한국 김제의 벼 경작 시스템의 기후스마트농업 (Climate-Smart Agriculture) 기반의 평가

학위논문 (박사) -- 서울대학교 대학원 : 농업생명과학대학 협동과정농림기상학, 2021. 2. Joon Kim.Food and Agriculture Organization (FAO)s climate-smart agriculture (CSA) challenges to avert world hunger through triple-win solutions: (1) sustainably increasing agricultural productivity and income, (2) reducing greenhouse gas (GHG) emission, and (3) building resilience to climate change. These are related to the United Nations sustainable development goals (SDGs) such as SDG1 (reduce poverty), SDG2 (zero hunger), SDG12 (responsible consumption and production), SDG13 (climate action), and SDG15 (life on land). However, the paucity of appropriate (1) conceptual framework, (2) holistic indicators, and (3) quantitative measurement data hinders farmers, researchers, and policy makers from making measurable assessment of the progress and the impact of CSA. The overarching question of this study is how a typical rice cultivation system in Korea is keeping up with the triple-win challenge of CSA. To answer this question, we have employed (1) a conceptual framework of self-organizing hierarchical open system with visioneering (SOHO-V) based on complex systems perspective; (2) quantitative data from direct measurement of energy, water, carbon and information flows in and out of a rice cultivation system, and (3) appropriate metrics to assess production, efficiency, GHG fluxes, and resilience. The study site was one of the Korean Network of Flux measurement (KoFlux) sites (i.e., GRK) located at Gimje, Korea, managed by National Academy of Agricultural Science, Rural Development Administration. Fluxes of energy, water, carbon dioxide (CO2) and methane (CH4) were directly measured using eddy-covariance technique during the growing seasons of 2011, 2012 and 2014. The production indicators include gross primary productivity (GPP), grain yield, light use efficiency (LUE), water use efficiency (WUE), crop coefficient (Kc), and carbon uptake efficiency (CUE). The GHG mitigation was assessed with indicators such as fluxes of carbon dioxide (FCO2), methane (FCH4), and nitrous oxide (FN2O). Resilience was assessed in terms of self-organization (S), using information-theoretic approach. The data obtained from the three growing seasons provided a wide range of contrasting environmental conditions and system states for our scrutiny. In terms of growing season averages from three years monitoring, growing season length was ~122 days, solar radiation (Rs) was 1,852 MJ m-2 season-1, air temperature was 22.4°C, and precipitation (P) was 830 mm. GPP was on average 889 g C m-2, RE was 565 g C m-2, grain yield was 588 g m-2, LUE was 1.94 g C MJ-1, WUE was 1.97 g C kg H2O-1, Kc was 1.26, CUE was 1.58, FCO2 was 324 g C m-2, FCH4 was 21.1 g C m-2, FN2O was 1.65 mg N2O m-2, and SAVG was 0.40 (for half-hourly time series) and 0.09 (for daily time series). These results for GRK are mostly within the middle to upper ranges of those reported from other studies, except GHG. GRK sequestered less CO2 and emitted more CH4 and N2O than those reported from other studies. Overall, the results of this study demonstrated that the rice cultivation system at GRK was not fulfilling the CSAs triple-win challenges. In fact, the competing goals and trade-offs among