Plant Disease Ecology Lab

2026 수원, 전주 밭 고추 정식

admpdel — Wed, 13 May 2026 16:44:58 +0000

PDEL_대전

admpdel — Wed, 13 May 2026 16:37:07 +0000

2026 한국식물병리학회 춘계학술대회

admpdel — Wed, 13 May 2026 16:27:43 +0000

석박사 대학원생 모집 공고

admpdel — Tue, 06 Jan 2026 17:29:21 +0000

서울대학교 농업생명과학대학 식물병생태학연구실에서는 식물병 생태모델링, 기후변화 영향 및 적응/완화 연구, 식물의 생물학적/비생물학적 스트레스 상호작용, 식물병 예측/진단/방제시스템 구축, 빅데이터기반 스마트식물병관리 연구 등을 수행하고 있습니다. 따라서 본 연구실에서는 식물병의 생태학적 특성 연구을 바탕으로 식물병의 진화생태학 구명, 예찰 및 조기경보, 관리, 방제 시스템 개발을 주도적으로 수행할 학위과정 지원자를 모집합니다. ○ 식물미생물학전공 연구분야: 데이터 기반 식물병 생태모델링, 식물병 예측/진단/방제시스템 연구, 기후변화 영향 및 적응/완화 연구, 식물의 생물학적/비생물학적 스트레스 상호작용 연구, 빅데이터기반 스마트식물병관리 (스마트팜)연구 ○ 모집분야 - 농생명공학부 석사 및 박사 학위과정 ○ 지원자격 - 식물미생물학전공: 농생물학/작물학/농업/환경/전산통계 학부 졸업예정 및 졸업자 ○ 졸업 후 진로 - 정부/민간 농업생명 관련 연구기관 - 화학/생물 농약 또는 종자 회사 - 국제기구 또는 국제농업연구기관 - 국내외 대학 연구원 또는 교원

Evaluating the 2019 NARO-APCC Joint Crop Forecasting Service yield forecasts for Northern Hemisphere countries.

admpdel — Tue, 06 Jan 2026 17:28:04 +0000

ABSTRACT: Forecasting global food production is of growing importance in the context of globalizing food supply chains and observed increases in the frequency of climate extremes. The National Agriculture and Food Research Organization– Asia-Pacific Economic Cooperation Climate Center (NARO-APCC) Crop Forecasting Service provides yield forecasts for global cropland on a monthly basis using seasonal temperature and precipitation forecasts as the main inputs, and 1 year of testing the operation of the service was recently completed. Here we evaluate the forecasts for the 2019 yields of major commodity crops by comparing with the reported yields and forecasts from the European Commission’s Joint Research Centre (JRC) and the U.S. Department of Agriculture (USDA). Forecasts for maize, wheat, soybean, and rice were evaluated for 20 countries located in the Northern Hemisphere, including 39 crop-producing states in the United States, for which 2019 reported yields were already publicly available. The NARO-APCC forecasts are available several months earlier than the JRC and USDA forecasts. The skill of the NARO-APCC forecasts was good in absolute terms, but the forecast errors in the NARO-APCC forecasts were almost always larger than those of the JRC and USDA forecasts. The forecast errors in the JRC and USDA forecasts decreased as the harvest approached, whereas those in the NARO-APCC forecasts were rather stable over the season, with some exceptions. Although this feature seems to be a disadvantage, it may turn into an advantage if skillful forecasts are achievable in the earlier stages of a season. We conclude by discussing relative advantages and disadvantages and potential ways to improve global yield forecasting. KEYWORDS: Climate prediction; Regression analysis; Forecast verification/skill; Seasonal forecasting; Agriculture; Climate services

Potential value of seasonal climate forecast and crop modelling in identifying optimal management practices in Tonga

admpdel — Tue, 06 Jan 2026 17:24:22 +0000

The value of improved seasonal forecasts for the agriculture sector depends on a wide range of complex and interrelated factors. These include forecast accuracy – including accuracy at relevant spatial resolution and lead times, forecast adoption rates, and farmers’ attitudes to risk. In the study we focused on addressing only a small component of the first factor by testing the utility of the seasonal forecasts in informing a number of on-farm management decisions for swamp taro growers in Tonga. In terms of specific recommendations derived as part of the integration of the seasonal forecasts and a crop model calibrated using ground-truth data, it was clear that the use of targeted irrigation for specific growth stages resulted in significant improvement in mean yields across the whole year. The simulation results also suggested that planting a taro crop in the March to May period and using the seasonal forecast to help inform decisions such as planting density, fertiliser management, and irrigation can successfully lead to improved production in most years examined. During my presentation, some other alternative approaches will be presented as well. Overall, our results indicate that using the seasonal forecasts can improve potential crop yields against seasonal climate variabilities if used to alter the management decisions above. Nevertheless, this approach does carry more risk to the individual farmer and thus should be more fully explored with further analysis of farm management decisions and sensitivity studies.

