South Korea experienced a significant decline in honey bee populations starting in 2021, which continued for two years until the winter of 2022. To investigate the potential causes of this decline, we conducted a virome analysis, considering viruses as possible culprits. Samples were collected during two periods: April-May 2022 and May-June 2023. From libraries contsructed from their total RNA, we secured a total of 25 raw FASTQ files by high-throughput sequencing. In the honey bees collected in 2022, we identified eight previously unreported honey bee viruses including Lake Sinai viruses, one novel honey bee-related virus, and one novel plant-related virus. In the subsequent sampling in 2023, we found that most of the viruses identified in 2022 were still present. Additionally, the novel honey bee virus reported in 2022 was also found in the 2023 collections, along with three more honey bee-related novel viruses. Notably, numerous plant viruses were detected in honey bees collected during the flowering season. This analysis suggests that the viruses observed in South Korean honey bees are likely distributed nationwide. These findings provide fundamental data for future research on honey bee viruses in South Korea.

For effective control of Frankliniella occidentalis, one of polyphagous pests with resistance to insecticides, necessitates the implementation of an integrated pest management strategy. Therefore, estimation of pest density is essential and this is achieved through the application of spatial statistical analysis methods. Because traditional methods often overlook the correlation between sampling locations and data, geostatistical analysis using variogram and kriging is introduced. Variogram provides information on the independent distance between data points. Kriging is a spatial interpolation technique for estimating the values at unsampled locations. For assessing model fitness, cross-validation is used by comparing predicted values with actual observations. This study focuses on the application of geostatistical techniques to estimate F. occidentalis density in hot pepper greenhouse, thereby contributing to making decision.

A causality exists between insect density and plant health, where plant health is affected by both the plant’s potential and environmental factors. In other words, causality is possible between insect density and environmental factors, allowing for the analysis of insect density based on these environmental factors. Machine learning enables studying insect density alongside environmental factors, providing insights into the causality between insects, the environment, and plant health. Machine learning is a methodology that involves the design of models by learning patterns from input data. This study aims to predict F. occidentalis density by sampling environmental factors and applying them to machine learning models.

Since the importance of integrated pest management to minimize environmental damage and maximize pest control effectiveness has emerged, efforts to put it into practice have continued. To implement IPM, it is necessary to estimate the economic injury level to determine the control method by identifying pests and weeds that damage the quantity and quality of crops in the field, investigating the occurrence level, and calculating the ratio of cost and effectiveness. Also, damage to host plants caused by increased density of insect pests appears to change plant’s health that key factor for managing crops. Therefore, understanding the relationship between the density of pests and the damage to the host plants is necessary. This study aims to analyze the causal relationship between the density of insect pests and damage to the host plants for estimating the economic injury level of insect pests on the host plants and investigating the possibility of pest control decision-making using plant health status.

Climate change and biological invasions are the greatest threats to biodiversity, agriculture, health and the global economy. Tomato leafminer(Tuta absoluta) (Meyrick) (Lepidoptera: Gelechiidae) is one of the most important threats to agriculture worldwide. This pest is characterized by rapid reproduction, strong dispersal ability, and highly overlapping of generations. Plants are damaged by direct feeding on leaves, stems, buds, calyces, young ripe fruits and by the invasion of secondary pathogens which enter through the wounds made by the pest. Since it invaded Spain in 2006, it has spread to Europe, the Mediterranean region, and, in 2010, to some countries in Central Asia and Southeast Asia. In East Asia, Tomato leafminer was first detected in China in Yili, Xinjiang Uygur Autonomous Region, in 2017. There is a possibility that this pest will invade South Korea as well. This study provides this by the use of MaxEnt algorithm for modelling the potential geographical distribution of Tomato Leafminer in South Korea Using presence-only data.

The genus Halictus Latreille, 1804 and Seladonia Robertson, 1918 are nearly cosmopolitan group, consisting of more than 206 described species worldwide except Antarctica region. In previous taxonomic and phylogenetic research, this genus regarded as a sister group of genus Halictus. In this study, a total of two genera seven species were reviewed from Korean peninsula (three Halictus, four Seladonia) with three new records (Halictus hedini hedini, Seladonia confusa, S. henanensis). A key to species and images of adult are provided.

