Estimation Of Correlation Coefficient Research Articles

Estimate of Genotypic and Phenotypic Correlation and Path Coefficient in Brinjal (Solanum melongena L)

The significant positive correlation among phenotypic and genotypic performance, as well as path correlation of crops, contributes to the selection of superior cultivars. Based on the essential relevance of these estimations, it was used in our research. The current research was carried out during autumn winter season 2021-2022 with the aim of to estimate correlation coefficient among the growth and yield attribute and to elucidate the direct and indirect effects of different traits on yield through path coefficient analysis. The experimental material for the study consisted of 40 genotypes including one check (KS-224), laid in Randomized Complete Block Design with three replications. Observations were recorded on twelve quantitative characters. The most important trait, total fruit yield per plant had exhibited highly significant and positive phenotypic correlation with average fruit weight (0.662), number of fruits per plant (0.476), fruit circumference (0.394) and fruit polar length (0.392). Average fruit weight, number of fruits per plant, fruit circumference and fruit polar length were found significantly and positively correlated among themselves. The genotypic direct and indirect effects of most of the traits were similar in nature and higher in magnitude than the phenotypic direct and indirect effect. The higher magnitude of positive direct effect on total fruit yield was exerted by average fruit weight (0.793), number of fruits per plant (0.684) and fruit circumference (0.046). While, negative direct effect on total fruit yield per plant was exerted by days to 50 per cent flowering (-0.093), calyx length (-0.052) and pedicel length (-0.022). Thus, it can be inferred from the data above that selecting for these qualities will effectively enhance the crop for increased production and contributing traits.

A Weighted Adaptive Range-Averaging Technique to Improve the Precision Consistency of Polarimetric Variable Fields

Abstract The two main metrics for the performance evaluation of radar-variable estimators are the bias and standard deviation (SD) of estimates. Depending on the estimator properties, the bias may increase as the signal-to-noise ratio (SNR) decreases. The standard deviation, however, always rises as the SNR becomes smaller. For instance, if estimates are computed from 16 samples (typically used for WSR-88D surveillance scans) using a rectangular data window and the maximum unambiguous velocity is ∼9 m s−1, the standard deviation of reflectivity estimates increases 1.6 times as the SNR drops from 20 to 2 dB. But for estimates of differential reflectivity, differential phase, and copolar correlation coefficient, SDs increase ∼6.7, ∼6, and ∼54 times, respectively. Hence, this effect impacts the polarimetric variables substantially more than the spectral moments. Additionally, the polarimetric variable SD is also sensitive to the correlation between signals in horizontal and vertical channels leading to reduced data quality in the regions where the correlation coefficient is low. Such increases in the variability of estimates are observable in the fields of dual polarization variables as an increased spatial inhomogeneity (or noisiness) in the areas where radar echoes exhibit low-to-moderate SNRs and/or decreased correlation coefficient. These effects can obscure the visual identification of weather features as well as adversely impact algorithms. Herein, a novel method that applies variable smoothing in the range where the smoothing intensity depends on the SDs of estimates is presented. It applies little or no range averaging in the regions where data SDs are deemed adequate while using more aggressive smoothing in areas where data appear noisy. Significance Statement The noisiness in the fields of polarimetric variables is an issue that has plagued dual-polarization weather radars since their inception. This is because standard deviations of polarimetric variable estimates increase significantly more with the reduction in SNR than those of spectral moment estimates. A typical mitigation approach that indiscriminately averages a fixed number of estimates in the range may lead to unnecessary loss of range resolution in regions where data appearance is satisfactory. Further, such an approach can be inadequate in regions with a high variability of estimates leading to insufficient enhancement of weather feature visibility. In this study, a method that mitigates these issues is proposed.

