• Title/Summary/Keyword: clay soil

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Effect of Slow-release Fertilizer Levels of Rice in Different Cultural Methods (벼 재배양식에 따른 유효성 비료의 시용량이 생육과 수량에 미치는 영향)

  • 정진일;최원영;최민규;이선용
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.40 no.6
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    • pp.747-756
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    • 1995
  • To find out the optimum application method of slow-releasing fertilizer(SRF) and conventional fertilizer(CF) with different fertilization rate under two culture methods[l0-day old seedling machine transplanting(MT) and direct-sowing on dry paddy(DS)] in the south-western region(clay loam soil) of Korea, used were Chosun slow-releasing fertilizer(silicate latex coated fertilizer: N-P$_2$O$_{5}$-K$_2$O =18-12-13) and conventional fertilizer. Plant height and number of tillers with different two culture methods were higher at MT than DS in early growth. The ratio of dry weight in heading stage was higher at CF than SRF in MT than DS and especially, SRF 80% + CF 20% than SRF 100% or CF 100%. Leaf area index (LAI) in heading stage was higher at CF in MT but higher at SRF in DS than their counterparts. Chlorophyll content was higher at SRF than in CF expect for heading stage(HS), especially in DS. It was highest at HS in CF without its difference during maximum tillering stage(MTS) and panicle formation stage(PFS), while highest at PFS in SRF with tendency of gradual increase and decrease before and after PFS, respectively. Heading was delayed 2~3 days at SRF in two cultrue methods and 4~5 days at SRF in DS in comparison with CF in MT with delay of 2 days at DS compared with MT. Culm length was longer at CF in MT and at SRF in DS than their counterparts. Panicle number per m was more at SRF and in DS. Filled grain ratio was higher at CF and in MT. Yield was obtained 101 and 100% at 100% and 80% level of SRF in DS respectively, and 96% at 80% level of CF in MT, compared with conventional application method (516kg /l0a), and increased 2~4% at DS and 0~3% at MT in SRF. Yield was high in order of 100%(SRF) =80%(SRF) + 20%(CF) > 100%(SRF) + 20%(CF) > 80%(SRF) at MT and 80%(SRF) + 20%(CF) =100%(SRF) > 80%(SRF) =100%(SRF) + 20%(CF) at DS.

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Geochemistry, Secondary Contamination and Heavy Metal Behavior of Soils and Sediments in the Tohyun Mine Creek, Korea (토현광산 수계에 분포하는 토양과 퇴적물의 지구화학적 특성, 이차적 오염 및 중금속의 거동)

  • 이찬희;이현구;윤경무
    • Economic and Environmental Geology
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    • v.34 no.1
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    • pp.39-53
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    • 2001
  • Environmental pollution of the Tohyun mine creek area was investigated on the basis of geology, mineralogy and geochemistry. In soils and sediments of the mine area, ${Al_2}{O_3}/{Na_2O}$ and ${K_2}O/{Na_2}O$ ratios are partly negative correlation against ${SiO_2}/{Al_2}{O_3}$, respectively. Geochemical characteristics of some trace and rare earth elements such as V/Ni, Ni/Co, La/Ce, Th/Yb, Th/U, La/Th, ${La_N}/{Yb_N}$, La/Sc and Sc/Th are revealed a narrow range and homogeneous compositions may be explained by simple source lithology. These results suggest that sediments source of the host shale around the mine area could be originated by basic to intermediate igneous rocks. Mineral compositions of soil and sediment near the mine area were partly variable mineralogy, which are composed of quartz, mica, feldspar, chlorite, clay minerals and some pyrite. Soils and sediments with highly concentrated heavy minerals, gravity separated mineralogy, are composed of some pyrite, arsenopyrite, chalcopyrite, sphalerite, galena, goethite and various kinds of hydroxide minerals on the polished sections. As normalized by bed rock composition, average enrichment indices of major elements in sediments, precipitates, farmland soils and paddy soils are 1.0, 1.7, 0.9 and 0.8, respectively. Maximum concentration of environmental toxic elements in the mine creek are detected with Ag = 186 ppm, As = 17,100 ppm, Bi = ]27 ppm, Cd = 77 ppm, Cu = 12,299 ppm, Pb = 8,897 ppm, Sb = 1,350 ppm, W = 599 ppm and Zn = 12,250 ppm, which are increasing with total FeO increasing, and extremely high concentrations of surface sediments and precipitates near the waste rock dump. These toxic elements (As, Bi, Cd, Cu, Pb, Sb, W and Zn) of the samples, normalizing by host rock concentration, revealed that average enrichment index is 106.0 for sediments, 279.6 for precipitates, 3.5 for farmland soils and 1.6 for paddy soils. However, on the basis of EPA values, enrichment indices of all the samples are 40.7, 121.4, 1.3 and 0.6, respectively.

