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Journal articles on the topic 'Optimum sample size'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Cho, Dooyong, Fazil T. Najafi, and Peter A. Kopac. "Determining Optimum Acceptance Sample Size." Transportation Research Record: Journal of the Transportation Research Board 2228, no. 1 (2011): 61–69. http://dx.doi.org/10.3141/2228-08.

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2

Pelkowitz, L., and S. C. Schwarts. "Asymptotically Optimum Sample Size for Quickest Detection." IEEE Transactions on Aerospace and Electronic Systems AES-23, no. 2 (1987): 263–72. http://dx.doi.org/10.1109/taes.1987.313381.

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3

Song, Xiaolan, Pradipta Sarkar, and William Veronesi. "Virtual Inspection: Optimum Sample Size for POD Experiment." Quality Engineering 14, no. 4 (2002): 623–44. http://dx.doi.org/10.1081/qen-120003563.

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4

Gharaibeh, Nasir G., Sabrina I. Garber, and Litao Liu. "Determining Optimum Sample Size for Percent-Within-Limits Specifications." Transportation Research Record: Journal of the Transportation Research Board 2151, no. 1 (2010): 77–83. http://dx.doi.org/10.3141/2151-10.

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5

Otis, David L. "Optimum Sample Size Allocation for Wood Duck Banding Studies." Journal of Wildlife Management 58, no. 1 (1994): 114. http://dx.doi.org/10.2307/3809557.

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Ukrainskiy, Pavel. "Еmpirical method for estimation of the optimum size of random point samples for assessment areas of land cover from space images". InterCarto. InterGIS 27, № 2 (2021): 368–78. http://dx.doi.org/10.35595/2414-9179-2021-2-27-368-378.

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A promising fast method for estimating land cover areas from satellite imagery is the use of random point sampling. This method allows you to obtain area values without spatially continuous mapping of land areas. The accuracy of the area estimate by this method depends on the sample size. The presented work describes a method for empirically finding the optimal sample size. To use this method, you must select a key site for which a reference land cover exists. For the key site, we perform multiple generation of samples of different sizes. Further, using these samples, we estimate the area of l

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Nanni, Marcos Rafael, Fabrício Pinheiro Povh, José Alexandre Melo Demattê, Roney Berti de Oliveira, Marcelo Luiz Chicati, and Everson Cezar. "Optimum size in grid soil sampling for variable rate application in site-specific management." Scientia Agricola 68, no. 3 (2011): 386–92. http://dx.doi.org/10.1590/s0103-90162011000300017.

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The importance of understanding spatial variability of soils is connected to crop management planning. This understanding makes it possible to treat soil not as a uniform, but a variable entity, and it enables site-specific management to increase production efficiency, which is the target of precision agriculture. Questions remain as the optimum soil sampling interval needed to make site-specific fertilizer recommendations in Brazil. The objectives of this study were: i) to evaluate the spatial variability of the main attributes that influence fertilization recommendations, using georeferenced

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Indira, V., R. Vasanthakumari, N. R. Sakthivel, and V. Sugumaran. "Determination of sample size using power analysis and optimum bin size of histogram features." International Journal of Data Analysis Techniques and Strategies 3, no. 1 (2011): 21. http://dx.doi.org/10.1504/ijdats.2011.038804.

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9

Islam, Md Saiful. "Estimation of optimum sample size and number of replications in split-split plot design." Bangladesh Journal of Agricultural Research 32, no. 3 (2008): 403–11. http://dx.doi.org/10.3329/bjar.v32i3.542.

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In field experiments, it is necessary to determine the optimum sample size as well as optimum number of replications if researchers have to use sampling techniques for collecting data from such experiments. Estimates of such optimum sample size and number of replications has been determined for split-split plot design minimizing the variance for a given cost of the experiment per treatment.DOI: http://dx.doi.org/10.3329/bjar.v32i3.542Bangladesh J. Agril. Res. 32(3) : 403-411, September 2007

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10

Singh, A., and G. Singh. "ESTIMATION OF OPTIMUM SAMPLE SIZE FOR DIFFERENT CHARACTERS OF GUAVA VARIETIES." Acta Horticulturae, no. 735 (March 2007): 325–27. http://dx.doi.org/10.17660/actahortic.2007.735.45.