productivity, resilience, and GHG mitigation were found within individual years as well as between the three years, causing clashes and difficulties in achieving seamless harmony under the triple-win scenarios. The pursuit of CSA requires for stakeholders to prioritize their goals (i.e., governance) and to practice opportune interventions (i.e., management) based on the feedback from real-time assessment of the CSA indicators (i.e., monitoring) - i.e., the purpose-driven visioneering. The employed SOHO-V framework was useful for understanding of the complex interactions in ecological-societal systems and the CSA visioneering but difficult to use for practical application to prioritize the triad goals. An improved framework is proposed, in which economy is embedding within social systems and the UNs 17 SDGs are also included. This will provide diverse stakeholders with opportunity to unifying the issues and options under one coherent vision - a healthy and sustainable world. The results from this study would facilitate a paradigm shift in agriculture from climate-smart to climate-wise, which will transform ourselves from being resilient to becoming antifragile so that agriculture may gain from volatility, shocks, and uncertainties.세계식량기구(Food and Agriculture Organization, FAO)는 기아종식을 위해 삼중도전, 즉 (1) 생산성과 농가 소득을 지속적으로 증가시키고, (2) 기후변화에 대한 회복력을 갖추면서, (3) 온실가스의 배출을 완화시키는 기후스마트농업 (Climate-Smart Agriculture, CSA)에 도전하고 있다. 유엔의 17개 지속가능발전목표 (sustainable development goals, SDG)의 SDG1(빈곤퇴치), SDG2(기아종식), SDG12 (책임감 있는 소비와 생산), SDG13(기후변화 대응), SDG15(육상생태계)와 연결되는 이러한 노력은 코로나19 팬데믹으로 인해 그 중요성과 시급성이 더욱 부각되고 있다. 그러나 전체적인 맥락을 볼 수 있는 적절한 개념적 틀과 총체적 지표 및 정량적인 측정 자료의 결핍이 농민, 연구자 및 정책입안자가 CSA의 진행 상황을 파악하고 그 효과를 정량적으로 평가하는데 걸림돌이 되고 있다. 본 연구에서는 한국의 전형적인 벼 경작 시스템이 CSA의 삼중 도전에 어떻게 부합하고 있는가?라는 질문에 답하기 위해, (1) 복잡계사고 기반의 자기-조직화하는 계층구조의 열린 시스템과 비전의 엔지니어링이 연결(Self-Organizing, Hierarchical, Open systems with Visioneering, SOHO-V)된 개념 모델을 채택하고, (2) 벼 경작 시스템의 에너지, 물, 탄소 및 정보의 흐름을 직접 관측하였고, (3) 생산성/효율성, 온실가스 방출/흡수 및 회복력을 평가할 수 있는 다양한 측정 수단(metrics)을 사용하여 기후스마트농업의 관점에서 평가하였다. 연구 장소로서 국내 플럭스 관측망인 KoFlux 관측지의 하나인 김제의 대표적인 벼 경작 시스템을 선택하였다. 3년간(2011, 2012, 2014)의 생육기간 동안 에디공분산 기술을 사용하여 에너지, 물, 이산화탄소 및 메탄 플럭스의 흐름을 모니터링하였다. 생산 효율성 평가를 위해서는 총일차생산량(GPP), 생태계 호흡량(RE), 곡물 수확량, 빛사용효율(LUE), 물사용효율(WUE), 작물계수(Kc) 및 탄소흡수효율(CUE) 지표를 사용하였다. 온실가스 정량화를 위해서는, 이산화탄소 플럭스(FCO2)와 메탄 플럭스(FCH4)의 경우 직접 관측한 자료를 사용하였고, 아산화질소 플럭스(FN2O)는 IPCC지침에 따라 간접적으로 산출한 자료를 사용하였다. 회복력 평가를 위해서는 자기-조직화(self-organization, S) 지표를 사용하였으며, 벼 경작 시스템에서 가장 포괄적인 세 과정(총일차생산, 메탄 플럭스, 그리고 증발산)을 대상으로 정보이론을 사용하여 정량화 하였다. 3년간의 생육기간으로부터 관측된 자료는 CSA평가에 필요한 넓은 범위의 다양한 환경 조건과 시스템 상태를 제공하였다. 3년간의 모니터링에서 얻은 생육기간 평균을 살펴보면, 생육기간은 ~122 일, 총일사량(Rs)은 1,852 MJ m-2, 기온은 22.4°C, 총강수량(P)은 830 mm였다. GPP는 889 g C m-2, RE는 565 g C m-2, 곡물수확량은 588 g m-2, LUE는 1.94 g C MJ-1, WUE는 1.97 g C kg H2O-1, Kc는 1.26, CUE는 1.58, FCO2는 324 g C m-2, FCH4는 21.1 g C m-2, FN2O는 0.165 g N2O m-2, 그리고 S 는 30분 단위 시계열 자료를 사용했을 경우에 0.40, 일(24시간) 단위 시계열 자료를 사용하였을 경우에 0.09이었다. 이러한 김제 벼 경작 시스템의 결과는, 대략 평균 이하의 범위를 보인 온실가스 FCO2 , FCH4 및 FN2O를 제외하면, 전반적으로 선행연구에서 보고된 값들의 중-상위의 범위에 속하였다. 각 당해년도 생육기간의 주요 결과를 요약하면 다음과 같다: (1) 2011년의 경우, 일사량이 가장 낮았음에도 불구하고, 빛을 효율적으로 사용하여 다른 두 해보다 더 높은 생산성을 보여 탄소 흡수량이 가장 높았고, 메탄 방출량은 낮았다. 그러나 그 대가로 물 사용 효율이 다른 두 해보다 낮았고, 자기-조직화가 최소화되어 변화에 더 민감하게 반응하면서 회복력은 3년 중에서 가장 낮았다; (2) 2012년의 경우, 강수량이 가장 많았으나 중간 물떼기(MSD) 기간 동안 강수가 발생하지 않았고 일사량이 높아 배수가 효과적이었다. 