Utilizing Buttock Measurements for Estimating Body Weight: Exploring Buttock Width and Popliteal Length for Ergonomic Design

This study explores the potential of utilizing buttock measurements, specifically buttock width and bottom popliteal length, as reliable indicators for estimating human body weight. Recognizing the increasing demand for accurate and accessible methods in various fields, author delves into the relationships between these lower body dimensions and overall body mass. The research evaluated 700 young adults, evenly split between 350 males and 350 females, utilizing random snowball sampling techniques from four local governments (Abeokuta South, Abeokuta North, Odeda and Ewekoro) areas of Ogun State, South Western Nigeria with participants aged between 19 and 27years The research centered on assessing human body weight (HBW), buttock width (BW), and bottom popliteal length (BPL) with all measurements documented in centimeters. Data analysis involved utilizing Statistical Package for Social Sciences software version 21.0, for computation of average mean values, standard deviation, coefficient of determination (r2), correlation coefficient (r), and standard error of estimates (SEE). Additionally, linear regression analysis was employed to formulate the model equation for determining HBW, in relation to BW, and BPL. The study provides an accuracy and applicability of anthropometric prediction of HBW and foundation for the development of practical methods with diverse applications, ranging from healthcare assessments to ergonomic design.

Development and validation of an overuse injury questionnaire for youth athletes: The Youth Overuse Injury Questionnaire

ObjectiveTo develop and validate the Youth Overuse Injury Questionnaire (YOvIQ). DesignA cross-sectional study. SettingOnline platforms. ParticipantsTwo content experts (in sports injury epidemiology and in sports science and medicine) and seven end-users (youth volleyball athletes) provided feedback during development of the YOvIQ. 227 competitive youth athletes across 14 different sports assessed the psychometric properties of the YOvIQ. Main outcome measuresParticipants completed both YOvIQ and the Oslo Sports Trauma Research Centre Overuse Injury Questionnaire (OSTRC-O2) for anatomical areas of the shoulder, elbow, lower back, knee, and ankle/foot. Validity was assessed via convergent validity. Reliability was assessed using internal consistency estimation and interclass correlation coefficient. ResultsFollowing feedback from content experts, examples and quantitative symbolization were added to the options in YOvIQ, with positive feedback from end-users. Convergent validity between YOvIQ and the OSTRC-O2 was demonstrated with non-significant differences (P ≥ .05) and significant correlations (P < 0.001) for prevalence and severity scores. YOvIQ demonstrated internal consistency for prevalence (Cronbach's alpha coefficient >0.70) and moderate-to-good reliability for severity scores (ICC: 0.51 to 0.88) for shoulder, lower back, and knee. ConclusionsThe YOvIQ is a valid and reliable instrument to identify overuse injuries to the shoulder, lower back, and knee in youth athletes.

Noninvasive Assessment of Intracranial Pressure: Deformability Index as an Adjunct to Optic Nerve Sheath Diameter to Increase Diagnostic Ability.

Today, invasive intracranial pressure (ICP) measurement remains the standard, but its invasiveness limits availability. Here, we evaluate a novel ultrasound-based optic nerve sheath parameter called the deformability index (DI) and its ability to assess ICP noninvasively. Furthermore, we ask whether combining DI with optic nerve sheath diameter (ONSD), a more established parameter, results in increased diagnostic ability, as compared to using ONSD alone. We prospectively included adult patients with traumatic brain injury with invasive ICP monitoring, which served as the reference measurement. Ultrasound images and videos of the optic nerve sheath were acquired. ONSD was measured at the bedside, whereas DI was calculated by semiautomated postprocessing of ultrasound videos. Correlations of ONSD and DI to ICP were explored, and a linear regression model combining ONSD and DI was compared to a linear regression model using ONSD alone. Ability of the noninvasive parameters to distinguish dichotomized ICP was evaluated using receiver operating characteristic curves, and a logistic regression model combining ONSD and DI was compared to a logistic regression model using ONSD alone. Forty-four ultrasound examinations were performed in 26 patients. Both DI (R = - 0.28; 95% confidence interval [CI] R < - 0.03; p = 0.03) and ONSD (R = 0.45; 95% CI R > 0.23; p < 0.01) correlated with ICP. When including both parameters in a combined model, the estimated correlation coefficient increased (R = 0.51; 95% CI R > 0.30; p < 0.01), compared to using ONSD alone, but the model improvement did not reach statistical significance (p = 0.09). Both DI (area under the curve [AUC] 0.69, 95% CI 0.53-0.83) and ONSD (AUC 0.72, 95% CI 0.56-0.86) displayed ability to distinguish ICP dichotomized at ICP ≥ 15mm Hg. When using both parameters in a combined model, AUC increased (0.80, 95% CI 0.63-0.90), and the model improvement was statistically significant (p = 0.02). Combining ONSD with DI holds the potential of increasing the ability of optic nerve sheath parameters in the noninvasive assessment of ICP, compared to using ONSD alone, and further study of DI is warranted.