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11

Hernandez, C. M., and J. Crossa. "A Program for Estimating the Optimum Sample Size for Germplasm Conservation." Journal of Heredity 84, no. 1 (1993): 85–86. http://dx.doi.org/10.1093/oxfordjournals.jhered.a111284.

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Shvydka, S., V. Sarabeev, V. D. Estruch, and C. Cadarso-Suárez. "Optimum sample size to estimate mean parasite abundance in fish parasite surveys." Helminthologia 55, no. 1 (2018): 52–59. http://dx.doi.org/10.1515/helm-2017-0054.

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Summary To reach ethically and scientifically valid mean abundance values in parasitological and epidemiological studies this paper considers analytic and simulation approaches for sample size determination. The sample size estimation was carried out by applying mathematical formula with predetermined precision level and parameter of the negative binomial distribution estimated from the empirical data. A simulation approach to optimum sample size determination aimed at the estimation of true value of the mean abundance and its confidence interval (CI) was based on the Bag of Little Bootstraps

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Al-Khayat, Haydar, Charles Gurganus, David E. Newcomb, and Maryam S. Sakhaeifar. "Determining the Optimum Sample Size for Quality Assurance (QA) of Asphalt Mixtures: A Case Study." Baltic Journal of Road and Bridge Engineering 17, no. 3 (2022): 92–103. http://dx.doi.org/10.7250/bjrbe.2022-17.570.

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Acceptance plans for asphalt mixtures use a certain sample size that is often established based on the purpose of sampling, population size, risk, and allowable error for evaluation. The rate of quality control (QC) sample size is often higher than the quality assurance (QA) sample size. The test results obtained from the QA samples are commonly used to validate the QC test results and to assist the state department of transportation (DOT) with payment decisions. However, if the QA sample size is insufficient to make accurate judgments, the probability of making incorrect decisions regarding a

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14

Quesada Carballo, Luís, María del Rosario Perez Perez, David Cantador Fernández, Alvaro Caballero Amores, and José María Fernández Rodríguez. "Optimum Particle Size of Treated Calcites for CO2 Capture in a Power Plant." Materials 12, no. 8 (2019): 1284. http://dx.doi.org/10.3390/ma12081284.

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This work has analyzed the influence of the particle size of a calcite from a quarry, whether original, calcined, or rehydrated, on the efficiency of CO2 capture of the gases emitted in a coal-fired power plant. Three different particle sizes 0.5 mm, 0.1 mm, and 0.045 mm have been studied. The calcination had a minimal effect on the particle size of the smaller samples A1045 and A1M1 (<30 μm). The N2 isotherms and the CO2 adsorption isotherms at 0 °C showed a very significant increase in the surface of the calcined and rehydrated samples (A15CH, A1045CH, and A1M1CH) with respect to the calc

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15

Gomes, Rafaela Lanças, José Raimundo de Souza Passos, Juliana Iassia Gimenez, et al. "Optimum Sample Size in the Germination of Atemoya Seeds (Annona× atemoya Mabb.)." Journal of Agricultural Science 11, no. 7 (2019): 239. http://dx.doi.org/10.5539/jas.v11n7p239.

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Atemoya currently has its seeds studied in several aspects, from the technological and physiological point of view. However, for the performance of the germination test, there is no standardization in relation to the number of seeds and replicates. Thus, this work aims to determine the optimal sample size for germination tests with atemoya seeds. A germination test was carried out with 5 treatments, considering 10, 20, 30 40 and 50 seeds per sampling unit with 50 replicates of each. Data were analyzed using logistic regression, non-linear Gompertz regression models, bootstrap simulation and gr

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Adams, G. C. "Optimum Sample Size for Detecting Virulence Differences in Leucostoma Isolates from Peach." Plant Disease 73, no. 9 (1989): 754. http://dx.doi.org/10.1094/pd-73-0754.

