• Journal of the Korean Society of Food Science and Nutrition
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• v.46 no.6
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• pp.730-738
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• 2017

In this study, we investigated the physicochemical properties of coffee brews according to coffee bean grinding grade. We also examined the effect of grinding grade on amounts of volatile flavor compounds. Coffee brew samples were separated using standard sieves (with pore sizes of 850, 600, and $425{\mu}m$), making particle sizes of ground beans as follows: whole bean (control), $850{\mu}m$ or more (coarse), $850{\sim}600{\mu}m$ (medium), $600{\sim}425{\mu}m$ (fine), and $425{\mu}m$ or less (very fine). For each particle size category, pH, total acidity, brown color intensity, chromaticity, total phenolic content, caffeine content, chlorogenic acid content, and total amounts of volatile flavor compounds generated were compared and analyzed. As grinding grade decreased, pH and brown color intensity increased from 4.84 to 5.18 and from 0.257 to 0.284, respectively, whereas total acidity decreased from 0.31 to 0.17%. As grinding grade decreased, the $L^*$ and $a^*$ color values decreased; however, $L^*$ value did not exhibit a significant difference depending on the grinding grade. The $b^*$ value was 15.75 in the very fine size category, which showed the highest yellowness. There was an 11 or higher color difference between the control and ground coffee powder, indicating a remarkable color difference. The total phenolic, caffeine, and chlorogenic acid contents of the coffee brewed from ground beans with a very fine size were 4.54 mg gallic acid equivalent/mL, $733.0{\mu}g/mL$, and $383.7{\mu}g/mL$, respectively, which were high values. The total amounts of volatile compounds in the very fine size category were found to be greater than 100 mg/kg. In this study, we suggest the basis for coffee quality evaluation, which involves evaluating changes in the physicochemical properties and amounts of flavor compounds of coffee relative to the grinding grade of the beans (basic step of coffee extraction).

• Korean Journal of Heritage: History & Science
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• v.51 no.1
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• pp.4-31
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• 2018

The Neolithic pottery excavated from the Jungsandong site has been classified into four types of pottery (I: feldspar type, II: mica type, III: talc type and IV: asbestos type) according to their mineral composition. These four types of potteries generally appear to have undergone incomplete firing, while the level of oxidation in the type I pottery objects, which have a relatively higher clay content, was found to be particularly low. The type III objects, which have a high talc content, are judged to have been somewhat slow in removing carbon because they contain saponite belonging to the smectite group. Of the four types of pottery, type IV showed the highest redness and the most uniform characteristics, thus indicating a good level of oxidation. In particular, fixed carbide (C; 33.7 wt.%) with a thickness of about 1mm, and originating from organic substances, was detected inside the walls of the type I pottery, while the deep radial cracks in the outer surfaces of the pottery are thought to have been caused by repeated thermal shocks. Given that all of the pottery except for the type I artifacts are considered to be have been made for storage purposes, those containing talc and tremolite are easy to done liquid storing vessels based on an analysis of their material characteristics. As for the type II relics, which are composed of various minerals and exhibit poor physical properties, they seem to have been used for simple storage purposes. As domestic talc and asbestos mines were concentrated in the areas of Gyeonggi, Gangwon, Chungbuk, and Chungnam, it seems likely that talc and tremolite were produced as contiguous minerals. Considering the distance between the remains in Jungsandong and these mines and their geographical distribution, there is a possibility - albeit somewhat slight - that these mines were developed for the mining of various minerals. Although ultramafic rock masses - such as serpentine capable of generating talc and tremolite - have not been found in the Jungsandong area, limestone and biotite granite containing mica schist have been identified in the northwestern part of Yeongjong Island, indicating that small rock masses might have formed there in the past. Therefore, it is judged necessary to accumulate data on pottery containing talc and tremolite, other than the remains in Jungsandong, and to investigate the rocks and soils in the surrounding area with greater precision. The firing temperatures of the pottery found at the Jungsandong site were interpreted by analyzing the stability ranges of the mineral composition of each type. As a result, they have been estimated to range from 550 to $800^{\circ}C$ for the type I artifacts, and from 550 to $700^{\circ}C$ for the type I, II and IV artifacts. However, these temperatures are not the only factors to have affected their physical properties and firing temperature, and the types, particle sizes, and firing time of the clay should all be taken into consideration.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.1
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• pp.17-27
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• 2023

Weeds are one of the factors that reduce crop yield through nutrient and photosynthetic competition. Quantification of weed density are an important part of making accurate decisions for precision weeding. In this study, we tried to quantify the density of weeds in images of maize fields taken by unmanned aerial vehicle (UAV). UAV image data collection took place in maize fields from May 17 to June 4, 2021, when maize was in its early growth stage. UAV images were labeled with pixels from maize and those without and the cropped to be used as the input data of the semantic segmentation network for the maize detection model. We trained a model to separate maize from background using the deep learning segmentation networks DeepLabV3+, U-Net, Linknet, and FPN. All four models showed pixel accuracy of 0.97, and the mIOU score was 0.76 and 0.74 in DeepLabV3+ and U-Net, higher than 0.69 for Linknet and FPN. Weed density was calculated as the difference between the green area classified as ExGR (Excess green-Excess red) and the maize area predicted by the model. Each image evaluated for weed density was recombined to quantify and visualize the distribution and density of weeds in a wide range of maize fields. We propose a method to quantify weed density for accurate weeding by effectively separating weeds, maize, and background from UAV images of maize fields.