Prospects for Enhancing Climate Services in Agriculture.

admpdel — Tue, 06 Jan 2026 14:46:21 +0000

ABSTRACT: Agricultural stakeholders can effectively manage the risks and opportunities arising from climate change and variability by enhancing climate services in agriculture. Key to understanding and addressing the climate challenge is the provision and the use of climate information to aid decision-makers and policy-makers. Climate services are now integral to the United Nations Framework Convention on Climate Change, the Intergovernmental Panel on Climate Change’s Assessment Reports, governments’ national adaptation plans, funding bodies, and a growing number of sectors and industries worldwide. The article provides our personal perspective, experience, and views on the important and timely issue of managing better the risks and opportunities to the agriculture sector and community that are arising from changes in climate. We describe a framework to help drive action to tackle the climate challenge comprising enhanced knowledge and information products, efficient information delivery and use, and assured policy and institutional support, in an iterative loop.

Past and Future Epidemiological Perspectives and Integrated Management of Rice Bakanae in Korea.

admpdel — Tue, 06 Jan 2026 14:45:45 +0000

In the past, rice bakanae was considered an endemic disease that did not cause significant losses in Korea; however, the disease has recently become a serious threat due to climate change, changes in farming practices, and the emergence of fungicide-resistant strains. Since the bakanae outbreak in 2006, its incidence has gradually decreased due to the application of effective control measures such as hot water immersion methods and seed disinfectants. However, in 2013, a marked increase in bakanae incidence was observed, causing problems for rice farmers. Therefore, in this review, we present the potential risks from climate change based on an epidemiological understanding of the pathogen, host plant, and environment, which are the key elements influencing the incidence of bakanae. In addition, disease management options to reduce the disease pressure of bakanae below the economic threshold level are investigated, with a specific focus on resistant varieties, as well as chemical, biological, cultural, and physical control methods. Lastly, as more effective countermeasures to bakanae, we propose an integrated disease management option that combines different control methods, including advanced imaging technologies such as remote sensing. In this review, we revisit and examine bakanae, a traditional seed-borne fungal disease that has not gained considerable attention in the agricultural history of Korea. Based on the understanding of the present significance and anticipated risks of the disease, the findings of this study are expected to provide useful information for the establishment of an effective response strategy to bakanae in the era of climate change.

Adapting to the projected epidemics of Fusarium head blight of wheat in Korea under climate change scenarios.

admpdel — Tue, 06 Jan 2026 14:45:14 +0000

Fusarium head blight (FHB) of wheat, mainly caused by Fusarium graminearum Schwabe, is an emerging threat to wheat production in Korea under a changing climate. The disease occurrence and accumulation of associated trichothecene mycotoxins in wheat kernels strongly coincide with warm and wet environments during flowering. Recently, the International Panel for Climate Change released the 6th Coupled Model Intercomparison Project (CMIP6) climate change scenarios with shared socioeconomic pathways (SSPs). In this study, we adopted GIBSIM, an existing mechanistic model developed in Brazil to estimate the risk infection index of wheat FHB, to simulate the potential FHB epidemics in Korea using the SSP245 and SSP585 scenarios of CMIP6. The GIBSIM model simulates FHB infection risk from airborne inoculum density and infection frequency using temperature, precipitation, and relative humidity during the flowering period. First, wheat heading dates, during which GIBSIM runs, were predicted over suitable areas of winter wheat cultivation using a crop development rate model for wheat phenology and downscaled SSP scenarios. Second, an integrated model combining all results of wheat suitability, heading dates, and FHB infection risks from the SSP scenarios showed a gradual increase in FHB epidemics towards 2100, with different temporal and spatial patterns of varying magnitudes depending on the scenarios. These results indicate that proactive management strategies need to be seriously considered in the near future to minimize the potential impacts of the FHB epidemic under climate change in Korea. Therefore, available wheat cultivars with early or late heading dates were used in the model simulations as a realistic adaptation measure. As a result, wheat cultivars with early heading dates showed significant decreases in FHB epidemics in future periods, emphasizing the importance of effective adaptation measures against the projected increase in FHB epidemics in Korea under climate change.

