• 한국작물학회지
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• 제50권4호
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• pp.247-255
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• 2005

ice yield and plant growth response to nitrogen (N) fertilizer may vary within a field, probably due to spatially variable soil conditions. An experiment designed for studying the response of rice yield to different rates of N in combination with variable soil conditions was carried out at a field where spatial variation in soil properties, plant growth, and yield across the field was documented from our previous studies for two years. The field with area of 6,600 m2 was divided into six strips running east-west so that variable soil conditions could be included in each strip. Each strip was subjected to different N application level (six levels from 0 to 165kg/ha), and schematically divided into 12 grids $(10m \times10m\;for\;each\;grid)$ for sampling and measurement of plant growth and rice grain yield. Most of plant growth parameters and rice yield showed high variations even at the same N fertilizer level due to the spatially variable soil condition. However, the maximum plant growth and yield response to N fertilizer rate that was analyzed using boundary line analysis followed the Mitcherlich equation (negative exponential function), approaching a maximum value with increasing N fertilizer rate. Assuming the obtainable maximum rice yield is constrained by a limiting soil property, the following model to predict rice grain yield was obtained: $Y=10765{1-0.4704^*EXP(-0.0117^*FN)}^*MIN(I-{clay},\;I_{om},\;I_{cec},\;I_{TN},\; I_{Si})$ where FN is N fertilizer rate (kg/ha), I is index for subscripted soil properties, and MIN is an operator for selecting the minimum value. The observed and predicted yield was well fitted to 1:1 line (Y=X) with determination coefficient of 0.564. As this result was obtained in a very limited condition and did not explain the yield variability so high, this result may not be applied to practical N management. However, this approach has potential for quantifying the grain yield response to N fertilizer rate under variable soil conditions and formulating the site-specific N prescription for the management of spatial yield variability in a field if sufficient data set is acquired for boundary line analysis.

• 서비스연구
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• 제6권4호
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• pp.59-74
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• 2016

본 연구의 목적은 주가연계사채(ELB)의 제시수익률에 대해 달성가능 정도를 분석하여 ELB 문제점을 도출하고, ELB 투자방안에 대한 방향성을 제시하고자 한다. 연구방법은 2015~2016년에 발행된 ELB 구조를 2010년 1월부터 2016년 6월까지 추정수익률을 분석하며, 최소보장수익률, 최고한도율, 참여율과 실제수익률 간의 상관관계와 회귀분석을 실시한다. 분석결과는 주가상승률이 최고상승률 한도를 벗어나지 않아서 주가상승률에 의해서 은행금리수준보다 높은 2%이상의 수익률을 달성할 확률은 20%에도 미치지 못하며, ELB 상품의 평균추정수익률은 1.49%에 불과하여 은행의 2015년 수신금리인 1.72% 보다 낮아서 ELB의 실현가능수익률이 기대치에 미치지 못한다. 최소보장수익율과 ELB 수익률의 상관계수는 0.843, 최고한도수익율과 ELB 수익률의 상관계수는 0.279로 산출되어 ELB 수익률과 최소보장수익율 간에 상관관계는 매우 높다. 시사점은 ELB 실제수익률이 은행예금금리 보다 높지 않으며, 주가상승률이 최고한도 이내에 있을 확률이 낮을 것이다.

• 한국작물학회지
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• 제63권2호
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• pp.158-163
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• 2018

Perilla (Perilla frutescens var.frutescens) is an annual plant of the Lamiaceae family, mainly grown for obtaining oil by press extraction after roasting the seeds. Oil yield is one of its important traits, but evaluating this yield is time-consuming, requires many seeds, and is hard to adjust to pedigrees in a breeding field. The objective of this study was to develop a method for selecting high-oil-yield lines in a breeding population without oil extraction. Twenty-three perilla cultivars were used for evaluating the oil yield and seed traits such as seed hardness, seed coat thickness, seed coat proportion and crude fat. After evaluation of the seed traits of 23 perilla cultivars, the ranges of oil yields, seed hardness, seed coat thickness, seed coat proportion, 100-seed weight, and crude fat were 24.68-38.75%, 157-1166 gf, $24-399{\mu}m$, 15.4-41.5%, 2.79-6.69 g, and 33.0-47.8%, respectively. In an analysis of correlation coefficients, the oil yield negatively correlated with seed length, seed width, the proportion of seed coat, seed hardness, and 1000-seed weight, but positively correlated with crude fat content. It was observed that as the seed coat proportion increased, the seed coat thickness, hardness, and 1000-seed weight also increased. Multiple linear regression (MLR) was employed to find major variables affecting the oil yield. Among the variables, traits crude fat content and seed coat proportion were assumed to be indirect parameters for estimating the potential oil yield, with respect to a significant positive correlation with the observed oil yield ($R^2=0.791$). Using these two parameters, an equation was derived to predict the oil yield. The results of this study show that various seed traits in 23 perilla cultivars positively or negatively correlated with the oil yield. In particular, crude fat and the seed coat proportion can be used for predicting the oil yield with the newly developed equation, and this approach will improve the efficiency of selecting prominent lines for the oil yield.