ПРЕИМУЩЕСТВА И НЕДОСТАТКИ СИСТЕМЫ ЭЛЕКТРОННЫХ РЕЦЕПТОВ С ТОЧКИ ЗРЕНИЯ ФАРМАЦЕВТИЧЕСКИХ РАБОТНИКОВ

Various electronic prescription systems are being developed both in Russia and around the world. For their effective implementation, it is necessary not only to bring regulatory and legal acts in line with modern technological innovations, but also to take into account the point of view of the users of such systems - patients, pharmacists and doctors. In order to identify the opinion of pharmacists about the current state of the system and their satisfaction, a survey was conducted. For this purpose, we used a questionnaire, tested for reliability (Cronbach's alpha measurement) and validity (Pearson correlation coefficient estimation). The results of the questionnaire, literature review, regulatory and legal documents allowed us to conduct a PEST-analysis with the establishment of political, economic, socio-cultural and technological factors that influence the system, as well as a SWOT-analysis with the identification of strengths, weaknesses, opportunities and threats of the system. Its advantages, with which most of the interviewed specialists agree, include reduction of medical errors in prescribing, increased protection of users' personal data, contribution to the fight against fake prescriptions. Strengths include simplified pharmaceutical review of prescriptions, no need to analyze doctors' handwriting and simplified dispensing of medicines. Weaknesses include various technical failures, lack of or insufficient training. It is important to note that more than half (54%) of the surveyed pharmacists encounter difficulties when working with the system. In addition, recommendations for the improvement of this system were proposed, taking into account the data of sociological research, PEST-analysis and SWOT-analysis.

Meta-Analytic Review of Temperamental Correlates of the Five-Factor Model and Hierarchical Taxonomy of Psychopathology Domains.

There is little and heterogeneous knowledge on the links between the temperamental predispositions of psychopathology and the contemporary dimensional models of psychopathology, such as the Hierarchical Taxonomy of Psychopathology (HiTOP) classification system, which can be aligned with the five-factor model (FFM) of personality. This meta-analysis seeks to expand the temperamental theoretical basis of the HiTOP model by incorporating associations of temperament traits of two temperamental theories measured, respectively, by the Temperament and Character Inventory (TCI) and the Temperament Evaluation of Memphis, Pisa, Paris, and San Diego Autoquestionnaire (TEMPS-A) with (a) the FFM's personality domains and (b) HiTOP's five psychopathological spectra. A systematic search was done on Web of Science, Scopus, PubMed, ProQuest, Cochrane Database, and Google Scholar for all articles published in English from January 1990 to August 2020. Because of heterogeneity in the results of almost 70% of studies, pooled estimates of correlation coefficients were calculated using the random-effects method. Risk of bias (low-quality studies) and publication bias are reported. The pooled correlations obtained from the analysis of 35 studies showed that the temperamental profile associated with each FFM domain and HiTOP spectra is distinct. Specifically, TCI-harm avoidance (HA) and all TEMPS temperaments were more strongly related to neuroticism/internalizing, extraversion/low detachment, and conscientiousness/disinhibition. In contrast, TCI-novelty seeking was more strongly related to both disinhibited/antagonistic externalizing and thought disorder. A large body of research supports maladaptive variants of all FFM domains and some psychopathological spectra of HiTOP related to the abnormal-range temperaments.