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Difference of Starch Characteristics of Sweetpotato (Ipomoea batatas (L.) Lam) by Cultivated Regions (재배지역에 따른 고구마(Ipomoea batatas (L.) Lam) 품종의 전분 특성 차이)

  • Han, Seon-Kyeong;Song, Yeon-Sang;Lee, Hyeong-Un;Ahn, Seung-Hyun;Yang, Jung-Wook;Lee, Joon-Seol;Chung, Mi-Nam;Suh, Sae-Jung;Park, Keun-Hyung
    • Korean Journal of Food Science and Technology
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    • v.45 no.6
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    • pp.682-692
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    • 2013
  • We investigated out the effect of cultivation region on the physicochemical characteristics of starch in six sweetpotato cultivars. The following sweetpotato cultivars were analyzed: Daeyumi, Shingeonmi, Jinhongmi, Shinyulmi, Yulmi, and Yeonhwangmi. Samples were cultivated in Muan, Iksan, Nonsan, Boryeong and Hamyang. The soil texture was found to be sandy loam in Muan, Iksan, and Boryeong, sandy clay loam in Nonsan, and loam in Hamyang. The starch content of the sweetpotato was higher in Muan than in Hamyang. The amylose content was 22.3-30.9%, and the highest amylose content was found in samples from Iksan. Rapid viscosity analysis showed that the samples from Hamyang had the lowest values of pasting temperature, while samples of the Daeyumi cultivar had the highest values. Thermal analysis with a differential scanning calorimeter showed that the Muan samples had the highest values of onset temperature, maximum peak temperature, and completion temperature, and the samples from Hamyang had the lowest values. There was no difference between the cultivation regions or the cultivar in the X-ray pattern of the starch or its appearance in scanning electron micrographs. Therefore, the results of this study confirm that cultivation region and cultivar play an important role in determining the quality of sweetpotato and the physicochemical characteristics of sweetpotato starch.

Studies on the Desertification Combating and Sand Industry Development(I) - Present Status and Countermeasures for the Combating Desertification in China - (사막화방지(沙漠化防止) 및 방사기술개발(防沙技術開發)에 관한 연구(硏究)(I) - 중국(中國)의 사막화현황(沙漠化現況) 및 방지대책(防止對策) -)