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17

M. Ohura, M. Li, and W. F. McClure. "DETERMINING OPTIMUM SAMPLE SIZE FOR MEASURING BODY WEIGHT OF SILKWORM, BOMBYX MORI." Applied Engineering in Agriculture 19, no. 6 (2003): 737–41. http://dx.doi.org/10.13031/2013.15652.

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18

Nam, Jun-Mo, and Thomas R. Fears. "Optimum sample size determination in stratified case-control studies with cost considerations." Statistics in Medicine 11, no. 4 (1992): 547–56. http://dx.doi.org/10.1002/sim.4780110416.

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19

Chandrasekharan, Subramanian, Jayadevan Sreedharan, and Aji Gopakumar. "Statistical Issues in Small and Large Sample: Need of Optimum Upper Bound for the Sample Size." International Journal of Computational & Theoretical Statistics 06, no. 02 (2019): 108–18. http://dx.doi.org/10.12785/ijcts/060201.

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20

Nokoe, Sagary, and Rodomiro Ortiz. "Optimum Plot Size for Banana Trials." HortScience 33, no. 1 (1998): 130–32. http://dx.doi.org/10.21273/hortsci.33.1.0130.

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Bananas (Musa spp. AAA group) are an important food and a source of income for farmers in tropical countries. Black sigatoka (Mycosphaerella fijiensis Morelet), a fungal leaf spot disease, is the major production constraint worldwide. The replacement of most of the susceptible banana landraces requires the proper assessment of host plant response to black sigatoka and the determination of yield potential (per unit area and time) of the new selections. Although optimum plot sizes have been reported earlier for banana trials, the number of plants per plot was determined primarily by using a subj

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21

Mohammedelameen, Eissa Qurashi, and H. Elhafian Mubarak. "The Impact of Sample Size on the Probability Samples to Estimate the Total population Number." Indian Journal of Science and Technology 16, no. 39 (2023): 3316–24. https://doi.org/10.17485/IJST/v16i39.303.

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Abstract <strong>Objectives:</strong> to determine the best sampling technique based on the allowable error. <strong>Method:</strong> Data of people infected with malaria in Khartoum State during the year 2019 was considered. The data were taken from the Ministry of Health, Khartoum State Sudan, where the population is divided into four stratums. The mean, the total number, and the confidence interval were estimated. A comparison between simple, stratified and systemic random sampling in terms of the accuracy of the estimate , and the effect of marginal error in determining the

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22

Wilamowsky, Yonah, Viswa Viswanathan, and Sheldon Epstein. "Pooled Testing: Determining The Optimum Pool Size To Minimize The Total Number Of Tests." Journal of Applied Business Research (JABR) 37, no. 1 (2021): 1–10. http://dx.doi.org/10.19030/jabr.v37i1.10366.

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In light of the rapidly spreading COVID-19 virus, the FDA has suggested pooling of samples in order to reduce the cost of testing a large population. Under this approach, several samples are pooled, and the pooled samples are first tested. If the pool tests negative, then the lab would have successfully tested many samples while consuming only the resources needed for a single test. If the pooled sample tests positive, then each sample that comprised the pool is individually tested. In this context, an important question for people in the field is “Given a certain overall infection rate among

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23

Delage, Pierre, Martine Audiguier, Yu-Jun Cui, and Michael D. Howat. "Microstructure of a compacted silt." Canadian Geotechnical Journal 33, no. 1 (1996): 150–58. http://dx.doi.org/10.1139/t96-030.

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This paper presents a qualitative and quantitative study of the microstructure of a compacted silt, carried out using a scanning electron microscope and mercury intrusion pore size distribution measurements. Samples have been statically compacted at three water contents: on the dry side of the standard Proctor optimum water content, at the optimum, and on the wet side. The wet sample has a matrix type structure, with a clayey fraction filling the voids and adhering to the silt-sized grains, whereas the other samples display a structure characterized by a skeleton made of silt grain aggregates

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24

Durner, Edward F. "OPS: A Computer Program for Estimating Optimum Plot Size for Field Research." HortScience 24, no. 6 (1989): 1040. http://dx.doi.org/10.21273/hortsci.24.6.1040.

