과정기반 작물모형은 재배환경과 상호작용하는 작물 내부의 기본적인 생리과정들을 과학적으로 결합하여 전체적인 작물 생육을 모의하고자 고안된 기술이다. 본 연구에서는 기후변화에 따른 양파의 생산예측 기술 개발을 목표로 과정기반 양파 모형을 제작하고, 이를 실제 포장 조건(온도구배하우스)에서 얻은 결과와 비교하였다. 양파 생육의 기본이 되는 광합성량을 추정하기 위하여 FvCB 모형, 기공전도도 모형(Ball-Berry) 및 엽온과 관련된 에너지 균형 방정식을 결합한 기체교환모형(gas-exchange model)을 이용하여 잎 수준의 광합성량을 예측하였으며, 이를 개체 수준으로 확장하기 위하여 잎을 양엽과 음엽의 두 범주로 구분하여 모델링하는 Sun/Shade 모형을 적용하였다. 또한, 양파의 구 비대 예측을 위해 기온에 따른 잎의 생장을 발달 단계 상의 엽면적의 변화와 연관시킴으로써 전체 작물 수준에서 광합성 산물의 양이 계산되도록 하였고, 최종적으로 전체 동화량에서 호흡량을 제외하고 양파의 인경 부위로 분배된 동화산물의 양을 누적함으로써 양파 수량을 계산하였다. 모델 내의 모든 과정은 시간별 기상자료(일사, 기온, 습도, 풍속)에 의해 반복적으로 계산될 수 있도록 Cropbox 프레임워크(Julia ver. 1.8.2)를 활용하여 제작하였다.
The process-based model (PBM) is based on the interactions between endogenous physiological processes and many environmental factors, and can be a powerful tool for estimating crop growth and productivity. The aim of this study was to develop a process-based model for onion as a predictive tool for assessing the impact of climate change on their growth and productivity, thus providing guidelines for stable crop production. Carbon acquisition and biomass accumulation consititute the main structure of PBM. In this study, ‘Tabo’ onion, a medium/late-maturing variety, was grown in the SPAR chamber and the temperature gradient chamber (TGC) to obtain the fundamental dataset for estimating parameters. The measured net CO2 assimilation rate and related variables were used for the parameterization of the coupled leaf gas-exchange model containing FvCB model, stomatal conductance model, and energy balance model as key components. Major parameters including Vcmax (maximum rate of carboxylation), Jmax (maximum rate of electron transport), TPU (rate of triose phosphate utilization), and Rd (dark respiration rate) were estimated using the Sharkey’s utility program. Then, two stomatal conductance models, Ball-Berry model and Medlyn model, were compared for coupling gas-exchange process in onion. Finally, the net CO2 assimilation rate of onion leaves was simulated for various levels of Ci, PPFD, and Ta. As the engine of the process-based whole-crop model, the leaf gas-exchange model calibrated in this study is expected to be able to explain the photosynthetic responses of onion under various environmental conditions (R2=0.95**). Phenology module deals with the timing of developmental stage, and the timing of phenological events is strongly influenced by the temperature during the growing season. The datasets for modeling the leaf appearance and elongation were collected from the SPAR chambers with five different temperature treatments. Then, the Beta distribution function (proposed by Yan and Hunt (1999)) was used for describing the leaf development as a function of temperature. The optimum temperature and the critical value were estimated to be 26.0°C and 35.3°C, respectively. The estimated value by the temperature model was compared with the observed values from the TGC test. The model equation to describe leaf elongation and senescence rate was obtained by the similar experiment in the SPAR chambers. A morphological relationship between leaf length and leaf area was calculated using the TGC dataset. Finally, leaf area was simulated dynamically by coupling morphology and phenology module to calculate the carbon gain from the gas-exchange process, and the sun-shade leaf model was used to scale up leaf photosynthesis to the canopy level. A critical photoperiod for bulb initiation (13 h) was included in the phenology model as a transition point in the developmental stage. Carbon partitioning ratio was calculated in each developmental stage by the ratio of dry weight of each plant part to the total dry weight, and used to describe the carbon allocation in onion. After performing the calibration for each module, the onion leaf appearance, green leaf area, total biomass accumulation, and biomass partitioning ratio in each plant part were estimated using the integrative whole crop model. These estimated values were compared with those obtained from the TGC chamber. It is expected that the process-based model should be a powerful strategy for estimating growth and yield of onion, thus effectively coping with climate change.
ABSTRACT ⅸⅠ. 서 언 1Ⅱ. 연구사 4Ⅲ. 연구결과 및 고찰 26제 1 장. 양파의 잎 출현 및 생장속도, 엽면적 증가 예측 271.1. Abstract 281.2. 서 언 291.3. 재료 및 방법 311.4. 결과 및 고찰 341.5. 적 요 431.6. 인용문헌 44제 2 장. 양파의 광합성 예측을 위한 기체교환모형 모수 추정 462.1. Abstract 472.2. 서 언 482.3. 재료 및 방법 502.4. 결과 및 고찰 542.5. 적 요 652.6. 인용문헌 66제 3 장. 양파의 구 비대 개시와 동화산물의 분배 예측 703.1. Abstract 713.2. 서 언 723.3. 재료 및 방법 733.4. 결과 및 고찰 773.5. 적 요 873.6. 인용문헌 88제 4 장. 개발 모형의 예측력 평가 904.1. Abstract 914.2. 서 언 924.3. 재료 및 방법 944.4. 결과 및 고찰 1004.5. 적 요 1064.6. 인용문헌 107Ⅳ. 종합고찰 108Ⅴ. 인용문헌 110Ⅵ. 국문초록 118APPENDIX 119
