Genotype plus genotype by-environment interaction biplot and genetic diversity analyses on multi-environment trials data of yield and technological traits of cotton cultivars

ABSTRACT: Understanding the genetic diversity and overcoming genotype-by-environment interaction issues is an essential step in breeding programs that aims to improve the performance of desirable traits. This study estimated genetic diversity and applied genotype + genotype-by-environment (GGE) biplot analyses in cotton genotypes. Twelve genotypes were evaluated for fiber yield, fiber length, fiber strength, and micronaire. Estimation of variance components and genetic parameters was made through restricted maximum likelihood and the prediction of genotypic values was made through best linear unbiased prediction. The modified Tocher and principal component analysis (PCA) methods, were used to quantify genetic diversity among genotypes. GGE biplot was performed to find the best genotypes regarding adaptability and stability. The Tocher technique and PCA allowed for the formation of clusters of similar genotypes based on a multivariate framework. The GGE biplot indicated that the genotypes IMACV 690 and IMA08 WS were highly adaptable and stable for the main traits in cotton. The cross between the genotype IMACV 690 and IMA08 WS is the most recommended to increase the performance of the main traits in cotton crops.

Trajectories of Energy Intake Distribution and Risk of Dyslipidemia: Findings from the China Health and Nutrition Survey (1991–2018)

Few studies have examined the secular trend of energy intake distribution. This study aims to describe trajectories of energy intake distribution and determine their association with dyslipidemia risk. Data of 2843 adult participants from the China Health and Nutrition Survey (CHNS) were analyzed. Trajectory groups of energy intake distribution were identified by multi-trajectory model over 27 years. Multilevel mixed-effects modified Poisson regression with robust estimation of variance was used to calculate risk ratio for incident dyslipidemia in a 9-year follow-up. Four trajectory groups were identified: “Energy evenly distributed group” (Group 1), “Lunch and dinner energy dominant group” (Group 2), “Dinner energy dominant group” (Group 3), “breakfast and dinner energy dominant group” (Group 4). Compared with Group 1, Group 3 was associated with higher risk of dyslipidemia (RR = 1.48, 95% CI = 1.26, 1.75), hypercholesterolemia (RR = 1.96, 95% CI = 1.37, 2.81) and high low-density lipoproteins cholesterols (LDL-C) (RR = 2.41, 95% CI = 1.82, 3.20). A U-shape was observed between cumulative average proportion of dinner energy and dyslipidemia risk (p for non-linear = 0.01), with stronger relationship at 40% and above. Energy intake distribution characterized by higher proportion of dinner energy, especially over 40% was associated with higher dyslipidemia risk in Chinese adults.

Genetic Parameters for First Lactation and Lifetime Traits of Nili-Ravi Buffaloes

The data on first lactation and lifetime performance records of 501 Nili-Ravi were collected for a period from 1983 to 2017 (35 years) maintained at ICAR-Central Institute for Research on Buffaloes, Sub-Campus, Nabha, Punjab. The data were analyzed to calculate heritability, genetic and phenotypic correlation for first lactation traits, viz., Age at First Calving (AFC), First Lactation Total Milk Yield (FLTMY), First Lactation Standard (305 days or less) Milk Yield (FLSMY), First Peak Milk Yield (FPY), First Lactation Length (FLL), First Dry Period (FDP), First Service Period (FSP) and First Calving Interval (FCI), Herd Life (HL), Productive Life (PL), Productive Days (PD), Unproductive Days (UD), Breeding Efficiency (BE), Total Lifetime Milk Yield (Total LTMY), Standard Lifetime Milk Yield (Standard LTMY), Milk Yield Per Day of Productive Life (MY/PL), Milk Yield Per Day of Productive Days (MY/PD), and Milk Yield Per Day of Herd Life (MY/HL). For estimation of variance component and heritability separately for each trait, the uni-trait animal model was equipped, whereas to estimate genetic and phenotypic correlations between traits, bi-trait animal models were fitted. The estimates of heritability for production and reproduction traits of Nili-Ravi were medium, i.e., 0.365 ± 0.087, 0.353 ± 0.071, 0.318 ± 0.082, 0.354 ± 0.076, and 0.362 ± 0.086 for FLSMY, FDP, FSP, FCI, and AFC, respectively. The estimates of heritability were low, i.e., 0.062 ± 0.088, 0.123 ± 0.090, 0.158 ± 0.090, 0.155 ± 0.091, and 0.129 ± 0.091 for HL, PL, PD, Total LTMY, and Standard LTMY and high, i.e., 0.669 ± 0.096 for BE. Genetic correlation for FLTMY was high with FLL (0.710 ± 0.103), and genetic correlation of FLTMY was high and positive with HL, Total LTMY, MY/PL, and MY/PD while low and positive with PL. Genetic correlation of AFC was low and negative with PL, PD, UD, BE, Total LTMY, Standard LTMY, MY/PL, and MY/PD and negative with MY/HL. Significant positive phenotypic association of FPY was seen with FLTMY, FLSMY, FLL, AFC, HL, Total LTMY, and Standard LTMY. Higher heritability of first lactation traits especially FPY suggests sufficient additive genetic variability, which can be exploited under selection and breeding policy in order to improve overall performance of Nili-Ravi buffaloes.

