논에 있어서 정밀농업시 변량시비가 벼 생육에 미치는 기초자료를 얻기 위하여 토양 및 생육정보를 조사한 결과는 다음과 같다. 1. 시험전 토양의 변이계수는 EC, 유기물, 전질소, 유효인산 및 칼리는 11.63~52.03% 로 10% 이상의 큰 변이를 보였으나 pH는 각각 1.96~4.9% 로 적었다. 2. 생육중의 경수는 10%이상의 변이를 보였으나 초장, 엽색 및 쌀수량, 현미중 단백질은 10%이하의 변이를 보였다. 변량시비에 의하여 변이계수가 쌀수량은 8.06%에서 5.22% 및 5.81%로, 현미중 단백질 함량은 4.06%에서 3.40%로 낮아졌다. 3. 공간구조의 강약을 보여주는 Q값은 시험전 토양의 pH, 전질소함량, 유효인산 및 칼리함량은 0.60이상으로 공간의존성이 강하였으며, 엽색, 초장, 쌀수량 및 현미중 단백질함량 등도 0.50이상으로 공간의존성이 강하였으나 유수 형성기 경수는 0.22로 공간 의존성이 약했다. 4. 공간거리를 나타내는 공간의존 거리는 현미중 단백질 함량을 제외하고는 20 m 이상의 공간의존성이 있었다. 5. 시험전 토양의 pH, SiO2 및 초장, 엽색은 기비와 정의 상관을 보였으나 O.M.은 부의상관을 보였다. 수비는 시험 전 토양중 EC, O.M. 및 토양 고저차와는 정의 상관을 보였으나 초장, 경수 및 엽색과는 부의상관을 보였다. 현미중 단백질 함량은 토양중 SiO2 및 엽색, 수량과는 정의 상관을 보였으나 토양중 O.M.과는 부의상관을 보였으며 쌀수량은 초장, 경수 및 엽색과는 정의상관을 토양중 PH와는 부의 상관을 보였다.

Rice yield and protein content have been shown to be highly variable across paddy fields. In order to characterize this spatial variability of rice within a field, two-year experiments were conducted in 2002 and 2003 in a large-scale rice field of 6,600m2 In year 2004, an experiment was conducted to know if variable rate treatment (VRT) of N fertilizer, that was prescribed for site-specific management at panicle initiation stage, could reduce spatial variation in yield and protein content of rice while increasing yield compared to conventional uniform N topdressing (UN, 33kg N/ha at PIS) method. VRT nitrogen prescription for each grid was calculated based on the nitrogen (N) uptake (from panicle initiation to harvest) required for target rice protein content of 6.8~% , natural soil N supply, and recovery of top-dressed N fertilizer. The required N uptake for target rice protein content was calculated from the equations to predict rice yield and protein content from plant growth parameters at panicle initiation stage (PIS) and N uptake from PIS to harvest. This model· equations were developed from the data obtained from the previous two-year experiments. The plant growth parameters for the calculation of the required N were predicted non-destructively by canopy reflectance measurement. Soil N supply for each grid was obtained from the experiment of year 2003, and N recovery was assumed to be 60~% according to the previous reports. The prescribed VRT N ranged from 0 to 110kg N/ha with an average of 57kg/ha that was higher than 33 kg/ha of UN. The results showed that VRT application successfully worked not only to reduce spatial variability of rice yield and protein content but also to increase rough rice yield by 960kg/ha. The coefficient of variation (CV) for rice yield and protein content was reduced significantly to 8.1~% and 7.1~% in VRT from 14.6~% and 13.0~% in UN, respectively. And also the average protein content of milled rice in VRT showed very similar value of target protein content of 6.8~% . In conclusion the procedure used in this paper was believed to be reliable and promising method for reducing within-field spatial variability of rice yield and protein content. However, inexpensive, reliable, and fast estimation methods of natural N supply and plant growth and nutrition status should be prepared before this method could be practically used for site-specific crop management in large-scale rice field.

For developing the site-specific fertilizer management strategies of crop, it is essential to know the spatial variability of soil factors and to assess their influence on the variability of crop growth and yield. In 2002 and 2003 cropping seasons within-field spatial variability of rice growth and yield was examined in relation to spatial variation of soil properties in the· two paddy fields having each area of ca. 6,600m2 in Suwon, Korea. The fields were managed without fertilizer or with uniform application of N, P, and K fertilizer under direct-seeded and transplanted rice. Stable soil properties such as content of clay (Clay), total nitrogen (TN), organic mater (OM), silica (Si), cation exchange capacity (CEC), and rice growth and yield were measured in each grid of 10~times10m . The two fields showed quite similar spatial variation in soil properties, showing the smallest coefficient of variation (CV) in Clay (7.6~%) and the largest in Si (21.4~%) . The CV of plant growth parameters measured at panicle initiation (PIS) and heading stage (HD) ranged from 6 to 38~% , and that of rice yield ranged from 11 to 21~% . CEC, OM, TN, and available Si showed significant correlations with rice growth and yield. Multiple linear regression model with stepwise procedure selected independent variables of N fertilizer level, climate condition and soil properties, explaining as much as 76~% of yield variability, of which 21.6~% is ascribed to soil properties. Among the soil properties, the most important soil factors causing yield spatial variability was OM, followed by Si, TN, and CEC. Boundary line response of rice yield to soil properties was represented well by Mitcherich equation (negative exponential equation) that was used to quantify the influence of soil properties on rice yield, and then the Law of the Minimum was used to identify the soil limiting factor for each grid. This boundary line approach using five stable soil properties as limiting factor explained an average of about 50~% of the spatial yield variability. Although the determination coefficient was not very high, an advantage of the method was that it identified clearly which soil parameter was yield limiting factor and where it was distributed in the field.