Estimated Coefficient Of Variation Research Articles

Genetic Architecture and Association Studies for Grain Yield and its attributing Traits in Recombinant Inbred Lines for Sodicity Tolerance in Rice (Oryza sativa L.)

The present study was undertaken at NSP Unit 6 Agricultural Research Farm and Main Experimental Station of Acharya Narendra Dev University of Agriculture and Technology, Uttar Pradesh, India, from July to November 2020, in which genetic variability and heritability of 250 recombinant inbred lines (F7) and their parents PUSA 44 and CSR 43 were evaluated and correlation studies were performed for grain yield and yield contributing traits. The experiment was conducted in two replications at two different and naturally occurring sodic conditions following α-lattice design. Analysis of variance revealed significant variations among the lines depicting inherent variability between lines. For attributes, viz., plant height, effective tillers plant-1, spikelet fertility percentage, test weight and grain yield plant-1, high phenotypic and genotypic coefficient of variation estimates were observed for both the locations indicating good scope for selection based on these traits. However, the attributes viz., test weight and effective tillers plant-1 values depicted the pertinent role of the environment and thus, require careful assessment in selection programs concerning these traits. For days to 50% flowering, filled grains panicle-1, spikelet fertility percentage, and grain yield plant-1, moderate heritability was discovered with a high genetic advance as a percentage of mean, indicating that there is less influence of environment over these traits. Correlation studies revealed a significant and positive association with these yield attributing traits. Mutual association between component traits exhibit variable responses at both locations, validating genotype and environment interactions among traits with respect to yield.

Estimation of coefficient of variation using linear moments and calibration approach for nonsensitive and sensitive variables

AbstractAssessment of coefficient of variation (CV) is of major importance in numerous examinations. However, the appearance of extreme observations raises concerns about the outcomes of CV estimates based on conventional moments. So, motivated by some recent developments in finite sampling theory, we propose some new estimators of CV based on the properties of linear moments (L‐moments and Trimmed L‐moments), which are highly robust whenever outliers or extreme observations appear in a dataset. The proposed estimators are initially established on the premise that the variable of interest is nonsensitive which deals with the subjects that do not embarrass respondents when asked about them explicitly. These estimators are also applied to situations where the variable of interest is associated with sensitive issues that cause measurement errors resulting from nonresponse or unreliable reporting where such issues can be mitigated by increasing respondent participation by scrambled response models which obscure the true value of the sensitive variable. Four models are considered for this article: additive, multiplicative, mixed, and combined additive‐multiplicative models. Finally, in both nonsensitive and sensitive settings, real‐life data sets are employed to undertake simulation‐based analysis. In all cases, the proposed estimators considerably increased efficiency.

Genetic parameters estimation for some wild wheat species and their F1 hybrids grown in different regions of Saudi Arabia

Wheat (Triticum aestivum L.) is the most important crop for human nutrition that underpins the food safety of Saudi Arabia. The investigation here was to determine heterosis effects using different genetic methods: heterosis over better, mid parents, the genetic advance, and genotype, phenotypic coefficient of variation for estimation some traits among six wheat landraces and their F1 hybrids. In 2019, these landraces were sown using hand and after 100 days, the emasculation and crossing were made among these six landraces using hand emasculation of anthers. In 2020, seeds for these genotypes (six wheat landraces and their F1) were sown under normal irrigation accordingly done in 2019. The results showed that the most important parent was Mabia resulted with the highest value in number of tiller/ plant, 1,000-grain weight, and fresh shoot weight. The highest value of plant height among six parents was Naqra while highest value at the same trait among F1 hybrids was P3 XP6. The estimations of heterosis showed that out of 15 crosses, one cross (P1XP5) was significantly better yield than all crosses for these four traits. The genotype coefficient of variation (GCV) ranged from 12.5% to 8.7% while phenotypic coefficient of variation ranged from 17.7% to 11.3%. The correlationcoefficients was found between fresh shoot weight and number of tiller and plant height and umber of tiller. Wild wheat still serve as a source of useful germplasm with proven adaption and productivity and thus assembles of the wild wheat assortments are the initial step of breeding program.

