• Horticultural Science & Technology
• /
• v.32 no.1
• /
• pp.105-114
• /
• 2014

We established a high throughput screening system of African yam tuber lines which contain high contents of total carotenoids, flavonoids, and phenolic compounds using ultraviolet-visible (UV-VIS) spectroscopy and Fourier transform infrared (FT-IR) spectroscopy in combination with multivariate analysis. The total carotenoids contents from 62 African yam tubers varied from 0.01 to $0.91{\mu}g{\cdot}g^{-1}$ dry weight (wt). The total flavonoids and phenolic compounds also varied from 12.9 to $229{\mu}g{\cdot}g^{-1}$ and from 0.29 to $5.2mg{\cdot}g^{-1}$dry wt. FT-IR spectra confirmed typical spectral differences between the frequency regions of 1,700-1,500, 1,500-1,300 and $1,100-950cm^{-1}$, respectively. These spectral regions were reflecting the quantitative and qualitative variations of amide I, II from amino acids and proteins ($1,700-1,500cm^{-1}$), phosphodiester groups from nucleic acid and phospholipid ($1,500-1,300cm^{-1}$) and carbohydrate compounds ($1,100-950cm^{-1}$). Principal component analysis (PCA) and subsequent partial least square-discriminant analysis (PLS-DA) were able to discriminate the 62 African yam tuber lines into three separate clusters corresponding to their taxonomic relationship. The quantitative prediction modeling of total carotenoids, flavonoids, and phenolic compounds from African yam tuber lines were established using partial least square regression algorithm from FT-IR spectra. The regression coefficients ($R^2$) between predicted values and estimated values of total carotenoids, flavonoids and phenolic compounds were 0.83, 0.86, and 0.72, respectively. These results showed that quantitative predictions of total carotenoids, flavonoids, and phenolic compounds were possible from FT-IR spectra of African yam tuber lines with higher accuracy. Therefore we suggested that quantitative prediction system established in this study could be applied as a rapid selection tool for high yielding African yam lines.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.7 no.3
• /
• pp.227-234
• /
• 2005

From published data of mature forests worldwide, Raich and Nadelhoffer suggested that total belowground carbon allocation (TBCA) could be estimated from the difference between annual rates of soil respiration and aboveground litterfall. Here we analyze new measurements of IRGA-based soil respiration and litterfall of natural mature oak forests dominated by Quercus mongolica in Korea. Rates of in situ soil respiration and aboveground litter production are highly and positively correlated. Our results disagree with the Raich and Nadelhoffer model far world forests. A regression analysis of the data from Q. mongolica forests produced the following relationship: annual soil respiration : 141 + 2.08 ${\times}$ annual litterfall. The least squares regression line has a more gentle slope (2.08) than the slope (2.92) described by Raich and Nedelhoffer for mature forests worldwide. The regression slope of our study indicates that, on average, soil respiration is about two times the aboveground litterfall-C, which further implies that TBCA is similar with annual aboveground litterfall-C at natural Q. mongolica forests in Korea. The non-zero Y-intercept (141) of the regression indicates that TBCA may be greater than litterfall-C where litterfall rate are relativery low. Over a gradient of litterfall-C ranging from 200-370 g C $m^{-2}yr^{-l}$, TBCA increased from 350-530 g C $m^{-2}yr^{-l}$.

