The objective of this study was to develop models for the predict of the milk properties (fat, protein, SNF, lactose, MUN) of unhomogenized milk using the visible and near-infrared (NIR) spectroscopic technique. A total of 180 milk samples were collected from dairy farms. To determine optimal measurement temperature, the temperatures of the milk samples were kept at three levels ($5^{\circ}C$, $20^{\circ}C$, and $40^{\circ}C$). A spectrophotometer was used to measure the reflectance spectra of the milk samples. Multilinear-regression (MLR) models with stepwise method were developed for the selection of the optimal wavelength. The preprocessing methods were used to minimize the spectroscopic noise, and the partial-least-square (PLS) models were developed to prediction of the milk properties of the unhomogenized milk. The PLS results showed that there was a good correlation between the predicted and measured milk properties of the samples at $40^{\circ}C$ and at 400~2,500 nm. The optimal-wavelength range of fat and protein were 1,600~1,800 nm, and normalization improved the prediction performance. The SNF and lactose were optimized at 1,600~1,900 nm, and the MUN at 600~800 nm. The best preprocessing method for SNF, lactose, and MUN turned out to be smoothing, MSC, and second derivative. The Correlation coefficients between the predicted and measured fat, protein, SNF, lactose, and MUN were 0.98, 0.90, 0.82, 0.75, and 0.61, respectively. The study results indicate that the models can be used to assess milk quality.
This study was undertaken to select a suitable Korean tissue paper for Baermann funnel method. Ten kinds of five manufacturers were evaluated as to nematode extraction efficiency in Baermann funnel. 'Crown Hankie'(Korea Special Paper Co., Ltd.) had suitable properties in nematode permeability and strength regardless of three soil types, loamy sand, sandy loam and clay loam. The number of nematodes extracted using 'Crown Hankie' 4 ply was 198, while that of 'Cottonwool Nematode Filter' was 227. Un-perfumed tissue papers showed higher nematode extraction efficiencies than perfumed tissue papers by 53 and 23% in 'Kleenex New Softness' and 'Monaliza Finely Soft Tissue', respectively. Among the nematode extraction efficiencies by temperatures, $15^{\circ},\;25^{\circ}\;and\;35^{\circ}C$, it was highest at $35^{\circ}C$. In experiment of evaluating nematode extraction using Baermann funnel at 12 hours interval to 92 hours, 35.3 and 40.3% of nematodes were extracted after 12 and 24 hours, respectively.
Journal of Korean Home Economics Education Association
/
v.29
no.4
/
pp.117-131
/
2017
This study was performed to analyze education contents related to milk in current home economics textbooks of middle school, and to investigate intake status, consumption behaviors, perception and nutritional knowledge of milk and dairy products among 364 middle school students in Gongju for improvement of milk education in home economics subjects and milk intake of adolescents. As a result, education contents of milk and dairy products in home economics textbooks currently applied in middle school were major nutrients, consumption method for balanced diet, and selection and storage of milk and dairy products, thus it tended not to match current food trend. Only 30.5% of subjects met 2 cups of milk a day, the recommended level. The main reason for drinking milk was to 'be taller' and 'to quench thirst' and there was a difference by gender(p<0.01). The rate of not participating in school milk program was 23.1% of total and its satisfaction was moderate. The most popular dairy products by subjects were ice cream, followed by yogurt and cheese, and the choice of milk was focused on 'taste' or 'expiration date'. The rate of knowing certification mark of K-MILK was low at 28.8%, and most subjects knew as 'domestic milk use'. In home economics class, experience-based learning such as cow ranch experience was the most preferred instruction method for milk followed by laboratory practice and lecture, and there was a difference by gender(p<0.001). Perception degree of milk and dairy products was moderate and male subjects were more positively perceived than female subjects(p<0.01). Nutritional knowledge level of milk and dairy products was moderate and female subjects were higher than male subjects(p<0.01). Therefore, education contents of milk and dairy products of home economics textbooks of middle school should be centered on real life in accordance with food trend, and applied student participation-based instruction methods such as experience-based learning. In addition, it is necessary to enhance taste and merchandise of milk and to provide them with preferred milk and dairy products in school milk program for improvement of milk intake of adolescents.