  • Woo, Bo-Myeong;Lee, Kyung-Joon;Jeon, Gi-Seong;Kim, Kyung-Hoon;Choi, Hyung-Tae;Lee, Seung-Hyun;Lee, Byung-Kwon;Kim, So-Yeon;Lee, Sang-Ho;Jeon, Jeong-Ill
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.3 no.3
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    • pp.45-76
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    • 2000
  • The purposes of this study were to investigate and understand the present status of various types of "deserts", such as sand desert, gravel desert, rock desert, earth desert, salt desert, desert, rocky desert, gobi desert, sandy desert, clay desert, etc., and the general countermeasures for the combating "desertification" "desertization", and to develop the technologies on the revegetation and restoration for the combating desertification in China. The methods of this study were mainly composed of field surveys on the several experimental sites and research institutes related to combating desertification in China, and examinations on the various technologies for the combating desertification at the Daxing Experimental Station of Beijing Forestry University. The conclusion from this study may be summarized as follows; 1. Status and tendency of desertification in China : China is one of the countries seriously threatened by desertification. Desertification affected areas in China are mainly distributed in arid, semi-arid and dry sub-humid areas in China, covering the most regions of the Northeast China (eastern region of Inner-Mongolia), the northern part of the North China (middle and western region of Inner-Mongolia, Shaanxi, Ningsha, Gansu) and the western part of the Northwest China (Xinzang, Qinghai, Xizang). The total area affected by desertification in China is approximately 2.622 million $km^2$. It covers 27.3% of the total territory of China. Until recently, it is estimated that the annual spreading ratio of desertification in China is 2,460 $km^2$. Therefore, desertification is mostly serious problems facing to the Chinese people. 2. The causes and environmental effect of desertification : The desertification in China is mainly caused by compound factors, including natural condition and human activities. In China, the desertification is started by the decrease of precipitation, continuous dry and drought, strong wind, wind and water erosion, land degradation and loss of natural vegetation caused by climate variation, and accelerated by the human activities, such as over-cultivating, over-grazing, over-cutting of woods, irrational use of water resources. Because desertification has affected the geographical features, soil nutrients contents, salinity, vegetation coverage and the functions of ecosystem, the environmental deteriorations in the desertification affected areas are very seriously. 3. The fundamental strategies of combating desertification in China are the increase of education and awareness of people through various mass media, the revision of laws to guarantee operation of Desertification Combating Law and to improve many relating laws and regulations, the application of advanced technologies and training of experts, the establishment of discriminative policies, and increasing arrangement of budget-investment, and so on. China, as a signed country in UNCCD, has made efforts for the combating desertification. Korea is also signed country in UNCCD, so we should play an important role in the desertification combating projects of China for the northest asia and global environmental conservation as well as environmental conservation of Korea.

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Environmental Survey on the Cultivation Ground in the West Coast of Korea (서해연안의 양식장 환경조사 3. 부안 백합 양식장 환경)

  • LEE Jeong-Yeol;KIM Young-Gill
    • Journal of Aquaculture
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    • v.4 no.2
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    • pp.111-128
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    • 1991
  • In puan area the environmental surveys were carried out at two farms of hard clam, Meretrix lusoria from April 1987 to November 1978 in order to know heather the farm environments could be rehabilitated for the cultivation of hard clam or not. The range of temperature of surface seawater was $10.7{\~}27.4^{\circ}C$, pH $7.6{\~}8.2$, salinity $22.3{\~}30.3$ ppt, COD $0.20{\~}4.71\;mg/{\ell}$, sulfide $0.04{\~}0.22\;{\mu}g-at./{\ell}$, suspended solid $34.8{\~}199.3\;mg/{\ell}$ chlorophyll a $3.71{\~}49.02\;mg/m^3$, TIN $2.01{\~}24.47\;{\mu}g-a5./{\ell}$, phosphate $0.60{\~}11.03\;{\mu}g-at./{\ell}$ and silicate $4.04{\~}476.36\;{\mu}g-at./{\ell}$. The range of temperature of substratum (bottom soil) was $14.2{\~}29.7^{\circ}C$, pH $8.3{\~}9.5$, water content of substratum was $0.28{\~}0.49\;mg/g$ dried mud, COD $2.80{\~}50.94\;mg/g$ dried mud, total organic matter $1.05{\~}1.97\%$ concentration of total Kjedhal nitrogen $31.9{\~}194.9\;{\mu}g./{\ell}$ dried mud, and sulfide $0.032{\~}0.133\;mg/g$ dried mud. Fine sand was dominant ranging over $92{\~}95\%$ and silt and clay was $2.8{\~}8.1\%$ of the composition of substratum. Some residual agricultural chemicals, ${\alpha},\;{\beta},\;{\gamma}$-BHC, heptachlor, heptachlor-epoxide, aldrin, DDE, DDT and dieldrin were detected in hard clams collected from Puan areas. Especialy, more chemical were detected during the period of rainfalls. From above results, it is considered that the hard clam frams were not yet recovered from deteriorated conditions for aquaculture.