• Asian-Australasian Journal of Animal Sciences
• /
• v.28 no.7
• /
• pp.936-942
• /
• 2015

The purpose of this study was to characterize genetic architecture of behavior patterns in Sapsaree dogs. The breed population (n=8,256) has been constructed since 1990 over 12 generations and managed at the Sapsaree Breeding Research Institute, Gyeongsan, Korea. Seven behavioral traits were investigated for 882 individuals. The traits were classified as a quantitative or a categorical group, and heritabilities ($h^2$) and variance components were estimated under the Animal model using ASREML 2.0 software program. In general, the $h^2$ estimates of the traits ranged between 0.00 and 0.16. Strong genetic ($r_G$) and phenotypic ($r_P$) correlations were observed between nerve stability, affability and adaptability, i.e. 0.9 to 0.94 and 0.46 to 0.68, respectively. To detect significant single nucleotide polymorphism (SNP) for the behavioral traits, a total of 134 and 60 samples were genotyped using the Illumina 22K CanineSNP20 and 170K CanineHD bead chips, respectively. Two datasets comprising 60 (Sap60) and 183 (Sap183) samples were analyzed, respectively, of which the latter was based on the SNPs that were embedded on both the 22K and 170K chips. To perform genome-wide association analysis, each SNP was considered with the residuals of each phenotype that were adjusted for sex and year of birth as fixed effects. A least squares based single marker regression analysis was followed by a stepwise regression procedure for the significant SNPs (p<0.01), to determine a best set of SNPs for each trait. A total of 41 SNPs were detected with the Sap183 samples for the behavior traits. The significant SNPs need to be verified using other samples, so as to be utilized to improve behavior traits via marker-assisted selection in the Sapsaree population.

• Journal of Biosystems Engineering
• /
• v.33 no.4
• /
• pp.260-268
• /
• 2008

Optical diffuse reflectance sensing has potential for rapid and reliable on-site estimation of soil properties. For good results, proper calibration to measured soil properties is required. One issue is whether it is necessary to develop calibrations using samples from the specific area or areas (e.g., field, soil series) in which the sensor will be applied, or whether a general "factory" calibration is sufficient. A further question is if specific calibration is required, how many sample points are needed. In this study, these issues were addressed using data from 42 paddy fields representing 14 distinct soil series accounting for 74% of the total Korean paddy field area. Partial least squares (PLS) regression was used to develop calibrations between soil properties and reflectance spectra. Model evaluation was based on coefficient of determination ($R^2$) root mean square error of prediction (RMSEP), and RPD, the ratio of standard deviation to RMSEP. When sample data from a soil series were included in the calibration stage (full information calibration), RPD values of prediction models were increased by 0.03 to 3.32, compared with results from calibration models not including data from the test soil series (calibration without site-specific information). Higher $R^2$ values were also obtained in most cases. Including some samples from the test soil series (hybrid calibration) generally increased RPD rapidly up to a certain number of sample points. A large portion of the potential improvement could be obtained by adding about 8 to 22 points, depending on the soil properties to be estimated, where the numbers were 10 to 18 for pH, 18-22 for EC, and 8 to 22 for total C. These results provide guidance on sampling and calibration requirements for NIR soil property estimation.

• The Journal of Information Systems
• /
• v.25 no.3
• /
• pp.31-60
• /
• 2016

Purpose In 2016, the market size of mobile(m-) shopping goes beyeond more than half of a total of online shopping. People use smartphones as the main device for m-commerce. Under the circmustances, this study attempts to address why people prefer to use smartphone-based m-commerce. In other words, it is necessary to understand the main value that smartphone-based m-commerce creates. Drawing on the studies of consumption value, this study focuses on utilitarian value in predicting customers' continuance intention in the context of smartphone-based m-commerce, recognizing that utilitarian value is a key extrinsic motivation in the goal-oriented, performance-oriented shopping contexts. Furthermore, this study identifies factors affecting customers' utilitarian value from the perspective of benefits and costs, following the notion that it represents the result of evaluating a trade-off of benefits and costs caused by smartphone-based m commerce. More specifically, in this study, ubiquitous service, location-based service (LBS), transaction speed, and price utility belong to the benefit dimension, whereas technology anxiety and cognitive effort belong to the cost dimension. Design/methodology/approach To test the proposed hypotheses, the study conducted partial least squares (PLS) analysis with a total of 294 data collected on users with experience in smartphone-based m-commerce. Findings The results show that first, utilitarian value is increased by the benefits, such as ubiquitous service, transaction speed, and price utility. However, LBS has no direct effect on utilitarian value. Second, the noteworthy finding is that ubiquitous service and LBS greatly increase transaction speed. Third, technology anxiety and cognitive effort considered as the cost dimension are negatively associated with utilitarian value but their impacts on it are non-significant. Finally, the results support the argument that utilitarian value is a determinant of continuance intention. Overall, the findings imply that utilitarian value greatly depends on the peception on benefits rather than the aspect of cost in smartphone-based m-commerce. Overall, the findings offer new insight into the studies of m-commerce by considering and verifying the impacts of its benefits and costs simultaneously.