그 결과 호기성 토양이 메탄을 산화시켜 배출을 전반적으로 완화시켰다. 이에 수반되는 생태계 호흡 증가로 이산화탄소 흡수가 감소하여 생산성이 가장 낮았다. 반면 자기-조직화가 활성화되면서3년 중에서 회복력이 가장 높았다; (3) 2014년은 일사량이 높았고 가장 적은 강수량으로 인해 빛 사용 효율이 낮았으나, 생태계 호흡의 감소로 인해 곡물 수확량과 GPP가 높았다. 그러나 MSD 기간 동안에 강수가 발생하여 중간 물떼기 효과가 최소화 되어, 다른 두 해보다 40% 더 많은 메탄을 배출하였다. 회복력은 다른 두 해의 중간 수준이었다; (4) 3년 자료의 연간 비교에서 뿐만 아니라 각 개별 연도 내에서도 나타난 CSA의 세 목표 간 경쟁과 대립 관계가 (애초부터 이러한 이해 상충은 없다고 가정한) CSA삼중 도전 시나리오에서 충돌을 야기하고 원활한 조화를 이끌어 내는데 어려움이 있음을 보여 주였다. 결론적으로, 본 연구에서 평가한 3년 간의 생육 기간 중 기후스마트농업의 삼중 목표를 모두 성취한 경우는 단 한 해도 없었으며, 특정 해에 성취된 목표도 연구기간 동안 지속적으로 유지되지 않고 다양한 변화를 보였다. 또한, 3년 간의 생육기간을 평균한 CSA 지표의 경우, 생산성에 관련된 지표들은 문헌에 보고된 다른 연구 결과와 비교할 때 대부분 중-상위의 범위에 속했으나, 온실가스 완화와 회복력 관련 지표들을 평균 이하였다. 따라서 김제의 벼 경작 시스템은 3년의 연구기간 동안 기후스마트농업의 삼중 도전에 부합하지 못한 것으로 나타났다. 이러한 연구 결과는 기후스마트농업을 추구할 때 다양한 이해관계자가 비전의 엔지니어링을 통해 시작부터 명확한 목적에 따라 목표의 우선순위를 정하고 CSA 지표들을 지속적으로 모니터링하여 관리에 반영하여 함을 시사한다. 본 연구에서 사용한 개념적 틀인 SOHO-V는 생태-사회시스템의 복잡한 상호작용을 학문적으로 이해하는 데는 유용하지만, 지속가능성을 지향하는 CSA 비전의 우선 순위를 실제로 적용하는 데에는 사용하기가 어려운 구조이다. 따라서 본 연구에서는 21세기 '도넛 경제학' 이론과 UN의 17개 SDGs를 함께 내재 시킴으로써 보다 개선된 개념적 틀을 제시하였다. 이 새로운 틀은 다양한 이해관계자들이 건강하고 지속가능한 세상이라는 하나의 일관된 비전 안에서 문제와 선택사양을 통합할 수 있도록 도울 것이다. 이러한 틀과 총체적인 CSA 측정 수단과 코로나19 팬데믹으로부터 배운 교훈이 기후스마트에서 '기후와이즈 (climate-wise) 농업으로의 패러다임 전환, 즉 회복력을 지향하는 현재의 농업을 뛰어 넘어, 충격과 불확실성을 오히려 더 나은 성장과 발전으로 이끄는 복잡성 기반의 반취약(antifragility) 농업으로의 변혁을 가져오길 희망한다.ABSTRACT i CONTENTS iv LIST OF TABLES vi LIST OF FIGURES ix LIST OF APPENDIXES xii LIST OF ABBREVIATIONS xiii 1 INTRODUCTION 1-6 1.1 Concerns and Motive 1 1.2 Challenges in Climate-Smart Rice Farming 2 1.3 Question, Goals and Strategies 4 2. MATERIALS AND METHODS 7-26 2.1 Conceptual Framework 7 2.1.1 Self-organizing hierarchical open systems (SOHO) 7 2.1.2 Coupling of SOHO with CSA Visioneering 8 2.2 Study Site 10 2.3 Biometeorological Measurements 11 2.3.1 Theoretical Background 11 2.3.1.1 Eddy Covariance technique 12 2.3.1.2 Energy Balance 14 2.3.2 Field Measurement 15 2.4 Bio-Meteorological Data Processing 16 2.4.1 Quality control 16 2.4.2 Gap filling 16 2.5 Flux Data Processing 16 2.5.1 Raw Data Processing 16 2.5.2 Spike Detection of Fluxes 17 2.5.3 Gap-filling of Flux Data 18 2.6 Assessment of Climate-Smart Agriculture (CSA) 20 2.6.1 Indicators for productivity and efficiency 20 2.6.1.1 Gross Primary Productivity (GPP) and Grain Yield 20 2.6.1.2 Crop Coefficient (Kc) 20 2.6.1.3 Water use efficiency (WUE) 22 2.6.1.4 Light Use Efficiency (LUE) 22 2.6.2 Indicators for GHG mitigation 22 2.6.2.1 Direct Measurement of CO2 and CH4 Fluxes 23 2.6.2.2 Estimation of N2O emission 23 2.6.2.3 Carbon Uptake Efficiency (CUE) 24 2.6.3 Resilience Indicators 24 3 RESULTS 27-43 3.1 Climatic conditions 27 3.1.1 Air temperature 27 3.1.2 Precipitation 28 3.1.3 Radiation 29 3.2 Energy Balance and the Bowen Ratio 31 3.3 Assessment of Climate-Smart Agriculture (CSA) 33 3.3.1 Indicators for Productivity 33 3.3.1.1 Gross primary productivity (GPP) 33 3.3.1.2 Evapotranspiration (ET) and crop coefficient (Kc) 34 3.3.1.3 Water use efficiency (WUE) 36 3.3.1.4 Light use efficiency (LUE) 37 3.3.2 Indicators for GHG mitigation 38 3.2.2.1 Carbon dioxide (CO2) uptake (FCO2) 38 3.2.2.2 Methane (CH4) emission (FCH4) 39 3.2.2.3 Nitrous Oxide (N2O) emission (FN2O) 40 3.3.3 Indicators for Resilience 40 4 DISCUSSION 44-59 5 SUMMARY AND CONCLUSIONS 60-63 6 SUGGESTIONS FOR FUTURE STUDY 64 7 REFERENCES 65-83 APPENDICES 83-89 ABSTRACT IN KOREAN 91-94 ACKNOWLEDGEMENT 95-97Docto