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Abstract The number of replicates (sample size) and the size of replicates (plot size) are important considerations in the design of plant science experiments. Sample size has recently been addressed by several authors (Snedecor and Cochran, 1980; Trout and Marini, 1984). Plot size is also important since smaller plots allow greater replication in a given area, but larger plots often have lower variances and are thus more statistically desirable.

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25

KOTULA, KATHRYN L., and MEGAN E. DAVIS. "Broiler Skin Sampling for Optimum Recovery of Salmonella spp." Journal of Food Protection 62, no. 3 (1999): 284–86. http://dx.doi.org/10.4315/0362-028x-62.3.284.

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The objective of this research was to determine the appropriate sample size (1, 5, or 10 g) and location (neck, breast, or vent) from which to sample processed poultry skin for Salmonella spp. Postkill, prescald broiler carcasses were used to help ensure that Salmonella spp. would be found. Mean Salmonella spp. counts from skin samples of 1 g (2.91 log10 CFU/g) were significantly lower (P &lt; 0.05) than skin samples of 5 and 10 g: 3.52 log10 CFU/g and 3.42 log10 CFU/g, respectively. Mean Salmonella spp. counts from breast (3.62 log10 CFU/g) or neck (3.40 log10 CFU/g) skin samples were sig

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26

Guo, Jiin-Huarng, and Wei-Ming Luh. "Optimum sample size allocation to minimize cost or maximize power for the two-sample trimmed mean test." British Journal of Mathematical and Statistical Psychology 62, no. 2 (2009): 283–98. http://dx.doi.org/10.1348/000711007x267289.

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27

Genç, S., and M. Mendeş. "Evaluating performance and determining optimum sample size for regression tree and automatic linear modeling." Arquivo Brasileiro de Medicina Veterinária e Zootecnia 73, no. 6 (2021): 1391–402. http://dx.doi.org/10.1590/1678-4162-12413.

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ABSTRACT This study was carried out for two purposes: comparing performances of Regression Tree and Automatic Linear Modeling and determining optimum sample size for these methods under different experimental conditions. A comprehensive Monte Carlo Simulation Study was designed for these purposes. Results of simulation study showed that percentage of explained variation estimates of both Regression Tree and Automatic Linear Modeling was influenced by sample size, number of variables, and structure of variance-covariance matrix. Automatic Linear Modeling had higher performance than Regression T

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28

Mohammad, N., MS Islam, KS Rahman, MM Rahman, and S. Nasrin. "Determination of optimum sample size for measuring the contributing characters of bottle gourd." Bangladesh Journal of Agricultural Research 40, no. 4 (2016): 703–9. http://dx.doi.org/10.3329/bjar.v40i4.26944.

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To improve efficiency in collecting data from field experiment on fruit attributes of bottle gourd (Lau), the sample size was studied for sample size at Olericulture Division, Horticulture Research Centre (HRC) of Bangladesh Agricultural Research Institute (BARI) Gazipur during 2012-13. The treatments/varieties were LS 0026-5-3, LS 0012-5-3, LS 117-F-1, LS 117-A-2 and BARI Lau-3. Fruit length, breadth and weight of bottle gourd (Lau) data were collected from the experimental plot. The data were used to design optimum sampling plan from equal number of observations per cell. The observation on

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29

Singh, M., K. Chabane, J. Valkoun, and T. Blake. "Optimum Sample Size for Estimating Gene Diversity in Wild Wheat using AFLP Markers." Genetic Resources and Crop Evolution 53, no. 1 (2006): 23–33. http://dx.doi.org/10.1007/s10722-004-0597-6.

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30

Das, Gautam Kumar. "Statistical Measures for Required Optimum Sample Size of Forest Stands in West Bengal." Reason-A Technical Journal 20 (July 1, 2021): 9. http://dx.doi.org/10.21843/reas/2021/9-16/212370.

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31

Terreaux, Jean-Philippe. "Frequency and Sample Size to Minimize the Cost of a Rapidly Evolving Infectious Animal or Plant Disease." Agricultural & Rural Studies 2, no. 4 (2024): 0021. http://dx.doi.org/10.59978/ar02040021.

