• Korean Journal of Food Science and Technology
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• v.47 no.1
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• pp.20-26
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• 2015

This study aimed to establish a rapid system for discriminating the cultivation origins and cultivars of dry persimmons, using metabolite fingerprinting by Fourier transform infrared (FT-IR) spectroscopy combined with multivariate analysis. Whole-cell extracts from the sepals of four Korean cultivars and two different Chinese dry persimmons were subjected to FT-IR spectroscopy. Principle component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) of the FT-IR spectral data successfully discriminated six dry persimmons into two groups depending on their cultivation origins. Principal component loading values showed that the 1750-1420 and $1190-950cm^{-1}$ regions of the FT-IR spectra were significantly important for the discrimination of cultivation origins. The accuracy of prediction of the cultivation origins and cultivars by PLS regression was 100% (p<0.01) and 85.9% (p<0.05), respectively. These results clearly show that metabolic fingerprinting of FT-IR spectra can be applied for rapid discrimination of the cultivation origins and cultivars of commercial dry persimmons.

• Journal of Plant Biotechnology
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• v.33 no.4
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• pp.283-288
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• 2006

Discrimination of 5 rice cultivars (Sangjubyeo , Dongjinbyeo Simbaekbyeo , Hwamanbyeo , and Simbaek-hetero ) using metabolic profiling was carried out. Whole cell extracts from each cultivar were subjected to $^1H$ NMR spectroscopy. When spectral data were analyzed by principal component analysis, 5 cultivars were clustered into 3 groups: SJ, DJ + SB, and HM + SH. Thecultivars showed great difference in carbohydrate region of $^1H$ NMR spectra, suggesting that qualitative and quantitative differences in carbohydrate compounds play a major role in discrimination of the cultivars. In addition, it was readily possible to determine relative quantification of major carbohydrates including sucrose, glucose, maltose from spectral data of the cultivars. SJ showed 2 to 4 times higher content of maltose than the other rice cultivars. Overall results indicate that metabolic discrimination of rice cultivars using $^1H$ NMR spectroscopy combined by multivariate statistical analysis can be used for rapid discrimination of numerous rice cultivars and simple quantitative analysis system of major carbohydrate compounds in rice grains.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.148-148
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• 2022

콩[(Glycine max(L.)]은 우리나라에서 벼와 더불어 주요한 식량작물이다. 농촌진흥청에서는 콩 생육데이터를 수집하여 생산성 향상모델을 개발하기 위해 '농업빅데이터수집및생산성향상모델개발' 사업을 수행하고 있다. 수집되는 콩 데이터는 농가정보, 콩 생육정보, 토양정보 부분으로 구성되어 있으며 농가정보는 시군, 시군구, 품종, 파종량, 종자확보경로 등이 수집되고 있다. 그리고 콩 생육정보는 경장, 줄기굵기, 마디수, 가지수, 꼬투리수, 꼬투리립수, 개체당 입수, 종실수량 등이 수집되어 있다. 토양정보는 수분, 지온, EC 등이 수집되고 있다. 주요 항목의 평균은 경장 47.4 cm, 줄기굵기 11.1 mm 마디수 12.7 개, 꼬투리수 54.0 개, 꼬투리립수 2.7 개, 종실수량 227.9 kg/10a 정도이며 토양수분은 26.3 %, 지온은 27.1 ℃ EC는 2.58 ds/CM 정도이다. 주요 형질의 상관관계는 종실수량과 개체당 협수가 0.651로 나타났으며 가지수, 꼬투리수, 개체당협수와 줄기굵기는 각각 0.783, 0.653, 0.663 정도로 나타났다. 추후 이를 기반으로 다중회귀 등 분석 가능한 방법(머신러닝 등)을 적용하여 콩수량을 예측할 수 있는지 검토할 필요가 있다. 또한 본 사업으로 수집된 자료를 분석하여 콩 수량에 영향을 미치는 주요 요인을 평가한 결과는 콩 생산성 향상을 위한 모델 작성에 중요한 자료로 활용될 수 있을 것으로 예상된다.

