crops from the provincial values of the yield. The average harvest indexes for all crops and rice are also shown in Table 1.
Based on the calibrated harvest indexes obtained, we calculated the distribution of the yields for all the. major crops and rice. Fig 2 shows the productivity distribution for rice. From these distributions of the productivities, were obtained the income distributions for three different cropping patterns, which was then compared with the land use patterns to determine the crop distribution. Fig 3. shows the distribution of the cropping patterns for the year of 1990.
Fig 2. Productivity distribution of Rice
Fig 3. Cropping Pattern in 1990
Conclusion
The climatic-based crop productivity estimation relations were formulated. The results show that the determination of the harvest index plays a significant role in such relations. As such, efforts must be made to suitably modify this factor to take into account the additional agricultural inputs such as fertiliser ,etc to increase the yield. The quality of the datasets is of importance in these studies and so it is required to update the datasets to get a better understanding of the cropping patterns .
Reference
-
Anonymous (1978), Report on the Agro-Ecological Zones Project. Food and Agricultural Organization of the United Nations, World Soil Resources Report 48, Rome.
- Rik Leemans and A.M. Solomon: Modeling the Potential Change in Yield and Distribution of the Earth's Crops under a warmed Climate: Climate Research Vol.3, 1993
- R. Leemans and G.J. van den Born: Determining the Potential Distribution of Vegetation, Crops and Agricultural Productivity: Water, Air and Soil Pollution Vo176, 1994
- Office of Agricultural Economics, Bangkok, Thailand. Agricultural Statistics
of Thailand.
