This study was performed to investigate antioxidant and anti-inflammatory activities of perilla(Perilla frutescens L.) seed, flower and leaf according to extraction condition. Perilla seed extracts(PSE), perilla flower extracts(PFE), perilla leaf extracts(PLE) was extracted by stirring extraction (STE, 25°C), shaking extraction (SHE, 80°C), and sonication assisted extraction(SAE, , 25°C) with 94% ethanol, 60% ethanol and distilled water, followed by analysis of total polyphenol and flavonoid and testing radical scavenging activities. The highest total polyphenol content (5.47, 9.36, 38.58 mg gallic acid equivalent/g), total flavonoid content(5.77, 8.62, 46.44 mg catechin equivalent/g), ABTS(10.68, 19.46, 63.56 mg trolox equivalent/g) and DPPH(6.51, 7.69, 79.73 mg trolox equivalent/g) radical scavenging activity of PSE, PFE and PLE was observed in the HWE with 60% ethanol,. Among the three extraction method, SHE provided the best results for yield, polyphenol, flavonoid content of perilla seed, flower, leaf in comparison to STE or SAE. SHE with 60% ethanol of perilla seed, flower, leaf more effectively inhibited secretion of nitric oxide(NO) and pro-inflammatory cytokine in RAW 264.7 macrophage exposed to LPS compared to other extraction solvent and method. Therefore, these extracts obtained from perilla seed, flower, leaf could be used antioxidant and anti-inflammatory ingredients in the food industry.

Growth modeling in plant factories can not only control stable production and yield, but also control environmental conditions by considering the relationship between environmental factors and plant growth rate. In this study, using the expolinear function, we modeled perilla [Perilla frutescens (L.) Britt.] cultivated in a plant factory. Perilla growth was investigated 12 times until flower bud differentiation occurred after planting under light intensity, photoperiod, and the ratio of mixed light conditions of 130 μmol·m-2·s-1, 12/12 h, red:green:blue (7:1:2), respectively. Additionally, modeling was performed to predict dry and fresh weights using the expolinear function. Fresh and dry weights were strongly positively correlated (r = 0.996). Except for dry weight, fresh weight showed a high positive correlation with leaf area, followed by plant height, number of leaves, number of nodes, leaf length, and leaf width. When the number of days after transplanting, leaf area, and plant height were used as independent variables for growth prediction, leaf area was found to be an appropriate independent variable for growth prediction. However, additional destructive or non-destructive methods for predicting growth should be considered. In this study, we created a growth model formula to predict perilla growth in plant factories.

Background : To select plant resources of the possibility of development as a natural antioxidant, the antioxidant activities including total polyphenol content (TPC), 2,2'-azino-bis-3-ethylbenzothiazoline-6-sulphonic acid (ABTS), 2,2-diphenyl-1-picryl-hydrazil (DPPH), ferric reducing antioxidant power (FRAP) and reducing power (RP) of perilla accessions collected from South Korea were conducted. Method and Results : A total of 18 perilla accessions by regions were selected. Two grams of dried perilla leaves were extracted with 85% ethanol and used for analysis of antioxidant activity. Antioxidant activity value was measured in a spectrophotometer. Perilla extracts showed variation in TPC ranging from 30.87 to 92.66 ㎍ GAE ㎎-1 dw. ABTS, DPPH, FRAP and RP ranged from 6.83 to 38.64 ㎍ Trolox ㎎-1 dw, 0.63 to 8.62 ㎍ ASC ㎎-1 dw, 5.05 to 17.57 ㎍ ASC ㎎-1 dw, and 4.52 to 35.69 ㎍ ASC ㎎-1 dw, respectively. TPC was high in perilla leaves of Gyeongsang-do, but other antioxidant activities were high in perilla leaves of Chungcheong-do. Cluster analysis based on antioxidant acitivities of 18 perilla accessions consist of group Ⅰ (3 accessions), Ⅱ (2 accessions), Ⅲ (5 accessions) and Ⅳ (8 accessions). Group Ⅱ characterized as higher antioxidant activities than other groups. Principal component analysis (PCA) based on antioxidant data revealed that the first two principal components (PC1 and PC2) together explained 97.78 % total variation. Conclusion : IT242410 and IT235354 of group Ⅱ showed high antioxidant activity. These resources will be useful for developing natural antioxidants.

자소는 여러 질환을 치료하는 식물로 알려져 있는데, 본 연구는 자소 추출물을 이용하여 항산화 활성 및 항염증 활성을 알아보았다. 자소 추출물을 이용한 DPPH, FRAP 실험 결과, 농도에 따른 항산화 활성을 확인할 수 있었으며, 자소자 추출물의 경우 고온/고압 추출시 활성이 증가하는 것을 알 수 있었다. 마우스 동물모델을 이용한 항아토피활성 결과 귀와 상피의 비후를 감소시키고, 면역세포의 침투현상을 억제하는 것으로 나타났다. 이상의 결과로, 자