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Study on Adsorption Characteristics of Arsenic on Magnetite (자철석의 비소에 대한 흡착특성 연구)

  • Jeong, Hyeon-Su;Lee, Woo-Chun;Cho, Hyen-Goo;Kim, Soon-Oh
    • Journal of the Mineralogical Society of Korea
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    • v.21 no.4
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    • pp.425-434
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    • 2008
  • Arsenic contamination in soil and groundwater has recently been one of the most serious environmental concerns. This arsenic contamination can be originated from natural or anthropogenic sources. It has been well known that arsenic behavior in geo-environmental is controlled by various oxides or hydroxides, such as those of iron, manganese, and aluminum, and clay minerals. Among those, particularly, iron (oxy)hydroxides are the most effective scavengers for arsenic. For this reason, this study characterized arsenic adsorption of magnetite which is a kind of iron oxide in nature. The physicochemcial features of the magnetite were investigated to evaluate adsorption of arsenite [As(III)] and arsenate [As(V)] onto magnetite. In addition to experiments on adsorption equilibria, kinetic experiments were also conducted. The point of zero charge (PZC) and specific surface area of the laboratory-synthesized magnetite used as an arsenic adsorbent were measured 6.56 and $16.6\;g/m^2$, which values seem to be relatively smaller than those of the other iron (oxy)hydroxides. From the results of equilibria experiments, arsenite was much more adsorbed onto magnetite than arsenate, indicating the affinity of arsenite on magnetite is larger than arsenate. Arsenite and arsenate showed adsorption maxima at pHs 7 and 2, respectively. In particular, adsorption of arsenate decreased with increase in pH as a result of electrical repulsion caused by anionic arsenate and negatively-charged surface of magnetite. These results indicate that the surface charge of magnetite and the chemical speciation of arsenic should be considered as the most crucial factors in controlling arsenic. The results of kinetic experiments show that arsenate was adsorbed more quickly than arsenite and adsorption of arsenic was investigated to be mostly completed within the duration of 4 hours, regardless of chemical speciation of arsenic. When the results of kinetic experiments were fitted to a variety of kinetic models proposed so far, power function and elovich model were evaluated to be the most suitable ones which can simulate adsorption kinetics of two kinds of arsenic species onto magnetite.

Economic Analysis, Growth and Pests of Wheat (Triticum aestivum L.) in Gelatin·Chitin Microorganisms-treated Organic Culture (젤라틴·키틴분해미생물을 이용한 밀 유기재배와 관행재배의 생육, 병해충 발생조사 및 경제성 분석)

  • Ahn, Philip;Lee, Jiho;Cha, Kwang-Hong;Seo, Dong-Jun;An, Kyu-Nam;Yoon, Chang-Yong;Kim, Kil-Yong;Jung, Woo-Jin
    • Korean Journal of Organic Agriculture
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    • v.29 no.2
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    • pp.223-240
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    • 2021
  • This study was carried out to investigate the economic value of organic wheat production using gelatin·chitin microorganisms in Gwangsan-gu, Gwangju city. The soil condition of experiment field was clay loam Jisan series. The organically cultivated fields were sprayed gelatin and chitin degrading bacteria. The test was performed at conventionally cultivated field and organically cultivated field. Emergence of weed on organically cultivated field was significantly higher than conventionally cultivated field which sprayed herbicide before seeding. Weed emergence have a critical impact on grain yield. Occurrence of diseases and insect pests were higher than conventionally cultivated fields. In 2019, the amount of lodging in conventionally cultivated field were higher than conventionally cultivated field. In 2020, lodging and wet injury were occur in both field. Comparing yield element between organically and conventionally cultivated experimental area, grain yield in organically cultivated field was shown slightly higher amount than conventionally cultivated field. However in the actual yield of 2019, organically cultivated field shows 20% deceased yield because of overgrown weed. In 2020, weed emergence and yellow mosaic virus by wet injury cause 30% decease in the grain yield in organically cultivated field. Content of protein, carbohydrates, ash, water and fat in the grain were not different significance. In 2019, net incomes of conventionally cultivated wheat was 461,031 won/0.1 ha while organically cultivated wheat was 443,437 won/0.1 ha. In the rate of income, conventionally cultivated field was 83.0% as against organically cultivated field (73.3%). In 2020, net incomes of organically cultivated wheat was 437,812 won/0.1 ha while conventionally cultivated wheat was 418,281 won/0.1 ha. In the rate of income, conventionally cultivated field was 81.6% as against organically cultivated field (73.0%).