GROWTH PERFORMANCE OF JOLDUPI PINEAPPLE (Ananas comosus) WITH INTEGRATED NUTRIENT MANAGEMENT

A study was conducted to evaluate the growth performances and yield, with the biochemical composition of Joldupi pineapple (Ananas comosus) variety Joldupgi/Honey queen under integrated nutrient management. The field experiment was conducted with seven treatments viz. T1 (BARI Recommended Dose consisted of 35g urea, 10g TSP, 30g MoP & 10g Gypsum later termed as BRD), T2 (½BRD + Well decomposed cow dung 300g), T3 (½BRD + Well decomposed cow dung 450g), T4 ( ½BRD + Vermicompost 300g), T5 (½BRD + Vermicompost 450g), T6 (½BRD + Biochar 300g), T7 (½BRD + Biochar 450g) at the existing germplasm center of Joldupi pineapple in the Agroforestry field laboratory of Sylhet Agricultural University campus during July 2019 to June 2020. The experiment was laid out in a Randomized Complete Block Design (RCBD) with three replications. The analysis revealed that the applied treatments with integrated nutrients influenced growth parameters such as leaf number, east-west (E-W) canopy length, north-south (N-S), and leaf height from the surface. T5 treatment produced the maximum leaves number (32.5±4.63) and N-S canopy length (74.4±19.8 cm). Meanwhile, T2 was responsible for the maximum E-W canopy length (77.13±10.29 cm). However, the maximum fruit weight (328.96±5.45 g) was found in the T7 treatment. In terms of biochemical composition, maximum total soluble solids, TSS (21%), citric acid (0.89%), and vitamin C (66.18mg/100g) were found in the T7 treatment. In comparison, total sugar (16.33%), reducing sugar (7.1%), and sucrose (8.11%) wasere found in T4, T5, and T6 treatments, respectively. The highest soil pH, electrical conductivity (EC), total dissolved solids (TDS), and soil organic matter (SOM) were found to be 7.39, 53.01μS/cm, 34.98 mg/L, and 3.59%, respectively, in T7 treatment. The study found that the growth performance of pineapple and soil health were accelerated through integrating organic amendments with BRD. [J Bangladesh Agril Univ 2023; 21(2.000): 132-143

The Effect of Fertilizer Rate and Pruning Material on Growth and Yield of Carrot (Daucus carota) under Alley Cropping System

The study was conducted at the Agroforestry Farm of Sylhet Agricultural University from October 2020 to March 2021 to evaluate the growth and yield performance of carrot and determine soil fertility status during the hedge establishment period of alley cropping. Hedges for alley cropping were established using ipil-ipil (Leucaena leucocephala) and vegetable hummingbirds (Sesbania grandiflora) tree species. The experiment was laid out in a randomized complete block design (RCBD). During the hedge establishment period, the carrot was cultivated in the alley of the hedgerow using four different treatments with three replications. The treatments were T0 (No application of fertilizer and pruning materials), T1 (application of recommended fertilizer dose), T2 (application of half dose of the recommended fertilizer + pruning materials), and T3 (application of pruning materials). The results exhibited