• Journal of the Korean Society of Food Culture
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• v.20 no.2
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• pp.243-252
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• 2005

This study identified how family restaurant customers' attitude toward yield management strategies, which include reservation, time, menu, and service factors. Generally, yield management explains how price and dining duration maximize the revenue of family restaurants. There are three ways to improve family restaurant yield; improving table turns, upgrading seat occupancy, increasing price per customer. The 45 items of yield management strategies are developed by literature reviews, web sites analysis, and interviews with family restaurant employers. Factor analysis and reliability analysis from present study found out 11 important factors, which represent the study's dependent variables. Regression analysis may be helpful to test whether demographic and socio-economic factors have relationships with family restaurant customers' attitude toward yield management strategies. As a regression result, gender, family size, age in demographic factors and education and occupation in socio-economic factors have relationships with family restaurant customers' attitude toward yield management strategies significantly.

• Journal of the Korean Operations Research and Management Science Society
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• v.36 no.3
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• pp.61-74
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• 2011

The objective of this study is to evaluate the effects of sharing uncertain yield information with a downstream supply chain player. We are interested in understanding how the amount of yield uncertainty affects the supply-side benefits and/or costs, which has not been considered in the literature, in addition to the customer-side benefits. With that purpose, this work evaluates a supplier who provides yield information in comparison with another supplier who shares no information. We simulate an order-up-to type heuristic policy that is adapted from the literature and reasonably modified to represent yield information sharing with error. From the simulation study, we argue that the customer would experience cost reduction, but the cost for supplier's inventory is increasing when sharing yield information. Furthermore, the amount of benefits and costs are situational and affected by level of yield uncertainty and demand variance. Based on the simulation study, we finally make several recommendations for the supply-side approaches to yield information sharing.

• Carbon letters
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• v.19
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• pp.57-65
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• 2016

Isroaniso matrix precursor synthesized from commercially available petroleum pitch was stabilized in air. The influence of oxygen mass gain during stabilization on the yield of matrix precursor was studied. Additionally, the influence of pressure on the yield of the stabilized matrix precursor in a real system was studied. The fourier transform infrared spectrometry (FTIR), thermogravimetric analysis (TGA), yield, yield rate, and yield impact were used to check the effect of stabilization and pressure on the yield of the matrix precursor and the end properties of the composite thereafter. The results showed that the yield increased with stabilization duration up to 20 h whereas it decreased for stabilization duration beyond 20 h. Further results showed that the stabilized matrix precursor for a duration of 5 h could withstand almost two-fold greater hot-pressing pressure without resulting in exudation as compared to that of a 1 h stabilized matrix precursor. The enhanced hot-pressing pressure significantly improved the yield of the matrix precursor. As a consequence, the densification and mechanical properties were increased significantly. Further, the matrix precursor stabilized for a duration of 20 h or more failed to provide proper and uniform binding of the reinforcement.

• Journal of Environmental Science International
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• v.18 no.1
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• pp.1-7
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• 2009

In this study a sediment yield is compared by IUSG, IUSG with Kalman filter, tank model and tank model with Kalman filter separately. The IUSG is the distribution of sediment from an instantaneous burst of rainfall producing one unit of runoff. The IUSG, defined as a product of the sediment concentration distribution (SCD) and the instantaneous unit hydrograph (IUH), is known to depend on the characteristics of the effective rainfall. In the IUSG with Kalman filter, the state vector of the watershed sediment yield system is constituted by the IUSG. The initial values of the state vector are assumed as the average of the IUSG values and the initial sediment yield estimated from the average IUSG. A tank model consisting of three tanks was developed for prediction of sediment yield. The sediment yield of each tank was computed by multiplying the total sediment yield by the sediment yield coefficients; the yield was obtained by the product of the runoff of each tank and the sediment concentration in the tank. A tank model with Kalman filter is developed for prediction of sediment yield. The state vector of the system model represents the parameters of the tank model. The initial values of the state vector were estimated by trial and error.

• Journal of Animal Science and Technology
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• v.45 no.5
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• pp.725-730
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• 2003

This study was conducted to evaluate the adequacy of an alternative a.m.-p.m. testing scheme for milk yield in comparison with the official test method based on weighing two milkings within 24 h. A total of 8,309 p.m. milking weights and 6,767 a.m. milking weights from 72 Holstein cows raised at N.L.R.I. were collected between October 2000 and November 2001. Ratios were computes for daily milk yield to a.m. and p.m. milking weights(direct yield ratios) and ratios of a.m. and p.m. milking weights to daily milk yield (inverse yield ratios). Analysis of variance indicated that the milking interval is the most important source of variation for yield ratios. Adjustment factors for estimating daily milk yield from single milking weights were derived through regression analysis of direct and inverse yield ratios on the length of the milking interval. Daily milk yield was estimated more precisely and accurately when adjustment factors were used than when single milking weights were doubled. In conclusion, alternative recording of a.m. and p.m. milking weights led to reliable estimates of milk yields.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.57 no.4
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• pp.401-408
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• 2012