• Asian-Australasian Journal of Animal Sciences
• /
• v.15 no.1
• /
• pp.11-15
• /
• 2002

The present investigation was undertaken to study the effects of non-genetic factors and association among replacement and lifetime production traits. The data on 542 Holstein Friesian cows maintained during 1975-98 at State Cattle Breeding Project, Sector III, Hisar, were utilized. The average sex-ratio, abnormal births, mortality, culling and replacement rates on total calf born and total female calf born basis were 51.62, 8.50, 17.52, 31.05, 22.78 and 51.41 per cent, respectively. The study revealed that a minimum of 4 to 5 progenies are required per cow over its lifetime to replace itself. It indicated that each cow should produce a minimum of 2 female calves during its life so as to replace herself before being lost. The least-squares means for productive herd life, longevity and lifetime production were $1439.32{\pm}87.64$ and $2419.18{\pm}8.25$ days and $11317.95{\pm}913.15kg$, respectively. The heritability estimates for all replacement traits were very low indicating that sire selection may bring no desirable change in these traits. Heritability estimates were $0.178{\pm}0.157$, $0.288{\pm}0.184$ and $0.096{\pm}0.195$ for corresponding lifetime production traits. Breeding values and ranking of sires were generated for replacement and lifetime production traits to estimate the rank correlations between these traits. Moderate desirable rank correlations were obtained between replacement rate and lifetime production traits indicating that sires proven on the basis of milk production are also expected to have better replacement rate.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.54 no.1
• /
• pp.29-35
• /
• 2009

The aim of the present study was to update the calibration that is used for the measurement of the total nitrogen content in the rice plant samples by using the visible and near infrared spectrum. Before the equation merge, correlation coefficient of calibration equation for nitrogen content on each rice parts was 0.945 (Leaf), 0.928 (Stem), and 0.864 (Whole plant), respectively. In the calibration models created by each part in the rice plant under the various regression method, the calibration model for the leaf was recorded with relatively high accuracy. Among of those, the calibration equation developed by Partial least squares (PLS) method was more accurate than the Multiple linear regression (MLR) method. The calibration equation was sensitive based on variety and location variations. However, we have merged and enlarged various of the samples that made not only to measure the nitrogen content more accurately, but also later sampling populations became more diversified. After merging, $R^2$ value becomes more accurate and significantly to 0.950 (L.), 0.974 (S.), 0.940 (W.). Also, after removal of outlier, R2 values increased into 0.998, 0.995, and 0.997. In view of the results so far achieved, Standard error of prediction (SEP) and SEP (C) were reduced in the stem and whole plant. Biases were reduced in the leaf, stem as well as whole plant. Slopes were high in the stem. Standard deviation reduced in the stem but $R^2$ was high in the stem and whole plant. Result was indicated that calibration equation make update, and updating robust calibration equation from merge function and multi-variate calibration.