Genetic evaluation of crossbred Bos indicus cow temperament at parturition.

Cow temperament at parturition may be mostly a measure of aggressiveness. The heritability of cow temperament at parturition in Bos taurus cows has been reported to be low. The objectives of this study were to estimate the heritability of cow temperament at parturition, conduct a genome-wide association analysis of cow temperament at the time of parturition, and estimate the correspondence of cow temperament at the time of parturition with cow productive performance and early-life temperament traits in Bos indicus crossbreds. Cow temperament was assessed from 1 to 5 indicating increasing levels of aggressiveness of cows (937 cows and 4,337 parturitions) from 2005 to 2022. Estimates of heritability and repeatability were 0.12 ± 0.024 and 0.24 ± 0.018. The estimates of proportion of phenotypic variance were 0.13 ± 0.019 and 0.02 ± 0.011 for permanent and maternal permanent environmental components, respectively. Estimates of heritability for maximum lifetime temperament score and proportions of temperament scores >1 were 0.18 ± 0.07 and 0.13 ± 0.072. Within cycles (generations), 2-yr-old cows had lower temperament score means than cows in most other age categories. There were low to moderate positive estimates of unadjusted correlation coefficients (r = 0.22 to 0.29; P < 0.05) of unadjusted temperament score with temperament measured on the same females when they were 8 mo old. There were low to moderate positive estimates of correlation coefficients (r = 0.09 to 0.37; P < 0.05) of unadjusted temperament score with calving rate, weaning rate, weaning weight per cow exposed, and weaning weight per 454kg cow weight at weaning. Cows with the lowest temperament score had lower (P < 0.05) calving and weaning rate than cows in other temperament categories. Within 3 of 5 cycles, cows with the lowest temperament score (totally docile) had lower (P < 0.05) weaning weight per cow exposed than cows in other temperament categories. There were 2 SNP on BTA 4 associated with maximum lifetime temperament score (FDR < 0.05). The non-genetic influence of a cow's mother was documented in her own temperament measured at the time of calving; this may be a consequence of learned behavior. Less aggressiveness displayed by cows at the time of calving may be accompanied by lower reproductive and maternal performance.

Analysing cluster randomised controlled trials using GLMM, GEE1, GEE2, and QIF: results from four case studies

BackgroundUsing four case studies, we aim to provide practical guidance and recommendations for the analysis of cluster randomised controlled trials.MethodsFour modelling approaches (Generalized Linear Mixed Models with parameters estimated by maximum likelihood/restricted maximum likelihood; Generalized Linear Models with parameters estimated by Generalized Estimating Equations (1st order or second order) and Quadratic Inference Function, for analysing correlated individual participant level outcomes in cluster randomised controlled trials were identified after we reviewed the literature. We systematically searched the online bibliography databases of MEDLINE, EMBASE, PsycINFO (via OVID), CINAHL (via EBSCO), and SCOPUS. We identified the above-mentioned four statistical analytical approaches and applied them to four case studies of cluster randomised controlled trials with the number of clusters ranging from 10 to 100, and individual participants ranging from 748 to 9,207. Results were obtained for both continuous and binary outcomes using R and SAS statistical packages.ResultsThe intracluster correlation coefficient (ICC) estimates for the case studies were less than 0.05 and are consistent with the observed ICC values commonly reported in primary care and community-based cluster randomised controlled trials. In most cases, the four methods produced similar results. However, in a few analyses, quadratic inference function produced different results compared to the generalized linear mixed model, first-order generalized estimating equations, and second-order generalized estimating equations, especially in trials with small to moderate numbers of clusters.ConclusionThis paper demonstrates the analysis of cluster randomised controlled trials with four modelling approaches. The results obtained were similar in most cases, however, for trials with few clusters we do recommend that the quadratic inference function should be used with caution, and where possible a small sample correction should be used. The generalisability of our results is limited to studies with similar features to our case studies, for example, studies with a similar-sized ICC. It is important to conduct simulation studies to comprehensively evaluate the performance of the four modelling approaches.