Measuring temporal patterns in ecology: The case of mast seeding.

Properly assessing temporal patterns is a central issue in ecology in order to understand ecosystem processes and their mechanisms. Mast seeding has traditionally been described as a reproductive behavior consisting of highly variable and synchronized reproductive events. The most common metric used to measure temporal variability and thus infer masting behavior, the coefficient of variation (CV), however, has been repeatedly suggested to improperly estimate temporal variability. Biases of CV estimates are especially problematic for non‐normally distributed data and/or data sets with a high number of zeros.Some recent studies have already adopted new metrics to measure temporal variability, but most continue to use CV. This controversy has started a strong debate about what metrics to use.We here summarize the problems of CV when assessing temporal variability, particularly across data sets containing a large number of zeros, and highlight the benefits of using other metrics of temporal variability, such as proportional variability (PV) and consecutive disparity (D). We also suggest a new way to look at reproductive behavior, by separating temporal variability from frequency of reproduction, to allow better comparison of data sets with different characteristics.We suggest future studies to properly describe the temporal patterns in fully scientific and measurable terms that do not lead to confusion, such as variability and frequency of reproduction, using robust and fully comparable metrics.

Investigating the potential of Sentinel-1 to detect varying spatial heterogeneity in pasture cover in grasslands

ABSTRACT Selective grazing by livestock may be indicative of a site’s grass species diversity and depending on the grazing intensity; this may or may not promote further diversity. However, the detection of sites with spatial heterogeneity in pasture cover as a manifestation of selective grazing has not yet been investigated using satellite remote sensing. Thus, this study was conducted to address the question; can Sentinel-1 detect spatial heterogeneity induced by livestock grazing in grassy fields? Since Synthetic Aperture Radar (SAR) imaging is noted to be sensitive to vegetation architectural arrangement, this study used Sentinel-1 C-band SAR to detect spatial heterogeneity created by selective livestock grazing. The study examined a range of semivariogram, grey-level co-occurrence matrix (GLCM), and eigenvector-eigenvalue polarimetric decomposition features. The coefficient of variation estimates of the GLCM contrast feature consistently produced the strongest correlation (R 2 = 0.71) with Lloyd’s Patchiness Index and semivariogram sill while the polarimetric scattering entropy (range estimates) produced a significant linear correlation with semivariogram sill (R 2 = 0.55, p < 0.05). Inferably, the GLCM contrast and polarimetric scattering entropy can predict spatial heterogeneity in a grazing environment. This is the first time polarimetric scattering entropy estimated from Sentinel-1 has been used for the detection of spatial heterogeneity in a grazing landscape, which makes this study different from past similar studies. Nonetheless, we recommend the testing of this parameter (polarimetric scattering entropy) with a multitemporal SAR data and encourage future studies to investigate the potential of Sentinel-1 for the detection of spatial distances between grass clumps.

Precision of Three Structures for Saugeye Age Estimation

AbstractWe evaluated the precision of age estimates obtained from sagittal otoliths, scales, and dorsal fin spines from 341 saugeyes (Walleye Sander vitreus × Sauger S. canadensis) collected from six Kansas reservoirs. Between‐reader agreement was greatest for otoliths, followed by dorsal spines and then scales. Coefficient of variation (CV) values for between‐reader comparisons were 1.3–3.1% for otoliths and 13.8–18.2% for dorsal spines. Between‐reader comparisons for scales were the most variable, with CV estimates between 19.9% and 23.1%. Age estimates from otoliths aligned with age estimates from scales more often than with estimates from dorsal spines, although age estimate comparisons between structures were generally variable. Between‐reader agreement for scales and dorsal spines decreased with increasing estimated age; however, agreement for otoliths generally remained high (i.e., &gt;80%) through age 10. Given greater precision relative to other structures, we recommend the use of sectioned otoliths to estimate ages of saugeyes, especially when sacrificing the fish is not a concern.

