국립원예특작과학원에서는 밝은 화색과 안정적인 화형의 생 육이 우수한 빨간색 스탠다드 장미 품종을 육성하기 위해 진한 적색 스탠다드 장미 품종 ‘엔드리스러브(Endless Love)’를 모 본으로, 꽃잎수가 많고 안정적으로 가시가 적은 밝은 노란색 ‘페니레인(Penny Lane)’ 품종을 부본으로 인공교배하였다. 37 개의 교배실생을 양성해 1, 2, 3차에 걸친 특성검정 및 현장실증 을 통해 꽃이 크고 화형이 안정적이며, 재배안정성 및 생산성, 절화특성이 우수한 ‘원교 D1-390’을 최종 선발하였다. 2023년 ‘루비레드(Ruby Red)’로 명명하여 국립종자원에 품종보호출원·등록되었다. ‘루비레드’ 품종은 밝은 적색(R53C)을 가졌으 며, 꽃잎수가 32.8매, 화폭과 화고는 각각 10.9, 5.9cm로 대조 품종보다 크다. 절화장은 평균 71.7cm, 절화수명은 약 16.7일, 수량은 연간 168대/m2로 대조품종인 ‘레드스퀘어(Red Square)’ 대비 절화장이 길고 절화수명도 2배 이상 길며, 수확량도 1.4배 우수하다. 2023년 국내 육성 장미 품종 서울식물원 관람객 대상 공동평가회에서 스탠다드 장미 중 우수한 평가를 받았으며, 현 장 실증 결과 농가별로 균일하고 우수한 수량과 절화품질을 보 였다. 절화용 장미 ‘루비레드’ 품종은 밝은 적색과 우수한 화형 을 가지는 품종으로 해외 대체 품종으로 국내에서 많이 재배될 것으로 기대된다.

Over the past decade, there has been global expansion in the advancement of underwater cleaning technology for ship hulls. This methodology ensures both diver safety and operational efficiency. However, recent attention has been drawn to the harmful effects of ship hull-cleaning wastewater on marine animals. It is anticipated that this wastewater may have various impacts on a wide range of organisms, potentially leading to populationand ecosystem-relevant alterations. This concern is especially significant when the wastewater affects functionally important species, such as aquaculture animals and habitat-forming species living in coastal regions, where underwater cleaning platforms are commonly established. Despite this, information on the ecotoxicological effects of this wastewater remains limited. In this mini review, we discuss the adverse effects of wastewater from in-water cleaning processes, as well as the current challenges and limitations in regulating and mitigating its potential toxicity. Overall, recent findings underscore the detrimental effects posed by sublethal levels of wastewater to the health status of aquatic animals under both acute and chronic exposure.

제충국(Tanacetum cineariaiaefolium), 데리스(Derris elliptica), 고삼(Sophora flavescens) 추출물은 다양한 해충을 방제하는데 사용되고 있다. 하지만, 국내에서 판매되고 있는 식물추춞물 자재는 유효성분의 표기가 없고, 살충농도와 살충시간에 대한 자료가 전무한 상황이다. 본 연구에서는 상 용화된 주요 식물추출물의 살충유효성분의 농도를 결정하고 복숭아혹진딧물에 대해 살충농도와 살충시간을 측정하였다. 식물추출물의 살충활성성분 인 pyrethrins, rotenone, matrine과 oxymatrine의 농도는 액체 크로마토그래피에서 표준물질을 활용하여 질량분석을 통해 측정하였다. 식물추출 물을 농도별로 희석하여 복숭아혹진딧물에 살포하여 살충력을 측정하였다. 표준화합물과 비교한 후 질량분석 및 결정했습니다. Myzus persicae에 대 한 lethal concentation과 lethal time을 조사했다. 살포 후 48시간 후 치사 농도(LC50)는 pyrethrins (20.4 ppm), roteone (34.1 ppm), matrine (29.6 ppm)였고, 100 ppm 살포한 LT50은 pyrethrins (13.4시간), rotenone (15.1시간), matrine (14.4시간)로 측정되었다. Kaplan-Meier 생존분 석 결과, 100 ppm에서 세 가지 식물 추출물의 LT50은 대조구인 화학 살충제인 Sulfoxaflor를 살포 처리구보다 유의하게 빨랐습니다. 본 결과는 복숭 아혹진딧물 방제를 위해 식물추출물의 제형화에 단일 또는 혼합 제제를 개발하는데 기준 살충농도와 살충시간을 제고하는데 의미가 있다.