The foraging behavior of honey bees can be attributed to the nutritional incentives they gain from their activities. Nevertheless, a persistent question has revolved around how the nutritional composition undergoes alterations during the process of converting pollen into bee bread. We embarked on a comprehensive investigation of nutritional shifts, spanning from fresh pollen to bee-pollen, pollen patties, and bee bread. Our research findings unveiled that pollen exhibited notably higher levels of individual amino acids, resulting in significantly elevated overall amino acid content compared to bee-collected pollen. While we provided pollen patty to the honey bee colony, initially, during the first 3 to 7 days, there were no substantial discrepancies in the total amino acid content between bee bread and the pollen patty. Intriguingly, unlike most amino acids, we detected a distinct pattern of higher proline content in bee bread compared to bee-pollen or the pollen patty. This shift in amino acid composition likely stems from the incorporation of nectar and other secretions during the bee bread-making process. Moreover, over a span of approximately 14 days within hive conditions, the amino acid content in bee bread increased. Conversely, in terms of fatty acid contents, they were found to be lower in bee bread than those in the pollen patty, with no significant temporal differences observed. Regarding mineral content, bee bread, in general, contained fewer minerals than bee pollen and pollen patties. In conclusion, the transformation of pollen into bee bread involves dynamic alterations in nutrient contents, influenced by both intrinsic bee-related factors and external factors within the hive environment.

화분매개의존도는 밀원가치를 평가하는데 매우 필요한 자료임에도 불구하고, 산림 자원에 대한 화분매개의 존도 자료는 매우 부족하다 본 연구는 국내 중부지방에 분포하는 밀원수를 대상으로 화분매개의존도, 화밀/화분 생산량 및 꽃의 형태학적 특징을 규명을 목적으로 하였다. 화분매개의존도는 개화 전 꽃봉오리를 망사를 씌워 화분매개자의 출입을 제한 후, 결실률을 조사하여 평가했다. 화밀은 모세관 튜브를 이용하여 조사하며, 화분은 꽃가루의 수와 무게 측정을 통해 생산량을 추정하였다. 식물의 특징으로는 각 식물의 본 당 꽃 수, 개화시기, 화관 및 화서의 형태 등 형태적 특징을 조사하였다. 65종 평균 화분매개자 의존도는 평균 56±3.12%로 나타났고, 최대 100%(산수유), 최소 0%(상수리)로 나타났다. 45종의 화밀 및 화분량을 추정한 결과, 꽃 당 평균 화밀의 분비량은 인동 3.56±0.33㎕으로 가장 높았으나, 본 당 평균 화밀 분비량은 피나무 212.7㎖로 가장 높았다. 평균 화분의 무게는 피나무가 141.75g로 가장 많았다. 꽃 당 화밀량은 밀원수의 개화하는 시기가 봄에서 여름이 가까워질수록 적어졌 으나, 7, 8월에는 본 당 꽃의 수가 증가하여 여름에 개화하는 식물들이 본 당 화밀의 양을 더 많이 분비하는 경향을 확인하였다. 이는 산림 생태계의 밀원가치를 평가하는데 기초적인 자료로 활용될 수 있을 것으로 판단된다.

모기는 감염병을 매개하는 종으로 전염병 확산 억제를 위해서는 개체수의 감시와 정확한 예측이 필요하다. 본 연구에서는 모기 개체수 및 기상 및 현장 자료를 활용해 모기 개체수 머신러닝 모델을 개발하였다. 모기 개체수는 디지털 모기 측정기(Digital Mosquito Monitoring System, DMS)의 2015 년~2022년의 5월~10월의 자료를 활용하였다. 기상 자료는 기온, 강수량, 풍속, 습도를 사용하였으며, 현장 조사 자료는 현장을 명목척도와 서열척도로 나누어 기록하여, 명목 척도의 경우 원핫 인코딩으 로 변환해 수치화하여 사용하였다. 분석에 사용된 머신러닝 모델은 Artificial Neural Network, Random Forest, Gradient Boosting Machine, Support Vector Machine이며 성능지표로 R2, RMSE를 사용하였다. 연구 결과, Gradient Boosting 모델이 R2 0.4, RMSE 22.45로 가장 좋은 성능을 나타냈다. 현장 조사 자료 를 분석에 활용하였을 때 R2는 증가하였고, RMSE는 감소하였다. 본 연구 결과 모기 개체수에 현장 조사 자료가 예측 정확도를 향상시킬 수 있음을 확인하였다.

한국임업진흥원은 2012년 1월 설립된 산림청 산하의 공공기관으로서 산림과학기술의 보급과 임업 및 임산업 의 고부가가치 창출을 위한 임업 서비스를 제공하고 있으며, 국내 산림분야 활성화 및 글로벌 경쟁력 확보에 기여하고 있다. 특히, 소나무재선충병으로부터 국가 산림자원 보호를 위해 소나무재선충병모니터링센터를 2016년 1월에 설치하였으며, 최근 산림병해충이 산림을 비롯하여 생활권, 농림지 등에 돌발대발생하여 국민생 활에 불편을 초래하고 재산피해를 야기함에 따라 2021년 1월에 산림병해충모니터링센터로 확대 개편하여 산림 병해충 피해 예방과 감소를 위한 다양한 역할을 수행하고 있다. 주요 역할로는 주요돌발외래 산림병해충의 예찰 및 발생피해현황 모니터링, 방제약제 등록시험 운영 및 방제품질 관리, 예찰방제 전문가 양성 교육, 대국민 홍보 등이 있으며 본 발표를 통해 현재까지 산림병해충 관리를 위한 수행 내용과 결과를 공유하고자 한다.