The reliability of the American Community Survey for injury surveillance

BackgroundTo evaluate the reliability and predictability of 49 socioeconomic indicators constructed from the annual and multiyear American Community Survey (ACS) data cycles for monitoring injury inequalities across the USA.MethodsCross-sectional analysis...

Genetic variation of several bread wheat (Triticum aestivum L.) genotypes based on some morphological traits

The genetic diversity among 56 bread wheat (Triticum aestivum L.) genotypes was evaluated by 18 agronomical traits in the experimental field at Maragheh, Iran. Significant differences among bread wheat genotypes in all of the measured traits i.e. stem diameter, plant height, leaf number, leaf length, leaf width, tiller number, internode length, peduncle length, spike length, floret number, spikelet number, grain number, length of awn, grain diameter, grain length, the number of days to flowering, thousand seed weight and grain yield. The coefficient of variation (CV) was high for grain yield (25.61%), number of tillers per plant (22.06%) and number of grains per spike (21.45). The other remaining traits recorded moderate to low CV estimates from 14.30% in grain number per spike to 4.81% in days to flowering. The largest thousand seed weight was 45.93 g, the lowest thousand seed weight was 26.16 g and the mean thousand seed weight was 37.85 g. The mean performance of grain yield was 5031.2 kg ha-1, the minimum grain yield was 2835.0 kg ha-1 and the maximum grain yield was 7125.3 kg ha-1. Ward’s minimum variance cluster analysis based on squared Euclidian distance on the raw data of 18 agronomic traits clearly separated five clusters. In general, cluster analysis of the 56 genotypes based on the selected agronomic traits was consistent with known information. Our plant materials could be important germplasm resources for enriching the genetic background of commercial cultivars. Such genetic differences of bread wheat traits studied in this investigation can be applied as a new source of variation in other breeding programs and crossing nurseries in breeding program

Psychometric properties of the Fatigue Severity Scale and the Modified Fatigue Impact Scale

ObjectiveFatigue is one of the most common, debilitating and life altering symptoms experienced by those with multiple sclerosis (MS) and has become the focus of therapeutic interventions and clinical rehabilitation. There is limited evidence regarding the psychometric properties and clinical relevance of fatigue outcomes for interpreting the effectiveness of intervention and rehabilitation strategies. This study determined the reliability, precision and clinically important change of the uni-dimensional Fatigue Severity Scale (FSS) and the multi-dimensional Modified Fatigue Impact Scale (MFIS). MethodsThe FSS and MFIS along with physical, psychological and cognitive clinical outcomes were administered to a sample of 82 persons with MS in a clinical research setting on two time points, separated by six months. Intraclass correlation coefficient (ICC) analyses established reliability; standard error of measurement (SEM) and coefficient of variation (CV) determined precision; minimal detectable change (MDC) defined clinically important change. ResultsParticipants varied in type of MS and disability status, with 77% of participants classified as having substantial fatigue, based on the criteria of a mean FSS score ≥4. The MFIS (ICC=0.863) and the FSS (ICC=0.751) had acceptable reliability over six months. Precision was reasonable for both scales (based on SEM and CV estimates) but better for the FSS. MDC estimates were established and were lower for the FSS. ConclusionReliability of the FSS and MFIS falls within acceptable ranges, and precision and clinically important change estimates provide guidelines for interpreting change in scores from these outcomes in clinical research of intervention and rehabilitation approaches for managing fatigue.

