본 연구에서는 변량방제기술을 적용한 농용 회전익기를 이용하여 살포한 입자의 구간비행 상태에서의 거리별 살포 패턴을 측정함으로써 무인 항공방제의 농약 부착률과 입자경의 분포 균일도를 평가하였다. 비행을 등속으로 유지하는 안내비행과 자동비행 모드에서 유효살포폭 3.6m로 인접비행 구간과 살포폭이 일부 중첩된 피복률에 대한 가로방향 분포의 변이계수는 30% 정도를 보였고, 비행방향 진로위치에 대한 피복률의 변이계수는 10% 미만으로 매우 균등한 것으로 평가되었다. 따라서 살포작업시 기체의 지면속도(ground speed)의 변이를 보상하는 변량살포기술은 균일도 측면에서 우수한 것으로 판명되었으며, 또한 입자경의 분포에 있어서 체적중위직경(VMD)과 개체중위직경(NMD) 모두 항공방제에 적절한 크기와 균일한 분포를 보였다. 따라서 농용 회전익기를 이용하여 소필지의 항공방제작업을 무인화 하는 데 있어, 변량방제장치를 적용함으로써 소규모 필지의 균일 정밀방제를 도모하고자 하였다.

광도와 온도 같은 환경 요인에 의해 광합성 속도가 변화하기도 하며, 생육 시기에 따른 광합성 효율의 변화가 수반되기도 한다. 본 연구에서는 흑로메인 상추(Lactuca sativa L., Asia Heuk romaine)를 이용하여 광도와 온도, 생육 시기에 따른 군락 광합성 속도를 표현하는 두 모델을 구축하고 비교하는 것을 목표로 하였다. 군락 광합성은 정식 후 4, 7, 14, 21, 28 일차 상추를 아크릴 챔버(1.0 × 0.8 × 0.5m)에 넣어 측정하였으며, 이 때 챔버 내부의 온도는 19oC에서 28oC까지 변화시켰고 광원은 LED를 이용하여 50에서 500μmol·m-2·s-1까지 변화시키며 실험하였다. 챔버 내부의 초기 이산화탄소 농도는 2,000μmol·mol-1로 설정하였으며, 시간에 따른 이산화탄소 농도의 변화율을 이용하여 군락 광합성 속도를 계산하였다. 각 환경요인을 표현하는 3개 식을 곱하여 만든 단순곱 모델을 구성하였다. 이와 동시에 온도와 생육 시기에 따라 변화하는 광화학 이용효율과 카르복실화 컨덕 턴스, 호흡에 의한 이산화탄소 발생 속도를 포함하는 수정된 직각쌍곡선 모델을 구성하여 단순곱 모델과 비교하였다. 검증 결과 단순곱 모델은 0.849의 R2 값을 나타내었으며, 수정된 직각쌍곡선 모델은 0.861의 R2 값을 나타내었다. 수정된 직각쌍곡선 모델이 단순곱 모델에 비해 환경 요인(광도, 온도), 생육 요인(생육 시기)에 따른 군락 광합성 속도를 표현하는데 더욱 적합한 모델인 것으로 판단하였다.

정밀농업의 핵심인 변량살포(VRA) 기술은 방제 분야에 적용이 가능하여, 경제적 효과뿐만 아니라 적정살포를 통한 환경 보전 효과도 기대할 수 있는 등 여러 이점이 입증되었다. 그러나 변량살포 기술에서 목표속도를 중심으로 제한된 속도범위 내에서 비행하고 살포율 오차를 안정시키는 것이 핵심요소이다. 본 연구의 이론에서 현실적으로 목표속도에 대하여 ±13% 정도의 속도변이를 허용할 수 있을 것으로 판단되었고, Koo & Park(2015)가 개발한 변량살포 제어시스템에 수동(manual), 자동(auto pilot), 경로안내(way-point guidance) 등 세 가지 비행모드의 적용성에 대하여 고찰하였다. 비행제어 모드에 따른 등속 비행에 대한 속도의 질을 비교하면, 수동과 자동은 실시간 속도를 모니터링 하지 않으므로, 두 경우 모두 평균 비행속도가 목표속도와 큰 편차를 보일 가능성이 있었다. 즉 범위율(PR)이 각각 18.1 및 16.1%로 나타났으나, 경로안내 모드에서는 6.5%로 나타나서 변량살포 제어시스템에의 적용성이 증명되었다. 자동 및 경로안내 모드에 대한 변이계수(CV)가 비슷하므로, 자동모드 또한 비행속도의 모니터링의 방법을 조종자에게 추가로 제공한다면 변량제어 시스템과의 적용성을 보일 것으로 생각된다.

We compared the germination rate of dehisced ginseng (Panax ginseng) seeds that were dried under two different conditions, slowly at 15℃ [relative humidity (RH) 10-12%] and rapidly under a laminar airflow cabinet at 25℃ (RH 22-25%). The measurements showed that drying rate and seed moisture content (SMC) play important roles in storage ability and vigor. The seeds that were dried rapidly at 25℃ showed high GR compared with the seeds that were dried at 15℃ after 6 and 12 months of storage at -80℃ irrespective of MC. Seeds dried slowly at 15℃ with MC higher than 7.0% showed high GR maintenance after storage at -18℃ and at 4℃ in comparison with rapidly dried seeds. However, the GR of the slowly desiccated seeds decreased as mean SMC was reduced to less than 5.0%, whereas the rapidly dried seeds were distinguished by significantly high GR irrespective of the storage conditions. The ginseng seeds desiccated under different conditions showed differences in storage performance. Seeds with 7-9% MC that were dried slowly at 15℃ for 5-7 days showed high GR after 4℃ and -18℃ storage; however, longer periods of desiccation decreased the germination level remarkably compared with that of rapidly dried seeds.

ice yield and plant growth response to nitrogen (N) fertilizer may vary within a field, probably due to spatially variable soil conditions. An experiment designed for studying the response of rice yield to different rates of N in combination with variable soil conditions was carried out at a field where spatial variation in soil properties, plant growth, and yield across the field was documented from our previous studies for two years. The field with area of 6,600 m2 was divided into six strips running east-west so that variable soil conditions could be included in each strip. Each strip was subjected to different N application level (six levels from 0 to 165kg/ha), and schematically divided into 12 grids (10m ~times10m~;for~;each~;grid) for sampling and measurement of plant growth and rice grain yield. Most of plant growth parameters and rice yield showed high variations even at the same N fertilizer level due to the spatially variable soil condition. However, the maximum plant growth and yield response to N fertilizer rate that was analyzed using boundary line analysis followed the Mitcherlich equation (negative exponential function), approaching a maximum value with increasing N fertilizer rate. Assuming the obtainable maximum rice yield is constrained by a limiting soil property, the following model to predict rice grain yield was obtained: Y=107651-0.4704*EXP(-0.0117*FN)*MIN(I-clay,~;Iom,~;Icec,~;ITN,~; ISi) where FN is N fertilizer rate (kg/ha), I is index for subscripted soil properties, and MIN is an operator for selecting the minimum value. The observed and predicted yield was well fitted to 1:1 line (Y=X) with determination coefficient of 0.564. As this result was obtained in a very limited condition and did not explain the yield variability so high, this result may not be applied to practical N management. However, this approach has potential for quantifying the grain yield response to N fertilizer rate under variable soil conditions and formulating the site-specific N prescription for the management of spatial yield variability in a field if sufficient data set is acquired for boundary line analysis.

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.