• Journal of the Korean Operations Research and Management Science Society
• /
• v.22 no.1
• /
• pp.51-58
• /
• 1997

In this paper, we propose a stochastic LP model for determining an optimal input quantity in a single-product multi-stage production system with random yields. Due to the random yields in our model, each stage of the production system can result in defective items, which can be re-processed or scrapped at certain costs. We assume that the random yield at each stage follows an independent discrete empirical distribution. Compared to dynamic programming models that prevail in the literature, our model can easily handle problems of larger sizes.

• Korean Journal of Agricultural Science
• /
• v.43 no.4
• /
• pp.547-559
• /
• 2016

The objectives of this study were to investigate the effects of excessive soil-water on crop growth and to predict decrease of yields caused by excessive soil-water. The following five crops were selected for investigation: foxtail millet, proso millet, sorghum, adzuki bean, and sesame. These were planted in pots and a soil-water table was set to 10cm for 10 days. Crop susceptibility (CS) factors and stress-day indexes (SDI) were calculated for each crop to estimate effects of excessive soil-water. SDI models were calculated using CS and SDI data for each crop and predicted the yields of crops cultivated in paddy fields. All crops were cultivated in paddy fields with different soil water contents to evaluate the yield-SDI models. Results showed that yields decreased most when crops were affected by excessive soil-water at the early development stage. Decrease of yields was the greatest when the excessive soil-water treatment was applied at early growth stage. In the field experiment, crops from soils with the greatest soil-water content had the smallest yield, while ones from soils with the smallest soil water contents showed the greatest yields. Observed yields from the field and predicted yields from SDI models showed the least correlation for proso millet, foxtail millet, and adzuki bean and the greatest correlation for sesame. In conclusion, proso millet, foxtail millet, and adzuki bean were more susceptible to soil water than other crops, while sorghum and sesame were more suitable to cultivation in paddy fields.

• Asian-Australasian Journal of Animal Sciences
• /
• v.33 no.9
• /
• pp.1387-1399
• /
• 2020

Objective: The objective of this study was to estimate the genetic parameters and trends for milk, fat, and protein yields in the first three lactations of Thai dairy cattle using a 3-trait,-3-lactation random regression test-day model. Methods: Data included 168,996, 63,388, and 27,145 test-day records from the first, second, and third lactations, respectively. Records were from 19,068 cows calving from 1993 to 2013 in 124 herds. (Co) variance components were estimated by Bayesian methods. Gibbs sampling was used to obtain posterior distributions. The model included herd-year-month of testing, breed group-season of calving-month in tested milk group, linear and quadratic age at calving as fixed effects, and random regression coefficients for additive genetic and permanent environmental effects, which were defined as modified constant, linear, quadratic, cubic and quartic Legendre coefficients. Results: Average daily heritabilities ranged from 0.36 to 0.48 for milk, 0.33 to 0.44 for fat and 0.37 to 0.48 for protein yields; they were higher in the third lactation for all traits. Heritabilities of test-day milk and protein yields for selected days in milk were higher in the middle than at the beginning or end of lactation, whereas those for test-day fat yields were high at the beginning and end of lactation. Genetics correlations (305-d yield) among production yields within lactations (0.44 to 0.69) were higher than those across lactations (0.36 to 0.68). The largest genetic correlation was observed between the first and second lactation. The genetic trends of 305-d milk, fat and protein yields were 230 to 250, 25 to 29, and 30 to 35 kg per year, respectively. Conclusion: A random regression model seems to be a flexible and reliable procedure for the genetic evaluation of production yields. It can be used to perform breeding value estimation for national genetic evaluation in the Thai dairy cattle population.

• Asian-Australasian Journal of Animal Sciences
• /
• v.7 no.2
• /
• pp.261-264
• /
• 1994

The lactation milk yields of 209 buffaloes and cattle were measured on farms in Taplejung and Dhankuta Districts in East Nepal. This includes local and crossbred buffaloes and cows. The average milk yield (${\pm}\;SD$) of 97 local buffaloes was $833\;{\pm}\;94.6\;kg$ whereas that for 83 local cows was only $455\;{\pm}\;61.5\;kg$. The milk yield of buffaloes decreased with number of calvings, but that for the cows increased. The milk yields of 18 Murrah crossbreds were on average 215 kg higher than the yields of local buffaloes, and the yields of 11 Jersey crossbred cows averaged 247 kg more than the local cows. Lactation length (${\pm}\;SD$) which averaged $326\;{\pm}\;100$ days for the buffaloes and $292\;{\pm}\;98$ days for the cows, was not affected by crossbreeding. The milk yields of the crossbreds were more variable than the local buffaloes and cows. In addition to milk yield the overall productivity of a milking animal depends on calf mortality, age at first calving, calving interval, longevity, food intake, the work performance of male cattle and the meat production of male buffaloes. Among these parameters, the work performance of Jersey crossbred and local male cattle was studied later. However, other factors could not be measured.