Against coefficient of variation for estimation of intraindividual variability with accuracy measures

Previous studies have shown that intraindividual variability ( iV ) in performance is an important indicator of individual’s cognitive functioning and neurological integrity. While most experiments have examined iV of performance using Reaction Time data (RTs), few studies have considered it with accuracy measures (e.g. number / percentage of correct responses). For these two types of measures, intraindividual standard deviation ( iSD ) or intraindividual coefficient of variation ( iCV ; intraindividual standard deviation divided by the individual mean) were used as indicators of iV in performance. However, because accuracy data have a lower and an upper bound (in contrast to RTs), we illustrate both formally and with simulated data, that the iCV cannot be used with accuracy measures. We also show that the coefficient iCV is influenced by the number of items which is an issue when dealing with missing data. We further provide formulas that may help researchers to visualize and correctly interpret their data using any spreadsheet software. The current article finally proposes an alternative coefficient ( ) to examine iV in performance with accuracy measures that shows similar behaviour as does iCV with RTs data.

Contrast magnetic resonance imaging for measurement of cartilage glycosaminoglycan content in dogs: A pilot study

To assess the ability of a contrast-enhanced magnetic resonance imaging (MRI) technique to quantitatively determine glycosaminoglycan content in canine articular cartilage. Fifty-four full-thickness cartilage discs were collected from the femorotibial and scapulohumeral joints of three adult dogs immediately following euthanasia. One set of discs from each dog was analysed for glycosaminoglycan content using a colourimetric laboratory assay. The remaining position-matched set of discs from contralateral limbs underwent pre- and post-contrast gadolinium-enhanced MRI, using repeated saturation recovery pulse sequences which were used to generate calculated T1 maps of the cartilage discs. Linear regression analysis was then performed relating delayed gadolinium-enhanced MRI T1 calculated signal intensity to the cartilage glycosaminoglycan content normalized to DNA content. Repeatability of triplicate measurements was estimated by calculating the coefficient of variation. Mean coefficient of variation estimates for the gadolinium-enhanced MRI T1 signal intensity values for nine sampling sites from three dogs ranged from 5.9% to 7.5%. Gadolinium-enhanced MRI T1 signal intensity was significantly correlated (p <0.05) with normalized glycosaminoglycan content in two dogs (r = 0.79, p = 0.011; r = 0.78, p = 0.048), but not in the third dog (r = 0.53, p = 0.071). Gadolinium-enhanced MRI assessment of cartilage may be predictive of glycosaminoglycan content and therefore offer an in vivo assessment of changes in cartilage characteristics over time. Additional studies appear indicated to determine the reliability and clinical applicability of gadolinium-enhanced MRI in detecting changes in cartilage over time.

Murthy’s Estimator in Unequal Probability Inverse Adaptive Cluster Sampling

This paper derives a Murthy’s unbiased estimator of population total under unequal probability inverse sampling. A general unequal probability inverse sampling is combined with adaptive cluster sampling. An unbiased estimator of population total and its variance estimator are given using Murthy’s approach. The general unequal probability inverse adaptive cluster sampling and general equal probability inverse adaptive cluster sampling are compared using simulation study based on real life data. The results indicate that the general unequal probability inverse adaptive cluster sampling has a small coefficient of variation for estimates compared to equal probability inverse adaptive cluster sampling. When the coefficients of correlation between study variable and probability of selection units increase, the coefficient of variation decreases.

A Reliable Methodology for Quantitative Extraction of Fruit and Vegetable Physiological Amino Acids and Their Subsequent Analysis with Commonly Available HPLC Systems

Many of the extraction and amino acid analysis methodologies currently employed do not provide complete analysis of all the physiological amino acids and biogenic amines. Extraction procedures frequently employ dilute acid which partially converts gln and asn to glu and asp. A commonly used pre-column derivatizing agent, o-phthalaldehyde, does not react with the imino acids, pro and hydroxypro. The purpose of this investigation was to integrate extraction and analysis procedures into a reliable method for measuring the complete physiological amino acid profiles of fruit and vegetables using HPLC instrumentation commonly available to most laboratories. Water extraction of ground, frozen-thawed tissues effected complete recovery of the physiological amino acids as demonstrated by spiking experiments and tissue combination experiments. HPLC of dabsyl derivatives of the free amino acids allowed their quantification in a selection of fruit and vegetables. Physiological amino acid levels were determined for peach, apple, potato, onion, tomato, bell pepper, broccoli, and seven types of cucurbits. The coefficient of variation for estimation of an amino acid level generally fell in the range of 5% to 7%. Because of marked variability in physiological amino acid content as a result of growing conditions, cultural practices, and inherent cultivar differences, comparisons of results with literature values were not possible.