• Journal of Ginseng Research
• /
• v.38 no.1
• /
• pp.52-58
• /
• 2014

To determine whether Fourier transform (FT)-IR spectral analysis combined with multivariate analysis of whole-cell extracts from ginseng leaves can be applied as a high-throughput discrimination system of cultivation ages and cultivars, a total of total 480 leaf samples belonging to 12 categories corresponding to four different cultivars (Yunpung, Kumpung, Chunpung, and an open-pollinated variety) and three different cultivation ages (1 yr, 2 yr, and 3 yr) were subjected to FT-IR. The spectral data were analyzed by principal component analysis and partial least squares-discriminant analysis. A dendrogram based on hierarchical clustering analysis of the FT-IR spectral data on ginseng leaves showed that leaf samples were initially segregated into three groups in a cultivation age-dependent manner. Then, within the same cultivation age group, leaf samples were clustered into four subgroups in a cultivar-dependent manner. The overall prediction accuracy for discrimination of cultivars and cultivation ages was 94.8% in a cross-validation test. These results clearly show that the FT-IR spectra combined with multivariate analysis from ginseng leaves can be applied as an alternative tool for discriminating of ginseng cultivars and cultivation ages. Therefore, we suggest that this result could be used as a rapid and reliable F1 hybrid seed-screening tool for accelerating the conventional breeding of ginseng.

• Animal Bioscience
• /
• v.34 no.12
• /
• pp.1930-1939
• /
• 2021

Objective: The aim of the study was to conduct metabolic profiling of dairy cattle serum and urine using proton nuclear magnetic resonance (¹H-NMR) spectroscopy and to compare the results obtained with those of other dairy cattle herds worldwide so as to provide a basic dataset to facilitate research on metabolites in serum and urine. Methods: Six dairy cattle were used in this study; all animals were fed the same diet, which was composed of total mixed ration; the fed amounts were based on voluntary intake. Blood from the jugular neck vein of each steer was collected at the same time using a separate serum tube. Urine samples were collected by hand sweeping the perineum. The metabolites were determined by ¹H-NMR spectroscopy, and the obtained data were statistically analyzed by performing principal component analysis, partial least squares-discriminant analysis, variable importance in projection scores, and metabolic pathway data using Metaboanalyst 4.0. Results: The total number of metabolites in the serum and urine was measured to be 115 and 193, respectively, of which 47 and 81, respectively were quantified. Lactate (classified as an organic acid) and urea (classified as an aliphatic acylic compound) exhibited the highest concentrations in serum and urine, respectively. Some metabolites that have been associated with diseases such as ketosis, bovine respiratory disease, and metritis, and metabolites associated with heat stress were also found in the serum and urine samples. Conclusion: The metabolites measured in the serum and urine could potentially be used to detect diseases and heat stress in dairy cattle. The results could also be useful for metabolomic research on the serum and urine of ruminants in Korea.

• Journal of Veterinary Science
• /
• v.21 no.1
• /
• pp.16.1-16.10
• /
• 2020

Cancer is a major cause of death in dogs worldwide, and the incidence of cancer in dogs is increasing. The attenuated total reflection Fourier transform infrared spectroscopic (ATR-FTIR) technique is a powerful tool for the diagnosis of several diseases. This method enables samples to be examined directly without pre-preparation. In this study, we evaluated the diagnostic value of ATR-FTIR for the detection of cancer in dogs. Cancer-bearing dogs (n = 30) diagnosed by pathologists and clinically healthy dogs (n = 40) were enrolled in this study. Peripheral blood was collected for clinicopathological diagnosis. ATR-FTIR spectra were acquired, and principal component analysis was performed on the full wave number spectra (4,000-650 cm^-1). The leave-one-out cross validation technique and partial least squares regression analysis were used to predict normal and cancer spectra. Red blood cell counts, hemoglobin levels and white blood cell counts were significantly lower in cancer-bearing dogs than in clinically healthy dogs (p < 0.01, p < 0.01 and p = 0.03, respectively). ATR-FTIR spectra showed significant differences between the clinically healthy and cancer-bearing groups. This finding demonstrates that ATR-FTIR can be applied as a screening technique to distinguish between cancer-bearing dogs and healthy dogs.