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One of the major effects of global change is the spread of animal and plant diseases on farms. Besides the impact on the farms themselves, it is the whole rural world that is affected, through the possible disruption of value chains. Combating these diseases is therefore a crucial but costly problem. So, when faced with an infectious animal or plant pathology, how can we minimize the cost of the disease and of the sampling and analyses testing required to monitor its progress? First, we calculate the imprecision of the results as a function of the sample size and the prevalence of the disease.

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32

Barron, Martin, Michael Davern, Robert Montgomery, et al. "Using Auxiliary Sample Frame Information for Optimum Sampling of Rare Populations." Journal of Official Statistics 31, no. 4 (2015): 545–57. http://dx.doi.org/10.1515/jos-2015-0034.

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Abstract We investigate disproportionate stratified sampling as a possibly efficient method of surveying members of a rare domain in circumstances in which there is no acceptable list of members. In this work, we assume that information is available at the sampling stage to stratify the general-population sampling frame into high- and low-density strata. Under a fixed constraint on the variance of the estimator of the domain mean, we make the optimum allocation of sample size to the several strata and show that, in comparison to proportional allocation, the optimum allocation requires (a) a sm

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33

Ng, Wartini, Budiman Minasny, Brendan Malone, and Patrick Filippi. "In search of an optimum sampling algorithm for prediction of soil properties from infrared spectra." PeerJ 6 (October 3, 2018): e5722. http://dx.doi.org/10.7717/peerj.5722.

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Background The use of visible-near infrared (vis-NIR) spectroscopy for rapid soil characterisation has gained a lot of interest in recent times. Soil spectra absorbance from the visible-infrared range can be calibrated using regression models to predict a set of soil properties. The accuracy of these regression models relies heavily on the calibration set. The optimum sample size and the overall sample representativeness of the dataset could further improve the model performance. However, there is no guideline on which sampling method should be used under different size of datasets. Methods He

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34

Grafström, Anton, and Alina Matei. "Coordination of Conditional Poisson Samples." Journal of Official Statistics 31, no. 4 (2015): 649–72. http://dx.doi.org/10.1515/jos-2015-0039.

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Abstract Sample coordination seeks to maximize or to minimize the overlap of two or more samples. The former is known as positive coordination, and the latter as negative coordination. Positive coordination is mainly used for estimation purposes and to reduce data collection costs. Negative coordination is mainly performed to diminish the response burden of the sampled units. Poisson sampling design with permanent random numbers provides an optimum coordination degree of two or more samples. The size of a Poisson sample is, however, random. Conditional Poisson (CP) sampling is a modification o

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35

Upadhyay, Hari Prasad, and Bijay Lal Pradhan. "Sample Size Estimation in Medical Research Based Upon Study Design." Journal of College of Medical Sciences-Nepal 19, no. 2 (2023): 237–45. http://dx.doi.org/10.3126/jcmsn.v19i2.23978.

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Background: In medical research the target of researcher is to generalize the finding to the population based upon the information of sample data. This sample has to be representative of the target population, and the number of participants must be appropriate. The determination of minimum optimum sample size is extremely important not only for ethical and economic purposes but also to achieve scientifically and statistically sound results and valid conclusion.  Conclusion: Choosing the best study design and calculation of sample size are the most important tool in any research. Be

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Liu, Wen Lin, Ri Jie Yang, Zhi Tao Mu, Xiu Xia Wang, and Da Zhao Yu. "Determination of the Optimum Fitting Probabilistic Distribution for Fracture Toughness in Small Sample Size." Advanced Materials Research 320 (August 2011): 263–68. http://dx.doi.org/10.4028/www.scientific.net/amr.320.263.

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Plane strain fracture toughness is an important mechanical performance index for damage tolerance design, so how to obtain this value through test deserves consideration. In this paper, the ductile fracture toughness test was performed. It was difficult for the specimen with big dimensions in the case of plane strain to be carried out through ordinary testing machine with lower capacity because of the higher fracture toughness value of the material, that it was attained indirectly for plane strain fracture toughness value by the way of ductile fracture toughness test and pertinent formula calc

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37

Adetunji, M. T. "Optimum sample size and sampling depth for soil nutrient analysis of some tropical soils." Communications in Soil Science and Plant Analysis 25, no. 3-4 (1994): 199–205. http://dx.doi.org/10.1080/00103629409369030.

