• Title/Summary/Keyword: partial least squares component

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LC/MS-based metabolomics approach for selection of chemical markers by domestic production region of Schisandra chinensis (오미자(Schisandra chinensis)의 국내 산지별 화학적마커 선정을 위한 LC/MS 기반의 대사체학 접근법)

  • In Seon Kim;Seon Min Oh;Ha Eun Song;Doo-Young Kim;Dahye Yoon;Dae Young Lee;Hyung Won Ryu
    • Journal of Applied Biological Chemistry
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    • v.66
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    • pp.467-476
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    • 2023
  • Schisandra chinensis (S. chinensis) is a deciduous broad-leaved cave plant belonging to the Schisandraceae family and is widely distributed in East Asia including Korea, Japan, China, and Taiwan. It has been reported that the main components contained in S. chinensis include lignan compounds and triterpenoid compounds. To distinguish the characteristics of S. chinensis by production region of Korea, a discriminant was established by performing metabolite profiling and principal component analysis, a multivariate statistical analysis technique. As a result, 16 types of triterpenoids, 9 types of lignan, and 1 type each of flavonoid, phenylpropanoid, and fatty acid were identified. In addition, through multivariate statistical analysis, it was confirmed that the four groups in Danyang, Moongyeong, Geochang, and Pyeongchang were divided, by applying the s-plot model of orthogonal partial least squares discriminant analysis. Biomarkers were identified: lanostane, cycloartane, schiartane triterpenoid, and dibenzocyclo-octadiene lignan were identified as chemical markers, respectively.

Discrimination of the drinking water taste by potentiometric electronic tongue and multivariate analysis (전자혀 및 다변량 분석법을 활용한 먹는물의 구별 방법)

  • Eunju Kim;Tae-Mun Hwang;Jae-Wuk Koo;Jaeyong Song;Hongkyeong Park;Sookhyun Nam
    • Journal of Korean Society of Water and Wastewater
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    • v.37 no.6
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    • pp.425-435
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    • 2023
  • Organoleptic parameters such as color, odor, and flavor influence consumer perception of drinking water quality. This study aims to evaluate the taste of the selected bottled and tap water samples using an electronic tongue (E-tongue) instead of a sensory test. Bottled and tap water's mineral components are related to the overall preference for water taste. Contrary to the sensory test, the potentiometric E-tongue method presented in this study distinguishes taste by measuring the mineral components in water, and the data obtained can be statistically analyzed. Eleven bottled water products from various brands and one tap water from I city in Korea were evaluated. The E-tongue data were statistically analyzed using multivariate statistical tools such as hierarchical clustering analysis (HCA), principal component analysis (PCA), and partial least squares discriminant analysis (PLS-DA). The results show that the E-tongue method can clearly distinguish taste discrimination in drinking water differing in water quality based on the ion-related water quality parameters. The water quality parameters that affect taste discrimination were found to be total dissolved solids (TDS), sodium (Na+), calcium (Ca2+), magnesium (Mg2+), sulfate (SO42-), chloride (Cl-), potassium (K+) and pH. The distance calculation of HCA was used to quantify the differences between 12 different types of drinking water. The proposed E-tongue method is a practical tool to quantitatively evaluate the differences between samples in water quality items related to the ionic components. It can be helpful in quality control of drinking water.

Genetic Analyses of Heading and Maturing Dates and Their Relationship to Freezing Resistance in Barley (보리 출수기와 성숙기의 유전분석 및 내동성과의 관계)

  • 천종은;강석원
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.47 no.6
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    • pp.395-401
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    • 2002
  • The combination of early heading time, maturing time and short grain-filling period is very important to develop early varieties in winter barley. The 4 parental half diallel crosses (parents, $F_1$s, $F_2$s) were cultivated at the field. The heading date was from April 3 to 26, maturing date from May 15 to 27 and grain-filling period from 31 days to 42 days, showing that the varietal differences about the 3 traits were remarkable. According to half diallel cross analyses, Dongbori 1 for heading time (late heading) was dominant, but Oweolbori (early heading) was recessive, showing partial dominance with high additive component of genetic variance. Dongbori 1 for maturing time was dominant, but Oweolbori was recessive, showing partial dominance with high additive variance. Reno for grain-filling period (short grain-filling period) was dominant, but Oweolbori (long grain-filling period) was recessive with additive, and partial dominance. There were highly significant mean squares for both GCA and SCA effects on the heading and maturing times, and GCA/SCA ratios for all traits were high, showing the additive gene effects more important. Sacheon 6 and Oweolbori had greater GCA effects for early heading and maturing times, and Dongbori 1 and Reno had greater GCA effects for late times. GCA effects were highly significant in $F_1$ and $F_2$ generations, showing high GCA/SCA ratios (7.02). The heading and maturing times in field were positively correlated with antifreeze proteins concentrations, accumulation, resistance to photoinhibition and winter survival, respectively) but the grain-filling period did negatively correlated with the trails.

Effect of Sample Preparation on Predicting Chemical Composition and Fermentation Parameters in Italian ryegrass Silages by Near Infrared Spectroscopy (시료 전처리 방법이 근적외선분광법을 이용한 이탈리안 라이그라스 사일리지의 화학적 조성분 및 발효품질 평가에 미치는 영향)

  • Park, Hyung Soo;Lee, Sang Hoon;Choi, Ki Choon;Lim, Young Chul;Kim, Jong Gun;Seo, Sung;Jo, Kyu Chea
    • Journal of Animal Environmental Science
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    • v.18 no.3
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    • pp.257-266
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    • 2012
  • Near infrared reflectance spectroscopy (NIRS) has become increasingly used as a rapid, accurate method of evaluating some chemical constituents in cereal and dired animal forages. Analysis of forage quality by NIRS usually involves dry grinding samples. Costs might be reduced if samples could be analyzed without drying or grinding. The objective of this study was to investigate effect of sample preparations on prediction ability of chemical composition and fermentation parameter for Italian ryegrass silages by NIRS. A population of 147 Italian ryegrass silages representing a wide range in chemical parameters were used in this investigation. Samples were scanned at 1nm intervals over the wavelength range 680-2500 nm and the optical data recorded as log 1/Reflectance (log 1/R) and scanned in oven-dried grinding and fresh ungrinding condition. The spectral data were regressed against a range of chemical parameters using partial least squares (PLS) multivariate analysis in conjunction with four spectral math treatments to reduced the effect of extraneous noise. The optimum calibrations were selected on the basis of minimizing the standard error of cross validation (SECV) and maximizing the correlation coefficient of cross validation (${R^2}_{CV}$). The results of this study show that NIRS predicted the chemical parameters with high degree of accuracy in oven-dried grinding treatment except for moisture contents. Prediction accuracy of the moisture contents was better for fresh ungrinding treatment (SECV 1.37%, $R^2$ 0.96) than for oven-dried grinding treatments (SECV 4.31%, $R^2$ 0.68). Although the statistical indexes for accuracy of the prediction were the lower in fresh ungrinding treatment, fresh treatment may be acceptable when processing is costly or when some changes in component due to the processing are expected. Results of this experiment showed the possibility of NIRS method to predict the chemical composition and fermentation parameter of Italian ryegrass silages as routine analysis method in feeding value evaluation and for farmer advice.