For developing standard method for diease, pest and weed control in environmental friendly 'Ssam' vegetable cultivation, this study was carried out to investigating agriculture material use in organic agriculture and no pesticide cultivation for lettuce, kale, leafy perilla and korean cabbage. The 28.6% of investigated farmer carried out seed sterilization by seed selection with salt solution and soaking in chitosan that not validated. For raising seedling periods, the 55.6% of farmer did not use environmental-friendly agriculture material for, diease control and the 50% of farmer used one time for. pest control. Therefore, the control of disease and pest could be achieved with one or two times use of environmental-friendly agriculture material. Seed sterilization was carried out by soil solar sterilization, one time per year in 71.4% of farmer. Weed was controled by black PE film for weed germination of furrow in many farmer, by man-power weeding for weed of ridge in 85% of farmer and by machine weeding and mulching in some farmer. During cultivation period, the major pest were Aphis gossypii in lettuce, Plutella xylostella in kale, Plutella xylostella and Phyllotreta striolata (Fabricius) in korean cabbage and Pyrausta panopealis (Walke) in feat perilla. The many farmers used environ-mental-friendly agriculture material for control of pest over 10 times for spring season, and more used sold materials in market than home-made materials. In result, it needs to develop standardized method and validate cultivation methods for control of disease and pest, and seed sterilization treatment environmental-friendly 'Ssam' vegetable.
Lee, Jundae;Park, Seok Jin;Do, Jae Wahng;Han, Jung-Heon;Choi, Doil;Yoon, Jae Bok
Horticultural Science & Technology
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v.31
no.4
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pp.473-482
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2013
Molecular markers, as an efficient selection tool, have been and is being used for practical breeding program in chili pepper (Capsicum annuum L.). Recently, a lot of researches on inheritance and genetic analysis for quantitative traits including capsaicinoids, carotenoids, and sugar content in pepper are being performed worldwide. It has been also reported that QTL mapping is a necessary tool to develop molecular markers associated with the quantitative traits. In this study, we suggested a new method to construct a pepper genetic map using SNP (HRM) markers generated from NGS resequencing of female and male parents. Plant materials were C. annuum 'NB1' (female parent), C. chinense 'Jolokia' (male parent), and their $F_2$ population consisting of 94 progenies. Sequences of 4.6 Gbp and 6.2 Gbp were obtained from NGS resequencing of 'NB1' and 'Jolokia', respectively. Totally, 4.29 million SNPs between 'NB1' and 'Jolokia' were detected and the 1.76 million SNPs were clearly identified. Among them, total 145 SNP (HRM) primer pairs covering pepper genetic map were selected, and the 116 SNP (HRM) markers of them were located on this map. Total distance of the map, which consisted of 12 linkage groups and matched with basic chromosome numbers of pepper, was 1,167.9 cM. According to the mapping result, we concluded that our mapping method was suitable to construct a pepper genetic map fast and accurately. In addition, the genetic map could be directly used for QTL analysis of traits different between both parents.
This paper proposed a method to separate a liver into left and right liver lobes for simple and exact volumetry of the river graft at abdominal MDCT(Multi-Detector Computed Tomography) image before the living donor liver transplantation. A medical team can evaluate an accurate river graft with minimized interaction between the team and a system using this algorithm for ensuring donor's and recipient's safe. On the image of segmented liver, 2 points(PMHV: a point in Middle Hepatic Vein and PPV: a point at the beginning of right branch of Portal Vein) are selected to separate a liver into left and right liver lobes. Middle hepatic vein is automatically segmented using PMHV, and the cutting line is decided on the basis of segmented Middle Hepatic Vein. A liver is separated on connecting the cutting line and PPV. The volume and ratio of the river graft are estimated. The volume estimated using 2 points are compared with a manual volume that diagnostic radiologist processed and estimated and the weight measured during surgery to support proof of exact volume. The mean ${\pm}$ standard deviation of the differences between the actual weights and the estimated volumes was $162.38cm^3{\pm}124.39$ in the case of manual segmentation and $107.69cm^3{\pm}97.24$ in the case of 2 points method. The correlation coefficient between the actual weight and the manually estimated volume is 0.79, and the correlation coefficient between the actual weight and the volume estimated using 2 points is 0.87. After selection the 2 points, the time involved in separation a liver into left and right river lobe and volumetry of them is measured for confirmation that the algorithm can be used on real time during surgery. The mean ${\pm}$ standard deviation of the process time is $57.28sec{\pm}32.81$ per 1 data set ($149.17pages{\pm}55.92$).