Estimating the rarity of birds and its ecological context in the University of the Philippines Diliman Campus

In this paper we use frequentist (classical) and Bayesian inference to estimate the rarity of birds in the University of the Philippines Diliman campus. Rare species have a detection probability of 1%. As sightings of certain species of birds are extremely rare, a frequentist approach to estimation will often result in overestimates of observation precision. Using McArdle’s rarity and Bayesian inference we estimated the probability of detecting rare species as between 4 to 10%. The Bayesian estimates are lower and may be a better method for estimating rarity. The coefficient of variation (CV) of the frequentist (24%) and Bayesian (25%) estimates are similar suggesting imprecision. Rare species are likely to be detected in areas of campus with common and highly abundant species. This may be an artifact of the fast paced Jokimäki method that was used in surveys of bird abundances. The higher probability of detecting rare species from the suggested 1% cutoff and similar CV estimates are likely due to the small data set used in the estimations and the lack of prior information. The ecological context of our observations is related to the increasing fragmentation of habitat in the campus as a consequence of urbanization.

Could the coefficient of variation (COV) of the corneal endothelium be overestimated when a centre‐dot method is used?

Background: Little has been published on the reliability of estimates of the coefficient of variation (COV) in cell area for human corneal endothelia. The present study compares two methods.Methods: A non‐contact specular micrograph (Topcon SP‐2000P) was obtained from the central region of the corneal endothelium of 20 healthy myopic white European subjects, aged from 32 to 53 years, half of whom were successful long‐term soft contact lens wearers. The captured image file was either assessed using a machine‐based algorithm, in which 25 cells in the middle of the image were marked and their areas reported (designated as ‘centre‐dot’ method) or by a manual method, by which all the cells in the image were outlined on very high magnification prints of the endothelia and the cell areas measured by a manual digitiser in stream mode. The average cell area was used to calculate the endothelial cell density (ECD), while the COV was calculated from the standard deviation (SD) of the cell area measures.Results: Identical mean cell area values were found (392 µm2) with the two methods, a marginally higher ECD estimate (2,594 versus 2,569) with the centre‐dot method (p = NS) but a much higher COV with the centre‐dot method (43.8 versus 29.0 per cent). This highly statistically significant difference in COV (p < 0.001) was seen in both contact lens wearers and non‐contact lens wearers. A Bland‐Altman analysis reveals a bias in the centre‐dot method, especially for the COV estimates, that appears to be linked to erroneous definition of a single large cell domain on any individual image.Conclusions: A centre‐dot method can be reliably used to generate useful data on cell area and ECD but it should be used cautiously for estimates of polymegethism (COV).

Novel Scaled Average Bioequivalence Limits Based on GMR and Variability Considerations