• Korean Journal of Radiology
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• 제22권10호
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• pp.1680-1689
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• 2021

Objective: To investigate the diagnostic yield of diffusion-weighted imaging (DWI) in patients with transient global amnesia (TGA) and identify significant parameters affecting diagnostic yield. Materials and Methods: A systematic literature search of the MEDLINE and EMBASE databases was conducted to identify studies that assessed the diagnostic yield of DWI in patients with TGA. The pooled diagnostic yield of DWI in patients with TGA was calculated using the DerSimonian-Laird random-effects model. Subgroup analyses were also performed of slice thickness, magnetic field strength, and interval between symptom onset and DWI. Results: Twenty-two original articles (1732 patients) were included. The pooled incidence of right, left, and bilateral hippocampal lesions was 37% (95% confidence interval [CI], 30-44%), 42% (95% CI, 39-46%), and 25% (95% CI, 20-30%) of all lesions, respectively. The pooled diagnostic yield of DWI in patients with TGA was 39% (95% CI, 27-52%). The Higgins I² statistic showed significant heterogeneity (I² = 95%). DWI with a slice thickness ≤ 3 mm showed a higher diagnostic yield than DWI with a slice thickness > 3 mm (pooled diagnostic yield: 63% [95% CI, 53-72%] vs. 26% [95% CI, 16-40%], p < 0.01). DWI performed at an interval between 24 and 96 hours after symptom onset showed a higher diagnostic yield (68% [95% CI, 57-78%], p < 0.01) than DWI performed within 24 hours (16% [95% CI, 7-34%]) or later than 96 hours (15% [95% CI, 8-26%]). There was no difference in the diagnostic yield between DWI performed using 3T vs. 1.5T (pooled diagnostic yield, 31% [95% CI, 25-38%] vs. 24% [95% CI, 14-37%], p = 0.31). Conclusion: The pooled diagnostic yield of DWI in TGA patients was 39%. DWI obtained with a slice thickness ≤ 3 mm or an interval between symptom onset and DWI of > 24 to 96 hours could increase the diagnostic yield.

• Asian-Australasian Journal of Animal Sciences
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• 제18권2호
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• pp.179-184
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• 2005

First lactation records (174) of Jersey${\times}$Sahiwal and Holstein Friesian${\times}$Sahiwal half breds under 9 sires maintained at Chandra Shekher Azad University of Agriculture and Technology, Kanpur, Uttar Pradesh, India from 1975-1983, were used to estimate the genetic parameters and to predict herd life milk yield and average milk yield per day of herd life from first lactation traits. The traits included were: age at first calving, first service period, first lactation period, first calving interval, first lactation milk yield, milk yield per day of first calving interval, herd life milk yield, herd life and average milk yield per day of herd life. Most of the production and reproduction traits were found to have positive and significant correlations between them on genetic as well as phenotypic scales. Total twelve regression equations were fitted. The prediction equation of herd life milk yield in both the genetic groups showed linear relationship with AFC, FSP, FLP, FLMY and MY/DCI and was apparent and significant. Similarly, polynomials for milk yield per day of herd life for J${\times}$S and HF${\times}$S half breds also showed linear trend, which was found highly significant. The highest and lowest $R^2$ values were found for FCI and AFC, respectively.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 2017년도 춘계공동학술대회
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• pp.42-42
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• 2017

Prediction of rice yield during a growing season would be very helpful to magnify rice yield as it also allows better farm practices to maximize yield with greater profit and lesser costs. UAV imagery based automatic detection of rice can be a relevant solution for early prediction of yield. So, we propose an image processing technique to predict rice yield using low altitude UAV images. We proposed $L^*a^*b^*$ color space based image segmentation algorithm. All images were captured using UAV mounted RGB camera. The proposed algorithm was developed to find out rice grain area from the image background. We took RGB image and applied filter to remove noise and converted RGB image to $L^*a^*b^*$ color space. All color information contain in both $a^*$ and $b^*$ layers and by using k-mean clustering classification of these colors were executed. Variation between two colors can be measured and labelling of pixels was completed by cluster index. Image was finally segmented using color. The proposed method showed that rice grain could be segmented and we can recognize rice grains from the UAV images. We can analyze grain areas and by estimating area and volume we could predict rice yield.