The grain and agronomic characteristics of Korean barley cultivars were investigated with respect to ethanol yield. Test weight, grain yield, and starch yield showed noticeable variation among the cultivars. Grain yields were higher in covered barley and non-waxy barley. Starch yield was higher in non-waxy barley than waxy barley. Protein, ${\beta}$-glucan, and starch content of tested cultivars ranged in 10.0-12.9%, 4.4-7.5% and 49.7-65.3%, respectively. Naked barley cultivar had higher starch content than covered barley cultivar. However, covered barley had high starch yield because it has higher grain yield than naked barley. Covered barley cultivar had higher husk content, ranging 7.6-14.0%, than that of naked barley cultivar, ranging 5.3-8.0%. Starch content was positively correlated with amylose content, test weight, ethanol yield and negatively correlated with protein, husk, ${\beta}$-glucan content. Ethanol yield per ton was positively correlated with starch content, but negatively correlated with husk content. Ethanol yield per hectare was positively correlated with starch yield, grain yield, grain weight and negatively correlated with protein, test weight. From this research, the important characteristics of barley cultivar as a bioethanol producing material were starch content and grain yield. Optimum barley genotype was non-waxy naked barley that had low protein, ${\beta}$-glucan, husk content, and high starch content and grain yield.

• Korean Journal of Remote Sensing
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• v.22 no.3
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• pp.183-197
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• 2006

Combinations of visible and near-infrared (NIR) bands in an image are widely used for estimating vegetation vigor and productivity. Using this approach to understand within-field grain crop variability could allow pre-harvest estimates of yield, and might enable mapping of yield variations without use of a combine yield monitor. The objective of this study was to estimate within-field variations in crop yield using vegetation indices derived from hyperspectral images. Hyperspectral images were acquired using an aerial sensor on multiple dates during the 2003 and 2004 cropping seasons for corn and soybean fields in central Missouri. Vegetation indices, including intensity normalized red (NR), intensity normalized green (NG), normalized difference vegetation index (NDVI), green NDVI (gNDVI), and soil-adjusted vegetation index (SAVI), were derived from the images using wavelengths from 440 nm to 850 nm, with bands selected using an iterative procedure. Accuracy of yield estimation models based on these vegetation indices was assessed by comparison with combine yield monitor data. In 2003, late-season NG provided the best estimation of both corn $(r^2\;=\;0.632)$ and soybean $(r^2\;=\;0.467)$ yields. Stepwise multiple linear regression using multiple hyperspectral bands was also used to estimate yield, and explained similar amounts of yield variation. Corn yield variability was better modeled than was soybean yield variability. Remote sensing was better able to estimate yields in the 2003 season when crop growth was limited by water availability, especially on drought-prone portions of the fields. In 2004, when timely rains during the growing season provided adequate moisture across entire fields and yield variability was less, remote sensing estimates of yield were much poorer $(r^2<0.3)$.

• Journal of Biosystems Engineering
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• v.30 no.1 s.108
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• pp.45-55
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• 2005

Knowledge of the relationship between crop yield and yield-limiting factors is essential for precision farming. However, developing this knowledge is not easy because these yield-limiting factors are interrelated and affect crop yield in different ways. In this study, data for grain yield and yield-limiting factors, including crop chlorophyll content, soil chemical properties, and topography were collected for a small (0.3 ha) rice paddy field in Korea and a large (36 ha) upland corn field in the USA, and relationships were investigated with path analysis. Using this approach, the effects of limiting factors on crop yield could be separated into direct effects and indirect effects acting through other factors. Path analysis provided more insight into these complex relationships than did simple correlation or multiple linear regression analysis. Results of correlation analysis for the rice paddy field showed that EC, Ca, and $SiO_2$ had significant (P<0.1) correlations with rice yield, while pH, Ca, Mg, Na, $SiO_2,\;and\;P_2O_5$ had significant correlations with the SPAD chlorophyll reading. Path analysis provided additional information about the importance and contribution paths of soil variables to rice yield and growth. Ca had the highest direct effect (0.52) and indirect effect via Mg (-0.37) on rice yield. The indirect effect of Mg through Ca (0.51) was higher than the direct effect (-0.38). Path analysis also enabled more appropriate selection of important factors limiting crop yield by considering cause-and-effect relationships among predictor and response variables. For example, although pH showed a positive correlation (r=0.35) with SPAD readings, the correlation was mainly due to the indirect positive effects acting through Mg and $SiO_2$, while pH not only showed negative direct effects, but also negatively impacted indirect effects of other variables on SPAD readings. For the large upland Missouri corn field, two topographic factors, elevation and slope, had significant (P<0.1) direct effects on yield and highly significant (P<0.01) correlations with other limiting factors. Based on the correlation analysis alone, P and K were determined to be nutrients that would increase corn yield for this field. With the help of path analysis, however, increases in Mg could also be expected to increase corn yield in this case. In general, path analysis results were consistent with published optimum ranges of nutrients for rice and com production. We conclude that path analysis can be a useful tool to investigate interrelationships between crop yield and yield limiting factors on a site-specific basis.