Optimizing Artificial Neural Network-Based Models to Predict Rice Blast Epidemics in Korea.

admpdel — Tue, 06 Jan 2026 14:44:41 +0000

To predict rice blast, many machine learning methods have been proposed. As the quality and quantity of input data are essential for machine learning techniques, this study develops three artificial neural network (ANN)-based rice blast prediction models by combining two ANN models, the feed-forward neural network (FFNN) and long short-term memory, with diverse input datasets, and compares their performance. The Blast_Weathe long short-term memory r_FFNN model had the highest recall score (66.3%) for rice blast prediction. This model requires two types of input data: blast occurrence data for the last 3 years and weather data (daily maximum temperature, relative humidity, and precipitation) between January and July of the prediction year. This study showed that the performance of an ANN-based disease prediction model was improved by applying suitable machine learning techniques together with the optimization of hyperparameter tuning involving input data. Moreover, we highlight the importance of the systematic collection of long-term disease data.

Information and communication technology-based service platform enabling the co-creation of agrometeorological services: A case

admpdel — Tue, 06 Jan 2026 14:44:13 +0000

Climate services for agriculture (agrometeorological services) are only possible through collaborative, interdisciplinary efforts. To this end, a national-scale service operated by centralized governments will mandate institutional coordination for data sharing, in addition to designated staff time and budget commitments for effective and sustainable operation; however, previous efforts have revealed that institutional coordination, particularly between meteorology and agriculture, represents the most difficult part preventing successful implementation in most countries. In this study, we examined the use of a top-down, information and communication technology (ICT)-based multidisciplinary platform for agrometeorological services for facilitating institutional coordination and ensuring project sustainability. The Strengthening Agro-climatic Monitoring and Information Systems (SAMIS) project, operational since 2018, focuses on building the adaptive capacity of agrometeorological services in Laos by combining the agricultural and meteorological sectors. The research here utilized the ICT-based service platform Laos Climate Services for Agriculture (LaCSA) to systematically engage relevant institutional partners in the co-creation process of agrometeorological services. The results showed that LaCSA enabled cocreation, including data sharing, collaborative tool use, institutional coordination, and policy support from multiple government entities across the agricultural and meteorological sectors. Key lessons and suggestions included co-training for both sectors, easy-to-use data management processes, early buy-in for policy makers, and creating standard operating procedures designating staff time and budgets. These results indicate that the coordinated operation of agrometeorological services through an ICT-based service platform can be successfully achieved in Laos as well as other developing countries, where institutional disconnects and human capital constraints hinder successful implementation of agrometeorological services.

수원 농장

admpdel — Wed, 31 Dec 2025 16:22:29 +0000

취약성 평가 출장

admpdel — Wed, 31 Dec 2025 16:18:25 +0000

PDEL_경주

admpdel — Wed, 22 Oct 2025 16:36:59 +0000

2025 한국식물병리학회 춘계학술대회

admpdel — Wed, 01 Oct 2025 15:57:24 +0000

2025 한국식물병리학회 추계학술대회

admpdel — Mon, 01 Sep 2025 16:33:25 +0000

PDEL _순천

admpdel — Mon, 01 Sep 2025 16:01:52 +0000

2025 화상병 시애틀 학회

admpdel — Tue, 01 Jul 2025 16:40:40 +0000

International Symposium of Fire Blight on Rosaceous Plants

Comparison of projected rice blast epidemics in the Korean Peninsula between the CMIP5 and CMIP6 scenarios.

관리자 — Mon, 30 Jun 2025 15:57:52 +0000

Abstract Recently, the International Panel for Climate Change released the 6th Coupled Model Intercomparison Project (CMIP6) climate change scenarios with shared socioeconomic pathways (SSPs). The SSP scenarios result in signifcant changes to climate variables in climate projections compared to their predecessor, the representative concentration pathways from the CMIP5. Therefore, it is necessary to examine whether the CMIP6 scenarios diferentially impact plant–disease ecosystems compared to the CMIP5 scenarios. In this study, we used the EPIRICE-LB model to simulate and compare projected rice blast disease epidemics in the Korean Peninsula using fve selected family global climate models (GCMs) of the CMIP5 and CMIP6 for two forcing scenarios. We found a similar decrease in rice blast epidemics in both CMIP scenarios; however, this decrease was greater in the CMIP6 scenarios. In addition, distinctive epidemic trends were found in North Korea, where the rice blast epidemics increase until the mid-2040s but decrease thereafter until 2100, with diferent spatial patterns of varying magnitudes. Controlling devastating rice blast diseases will remain important during the next decades in North Korea, where appropriate chemical controls are unavailable due to chronic economic and political issues. Overall, our analyses using the new CMIP6 scenarios reemphasized the importance of developing efective control measures against rice blast for specifc high-risk areas and the need for a universal impact and vulnerability assessment platform for plant–disease ecosystems that can be used with new climate change scenarios in the future.

2025 순천 지리산 워크샵

admpdel — Sun, 01 Jun 2025 10:35:08 +0000