Estimation of correlation coefficient with monotone transformation and multiplicative distortions

This article studies the estimation of the correlation coefficient between unobserved variables of interest. These unobservable variables, mixed with some known monotone link functions, are distorted in multiplicative fashion by an observed confounding variable. We propose four calibration methods for the unobserved variables and the estimation of the correlation coefficient. Theoretical results show that the proposed estimators of correlation coefficient can be asymptotically efficient as if there are no distortions in the variables. Moreover, we suggest an asymptotic normal approximation and an empirical likelihood-based statistic to construct the confidence intervals. We conduct Monte Carlo simulation experiments to examine the performance of the proposed estimators. These methods are applied to analyze a real dataset for an illustration.

The level of agreement between the numerical rating scale and visual analogue scale for assessing pain intensity in adults with chronic pain.

The numerical rating scale and visual analogue scale are used to quantify pain intensity. However, it has not yet been explored whether these scores are interchangeable in adults with chronic pain. Data from the prospective multicentre cross-sectional INTERVAL study were used to evaluate the one-dimensionality and agreement between numerical rating scale scores and visual analogue scale scores in adults with chronic pain. Pain intensity scores using the numerical rating scale and visual analogue scale were provided by 366 patients with chronic pain for current, average, minimal and maximal pain. To evaluate whether pain intensity scales are completed in accordance with each other, the proportion of patients who satisfied the following condition was calculated: minimal pain intensity ≤ maximal pain intensity. A factor analysis confirmed the one-dimensionality of the pain measures. A significant difference was found between numerical rating scale and visual analogue scale scores for average, current, minimum and maximum pain. Intra-class correlation coefficient estimates ranged from 0.739 to 0.858 and all measures failed to show sufficient and acceptable agreement at the 95% level. The strength of agreement between pain severity categories was classified as 'moderate' for average and minimal pain and 'substantial' for current and maximal pain. The proportion of patients who scored minimal pain ≤ maximal pain was 97.5% for the numerical rating scale and 89.5% for the visual analogue scale. This study failed to show an acceptable agreement between the numerical rating scale and visual analogue scale when pain intensity was rated by adults with chronic pain, despite showing both scales measure the same information.

Establishing the interpretability and utility of the 4-item BriefPCS

To reduce the patient burden associated with completing the 13-item Pain Catastrophizing Scale (PCS), the 4-item “BriefPCS” was developed. To date, no crosswalk has been developed that associates scores on the BriefPCS with PCS scores. Further, no study has compared the use of BriefPCS and PCS scores in a randomized clinical trial (RCT). We aimed to: (1) establish the interpretability of BriefPCS scores in reference to PCS scores, (2) compare the concurrent validity between the BriefPCS and PCS, and (3) asssess the use of BriefPCS in an RCT. First, we conducted equipercentile linking, created a crosswalk that associated scores of BriefPCS with PCS, and calculated differences between PCS and crosswalked PCS scores. Secondly, we compared Bootstrap correlation coefficients between PCS and self-reported measures of other domains. Lastly, we compared results from an RCT using BriefPCS scores versus PCS scores. Findings indicated that the correlation coefficient estimates with the BriefPCS and PCS scores were not significantly different. BriefPCS and PCS scores had similar ability to detect treatment-related changes. The BriefPCS scores validly, reliably, and accurately distinguish levels of pain catastrophizing. Additionally, the BriefPCS scores are sensitive to changes after behavioral interventions, with less respondent burden compared to the PCS scores.