우리나라 식물방역법은 검역병해충으로부터 국내 농업 및 자연환경을 보호하고자 규제병해충(검역병해충, 잠정규제병해충, 규제비검역병해충) 관련 위험평가, 식물검역기술개발계획, 식물검역 절차 및 방법, 검역결과 에 따른 처분, 규제병해충 예찰 및 방제 등에 관한 다양한 법적 절차 등을 규정하고 있다. 하지만, 식물검역병해충 을 어떻게 취급하여야 할 지에 관한 내용은 없다. 따라서 식물방역법이 추구하는 목적을 달성하기 위하여서는 ① 검역병해충을 어떻게 취급하여야 할 지를 규정하여야 하며, ② 검역병해충을 취급하는 시설(검사, 연구, 운송, 보관 등) 기준을 설정하고, ③ 검역병해충 취급 시설을 인증하고, 주기적인 재인증 기준을 설정하여야 한다. 이를 위하여 먼저 식물방역법에 검역병해충 취급시설 등에 관한 규정을 신설하고, 시행령, 시행규칙에 반영한 후에 ① 검역병해충 취급요령 ② 검역병해충 취급시설 기준 ③ 검역병해충 취급시설 인증기준 등의 고시를 제정하여 야 한다. 이를 위하여 식물병해충 관련 학계의 의견 반영이 가장 중요하다.

Honey bees are crucial pollinators for agricultural and natural ecosystems, but are experiencing heavy mortality in Korea due to a complex suite of factors. Extreme winter losses of honey bee colonies are a major threat to beekeeping but the combinations of factors underlying colony loss remain debatable. Finding solutions involves knowing the factors associated with high loss rates. To investigate whether loss rates are related to Varroa control and climate condition, we surveyed beekeepers in korea after wintering (2021–2022 to 2022–2023). The results show an average colony loss rate of 46%(2022) and 17%(2023), but over 40% colony loss before wintering at 2022. Beekeepers attempt to manage their honey bee colonies in ways that optimize colony health. Disentangling the impact of management from other variables affecting colony health is complicated by the diversity of practices used and difficulties handling typically complex and incomplete observational datasets. We propose a method to 1) Varroa mite population Control by several methods , and 2) Many nursing bee put in hive before wintering.

Over the course of two winters, the significant decline in honey bee populations in Korea has emerged as a major social issue. This phenomenon is expected as attributed to factors such as the failure of pest control due to the pesticide resistance of the Varroa mite. This mite can transmit some viruses that infect honey bees, and these viruses are among the primary causes of the globally occurring colony collapse disorder. Traditional diagnostic methods like (RT-)PCR and ELISA are not ideal for identifying pathogens that are newly emerging or have undergone mutations. To detect any novel or mutated viruses beyond those that have been primarily diagnosed in Korea, we introduced virome analysis technology in the field of honey bees. Employing this method with high-throughput sequencing techniques, we were able to identify all existing viruses within individual or group samples. We discovered that the Lake Sinai virus, which has been reported worldwide but not in Korea, has already significantly spread within the country. Additionally, we were able to confirm the prevalence of viruses previously reported in Korea, such as the recently dominant Black Queen Cell Virus. Through this virome analysis, we can provide foundational data for determining the direction and countermeasures for virus diagnosis.

Honeybee winter failure and mortality are a big issue in korea, especially from 2021 to 2023. Traditionally, honeybee winter failure has been estimated as Approximately 10-20%. However, for last 2 years, we had more than 35% of winter failure which impacted not only beekeeping sectors but also agriculture and the whole society as well. Primary factor was ascribed as honeybee mite resistance development to conventional acaricudes. Coinhabitance of tropilaelaps mite in honeybee complicated the mite problem. Further threat of vespa hornets especially in fall season would exerbate the wintering condition. More important is that the more frequent abnormal weather condition in fall and winter season could affected the winter bee production and maintenance of honeybee overwintering physiology. On these situation, we also observed some diseases were associated to the death of bees.

Honeybee winter failure and mortality are a big issue in korea, especially from 2021 to 2023. Traditionally, honeybee winter failure has been estimated as Approximately 10-20%. However, for last 2 years, we had more than 35% of winter failure which impacted not only beekeeping sectors but also agriculture and the whole society as well. Primary factor was ascribed as honeybee mite resistance development to conventional acaricudes. Coinhabitance of tropilaelaps mite in honeybee complicated the mite problem. Further threat of vespa hornets especially in fall season would exerbate the wintering condition. More important is that the more frequent abnormal weather condition in fall and winter season could affected the winter bee production and maintenance of honeybee overwintering physiology. On these situation, we also observed some diseases were associated to the death of bees.