Classifications by Materials and Physical Characteristics for Neolithic Pottery from Jungsandong Site in Yeongjong Island, Korea (영종도 중산동 신석기시대 토기의 재료학적 분류와 물리적 특성)

  • Kim, Ran Hee;Lee, Chan Hee;Shin, Sook Chung
    • Korean Journal of Heritage: History & Science
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    • v.50 no.4
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    • pp.122-147
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    • 2017
  • The Jungsandong sites are distributed across quartz and mica schist formations in Precambrian, and weathering layers include large amounts of non-plastic minerals such as mica, quartz, felspar, amphibole, chlorite and so on, which form the ground of the site. Neolithic pottery from Jungsandong exhibits various brown colors, and black core is developed along the inner part for some samples, and sharp comb-pattern and hand pressure marks can be observed. Their non-plastic particles have various composition, size distribution, sorting and roundness, so they are classified into four types by their characteristic mineral compositions. I-type (feldspar pottery) is including feldspar as the pain component or mica and quartz. II-type (mica pottery) is the combination of chloritized mica, talc, tremolite and diopside. III-type (talc pottery) is with a very small amount of quartz and mica. IV-type (asbestos pottery) is containing tremolite and a very small amount of talc. The inner and outer colors of Jungsandong pottery are somewhat heterogeneous. I-type pottery group shows differences in red and yellow degree, depending on the content of feldspar, and is similar to III-type pottery. II-type is similar to IV-type, because its red degree is somewhat high. The soil of the site is higher in red and yellow degree than pottery from it. The magnetic susceptibility has very wide range of 0.088 to 7.360(${\times}10^{-3}$ SI unit), but is differentiated according to minerals, main components in each type. The ranges of bulk density and absorption ratio of pottery seem to be 1.6 to 1.7 and 13.1 to 26.0%, respectively. Each type of pottery shows distinct section difference, as porosity and absorption ratio increase in the order as follows: I-type (organic matter fixed sample) < III-type and IV-type < I-type < II-type (including IV-type of IJP-15). The reason is that differences in physical property occur according to kind and size of non-plastic particles. Although Jungsandong pottery consists of mixtures of various materials, the site pottery has a geological condition on which all mineral composition of Jungsandong pottery can be provided. There, it is thought that raw materials can be supplied from weathered zone of quartz and mica schist, around the site. However, different constituent minerals, size and rock fragments are shown, suggesting the possibility that there can be more raw material pits. Thus, it is estimated that there may be difference in clay and weathering degree.

Characteristics and pedigree selection of a shortened cultivation period strain in Lepista nuda (재배기간이 짧은 민자주방망이버섯 우량계통 선발 및 특성)