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38

Mazei, Yuri A., Andrey N. Tsyganov, Anton S. Esaulov, Alexander Yu Tychkov, and Richard J. Payne. "What is the optimum sample size for the study of peatland testate amoeba assemblages?" European Journal of Protistology 61 (October 2017): 85–91. http://dx.doi.org/10.1016/j.ejop.2017.09.004.

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39

HAMDI, AHMED H. I., ELSAYED M. H. SHOKR, SEDHOM A. SEDHOM, and SALWA A. A. HASSANEIN. "ESTIMATION OF THE OPTIMUM PLANT SAMPLE SIZE FOR YIELD AND ITS COMPONENTS IN LENTIL." Egyptian Journal of Agricultural Research 81, no. 4 (2003): 1707–22. http://dx.doi.org/10.21608/ejar.2003.298653.

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40

Jordan, Lewis, Laurence R. Schimleck, Alexander Clark, Daniel B. Hall, and Richard F. Daniels. "Estimating optimum sampling size to determine weighted core specific gravity of planted loblolly pine." Canadian Journal of Forest Research 37, no. 11 (2007): 2242–49. http://dx.doi.org/10.1139/x07-085.

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Data from a variability study of loblolly pine ( Pinus taeda L.) based on weighted core specific gravity (WCSG) were examined to show how costs and variance estimates are used in designing efficient sampling strategies. Increment cores for the determination of WCSG were taken from 3957 trees across six distinct physiographic regions in the southeastern United States. More variability was found to exist among stands than within stands. This indicates that reducing the variation of the mean of WCSG can be accomplished by sampling more stands and fewer trees in the region of interest. The number

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Murray, Audrey, and Banu Örmeci. "Impact of polymer-sludge interaction on rheogram peaks and optimum dose determination." Water Science and Technology 57, no. 3 (2008): 389–94. http://dx.doi.org/10.2166/wst.2008.018.

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Torque rheometry offers potential for in-line monitoring use, screening polymers, and on site optimization of polymer dose by treatment plant operators. This study investigates the peaks formed following direct polymer injection into sludge during rheological analysis. The peaks enable observation of both flocculation and deflocculation phases, and the highest point of the peaks indicates the point where network bonds rupture. The goal of this study was to test the method reported by Örmeci on anaerobically digested sludge samples with several polymers, covering a wide spectrum of molecular we

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Jasim, Balasim Saadoun, and Dejela I. Mahdi. "Comparison Bennett's Inequality and Regression in Determining the Optimum Sample Size for Estimating the Net Reclassification Index (NRI) Using Simulation." Journal of Economics and Administrative Sciences 27, no. 129 (2021): 139–53. http://dx.doi.org/10.33095/jeas.v27i129.2181.

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Researchers have increased interest in recent years in determining the optimum sample size to obtain sufficient accuracy and estimation and to obtain high-precision parameters in order to evaluate a large number of tests in the field of diagnosis at the same time. In this research, two methods are used to determine the optimum sample size to estimate the parameters of high-dimensional data. These methods are the Bennett inequality method and the regression method. The nonlinear logistic regression model is estimated by the size of each sampling method in high-dimensional data using artificial

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Jasim, Balasim Saadoun, and Dejela I. MAHDI. "comparison Bennett's inequality and regression in determining the optimum sample size for estimating the Net Reclassification Index (NRI) using simulation." Journal of Economics and Administrative Sciences 27, no. 128 (2021): 152–66. http://dx.doi.org/10.33095/jeas.v27i128.2161.

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Researchers have increased interest in recent years in determining the optimum sample size to obtain sufficient accuracy and estimation and to obtain high-precision parameters in order to evaluate a large number of tests in the field of diagnosis at the same time. In this research, two methods were used to determine the optimum sample size to estimate the parameters of high-dimensional data. These methods are the Bennett inequality method and the regression method. The nonlinear logistic regression model is estimated by the size of each sampling method in high-dimensional data using artificial

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44

Gumpili, Sai Prashanti, and Anthony Vipin Das. "Sample size and its evolution in research." IHOPE Journal of Ophthalmology 1 (January 7, 2022): 9–13. http://dx.doi.org/10.25259/ihopejo_3_2021.