Estimation of genetic variability and correlation coefficients of different salinity levels in mungbean genotypes

For this study eight mungbean genotypes viz., ADT 2, BM-2002-1, ML 5, AKM 4, Vishal, Vamban, TARM 1 and Utkarsh were used. Observation were taken on seven seedling characters and 7 quantitative characters. Statistical analysis of the seedling and quantitative characters showed that the PCV was higher than that of GCV for all the characters studied. Highest GCV and PCV were expressed by seedling shoot dry weight at 6 dSm-1 salinity level followed by seedling shoot fresh weight at 6 dSm-1, indicating that variation among the genotypes was highest for these traits. The PCV and GCV values were lowest in germination percentage followed by the shoot length at control. Among the growth characters heritability (broad sense) was found to range from 41.57 % to 100 % in control, while in salinity levels broad sense heritability ranged from 50 % to 100 %. Under control, heritability was high for all characters except for germination percentage, shoot length and plant height. While in salinity condition, it was high for all characters except for number of pods/plant at 6 dsm-1 salinity level. The genetic advance was high in nature only for the germination percentage whereas, the remaining character revealed low GA estimates. The maximum genetic advance in percent of mean (GAMP) was obtained for seedling shoot dry weight followed by seedling root dry weight at 6 dsm-1 and the lowest was for plant height followed by germination percentage at control. The study revealed that all the 14 characters were positively correlated with each other. For all the characters, the genotypic correlation was at higher level than the phenotypic correlation. Four elite genotypes were found to be superior based on the mean performance namely Utkarsh, TARM 1, Vamban and Vishal among the various levels of salinity.

Grounding the economic selection index for evaluation and selection of dairy cattle

The aim of the research was to develop a selection index for the evaluation and selection of dairy cattle for increasing milk production and reproductive traits. Materials of the research were data on milk production and reproduction of cows of the Ukrainian Black-and-White dairy breed in commercial farm in Kharkiv region. Studies showed that there was a certain antagonism between milk productivity and reproduction of the Ukrainian Black-and-White dairy cow. The coefficients of phenotypic correlation between milk yield, fat and protein yield and the days open ranged from +0.284 to +0.293. Selection indexes were built, which included protein, fat yield, and days open. The developed selection indexes were characterized by a high relationship with the protein yield (α&lt;0.001), much lower – with the fat yield (α&lt;0.05), while the relationship of the selection indexes with the days open was almost absent. The calculated estimates of correlation and regression coefficients made possible to predict correlated responses of milk production and reproduction traits on selection index. The results showed that the developed selection indexes allow increase the milk production of cows and at the same time to prevent decrease in the level of reproduction.

Phenological Changes of Woody Plants in the Southern and Northern Regions of Nanling Mountains and Their Relationship with Climatic Factors

In addressing the challenges posed by the implications of climate change, understanding the phenological variations of woody plants has become a pivotal research topic. This research centers on the phenological shifts of woody plants and their connections with climatic factors in the southern and northern regions of the Nanling Mountains, which serve as the boundary between the north subtropical climate zone and the south subtropical climate zone in South China. The data were gathered through extensive manual observations conducted at four plant phenology observation stations (Ganxian, Foshan, Guilin, and Changsha) spanning different periods from 1963 to 2008. The study scrutinized four widely distributed woody plant species in the research area, specifically C. mollissima, P. fortunei, M. azedarach, and M. grandiflora. The analytical methods utilized were linear trend estimation and Pearson correlation coefficient analyses. The principal findings were as follows: (i) over the past several decades, the phenological stages of woody plants in the southern region consistently preceded those in the northern region with variations ranging from 2 to 38 days; (ii) an advancing trend of 0.1 to 2 days per decade was discerned in the phenological stages of all woody plants in the southern region; (iii) within the same geographic region, distinct species exhibited varying sensitivities to climatic factors, and M. azedarach demonstrated a particularly high sensitivity to climate fluctuations affecting phenological stages; and (iv) different climatic factors exerted distinct influences on individual plant species. Notably, temperature emerged as the primary driver of phenological changes, which was supported by a significant negative correlation between the phenological stages of the studied plants and spring temperatures. This study contributes to our understanding of the effects of climate change on plant phenology and offers valuable insights to guide ecological conservation and management strategies within the region.