  • Jeon, Jong-Ock;Lee, Kwan-Woo;Lee, Kyoung-Jun;Kim, Min-Ja;Kim, In-Jae;Kim, Young-Ho
    • Journal of Mushroom
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    • v.18 no.4
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    • pp.331-338
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    • 2020
  • This study was conducted to cultivate new Lepista nuda varieties with shorter cultivation period and better fruiting body compared to that of wild strains, for mass production and commercial application. Eighteen genetic resources of L. nuda were collected and grown in boxes using rice straw-fermented growth medium. Four lines with fruiting bodies were formed and selected as cross-breeding lines. Although 657 combinations were crossed through monospore crossing, only 17 combinations were bred between the 'CBMLN-19' line and the 'CBMLN-30' line. Among them, 8 lines with fast mycelial growth and high density were selected. After inoculating the rice straw-fermented growth medium with 14 genetic resources and 8 cross-breeding lines, their incubation period was investigated. Six of the cross-breeding lines completed their incubation in 20 days, while 7 of the 14 genetic resources took more than 40 days to complete their incubation, reducing the incubation period by more than 20 days in most cross-breeding lines. After the incubations were completed, the clay loam soil was covered with for post-cultivation, and when the mycelial cultivation was complete, the formation of fruiting bodies was induced after scraping the mycelial bodies under these environmental conditions: 14℃, 95% relative humidity or higher, and 1,500 to 2,000 ppm CO2 concentration. The temperature was reduced to 6℃ at night, resulting in a low temperature shock. Thus, 4 lines of fruiting bodies occurred from two genetic resources 'CBMLN-31' and 'CBMLN-44' and two cross-bred lines 'CBMLN-96' and 'CBMLN-103'. After inoculation, the longest period for fruiting bodies to occur was 100 days for the control:, the genetic resource 'CBMLN-31', and the shortest period (45 days) was observed for the cross-breeding line 'CBMLN-103'. The result of the investigation of the fruiting body characteristics shows that the cross-bred line 'CBMLN-103' showed a small form with 1.9 g of individual weight and 123validstipes per box, which was the highest incidence among the four lines. Another cross-bred line, 'CBMLN-96', had an individual weight of 5.5 g, which is larger than that of 'CBMLN-103'; however, the number of valid stipes per box was 30 less than that of 'CBMLN-103'. Quantity analysis showed that the control, 'CBMLN-31', had the highest quantity of 783 g per box, followed by the cross-bred line, 'CBMLN-96' with 165 g per box, and then the 'CBMLN-103' with 232 g. The quantity of the two crossbred lines was lower than that of the control 'CBMLN-31'; however, the amount of fruiting bodies was higher, and the cultivation period was shortened by 32 to 33 days. Therefore, these two lines would be selected as superior lines.

Identifying sources of heavy metal contamination in stream sediments using machine learning classifiers (기계학습 분류모델을 이용한 하천퇴적물의 중금속 오염원 식별)

  • Min Jeong Ban;Sangwook Shin;Dong Hoon Lee;Jeong-Gyu Kim;Hosik Lee;Young Kim;Jeong-Hun Park;ShunHwa Lee;Seon-Young Kim;Joo-Hyon Kang
    • Journal of Wetlands Research
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    • v.25 no.4
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    • pp.306-314
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    • 2023
  • Stream sediments are an important component of water quality management because they are receptors of various pollutants such as heavy metals and organic matters emitted from upland sources and can be secondary pollution sources, adversely affecting water environment. To effectively manage the stream sediments, identification of primary sources of sediment contamination and source-associated control strategies will be required. We evaluated the performance of machine learning models in identifying primary sources of sediment contamination based on the physico-chemical properties of stream sediments. A total of 356 stream sediment data sets of 18 quality parameters including 10 heavy metal species(Cd, Cu, Pb, Ni, As, Zn, Cr, Hg, Li, and Al), 3 soil parameters(clay, silt, and sand fractions), and 5 water quality parameters(water content, loss on ignition, total organic carbon, total nitrogen, and total phosphorous) were collected near abandoned metal mines and industrial complexes across the four major river basins in Korea. Two machine learning algorithms, linear discriminant analysis (LDA) and support vector machine (SVM) classifiers were used to classify the sediments into four cases of different combinations of the sampling period and locations (i.e., mine in dry season, mine in wet season, industrial complex in dry season, and industrial complex in wet season). Both models showed good performance in the classification, with SVM outperformed LDA; the accuracy values of LDA and SVM were 79.5% and 88.1%, respectively. An SVM ensemble model was used for multi-label classification of the multiple contamination sources inlcuding landuses in the upland areas within 1 km radius from the sampling sites. The results showed that the multi-label classifier was comparable performance with sinlgle-label SVM in classifying mines and industrial complexes, but was less accurate in classifying dominant land uses (50~60%). The poor performance of the multi-label SVM is likely due to the overfitting caused by small data sets compared to the complexity of the model. A larger data set might increase the performance of the machine learning models in identifying contamination sources.