• Plant Resources
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• 제5권2호
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• pp.104-108
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• 2002

In order to obtain basic information for selecting early maturing rice varieties which is suitable for early cropping before Alisma plantago in the southern part of Korea. Six rice varieties were grown from May to August in 2002 at Youngjeon Experiment Field, Sunchon and yield components and yield of plants were investingated. Early maturing rice cv. Grubyeo showed higher rough rice yield than any other varieties used in the experiment. It showed high yield components, such as culm length, panicle length, number of panicles per plant, number of spikelets per panicle and ratio of ripened grains. Therefore, it was concluded that Grubyeo was the most suitable variety with high yield for the cultivation before growing of Alisma plantago at the southern part of Korea. The heritability of culm length number of spikelets per panicle and rough rice yield were high and that of panicle length number of panicle per plant, ratio of ripened grain and 1,000 grain wt. of milled rice were low. According to the result of path coefficient analysis, characters highly correlated with rough rice yield showed large direct effects on rough rice yield.

• Structural Engineering and Mechanics
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• 제57권6호
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• pp.1015-1038
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• 2016

In the current research an advanced criterion with non-associated flow rule (non-AFR) for depicting the behavior of anisotropic sheet metals is presented to consider the strength differential effects (SDEs) for these materials. Owing to the fact that Lou et al. (2013) yield function is dependent on structure of an anisotropic material (BCC, FCC and HCP), an advanced yield function with inspiring of Yoon et al. (2014) yield function is proposed which is dependent upon anisotropic structures. Furthermore, to compute Lankford coefficients, a new pressure sensitive plastic potential function which would be dependent to anisotropic structure is presented and coupled with the proposed yield function with employing a non-AFR in a novel criterion which is called here 'dvanced criterion'. Totally eighteen experimental data are required to calibrate the criterion contained of directional tensile and compressive yield stresses for the yield function and directional Lankford coefficients for the plastic potential function. To verify the criterion, three anisotropic sheet metals with different structures are taken as case studies such as Al 2008-T4 (a BCC material), Al 2090-T3 (a FCC material) and AZ31 (a HCP material).

• 산업공학
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• 제22권3호
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• pp.252-262
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• 2009

It is crucial to prevent low yields in the semiconductor industry. Since many factors affect variation in yield and they are deeply related, preventing low yield is difficult. There have been substantial researches in the field of yield prediction. Many researchers had used the statistical methods. Many studies have shown that artificial neural network (ANN) achieved better performance than traditional statistical methods. However, despite ANN's superior performance some problems such as over-fitting and poor explanatory power arise. In order to overcome these limitations, a relatively new machine learning technique, support vector machine (SVM), is introduced to classify the yield. SVM is simple enough to be analyzed mathematically, and it leads to high performances in practical applications. This study presents a new efficient classification methodology, Stepwise-SVM (SSVM), for detecting high and low yields. SSVM is step-by-step adjustment of parameters to be precisely the classification for actual high and low yield lot. The objective of this paper is to examine the feasibility of SVM and SSVM in the yield classification. The experimental results show that SVM and SSVM provides a promising alternative to yield classification for the field data.

• Asian-Australasian Journal of Animal Sciences
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• 제7권2호
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• pp.239-248
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• 1994

To study the relationship between certain hormones and metabolites and between hormones and milk yield during different stage of lactation, six lactating Karan Swiss cows and six Murrah buffaloes were maintained. Growth hormone, insulin, $T_3$, $T_4$, glucose, BHBA, NEFA and milk yield were studied. Highly negative relationship of growth hormone with insulin and triiodothyronine in cows and marginally negative in buffaloes suggest that insulin and triiodothyronine aid in the process of partitioning of nutrients towards milk production through reducing the demands of nutrients by peripheral tissue. The significant and negative correlation of growth hormone with dry matter intake in both the species suggest that the availability of nutrients from the digestive tract play a role in the regulation of growth hormone secretion. Positive relationship of growth hormone with non esterified fatty acids in both the species suggest that high growth hormone levels may result in fat mobilization and thereby increase the availability of energy precursors for milk synthesis. Insulin was negatively correlated with milk yield and lactose content and positively with milk fat and protein but the degree of relationship varied. In both the species the relationship between triiodothyronine and milk yield was negative and between thyroxine and milk yield was positive. However, it was significant only in cows and not in buffaloes. Thyroxine was positively correlated with beta-hydroxybutyrate and non-esterified fatty acids with milk yield in both the species.