• Journal of Internet Computing and Services
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• v.5 no.5
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• pp.1-15
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• 2004

In this paper, we explain the design and implementation of GWB(Gene WorkBench), which is a web-based, integrated system for efficiently managing and analyzing genomic sequences, Most existing software systems handling genomic sequences rarely provide both managing facilities and analyzing facilities. The analysis programs also tend to be unit programs that include just single or some part of the required functions. Moreover, these programs are widely distributed over Internet and require different execution environments. As lots of manual and conversion works are required for using these programs together, many life science researchers suffer great inconveniences. in order to overcome the problems of existing systems and provide a more convenient one for helping genomic researches in effective ways, this paper integrates both managing facilities and analyzing facilities into a single system called GWB. Most important issues regarding the design of GWB are how to integrate many different analysis programs into a single software system, and how to provide data or databases of different formats required to run these programs. In order to address these issues, GWB integrates different analysis programs byusing common input/output interfaces called wrappers, suggests a common format of genomic sequence data, organizes local databases consisting of a relational database and an indexed sequential file, and provides facilities for converting data among several well-known different formats and exporting local databases into XML files.

• Journal of Applied Biological Chemistry
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• v.65 no.4
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• pp.429-438
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• 2022

The composition of crops reveal natural variation according to genetic characteristics and environmental factors such as the cultivated regions. For comparative investigation of the impact of genetic difference and environmental influence on the levels of bioactive components in rice seeds, 23 cultivars including indica, japonica, and tongil rice were grown in two location in Korea (Jeonju and Cheonan) for two years (2015 and 2016). Sixteen compounds consisting of tocopherols, tocotrienols, phytosterols, and policosanols were identified from 368 rice samples and the compositional data were subjected to data mining processes including principal component analysis and Pearson's correlation analysis. Under 4 different environmental conditions (Jeonju in 2015, Cheonan in 2015, Jeonju in 2016, Cheonan in 2016), the natural variability of rice seeds showed that the genetic background (indica vs japonica vs tongil) had more impact on the compositional changes of bioactive components compared to the environments. Especially, the results of correlation analysis revealed negative correlation between α-, β-tocopherols and γ-, δ-tocopherols as a representative genetic effect that did not changed by the environmental influence.

• Annual Conference of KIPS
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• 2018.10a
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• pp.603-605
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• 2018

최근 대두되고 있는 딥 러닝은 학습을 통해 사물이나 데이터를 군집화하거나 분류하는 데 사용하는 기술이다. 본 논문은 딥 러닝에 활용하기 위해 개발된 오픈소스 소프트웨어인 텐서플로 Inception V3을 사용해 연구를 진행했다. 딥 러닝을 활용한 씨앗 발아 확인 시스템은 기존의 영상 처리를 활용한 시스템에서 고안했으며, 씨앗 발아 여부의 정확성이 떨어지는 단점을 개선하고, 모든 종자들의 발아 여부를 확인할 수 있도록 구현해 사용자가 효과적으로 연구를 수행할 수 있도록 하는 목적에 있다.

• Proceedings of the Korean Society of Crop Science Conference
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• 2020.11a
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• pp.132-132
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• 2020

아직까지 국내에서 GM작물이 상업화를 위해 승인된 예는 없지만 생명공학기술의 발전으로 GM작물의 개발은 급속한 증가 추세에 있다. 비의도적인 방출로 인해 미승인 LMO 목화가 전국적으로 재배되어 국립종자원 주관으로 양성 판정된 재배지의 목화를 폐기 처분하였으나(2017), GM작물이 유해하다는 인식과 환경에 방출되어 생태계를 교란시킨다는 인식이 팽배해 있는 현실에서 과학적으로 유전자의 이동성을 검증하는 노력이 중요하다. 자식성 작물의 화분의 이동성 조사를 위해 중앙의 코어 위치에 LM작물을 식재한 후 LM작물 주변에 재배품종을 심어 유전자이동 가능성을 조사하고 재배 환경에 의한 영향을 평가하기 위해 포장 주변 기상상황 데이터-온도, 습도, 풍속, 풍향, 기압, 강수량 등을 분석하고 기상상황이 화분의 전이에 미치는 영향 조사하였다.