In order to determine an authenticity of food ingredient, we used DNA barcode method by universal primers. For identification of animal food ingredients, LCO1490/HCO2198 and VF2/FISH R2 designed for amplifying cytochrome c oxidase subunit1 (CO1) region and L14724/H15915 for cytochrome b (cyt b) region on mitochondrial DNA were used. Livestock (cow, pig, goat, sheep, a horse and deer) was amplified by LCO1490/HCO 2198, VF2/FISH R2 and L14724/H15915 primers. Poultry (chicken, duck, turkey and ostrich) was amplified by LCO1490/HCO 2198 and VF2/FISH R2 primers. But, Fishes (walleye pollack, herring, codfish, blue codfish, trout, tuna and rockfish) were only amplified by VF2/FISH R2 primers. For plant food ingredients, 3 types of primers (trnH/psbA, rpoB 1F/4R and rbcL 1F/724R) have been used an intergenic spacer, a RNA polymerase beta subunit and a ribulose bisphosphate carboxylase region on plastid, respectively. Garlic, onion, radish, green tea and spinach were amplified by trnH/psbA, rpoB 1F/4R and rbcL 1F/724R. The PCR product sizes were same by rpoB 1F/4R and rbcL 1F/724R but, the PCR product size using trnH/psbA primer was different with others for plants each. We established PCR condition and universal primer selection for 17 item's raw materials for foods and determine base sequences aim to PCR products in this study. This study can apply to determine an authenticity of foods through making an comparison between databases and base sequences in gene bank. Therefore, DNA barcode method using universal primers can be a useful for species identification techniques not only raw materials but also processed foods that are difficult to analyze by chemical analysis.
Sheath rot and dry rot disease caused by Pseudomonas marginalis and Fusarium oxysporum were serious problems in garlic farmland. In this study, total of 160 indigenous antagonistic bacteria were isolated from 16 farmlands in Yeongcheon, Korea. Among these, 15 strains were able to inhibited P. marginalis and F. oxysporum. The 16s rDNA genes of the selected 15 strains were amplified and sequenced. The strains has strong antagonistic ability against garlic pathogens was achieved Bacillus subtilis YC82, B. vallismortis YC84, B. amyloliquefaciens YC240. The selected 3 strains tested for investigation of antifungal mechanisms further analyses; 3 strains of these validated for production of siderophore, ${\beta}$-glucanase and chitinase using CAS (chrome azurol S) blue agar, CMC-congo red agar and DNS method. The 3 strains were able to utilized insoluble phosphate as dertermined by vanado-molybdate method. The 3 strains verified for production of auxin and gibberellic acid using Salkowski test and holdbrook test. Also, 3 strains showed stimulation germination, stem growth promoting activity on the in vivo test. The 3 strains were able to effectively suppress P. marginalis and F. oxysporum causing sheath rot and dry rot diseases on the in vivo pot test.
Journal of the Korean Society of Food Science and Nutrition
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v.34
no.7
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pp.1000-1007
/
2005
The aim of the present study was to examine the relationship of maternal factors such as knowledge, attitude and practice of weaning with infant feeding. The subjects were 103 mothers visiting a public health center in Gumi, Kyungbook who filled out self-administered Questionnaires. First of all, about $90\%$ of the participants recognized the importance of complementary foods and proper weaning practices. The response for the recognition of the importance of infant weaning process showed a significant difference by education levels. Concerning an appropriate time for the introduction of weaning foods, $53\%$ of mothers had commenced weaning at age $4\~6$ months, while $38\%$ had done so at age $6\~8$ months. Approximately $76\%$ of mothers fed their babies without the knowledge of age-related weaning method and type of weaning foods. There were no statistical differences in maternal weaning knowledges between levels of education and house income. Mothers with higher levels of education and family income tended to show high perception scores regarding possibility of food allergies caused by baby foods. A demand for reliable sources and education related to nutritious weaning foods and weaning practices were strong in the group with higher education. Knowledge of weaning method and baby foods were obtained by 59 of the 103 mothers from mass media, 35 from friends caring babies, and 9 obtained advice from health professionals or family. Advice from the heath professionals was not the main influence on their decision to introduce weaning foods. Although commercial baby foods are the most commonly used as first weaning foods, those with higher education groups considered commercial baby food are not nutritionally better than home-maid foods. The current findings suggest to us that to improve weaning process, mothers should be educated on the selection and preparation of nutritious, balanced weaning foods and on good weaning practices. It is advised that supportive health professionals from community public health centers should lead the education of infant feeding practices based on maternal characteristics and on basic food and nutritional knowledge.
