• Journal of Korean Society of Forest Science
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• v.95 no.5
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• pp.595-600
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• 2006

The plot design influences the budgets and the precision of forest inventory results. The objective of this study is to determine the efficiency of estimating forest variables such as tree density, basal area, volume, and species richness based on various plot sizes using fixed-area plot sampling in the natural deciduous forest of Pyeong-Chang County, Gang-won Province, Korea. In this study, 108 reference plots were established with a fixed plot size and shape of 0.09 ha ($30m{\times}30m$). In order to determine the optimal plot size for the interest of variables, each sample plot was established using different shapes (square, circle, and rectangle) and was divided into different plot sizes from 100 to $900m^2$. The mean relative difference (MRD) for the sum of the basal area and volume, and tree density per hectare decreased as plot size increased. But the MRD for three variables were only below 13% at the plot size of $500m^2$. Species richness for each reference stand observed ranging from 2 to 15 species, demonstrated highly positive significant relationships with plot size. The minimum plot size for the estimation of tree density, the sum of the BA and volume was determined to be about $400m^2$, whereas the estimation of species richness required a minimum plot size of $500m^2$.

• Journal of Korean Society of Forest Science
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• v.80 no.4
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• pp.379-382
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• 1991

Tree height at age 10 was used to estimate the statistical efficiencies of sampling size in the progeny test of Pinus koraiensis S. et Z. Experimental design was RCB design which consists of 25 half-sib families in each of three blocks. The number of families and blocks were fixed, therefore, the number of trees sampled per plot was the only factor that influences the environmental portion of the family mean height. Coefficient of variation, the estimate of the standard error of the family mean height, decreased with increase of sampling plot size, and became stable from 4-tree plot sampling (6.97%). The experimental error was significant from 7-tree sampling plot size. Nonlinear relationship (${\hat{Y}}=10.425e-^{0.073x}$ ; $R^2$=0.840) was found between the sampling plot size and the standard error of family mean height.

• Journal of Korean Society of Forest Science
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• v.77 no.4
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• pp.421-428
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• 1988

The purpose of this study was to analyze the working time and the efficiency according to plot shape and plot size under the same conditions. We chose two stands which were relatively gently sloped end evenly distributed in number of trees and surveyed 198 plots, and 306 plots in each stand. 1. As to the time advantage of plot establishment method, the direct-four line establishment method was more favorable than the diagonal-line establishment method in a rectangular plot. 2. The method by Blumeleiss-$Me{\beta}$ trommel was more favorable than the method using a tape in a circular plot. 3. As to the time advantage, the circular plot was more favorable than the rectangular plot. Especially, the circular plot was twice more available than rectangular plot in small plot size, but enlargement of plot size gradually decreased time advantage of circular plot.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.119-128
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• 1993

Effective machine capacity is affected by the physical and geometrical conditions of the fields. In the small and scattered farmland structure field efficiency is greatly influenced by plot geometry. In this paper, a method for estimating field efficiency and effective machine capacity was developed . The developed method was applied to Korean paddy cultivation. Various time elements related to farm operations for small and scattered plots are discussed in this paper . Available working time is divided into two parts, viz. the preparation time for machine operation and actual working time. Two kinds of machine efficiencies, namely , Machine Efficiency 1, applicable on a single large plot or set of well consolidated plots ; and Machine Efficiency 2, applicable on small and scattered multiple plots, are considered. Based assumptions made and steps followed to construct the model are discussed. Effective capacity of each machine based on different plot geometries are calculated y the model. Machine efficiency on a single plot increases with increase in the dimension of longer side of the plot . Low speed, low theoretical capacity machines have higher machine efficiency which is only slightly influenced by plot geometry. As plot geometry is improved , the machine efficiency of high speed, high capacity machines increases rapidly. The effects of short side length and plot size on machine efficiency on a single plot depend on the type of farm operation. For a particular plot shape, as plot size increases, machine efficiency on multiple plots increases rapidly. The effects of consolidation on machine efficiency is highly significant if the plot size is small and/or machine size is large.

• Journal of Biosystems Engineering
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• v.21 no.3
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• pp.343-356
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• 1996

The plot geometry of the paddy land is directly related to the performance of machines, especially those having a large size and high speed. The study was to investigate the optimum plot geometry from the standpoint of mechanization. A simulator, Field-Plot-Structure-Evaluation-System(FPSES) was developed for evaluation of the field performance of machines according to the plot geometry. The efficiency and capacity of different sizes of machinery used for rice farming functions were analyzed for a various combination of plot geometry, which could be used as reference for the land reclamation planning and mechanization programming. It is shown that the plot size of about two hectares having a length of 200m and width of loom may be optimum, considering the efficiency and capacity of large sized machinery available currently and in near future.

• Journal of Korean Society of Forest Science
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• v.65 no.1
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• pp.96-99
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• 1984

The analysis of data about the 6-year-old Korean pine plantation was done in order to decide the suitable plot size for the survey on several stand characters. The plot size of at least 0.04 ha was recommendable for the investigation of height; but the size of 0.08 ha for D.B.H. and for crown width.