The degree of food processing contributes to sugar intakes in families with preschool-aged children

Evidence implicates ultra-processed food intake as a major contributor of excess dietary sugars. However, little research exists on the relationship between the degree of food processing and sugar intake in families with young children. We investigated associations between the degree of food processing and sugar intake (total and free sugars) in Canadian preschool-aged children and parents. This cross-sectional study of 242 families included preschool-aged children (n=267) and parents (n=365) participating in the Guelph Family Health Study. Dietary intake was assessed via the web-based Automated Self-Administered 24-h Dietary Assessment Tool (ASA24-Canada-2016) and classified according to the NOVA Food Classification System including, unprocessed or minimally processed foods, processed culinary ingredients, processed foods and ultra-processed foods. Linear regression models with generalized estimating equations were used to examine associations between the energy contribution of each NOVA classification category and sugar intake (% kcal of total and free sugars). Pearson correlation coefficient estimates were used to assess dietary relationships between parents and children. Ultra-processed foods were the greatest source of energy (44.3%) and energy from total (8.7%) and free sugars (7.3%) in the parents' diets, and the greatest source of energy (41.3%) and energy from free sugars (7.6%) in the children's diet. Ultra-processed food intake was positively associated with sugar intake in parents (total sugars: B=0.05, 95% CI: 0.02-0.09, p=0.01; free sugars: B=0.11, 95% CI: 0.08-0.15, p<0.001) and children (total sugars: B=0.10, 95% CI: 0.04-0.16, p=0.001; free sugars: B=0.16, 95% CI: 0.12-0.21, p<0.001). Unprocessed or minimally processed food intake was negatively associated with free sugar intake in parents (B=-0.08, 95% CI:-0.12 to-0.05, p<0.001) and children (B=-0.15, 95% CI:-0.19 to-0.10, p<0.001). Weak correlations were found between parents and children for processed culinary ingredients and ultra-processed processed food intake (p<0.001). This study highlights the associations between degree of food processing and sugar intake in parents and children, whereby ultra-processed foods were positively, and unprocessed or minimally processed foods were negatively, associated with sugar intake. These are important considerations in the development of policy and recommendations for foods to potentially promote or limit.

Estimation of Variability, Correlation Coefficient and Path Analysis in Improved Restorer Lines of Rice (Oryza sativa L.)

The present investigation was conducted to estimate genetic variability parameters such as genotypic coefficient of variation (GCV), phenotypic coefficient of variation (PCV), heritability (h2) and genetic advance (GA) along with correlations and path coefficients from data collected on 40 F4-F5 population derived from a cross between aerobic restorer AR 9-18 and blast resistant donor MSM 1212 possessing Pi54. Analysis of variance indicated significant differences among the genotypes for all the characters studied. Moderate GCV and PCV was observed for number of productive tillers per plant, number of grains per panicle, per day productivity and single plant yield. High heritability coupled with high genetic advance as percent of mean were observed for number of productive tillers per plant, number of grains per panicle, per day productivity and single plant yield, whereas high heritability coupled with moderate genetic advance as percent of mean were observed for panicle length, spikelet fertility, thousand grain weight and plant height. Grain yield per plant showed positive correlation with per day productivity, days to 50% flowering, panicle length, number of productive tillers per plant, thousand grain weight and spikelet fertility, while, negative association with number of grains per panicle and plant height. The trait per day productivity had highest direct effect on single plant yield followed by days to 50% flowering, panicle length, number of productive tillers per plant, thousand grain weight, spikelet fertility (%). Hence, per day productivity and number of productive tillers per plant are identified as key traits for developing high yielding genotypes of rice for future breeding programme.

Estimation of Genetic Variability, Correlation and Path Analysis for Yield and Some Yield Contributing Traits in Bread Wheat (Triticum aestivum L.)

