**3.2 Paddy soil variability**

126 Current Issues of Water Management

Precision farming (PF) is considered the best practicable approach to achieve sustainable agriculture. Precision farming is an integrated, information- and production- based farming system that aims to raise efficiency, productivity and profitability of long term, site-specific and whole farm production while avoiding the undesirable effects of excessive chemical

The role of PF in crop production technology is recognized worldwide, but so far, it is applied mostly on large farms. Implementation of PF should be followed in three main steps of information gathering in terms of variability, data processing to evaluate the significance of variation and employ new management strategy to apply farming inputs. Fig. 9 demonstrates some equipment and technologies in a typical precision farming crop growing cycle. Some describe precision farming as applying the right inputs, at the right place, at the

Implementation of management strategy based on precision farming concept is the vital factor to achieve a desired outcome for the farm. Managers should make out their own

**3. Precision farming of rice** 

**3.1 Saving resources through precision farming** 

right time, right amount, and in the right manner.

Fig. 9. Precision Farming Cycle (Grisso, 2009)

loading to the environment or insufficient input application.

Soil variability in paddy fields is well recognized. The spatial description is an important component of the precision farming cycle for zone management practices. Precision farming requires topping up of only the nutrients that are lacking in the soil to attain the optimum yield with the least inputs. Manual soil sampling and the consequent laboratory analysis are expensive, labour intensive and requires a long time. The use of an on-the-go electrical conductivity (ECa) sensor can replace the traditional way of acquiring data in a more efficient way. Research results have confirmed the usefulness of the ECa data as a summary indicator for zoning paddy soils to facilitate water and fertilizer management.

Soil ECa measurements can provide information on soil texture, in addition to estimating soil water content. Maps of soil physical properties and yield maps have shown visible correlation. Soil ECa can serve as a proxy for soil physical properties such as organic matter (Jaynes, et al., 1994), clay content (Williams and Hoey, 1987), and cation exchange capacity (McBride, et al., 1990). These properties have a significant effect on water and nutrientholding capacity, which are major drivers of yield (Jaynes, 1995). The relationship between soil ECa and yield has been reported (Kitchen and Sudduth, 1996; Fleming, et al., 1998). Sudduth et al. (1998) found that within field variation in soil properties could be explained with soil conductivity measurements. They found a significant relationship between soil conductivity and topsoil depth and Fraisse et al. (1999) added to this work by using soil electrical conductivity for zone delineation. Both of these works concentrated on using soil ECa to characterize local spatial variability. Lund et al. (1998) show that sampling according to soil management zones identified with a soil conductivity map can be more effective than grid sampling.