Ensemble learning is a method for improving the performance of classification and prediction algorithms. It is a method for finding a highly accurateclassifier on the training set by constructing and combining an ensemble of weak classifiers, each of which needs only to be moderately accurate on the training set. Ensemble learning has received considerable attention from machine learning and artificial intelligence fields because of its remarkable performance improvement and flexible integration with the traditional learning algorithms such as decision tree (DT), neural networks (NN), and SVM, etc. In those researches, all of DT ensemble studies have demonstrated impressive improvements in the generalization behavior of DT, while NN and SVM ensemble studies have not shown remarkable performance as shown in DT ensembles. Recently, several works have reported that the performance of ensemble can be degraded where multiple classifiers of an ensemble are highly correlated with, and thereby result in multicollinearity problem, which leads to performance degradation of the ensemble. They have also proposed the differentiated learning strategies to cope with performance degradation problem. Hansen and Salamon (1990) insisted that it is necessary and sufficient for the performance enhancement of an ensemble that the ensemble should contain diverse classifiers. Breiman (1996) explored that ensemble learning can increase the performance of unstable learning algorithms, but does not show remarkable performance improvement on stable learning algorithms. Unstable learning algorithms such as decision tree learners are sensitive to the change of the training data, and thus small changes in the training data can yield large changes in the generated classifiers. Therefore, ensemble with unstable learning algorithms can guarantee some diversity among the classifiers. To the contrary, stable learning algorithms such as NN and SVM generate similar classifiers in spite of small changes of the training data, and thus the correlation among the resulting classifiers is very high. This high correlation results in multicollinearity problem, which leads to performance degradation of the ensemble. Kim,s work (2009) showedthe performance comparison in bankruptcy prediction on Korea firms using tradition prediction algorithms such as NN, DT, and SVM. It reports that stable learning algorithms such as NN and SVM have higher predictability than the unstable DT. Meanwhile, with respect to their ensemble learning, DT ensemble shows the more improved performance than NN and SVM ensemble. Further analysis with variance inflation factor (VIF) analysis empirically proves that performance degradation of ensemble is due to multicollinearity problem. It also proposes that optimization of ensemble is needed to cope with such a problem. This paper proposes a hybrid system for coverage optimization of NN ensemble (CO-NN) in order to improve the performance of NN ensemble. Coverage optimization is a technique of choosing a sub-ensemble from an original ensemble to guarantee the diversity of classifiers in coverage optimization process. CO-NN uses GA which has been widely used for various optimization problems to deal with the coverage optimization problem. The GA chromosomes for the coverage optimization are encoded into binary strings, each bit of which indicates individual classifier. The fitness function is defined as maximization of error reduction and a constraint of variance inflation factor (VIF), which is one of the generally used methods to measure multicollinearity, is added to insure the diversity of classifiers by removing high correlation among the classifiers. We use Microsoft Excel and the GAs software package called Evolver. Experiments on company failure prediction have shown that CO-NN is effectively applied in the stable performance enhancement of NNensembles through the choice of classifiers by considering the correlations of the ensemble. The classifiers which have the potential multicollinearity problem are removed by the coverage optimization process of CO-NN and thereby CO-NN has shown higher performance than a single NN classifier and NN ensemble at 1% significance level, and DT ensemble at 5% significance level. However, there remain further research issues. First, decision optimization process to find optimal combination function should be considered in further research. Secondly, various learning strategies to deal with data noise should be introduced in more advanced further researches in the future.
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