Botanical extracts are employed in management of aphids. Extracts from Tanacetum cineariaiaefolium, Derris elliptica, and Sophora flavescens are widely used to control various insects. In this study, we determined concentrations of active insecticidal compounds (Ais) in commercial botanical extracts of these plants, and we investigated the time and concentration for lethal results with the green peach aphid, Myzus persicae. The concentrations of Ais, pyrethrins from T. cineariaiaefolium, rotenone from D. elliptica, and matrine and oxymatrine from S. flavescens, were determined after their fractionation by liquid chromatography followed by mass analysis and comparison with standard compounds. The extracts were tested for lethality in a bioassay with green peach aphids. Sprays at defined doses were applied to tobacco leaves infested with aphid nymphs. The lethal concentrations (LC50) were 20.4 ppm for pyrethrins, 34.1 ppm for rotenone, and 29.6 ppm for matrine at 48 h after treatments. At 100 ppm application levels, the lethal time LT50 was 13.4 h for pyrethrin, 15.1 h for rotenone, and 14.4 h for matrine. Kaplan - Meier analysis indicated the lethal times for the three botanical extracts at 100 ppm were significantly faster than application of a chemical insecticide, Sulfoxaflor, applied at the recommended level. These results provide baselines to develop and formulate single or mixed preparations containing botanical extracts to control green peach aphids on commercial crops.

Leaf-spray in vitro bioassays appraise new aphicidal formulations for managing deleterious plant-feeding aphids. The formulation may utilize alternative and integrated strategies. However, leaf spraying even under controlled conditions may affect aphid reproduction and mortality. This study examines leaf spray applications for optimum and reproducible aphicidal results using tobacco leaves overlaid on cotton fabric or water agar surfaces. Infestation of the undersides of tobacco leaves with nymphs of green peach aphids was used in the assays. Spray distance and volume were optimized using water-sensitive paper to ascertain the best surface coverage. Overlays of the leaves on water agar caused less mortality and greater reproduction than the use of cotton fabric. The relative humidity of the insect-rearing chambers changed with the watering regime for the insect - rearing chambers with cotton fabric; 60% relative humidity was optimal. Relative humidity was not affected by the concentration of agar in the water agar chambers. Applications of the chemical aphicidal standard, Sulfoxaflor, under the optimized conditions exhibited similar times for lethality although the rate was faster with leaves on the cotton fabric than on water agar. These studies establish reproducible and sensitive techniques for assessing the lethality and effects on reproduction of potential aphicidal products.

기후변화 위기에 대응하기 위하여 대한민국은 2030년까지 신재생연료 혼합비율(Renewable Fuel Standard, RFS)을 3.5%에서 8%까지 상향하기로 결정하였다. 국내에서 제조되는 신재생연료의 원료가 되는 바이오매스의 60%이상이 해외에서 수입하는 실정이며, 2030 탄소중립 및 RE100과 같은 바이오연료 사용증가 정책의 확대로 인하여 국내에서 제조되어 활용가능한 바이오매스의 확보가 절실하게 필요하다. 곤충은 높은 비율의 단백질과 지질을 체내에 저장하는 특징을 가지고 있으며, 곤충의 대량사육을 통하여 지질의 대량생산이 가능할 것으로 판단된다. 본 연구에서는 곤충의 대량사육환경에서 제조되는 지질을 원료로 하여 기후변화에 대응할 수 있는 바이오연료로의 전환 제조가능성을 확인하고자 하였으며, 이를 위하여 촉매공정을 통하여 디젤과 혼합하여 사용할 수 있는 수첨바이오디젤을 제조하여 그 특성을 분석하였다. 그 결과 곤충지질을 활용하여 수첨바이오디 젤로 전환가능함을 확인하였다.

Buckwheat (Fagopyrum esculentum), which is a traditional Korean crop, has been known as a health food due to its rich nutrition. This study was conducted to evaluate the change in flavonoid content of flowers and seeds during post-flowering growth of Korean tartary buckwheat variety ‘Hwanggeummiso’, with the aim of providing basic data for the development of functional food and feed additive. Tartary buckwheat took 69 and 99 days from the sowing date to reach the flowering and maturity stages, respectively. As a result of examining the flavonoid components of each part of tartary buckwheat, chlorogenic acid, rutin, and isoquercitrin of flowers increased from the flowering period on 22 May (0 days after flowering) to 42 days after flowering, while quercetin increased until 21 days after flowering and then decreased thereafter. In seeds, chlorogenic acid, rutin, and isoquercitrin were most abundant at the time of seed-bearing on 14 days after flowering, and showed a decreasing tendency thereafter. On the other hand, quercetin showed a tendency to increase until 21 days after flowering and then decrease. Overall, the flavonoid content was higher in flowers than in seeds, with rutin being particularly prominent. Based on this, the possibility as food materials and feed additives was confirmed using buckwheat produced in Korea.