• Journal of Korean Society of Forest Science
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• v.4 no.1
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• pp.24-25
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• 1965

A statistical study was made on the size of sample plot to be used in the preparation of a yield table. This has always been an important problem needing solution in Korea. For this purpose, 3 replications of Korean white pine plantings with block size of $80m{\times}80m$ were established in the Kwangneung Experimental Forest. A location map was prepared of the pines in the blocks and the heights and the breast height diameters measured. Then those blocks were divided into 64, 64, 16, 16, 4, 4, and 1 standed $40m{\times}80m$ and $80m{\times}80m$ each. After these divisions, the average heights, average breast height diameters, standard deviations and coefficient of variations were computed for the plots and averaged according to plot size. As the results of these computations, it was shown that the standard deviation and the coefficient of variation suddenly increased with the beginning of an increase in plot size. However, these indicated an approximately constant value at a certain limit. Although the average value decreases with the initial increase in plot size, it also indicates an approximately constant value at a certain limit. This limit was between $20m{\times}40m$ and $40m{\times}40m$. With the purpose of evaluating these facts, the average height and the average diameter were computed for the number of standing trees in the $10m{\times}10m$ plots. A negative (minus) relationship was found between the number of standing trees and the average value. As a result of above evaluation, it was found that when the size of plot area was small, a larger estimated value, was obtained as well as a smaller standard deviation and coefficient of variation. It is possible, therefore, that an incorrect value might be used in the evalution of data as the stand structure could appear to be uniform when the plot size was small. In general, when the size of plot area is larger than $40m{\times}40m$, the probability of the difficulty occurring mentioned above is estimated to be small.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.14
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• pp.87-90
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• 1973

Optimum plot shape and size in a uniformity trial in the newly founded experimental farm of KAERI were determined for seed yield with the basic units consisted of 2.5m $\times$ 0.6m plot. Various plot sizes and shapes were made by combination of the basic units. Coefficients of variations for yield were 21% in local branch type variety Kumkang-Dairip and 20% in the introduced branchless type variety Clark. This result indicates that the field in the new experimental farm is appropriate for soybean yield trials when adequate number of replications are employed in the field experiment. In general, C. V. values were gradually decreased with increase of plot sizes. Although the data were not consistant, the errors for the long narrow plots tend to have somewhat smaller than for the square shape plots. A sharp decrease in C.V. value was found from the $4.5\textrm{m}^2$ plot in the variety Kumkang-Dairip and from the $6\textrm{m}^2$ plot in the variety Clark. These results imply that 5-$6\textrm{m}^2$ plot could be used for yield trials in early generations of hybrid progenies. 2.5-5m long plot with 3-4 replications will be practical for yield trials in the early hybrid generations. The C.V. values with 7.5m long plot was about 16% in both varieties and 15.3% in 10m plot. These results indicate that 7.5-10m plot with 3-4 replications could be employed in accurate yield test in the advanced generations.

• Korean Journal of Environmental Agriculture
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• v.22 no.1
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• pp.26-35
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• 2003

An investigation was carried out to evaluate the effects of pebble size on the small-scale sewage treatment apparatus by natural purification method that consisted of aerobic and anaerobic plot. pH and EC in both plots varied minimally regardless of pebble size. DO in aerobic plot increased as the pebble size decreased. That in the anaerobic plot was slightly less in comparison with that of the aerobic plot but varied minimally, $2.4{\sim}5.1\;mg/L$ regardless of pebble size. Under all experimental conditions, removals of BOD, COD and turbidity in anaerobic plot were more than 98, 91 and 98, 98% respectively. Removals of T-N and T-P increased as pebble size decreased. Under all experimental conditions, removals of T-N and T-P in anaerobic plot were about $45{\sim}59$ and $480{\sim}96%$, respectively. Judging from the above results, it should be considered that the optimum pebble size and pebble permeability in both plot was $2{\sim}4$ and $0.1{\sim}4\;mm$, respectively.

• Journal of Korean Society for Quality Management
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• v.46 no.3
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• pp.651-658
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• 2018

Purpose: The algorithm described in Lim(1998) is available to determine the sample size directly given specified significance level, power and signal-to-noise ratio. We research on the efficient determination of the sample size by visual methods. Methods: We propose three graphs for investigating the mutual relationship between the sample size r, power $1-{\beta}$ and the detectable signal-to-noise ratio ${\Delta}$. First graph shows the relationship between ${\Delta}$ and $1-{\beta}$ for the given r and it can be checked whether the power is sufficient enough. Second graph shows the relationship between r and ${\Delta}$ for the given power $1-{\beta}$. Third graph shows the relationship between r and $1-{\beta}$ for the given ${\Delta}$. It can be checked that which effects are sensitive to the efficient sample size by investigating those graphs. Results: In factorial design, randomized block design and the split plot design how to determine the sample size directly given specified significance level, power and signal-to-noise ratio is programmed by using R. A experiment to study the split plot design in Hicks(1982) is used as an example. We compare the sample sizes calculated by randomized block design with those by split plot design. By using graphs, we can check the possibility of reducing the sample size efficiently. Conclusion: The proposed visual methods can help an engineer to make a proper plan to reduce the sample size.