i) To develop novel approaches for the construction of bioequivalence (BE) limits incorporating both the intrasubject variability and the geometric mean ratio (GMR), and ii) to assess the performance of the novel approaches in comparison to several scaled BE procedures and the classic unscaled average BE. Plots of the BE limits or the extreme GMR values accepted as a function of the coefficient of variation (CV) were constructed for published and the developed scaled procedures. Two-period crossover BE investigations with 12, 24, or 36 subjects were simulated with assumptions of a CV 10%, 20%, 30%, or 40%. The decline in the percentage of accepted studies was recorded as the true GMR for the two formulations was raised from 1.00 to 1.50. Acceptance of BE was evaluated by published and the developed scaled procedures, and, for comparison, by the unscaled average BE. Two GMR-dependent BE limits are proposed for the evaluation of average BE: i) BELscG1 with Ln(Upper, Lower BE limit) = +/-[(5 - 4GMR)0.496s + Ln(1.25)], and ii) BELscG2 with Ln(Upper, Lower BE limit) = +/-[(3 - 2GMR)(0.496s + Ln(1.25))], where s is the square root of the intrasubject variance. The range of BE limits becomes narrower as GMR values deviate from unity, and increases with variability. The two new approaches exhibit the highest statistical power at low CV values. At high levels of variability, BELscG1 and BELscG2 show high statistical power, as well as the lowest percentages of acceptance among the scaled methods when GMR = 1.25. The latter becomes more obvious when a large number of subjects is incorporated in the studies. The GMR and CV estimates of the BE study can be used in conjunction with the GMR vs. CV plot for the assessment of average BE. The new approaches, BELscG1 and BELscG2, appear to be highly effective at all levels of variation investigated.

Bias in the Wagner-Nelson estimate of the fraction of drug absorbed.

To examine and quantify bias in the Wagner-Nelson estimate of the fraction of drug absorbed resulting from the estimation error of the elimination rate constant (k), measurement error of the drug concentration, and the truncation error in the area under the curve. Bias in the Wagner-Nelson estimate was derived as a function of post-dosing time (t), k, ratio of absorption rate constant to k (r), and the coefficient of variation for estimates of k (CVk), or CV% for the observed concentration, by assuming a one-compartment model and using an independent estimate of k. The derived functions were used for evaluating the bias with r = 0.5, 3, or 6; k = 0.1 or 0.2; CV, = 0.2 or 0.4; and CV, =0.2 or 0.4; for t = 0 to 30 or 60. Estimation error of k resulted in an upward bias in the Wagner-Nelson estimate that could lead to the estimate of the fraction absorbed being greater than unity. The bias resulting from the estimation error of k inflates the fraction of absorption vs. time profiles mainly in the early post-dosing period. The magnitude of the bias in the Wagner-Nelson estimate resulting from estimation error of k was mainly determined by CV,. The bias in the Wagner-Nelson estimate resulting from to estimation error in k can be dramatically reduced by use of the mean of several independent estimates of k, as in studies for development of an in vivo-in vitro correlation. The truncation error in the area under the curve can introduce a negative bias in the Wagner-Nelson estimate. This can partially offset the bias resulting from estimation error of k in the early post-dosing period. Measurement error of concentration does not introduce bias in the Wagner-Nelson estimate. Estimation error of k results in an upward bias in the Wagner-Nelson estimate, mainly in the early drug absorption phase. The truncation error in AUC can result in a downward bias, which may partially offset the upward bias due to estimation error of k in the early absorption phase. Measurement error of concentration does not introduce bias. The joint effect of estimation error of k and truncation error in AUC can result in a non-monotonic fraction-of-drug-absorbed-vs-time profile. However, only estimation error of k can lead to the Wagner-Nelson estimate of fraction of drug absorbed greater than unity.

In vitro and in vivo comparisons of diaminopimelic acid and purines for estimating protein synthesis in the rumen