that growth parameters, viz. plant height (cm), leaf number per plant, root length (cm), and root diameter (cm) of carrot were almost similar in all treated plots, except control (T0). The carrot yield was statistically similar in all fertilizer and pruning materials treated plots, but it was drastically reduced in the control plots and decreased by about 40-45% compared to fertilizer and pruning materials applied plots. During hedgerow establishment, soil pH among different plots has not changed significantly compared to the initial field, but organic matter (OM), nitrogen (N), phosphorus (P), potassium (K), and sulfur (S) in different alleys found to be increased significantly in treatment T2 and treatment T1 after carrot cultivation. Improvement in soil fertility was also found in the alleys between the hedgerows of ipil-ipil and vegetable hummingbirds when only pruning material was applied to the soil. Therefore, an alley cropping system with Leucaena leucocephala and Sesbania grandiflora may enhance the yield performance of carrot and organically improve soil fertility during the hedge establishment period

The status of implemented climate smart agriculture practices preferred by farmers of haor area as a climate resilient approach

Bangladesh's Haor regions are famous for their natural resources and are unable to escape climate vulnerability. Triggered by climate vulnerabilities farmers are heading towards climate-resilient approaches. Hence, research was done in the haor area of Sunamganj district to analyze the status of adopted Climate-Smart Agriculture (CSA) techniques in Chhatak, Sunamganj, and Jagannathpur which are prone to severe flooding and climate conditions. Around 450 farmers were randomly selected and CSA adopters were contacted. A structured questionnaire was prepared with open-ended and closed-ended questions. The final questionnaire contained demographic questions and a list of adopted cropland and homestead CSA practices, and the survey proceeded with 115 finalized CSA adopters. MS Excel and SPSS were used to analyze the data. The data were expressed using frequency, percent, mean, and standard deviation. A t-test, analysis of variance, multiple linear regression, Pearson correlation, boxplot, and normal P–P plots were employed to test data normality. The analysis revealed that 30 CSA practices were identified to be practiced in cropland where major preferences were found for appropriate seed storage (100%), USG application (100%), IPM (98%), and good quality seed (95%) in cropland, whereas agroforestry (71%), organic fertilizer application (63%), perching (63%) and IPM (59%) were major CSA practices among the 18 identified practices in homesteads. The adoption level of CSA practices was found in the score category of 11–23 for cropland (90%) and up to 10 for homestead (68%). The results showed that the adoption status of CSA practices was inefficient for quick flood occurrence. CSA practices are not applied enough in haor areas' homesteads due to lack of knowledge, information access, and technical and financial resources. Thus, CSA should be implemented which necessitates working on barriers restricting CSA adoption through strengthening the infrastructure of technologies, supportive policies, and institutional framework