• Horticultural Science & Technology
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• v.28 no.4
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• pp.567-573
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• 2010

Research was initiated to investigate early establishment characteristics and germination pattern of fine-textured fescues (FF). Six varieties from Chewings fescue ($Festuca$ $rubra$ L. ssp. $commutata$ Gaud., CF), creeping red fescue ($F.$ $rubra$ L. ssp. $rubra$ Gaud., CRF), hard fescue ($F.$ $ovina$ ssp. $longifolia$ Thuill., HF) and sheep fescue ($F.$ $ovina$ L., SF) were evaluated in the study. An alternative environmental condition requiring a FF germination test by International Seed Testing Association (ISTA) was applied in the experiment, consisting of 8-hr light at $25^{\circ}C$ and 16-hr dark at $15^{\circ}C$ (ISTA conditions). Daily and cumulative germination patterns were measured and analyzed on a daily basis. Significant differences were observed in germination pattern, days to the first germination, days to 50% germination, days to 60% germination, and germination rate. The final germination percentage was variable with species and varieties, being 40.25 to 82.00% at the end of study. There were considerable variations in early germination characteristics and germination pattern among FF species. The first germination in all entries except HF was initiated between 5 and 6 DAS (days after seeding) under ISTA conditions, while HF between 6 and 7 DAS, being 1 day later. It was 8 to 10 DAS in days to the 50% germination, which was 2 to 4 days after the first germination date. Days to the 60% germination were 9.10 to 14.80 DAS under ISTA conditions, being 5.70 days in differences among the entries. CF 'Jamestown II' and 'Shadow II' and HF 'Aurora Gold' were the fast varieties. The slowest one was HF 'Rescue 911'. Among FF species, turf establishment speed was becoming faster in CRF, SF, HF and CF in this order. Information on differences in germination characteristics and pattern from this study would be usefully applied for golf course design and construction, when established with FF.

• Journal of Plant Biotechnology
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• v.42 no.1
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• pp.60-70
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• 2015

The aim of this study was to investigate whether fourier transform infrared (FT-IR) spectroscopy can be applied to simultaneous determination of fatty acids contents in different soybean cultivars. Total 153 lines of soybean (Glycine max Merrill) were examined by FT-IR spectroscopy. Quantification of fatty acids from the soybean lines was confirmed by quantitative gas chromatography (GC) analysis. The quantitative spectral variation among different soybean lines was observed in the amide bond region ($1,700{\sim}1,500cm^{-1}$), phosphodiester groups ($1,500{\sim}1,300cm^{-1}$) and sugar region ($1,200{\sim}1,000cm^{-1}$) of FT-IR spectra. The quantitative prediction modeling of 5 individual fatty acids contents (palmitic acid, stearic acid, oleic acid, linoleic acid, linolenic acid) from soybean lines were established using partial least square regression algorithm from FT-IR spectra. In cross validation, there were high correlations ($R^2{\geq}0.97$) between predicted content of 5 individual fatty acids by PLS regression modeling from FT-IR spectra and measured content by GC. In external validation, palmitic acid ($R^2=0.8002$), oleic acid ($R^2=0.8909$) and linoleic acid ($R^2=0.815$) were predicted with good accuracy, while prediction for stearic acid ($R^2=0.4598$), linolenic acid ($R^2=0.6868$) had relatively lower accuracy. These results clearly show that FT-IR spectra combined with multivariate analysis can be used to accurately predict fatty acids contents in soybean lines. Therefore, we suggest that the PLS prediction system for fatty acid contents using FT-IR analysis could be applied as a rapid and high throughput screening tool for the breeding for modified Fatty acid composition in soybean and contribute to accelerating the conventional breeding.

• Language Facts and Perspectives
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• v.45
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• pp.35-59
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• 2018

In this paper, as a proposal to an effective corpus construction and utilization scheme, there is a purpose to explore the present situation of Japanese corpus construction, concrete content and current trend. In Japan, dependence on google is remarkable, there has been a steady effort to develop high-quality corpus and development tool. On the other hand, the Japanese corpus should clearly grasp the location and information from those created by individual researchers to their own purpose to those created mainly by universities, research institutes, national policy institutions, etc. It is difficult. In this survey, it was possible to distinguish by "media corpus", "literary·magazine·web and balanced corpus", "spoken language corpus", "learner corpus", "historical material corpus" etc. by field and type. In addition, there were not many tools developed for corpus efficient use and secondary processing such as "example search", "morphological analysis", "machine translation", etc. for tool corpus only. The current trend in Japanese corpus construction spurred preparations for Seed data which can be utilized in linguistic research and various fields of the fourth industry, including national policy and research institutes such as NINJAL, JPO, NICT, ALAGIN and companies such as RAKUTEN ing.