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Objective: Sample size is one of the crucial and basic steps involved in planning any study. This article aims to study the evolution of sample size across the years from hundreds to thousands to millions and to a trillion in the near future (H-K-M-B-T). It also aims to understand the importance of sampling in the era of big data. Study Design - Primary Outcome measure, Methods, Results, and Interpretation: A sample size which is too small will not be a true representation of the population whereas a large sample size will involve putting more individuals at risk. An optimum sample size needs

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45

Fizal, A. N. S., N. H. Zainordin, M. I. M. Jamil, et al. "Optimization of lipids extraction from Moringa oleifera seeds for biodiesel feedstock." IOP Conference Series: Materials Science and Engineering 1195, no. 1 (2021): 012020. http://dx.doi.org/10.1088/1757-899x/1195/1/012020.

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Abstract This paper explore the mechanism of lipid extraction efficiency on Moringa oleifera seeds using Soxhlet extraction method. This present study essential to determine the effect of particle size of the sample, extraction time and type of solvent applied towards the efficiency in extracting the lipids from the material. Soxhlet extraction method utilizing Buchi B118 was use in this study and response surface method was applied to analysed the data and determine the optimum parameter condition to obtain the highest yield of Moringa oil extraction. Moringa oil derived from Moringa oleifera

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Hamid, Roszilah, and M. A. Zubir. "Compressive Strength of Concrete with Recycled Glass as Partial Aggregate Replacement." Materials Science Forum 803 (August 2014): 21–25. http://dx.doi.org/10.4028/www.scientific.net/msf.803.21.

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In this study, recycled glass is used to replace the natural fine aggregate in different mix proportions to obtain the optimum combination that will produce the highest strength. The control samples are Grade 30 ordinary Portland cement concrete (OPCC) containing 100% natural sand and coarse aggregate. The recycled glass concretes contain 70% natural fine aggregate + 30% size 300 micron crushed glass (Sample 2), and 70% fine aggregate + 15% size 300 micron crushed glass + 15% size greater than 300 micron crushed glass (Sample 3). The compressive strengths of the concrete samples with recycled

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Ojiambo, P. S., and H. Scherm. "Optimum Sample Size for Determining Disease Severity and Defoliation Associated with Septoria Leaf Spot of Blueberry." Plant Disease 90, no. 9 (2006): 1209–13. http://dx.doi.org/10.1094/pd-90-1209.

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In a 3-year field study, Premier rabbiteye blueberry plants were sampled at three hierarchical levels (leaf, shoot, and bush) to assess severity of Septoria leaf spot (caused by Septoria al-bopunctata) and incidence of defoliation. A positive linear relationship (R 2 = 0.977, P < 0.0001, n = 2127) was observed between the number of spots per leaf and percent necrotic leaf area, both assessed on individual leaves in mid- to late October. For data summarized at the shoot level, percent defoliation increased nonlinearly (R 2 = 0.729, P < 0.0001, n = 224) as disease severity increased, with

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Taha,, R., and M. Shafik. "RELATIVE PRECISION OF SOME INCOMPLETE BLOCK DESIGNS FOR SOYBEAN UNIFORMITY TRIALS AND OPTIMUM SAMPLE SIZE." Journal of Plant Production 25, no. 9 (2000): 5601–10. http://dx.doi.org/10.21608/jpp.2000.259721.

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Ortiz, Marco. "Optimum Sample Size to Detect Perturbation Effects: The Importance of Statistical Power Analysis - A Critique." Marine Ecology 23, no. 1 (2002): 1–9. http://dx.doi.org/10.1046/j.1439-0485.2002.02735.x.

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Mestre, X., and M. A. Lagunas. "Finite sample size effect on minimum variance beamformers: optimum diagonal loading factor for large arrays." IEEE Transactions on Signal Processing 54, no. 1 (2006): 69–82. http://dx.doi.org/10.1109/tsp.2005.861052.

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