A study was conducted at the Student Instruction Farm, Chandra Shekhar Azad University of Agriculture and Technology, Kanpur, during the rabi season of 2022–2023, to estimate the genetic variability, correlation, and path coefficient analysis of yield and its contributing traits in cross combination. Ten wheat cultivars were grown in a randomized block design with three replications. The analysis of variance revealed that the treatments were highly significant for all the characters. The higher magnitudes of genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) were recorded for grain yield, biological yield, harvest index and plant height. The high heritability in broad sense was estimated for all the characters except for day to 50% heading, flag leaf area (cm2), number of leaves/main tiller, number of spikelets/ear and protein content (%).A high value of heritability suggests that it could be due to a higher contribution of genotypic components. High heritability associated with high genetic advantage as a percentage of the mean was found for plant height, harvest index, biological yield, and grain yield, indicating a predominance of additive gene action in the inheritance of these traits. The estimated correlation coefficients showed high direct genotypic and phenotypic correlations for days to 50% flowering, days to maturity, plant height, productive tillers/plant, test weight, biological yield, and harvest index. In contrast, flag leaf area (cm2), number of leaves/main picks, number of kernels/spike, and seed hardiness were negatively correlated with grain yield. Path analysis showed that biological yield had the largest direct positive effect on grain yield, followed by harvest index, ear length, plant height, and days to 50%, indicating that these factors were the largest contributors to grain yield.

Familial Correlation and Heritability of Hand Grip Strength in Korean Adults (Korea National Health and Nutrition Examination Survey 2014 to 2019).

The onset and progression of sarcopenia are highly variable among individuals owing to genetic and environmental factors. However, there are a limited number of studies measuring the heritability of muscle strength in large numbers of parent-adult offspring pairs. We aimed to investigate the familial correlation and heritability of hand grip strength (HGS) among Korean adults. This family-based cohort study on data from the Korea National Health and Nutrition Examination Survey (2014 to 2019) included 5,004 Koreans aged ≥19 years from 1,527 families. HGS was measured using a digital grip strength dynamometer. Familial correlations of HGS were calculated in different pairs of relatives. Variance component methods were used to estimate heritability. The heritability estimate of HGS among Korean adults was 0.154 (standard error, 0.066). Correlation coefficient estimates for HGS between parent-offspring, sibling, and spouse pairs were significant at 0.07, 0.10, and 0.23 (P<0.001, P=0.041, and P<0.001, respectively). The total variance in the HGS phenotype was explained by additive genetic (15.4%), shared environmental (11.0%), and unique environmental (73.6%) influences. The odds of weak HGS significantly increased in the offspring of parents with weak HGS (odds ratio [OR], 1.69-3.10; P=0.027-0.038), especially in daughters (OR, 2.04-4.64; P=0.029-0.034). HGS exhibits a familial correlation and significant heritable tendency in Korean adults. Therefore, Asian adults, especially women, who have parents with weak HGS, need to pay special attention to their muscle health with the help of healthy environmental stimuli.

Iteratively Reweighted Least Squares Method for Estimating Polyserial and Polychoric Correlation Coefficients

An iteratively reweighted least squares (IRLS) method is proposed for the estimation of polyserial and polychoric correlation coefficients in this article. It calculates the slopes in a series of weighted linear regression models fitting on conditional expected values. For polyserial correlation, conditional expectations of the latent predictor is derived from the observed ordinal categorical variable, and the regression coefficient is obtained with the weighted least squares method. In estimating polychoric correlation coefficient, conditional expectations of the response variable and the predictor are updated in turns. Standard errors of the estimators are obtained using the delta method based on data summaries instead of the whole data. Conditional univariate normal distribution is exploited and a single integral is numerically evaluated in the proposed algorithm, comparing to the double integral computed numerically based on the bivariate normal distribution in the traditional maximum likelihood (ML) approaches. This renders the new algorithm very fast in the estimation of both polyserial and polychoric correlation coefficients. Thorough simulation studies are conducted to compare the performances of the proposed method with the classical ML methods. Real data analyses illustrate the advantage of the new method in computing speed. Supplementary materials for this article are available online.