• Asian-Australasian Journal of Animal Sciences
• /
• v.15 no.3
• /
• pp.315-320
• /
• 2002

Test-day records (n=13677) sampled from 896 ewes in 5-9 (${\mu}$=7.5) monthly test-days were used to estimate genetic and phenotypic parameters of test-day yields, lactation milk yield (TMY), length of the milking period (DAYS) and three measures of persistency of milk yield in Boutsico dairy sheep. Τhe measures of persistency were the slope of the regression line (${\beta}$), the coefficient of variation (CV) of the test-day milk yields and the maximum to average daily milk yield ratio (MA). The estimates of variance components were obtained under a linear mixed model by restricted maximum likelihood. The heritability of test-day yields ranged from 0.15 to 0.24. DAYS were found to be heritable ($h^2$=0.11). Heritability estimates of ${\beta}$, CV and MA were 0.15, 0.13, 0.10, respectively. Selection for maximum lactation yields is expected to result in prolonged milking periods, high rates of decline of yields after peak production, variable test-day yields and higher litter sizes. Selection for flatter lactation curves would reduce lactation yields, increase slightly the length of the milking period and decrease yield variation as well as litter size. The most accurate prediction of TMY was obtained with a linear regression model with the first five test-day records.

• Journal of Microbiology and Biotechnology
• /
• v.13 no.4
• /
• pp.571-577
• /
• 2003

The intracellular metabolic fluxes can be calculated by metabolic flux analysis, which uses a stoichiometric model for the intracellulal reactions along with mass balances around the intracellular metabolites. In this study, metabolic flux analyses were carried out to estimate flux distributions for the maximum in silico yields of various metabolites in Escherichia coli. The maximum in silico yields of acetic acid and lactic acid were identical to their theoretical yields. On the other hand, the in silico yields of succinic acid and ethanol were only 83% and 6.5% of their theoretical yields, respectively. The lower in silico yield of succinic acid was found to be due to the insufficient reducing power. but this lower yield could be increased to its theoretical yield by supplying more reducing power. The maximum theoretical yield of ethanol could be achieved, when a reaction catalyzed by pyruvate decarboxylase was added in the metabolic network. Futhermore, optimal metabolic pathways for the production of various metabolites could be proposed, based on the results of metabolic flux analyses. In the case of succinic acid production, it was found that the pyruvate carboxylation pathway should be used for its optimal production in E. coli rather than the phosphoenolpyruvate carboxylation pathway.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.61 no.2
• /
• pp.104-112
• /
• 2016

A double-cropping system with soybean (Glycine max) following the cultivation of potato, garlic, and onion is widely adopted in the southern region of Korea. For this system, marginal dates for planting must be determined for profitable soybean yields, because the decision to plant soybean as a second crop is occasionally delayed by harvest of the first crop and weather conditions. In order to investigate the effect of planting date on soybean yield, three cultivars (early and late maturity) were planted on seven different dates from May 1 to July 30 in both paddy and upland fields across 2012 and 2013. Soybean yields were significantly different among the planting dates and the cultivars; however, the interaction between cultivar and planting date was not significant. Based on linear regression, the maximum yield of soybean was reached with a June 10 planting date, with a sharp decline in yield for crops planted after this date. The results of this study were consistent with those of a previous one that recommends early and mid-June as the optimum planting period. Regardless of soybean ecotype, a reduction in yield of greater than 20% occurred when soybean was planted after mid-July. Frost during soybean growth can reduce yields, and the late maturity cultivars planted on July 30 were damaged by frost before completing maturation and harvest; however, early maturity cultivars were safely harvested. For sufficient time to develop and reach profitable yields, the planting of soybean before mid-July is recommended.

• Journal of Animal Science and Technology
• /
• v.58 no.8
• /
• pp.30.1-30.12
• /
• 2016

Background: The effect of choline chloride supplementation through forced drinking combined with concentrate diets containing Ca-fish oil on milk production and milk composition of Etawah Grade goats was evaluated. Choline chloride is an essential component in ruminant diets as it is required for fat metabolism. Method: The experiment was conducted in a completely randomized block design with three types of treatments and eight replications. The trial had two successive experimental periods; the first, during the eight weeks of late pregnancy, and the second, during the first 12 weeks of lactation. Twenty-four Etawah Grade does in the second gestation period were divided into three treatment groups. Commercial choline chloride 60 % in corncobs-based powder was used as a source of choline chloride. The treatments were no supplementation (control) and supplemented with either 4 g or 8 g/2days of choline chloride. Choline chloride was given to the animals through a forced drinking technique, after dissolving it in 60 ml drinking water. The initial body weight of does was $38.81{\pm}3.66kg$. The does were penned individually, and were given fresh chopped King Grass ad libitum and 700 g/day of concentrate diets containing Ca-fish oil, starting eight weeks prior to expecting kidding and continuing for 12 weeks of parturition. Results: All nutrient intakes were not significantly different (p > 0.05) among the treatments during the late pregnancy and the lactation periods. Supplementation did not affect (p > 0.05) the average daily gains and feed conversion ratio during pregnancy but gave effects (p < 0.05) on the average daily gains, feed conversion ratio and income over feed cost during lactation. The highest average daily milk yields and 4 % fat corrected milk yields were found in goats supplemented with 4 g/2days of choline chloride and increased by 17.00 % and 24.67 %, respectively, compared to the control. Moreover, milk composition percentage and milk constituent yields improved significantly (p < 0.05) in those supplemented with 4 g/2days of choline chloride. Conclusion: The supplementation of 4 g/2days of choline chloride through forced drinking increased milk yields, the 4 % fat corrected milk yields, milk composition, milk constituent yields, and improved feed conversion ratio and income over feed cost of Etawah Grade goats.