Means analyses were used to compare estimates of crude protein (CP) degradation (%), true organic matter (OM) digestion (%), efficiency of microbial synthesis (g N kg −1 OM truly digested) and microbial nitrogen (N) flow (g d −1) using diaminopimelic acid (DAPA) and purines as microbial markers for 12 in vitro and four in vivo experiments. In vitro experiments included 268 determinations and in vivo experiments included 80 determinations of microbial activity by each marker. In vitro estimates of ruminal CP degradation, true OM digestion, efficiency of microbial synthesis and microbial N flow by purines (60.5, 52.4, 33.1 and 1.3) were lower ( P < 0.05) than estimates by DAPA (69.9, 55.0, 36.1 and 1.4). Coefficients of variation of estimates of ruminal CP degradation, true OM digestion, efficiency of microbial synthesis and microbial N flow determined by purines (22.0, 12.4, 17.0 and 22.4) or DAPA (22.2, 12.3, 14.2 and 20.5) were similar for in vitro experiments. In vivo estimates of ruminal CP degradation, true OM digestion and microbial N flow by purines (57.2, 53.1 and 137.2) were lower ( P < 0.05) than estimates by DAPA (65.9, 61.1 and 162.2). Estimates of efficiency of microbial synthesis determined using purines (28.4) and DAPA (27.9) were similar. Coefficients of variation for estimates of ruminal CP degradation, true OM digestion, efficiency of microbia l synthesis and microbial N flow determined by purines (21.4, 23.8, 38.6 and 32.4) and DAPA (16.5, 16.7, 37.3 and 33.9) were similar for in vivo experiments. Estimates of CP degradation exceeded 90% on 26 occasions when DAPA was used as the marker, compared with seven occasions when purines were used. Using purines as the microbial marker resulted in lower microbial activity and similar coefficients of variation compared with DAPA. Unrealistic values of CP degradation were observed more frequently using DAPA as the microbial marker.

Assessment of the reliability of calculations of the coefficient of variation for normal and polymegethous human corneal endothelium.

In endothelial morphometry, uncertainty exists concerning how many cells should be measured. A study was undertaken to calculate mean cell area and coefficient of variation (COV) of cell areas using different numbers of cells from photo-slitlamp pictures and published micrographs. Groups of 65, 95, or 165 tesselated cells were measured and area and COV values calculated in progressive sets of 5 cells; each pair of values was compared to that obtained using all cells in each group. The results show that, for both normal (homomegethous) and irregular (polymegethous) endothelia, even cell counts as low as 50 cells can usually provide average cell area values that are within 1 to 2% of the values estimated from larger groups of cells. A similar reliability was observed for estimates of COV for normal endothelia. However, for polymegethous endothelia, even with 100 cells analyzed, the estimates of COV generally only approached a +/- 4% reliability. This uncertainty in COV estimates should be considered in both comparative studies and in regression analyses of COV changes over time or other variables.

Spatial variation in black cottonwood (Populustrichocarpa) foliar nutrient concentrations at seven alluvial sites in coastal British Columbia

Spatial variability of 13 foliar nutrients was assessed within and between individual black cottonwood (Populustrichocarpa Torr. &amp; Gray ex Hook.) trees at seven alluvial sites in coastal British Columbia to help in the development of foliar sampling protocol for the determination of black cottonwood nutrient status. Foliar nutrients were divided into two groups based on concentration differences in foliage samples from within black cottonwood canopies: group 1 included N, P, K, S, SO4-S, Cu, and possibly Mg and B, mostly macronutrients that are mobile in the phloem; group 2 included mostly immobile micronutrients (Mn, Zn, Ca, and possibly Fe and active Fe, although these last two might best be included in a third group). Group 1 nutrient concentrations were significantly higher in the upper canopy, while group 2 nutrient concentrations were higher in the lower canopy at the two sites studied. Numbers of samples required for several combinations of accuracy (including both α and β significance) and precision were calculated based on mean coefficient of variation estimates from the seven stands. Fifteen foliar samples collected from the most recently matured late leaves on lateral branches in the top one-third of the canopy of dominant or codominant black cottonwood trees will estimate the mean with an allowable error of 10% at an α significance level of 0.95 for most macronutrients (N, P, K, S, Mg, and Ca). Including a β significance level of 0.95 at this level of precision and α significance would increase the number of required samples to at least 20 for these nutrients. Between 21 and 56 samples would be required to estimate the mean concentrations of SO4-S, Cu, Zn, Mn, B, active Fe, and Fe at the same levels of accuracy and precision.