진딧물 방제제 개발을 위해 In vitro 경엽살포 검정방법이 널리 사용되고 있다. 이러한 신소재 진딧물 방제 제형은 종합방제와 화학농약의 대안 으로 많은 연구가 진행되고 있다. 하지만, 경엽살포 검정방법은 환경이 조절되는 실내에서도 진딧물의 증식과 살충에 영향을 받는다. 본 연구에서는 담배를 기주로 하여 솜과 한천방법을 이용하여 진딧물 방제제 검정을 위한 최적 경엽살포 확립하고자 하였다. 진딧물 검정 챔버에 솜과 한천을 넣은 후 담배 잎과 진딧물 3-4령 약충을 접종하였다. Water-sensitive paper를 이용하여 경엽살포 시에 가장 표면 피복이 높은 최적 경엽살포 거리와 살 포량을 확립하였다. 대조구로 물을 처리한 구에서 한천 방법이 솜 방법에 비해 살충율이 낮고, 증식율이 높았다. 솜 검정 방법에는 곤충 검정 챔버의 상대습도를 60% 이상 유지시켰을 때 가장 최적 조건이었지만, 한천 검정 방법에서는 한천의 농도에 상대습도 차이가 없었다. 최적화된 조건하에서 대조화학 농약, Sulfoxaflor, 경엽살포 시 솜 방법에서 살충율이 한천방법보다 빨랐지만, 최종 살충율은 통계적으로 유의하지 않았다. 본 연구는 살 진딧물 물질을 검정 시 재현성과 활용성이 가능한 최적화된 증식율과 살충율 검정 조건을 제시하였다.

A sample size calculation algorithm was developed in a prototype version to select inspection samples in domestic bulk handling facilities. This algorithm determines sample sizes of three verification methods satisfying target detection probability for defected items corresponding to one significant quantity (8 kg of plutonium, 75 kg of uranium 235). In addition, instead of using the approximation equation-based algorithm presented in IAEA report, the sample size calculation algorithm based on hypergeometric density function capable of calculating an accurate non-detection probability is adopted. The algorithm based the exact equation evaluates non-detection probability more accurately than the existing algorithm based on the approximation equation, but there is a disadvantage that computation time is considerably longer than the existing algorithm due to the large amount of computational process. It is required to determine sample size within a few hours using laptop-level performance because sample size is generally calculated with an inspector’s portable laptop during inspection activity. Therefore, it is necessary to improve the calculation speed of the algorithm based on the exact equation. In this study, algorithm optimization was conducted to improve computation time. In order to determine optimal sample size, the initial sample size is calculated first, and the next step is to perform an iterative process by changing the sample size to find optimal result. Most of the computation time occurs in sample size optimization process performing iterative computation. First, a non-detection probability calculation algorithm according to the sample sizes of three verification methods was improved in the iterative calculation process for optimizing sample size. A computation time for each step within the algorithm was reviewed in detail, and improvement approaches were derived and applied to some areas that have major effects. In addition, the number of iterative process to find the optimal sample size was greatly reduced by applying the algorithm based on the bisection method. This method finds optimal value using a large interval at the beginning step and reduces the interval size whenever the number of repetitions increases, so the number of iterative process is less than the existing algorithm using unit interval size. Finally, the sample sizes were calculated for 219 example cases presented by the IAEA report to compare computation time. The existing algorithm took about 15 hours, but the improved algorithm took only about 41 minutes using high performance workstation (about 22 times faster). It also took 87 minutes for calculating the cases using a regular laptop. The improved algorithm through this study is expected to be able to apply the sample size determination process, which was performed based on the approximate equation due to the complexity and speed issues of the past calculation process, based on the accurate equation.

The measurement activities to evaluate material balance of nuclear material are usually performed by operator. It is because that the IAEA does not have enough manpower to carry out nuclear measurement accountancy of all nuclear materials in the world. Therefore, the IAEA should consider scenarios which facility operator tries to divert nuclear material for misuse by distorting measurement record. It is required to verify the operator’s measurement data whether it is normal or not. IAEA measures inventory items using their own equipment which is independent of facility operator equipment for verification. Since all inventory lists cannot be verified due to limited resources, the number of items to be verified is determined through statistical method which is called as sample size calculation. They measure for the selected items using their own equipment and compares with operator’s record. The IAEA determines sample size by comprehensively considering targeted diverted nuclear material amount and targeted non-detection probability and performance of measurement equipment. In general, the targeted diverted nuclear material amount is considered significant quantity (plutonium: 8 kg, uranium-235: 75 kg). If the targeted non-detection probability or the performance of the verification equipment is low, the sample size increases, and on the contrary, in the case of high non-detection probability or good performance of verification equipment, even a small sample size is satisfied. It cannot be determined from a single sample size calculation because there are so many sample size combinations for each verification equipment and there are many diversion scenarios to be considered. So, IAEA estimates initial sample size based on statistical method to reduce calculation load. And then they calculate non-detection probability for a combination of initial sample size. Through the iteration calculation, the sample size that satisfies the closest to the target value is derived. The sample size calculation code has been developed to review IAEA’s calculation method. The main difference is that IAEA calculates sample size based on approximate equation, while in this study, sample size is calculated by exact equation. The benchmarking study was performed on reference materials. The data obtained by the code show similar results to the reference materials within an acceptable range. The calculation method developed in this study will be applied to support IAEA and domestic inspection activities in uranium fuel fabrication facility.