• Journal of The Korean Society of Grassland and Forage Science
• /
• v.17 no.2
• /
• pp.123-134
• /
• 1997

The effects of cutting 6equency and nitrogen fertilization on feed values of reed canarygrass were investigated in uncultivated rice paddy and the attemp was made to estimate the economical and efficient levels of nitrogen fertilization for the increased production of nutrients in reed canarygrass. The results are summarized as follows; 1. Crude protein(CP) content was higher at 1st cut of all treatments(12.5% in 3 cutting 6equency; 19, 7% in 4 cutting frequency; 22.5% in 5 cutting kquency). However, Total Digestible Nutrients(TDN) and Relative Feed Value(RFV) in 3 and 4 cutting 6equencies were higher at 3rd cut(63.5%, 126.8) and 4th cut(65.7%, 146.4) respectively in which the contents of Neutral Detergent Fiber(NDF) and Acid Detergent Fiber(ADF) were lowest. In 5 cutting frequency, 1st cut showed the highest TDN and RFV as 70.5% and 232.4 respectively. 2. The level of nitrogen fertilization affected CP content of reed canarygrass. Nitrogen fertilization of 120kgl halcut showed high CP contents of 11.4, 14.7 and 16.5% in 3, 4 and 5 cutting eequency respectively. In 3 and 4 cutting frequency, TDN and RFV were highest with nitrogen fertilization of 90kg/ha/cut where NDF and ADF were lowest, however those in 5 cutting frequency were highest with nitrogen fertilization of 30kg/ha/cut. 3. The yields of CP varied according to the number of cutting frequency and those were 0.45~0.65 in 3 cutting hquency, 0.35~0.50 in 4 cutting frequency, and 0.19~0.67tond/ha in 5 cutting 6equency respectively and TDN was 2.09~3.60, 1.64~2.77 and 0.73~2.96tons/ha respectively. 4. The ratios between the yields of CP and TDN were 5.48, 4.60 and 4.34 in 3, 4 and 5 cutting 6equency respectively and it indicates lower ratio in result of higher number of cutting 6equency. 5. Higher nitrogen fertilization increased the yields of CP and TDN. The yields of CP were higher in 5 cutting frequency as 1.55~2.62tons/ha than of 3(1.20~1.91tons/ha) and 4 cutting frequency(1.35-2.23tons/ha). The yields of TDN were 6.31~9.93, 5.99~9.99 and 7.16~10.57tons/ha in 3, 4 and 5 cutting frequency respectively. 6. The levels of nitrogen fertilization for high production efficiency of crude protein(kg CPYkg N) was estimated as 113.4~302.5kg/ha and it resulted in 1.44~2.09ton/ha of CP yields. The levels of nitrogen fertilization for high production efficiency of dry matter was 199.2-361.3kgha in which nitrogen were fertilized below 400kg/ha and it resulted in 1.64~2.17ton/ha of CP yields. 7. The levels of nitrogen fertilization for high production efficiency of total digestible nutrients(kg TDNYkg N) were 149.9~294.1kg/ha in 3 and 4 cutting kequency and it resulted in 8.66~8.89ton/ha of TDN yileds. With the levels of nitrogen fertilization for high production efficiency of dry matter of 199.2~361.3kg/ha, TDN yields were high as 8.77~9.94ton/ha.

• The Journal of Information Systems
• /
• v.26 no.2
• /
• pp.105-121
• /
• 2017

Purpose It is a major goal to improve the product yields during production operations in the manufacturing industry. Therefore, factory is trying to keep the good quality materials and proper production resources, also find the proper condition of facilities and manufacturing environment for yields improvement. Design/methodology/approach We propose the hybrid framework to analyze to dataset extracted from MES. Those data is about the alarm information generated from equipment, both measurement and equipment process value from production and cycle/pitch time measured from production data these covered products during production. We adapt a data warehousing techniques for organizing dataset, a logistic regression for finding out the significant factors, and a association analysis for drawing the rules which affect the product yields. And then we validate the framework by applying the real data generated from the discrete process in secondary cell battery manufacturing. Findings This paper deals with challenges to apply the full potential of modeling and simulation within CPPS(Cyber-Physical Production System) and Smart Factory implementation. The framework is being applied in one of the most advanced and complex industrial sectors like semiconductor, display, and automotive industry.