• Asian-Australasian Journal of Animal Sciences
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• v.15 no.12
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• pp.1813-1821
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• 2002

The aim of this study was to identify useful secondary traits for estimating genetic ability of milk production traits. We investigated the value of using plasma metabolites concentrations. Two hundred and nineteen cattle out of 271 had only milk production traits records (G1), 33 had only metabolites records (G2), and 19 had both milk production traits and metabolites records (G3). Fifty two calves with metabolites records (G2 and G3) were born from 1992 to 1997. Forty three calves (29 females, 14 males) were used from 10 to 90 d of age and the others (3 females, 6 males) from 10 to 60 d of age. A total of 566 records of milk yield, fat yield and protein yield for 240 to 305 d on 238 heads (G1 and G2) were collected The collected blood samples were divided into three age groups: AG1, 10 to 30 d; AG2, 40 to 60 d; and AG3, 70 to 90 d. Heritabilities of milk yield, fat yield and protein yield were $0.45{\pm}0.04$, $0.50{\pm}0.04$ and $0.38{\pm}0.04$, respectively. Heritability of plasma glucose concentration at AG1 was $0.45{\pm}0.08$. Genetic correlations between plasma glucose concentration and milk yield, fat yield and protein yield were -$0.35{\pm}0.28$, $0.64{\pm}0.24$ and $0.36{\pm}0.35$, respectively. When the plasma glucose concentration at AG1 was used to estimate genetic ability of these milk production traits, reliability of milk yield of animals without milk record increased 8.2%, fat yield increased 24.2% and protein yield increased 9.5%. Heritability of plasma total cholesterol concentration at AG3 was $0.83{\pm}0.04$. Genetic correlation between plasma total cholesterol concentration and milk yield, fat yield and protein yield were $0.58{\pm}0.21$, $0.42{\pm}0.20$ and $0.45{\pm}0.22$, respectively. When the plasma total cholesterol concentration at AG3 was using to estimate genetic ability of these milk production traits, reliability of milk yield of animals without milk record increased 19.0%, fat yield increased 9.6%, and protein yield increased 13.5%. The annual genetic gain is in proportion to the reliability of selection. These results show that the plasma metabolite concentrations would be useful for improvement of genetic ability for milk production traits in the genetic improvement in herd of cows, where half of the animals selected are from a herd without its own milk record.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.48 no.4
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• pp.316-321
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• 2003

Analysis of breeding gains in grain yield has been intensively conducted in wheat, barley, oat, maize, and soybean. Such information is limited in rice. The objective of this study was to compare the breeding gains and cultural gains contributed to yield gains of Korean rice varieties since early 1900s. Two sets of yield data were used for analysis; the historical yield data of 1908 for old japonica cultivars, and present yield data in the years from 1996 to 1998 for the six cultivars, consisting of previous two old cultivars and four contemporary cultivars. The old cultivars were two native cultivars, Jodongi and Damageum, while contemporary cultivars were two premium quality japonica cultivars, Hwaseongbyeo and Dongjinbyeo, and two Tongil-type cultivars, high yielding cultivars developed from indica/japonica hybridization, Milyang23 and Dasanbyeo. The yield differences of old cultivars between the experiments in 1908 and the experiments from 1996 to 1998 were estimated as cultural gains (1.84 tons $\textrm{ha}^{-1}$) due to the improvement of cultivation technology. Yield differences between the old cultivars and contemporary cultivars were considered total yield gains during the periods. These were 2.51 tons $\textrm{ha}^{-1}$ for japonica cultivars and 3.81 tons $\textrm{ha}^{-1}$ for Tongil-type cultivars. From these data, the genetic gain of 0.67 tons $\textrm{ha}^{-1}$ and 1.97 tons $\textrm{ha}^{-1}$ were estimated for japonica cultivars and Tongil-type cultivars respectively. The ratio between cultural gain and genetic gain appeared to be 2.7:1 for japonica cultivars and 1:1 for Tongil-type cultivars. This analysis clearly showed the higher genetic contribution in Tongil-type cultivars than in japonica cultivars, suggesting a guideline to be used when planning new yield improvement programs. Additional implication has emerged when a better yield response to modem cultivation technology was found in one of the old cultivars, suggesting the combined improvement between breeding and cultural improvement is necessary for attaining the maximum yield capacity of a crop.