Dietary patterns are associated to pre-gestational obesity in pregnant women

This study aimed to evaluate the association between the eating patterns and the pre gestational obesity in pregnant women from Fortaleza, Ceará. The method used was a cross-sectional study with 401 pregnant women between 19 and 45 years old, treated in a hospital that is a reference in the care of risk pregnancy and in eight health units in Fortaleza, Ceará. Food consumption was investigated using a validated food frequency questionnaire, and the eating patterns were identified using factor analysis for main components, followed by Varimax orthogonal rotation. Obesity was measured according to the body mass index (BMI). Poisson Regression with robust estimation of variance was used to estimate the prevalence ratio of eating patterns in relation to pre gestational obesity, adjusted by sociodemographic variables. Four main eating patterns were identified: “healthy cearense”, “rich in protein”, “snacks” and “popular”. A higher adherence to the “healthy cearense” pattern was associated to a higher prevalence of pre gestational obesity (PR: 1,33; CI 95% 1,01-1,77), the greater adherence to the “popular” pattern was related to the lower prevalence of pre-pregnancy obesity (PR: 0.69; 95% CI 0.51-0.92). It was concluded that there are four main food consumption patterns in the pregnant women from Fortaleza that were studied and the associations between the “healthy cearense” and “popular” patterns and pre gestational obesity were shown.

An approximate point-based alternative for the estimation of variance under big BAF sampling

Background A new variance estimator is derived and tested for big BAF (Basal Area Factor) sampling which is a forest inventory system that utilizes Bitterlich sampling (point sampling) with two BAF sizes, a small BAF for tree counts and a larger BAF on which tree measurements are made usually including DBHs and heights needed for volume estimation. Methods The new estimator is derived using the Delta method from an existing formulation of the big BAF estimator as consisting of three sample means. The new formula is compared to existing big BAF estimators including a popular estimator based on Bruce’s formula. Results Several computer simulation studies were conducted comparing the new variance estimator to all known variance estimators for big BAF currently in the forest inventory literature. In simulations the new estimator performed well and comparably to existing variance formulas. Conclusions A possible advantage of the new estimator is that it does not require the assumption of negligible correlation between basal area counts on the small BAF factor and volume-basal area ratios based on the large BAF factor selection trees, an assumption required by all previous big BAF variance estimation formulas. Although this correlation was negligible on the simulation stands used in this study, it is conceivable that the correlation could be significant in some forest types, such as those in which the DBH-height relationship can be affected substantially by density perhaps through competition. We derived a formula that can be used to estimate the covariance between estimates of mean basal area and the ratio of estimates of mean volume and mean basal area. We also mathematically derived expressions for bias in the big BAF estimator that can be used to show the bias approaches zero in large samples on the order of $\frac {1}{n}$ 1 n where n is the number of sample points.

REHE: Fast Variance Components Estimation for Linear Mixed Models

Linear mixed models are widely used in ecological and biological applications, especially in genetic studies. Reliable estimation of variance components is crucial for using linear mixed models. However, standard methods, such as the restricted maximum likelihood (REML), are computationally inefficient and may be unstable with small samples. Other commonly used methods, such as the Haseman-Elston (HE) regression, may yield negative estimates of variances. Utilizing regularized estimation strategies, we propose the restricted Haseman-Elston (REHE) regression and REHE with resampling (reREHE) estimators, along with an inference framework for REHE, as fast and robust alternatives that provide non-negative estimates with comparable accuracy to REML. The merits of REHE are illustrated using real data and benchmark simulation studies.

Genetic parameters of the type traits of Holstein-Friesian primiparous dairy cows

The aim of this study was to determine the level and variability of type traits in primiparous Holstein-Friesian cows, as well as to assess the additive genetic variance of type traits and heritability coefficients. The research was conducted on a data set of linearly evaluated primiparous Holstein-Friesian cows, which is ceded by the Main dairy cattle breed organization in the Province of Vojvodina, which is a unit of the Department of Animal Science, at the Faculty of Agriculture in Novi Sad. Data of 24226 primiparous Holstein-Friesian cows, refer to the period 2012-2015, were analysed. The phenotypic variability of the type traits, as well as effects of systemic factors affecting these traits, were analyzed using standard statistical methods in the Statistica software 13.2, and the general linear model (GLM). A Statistically highly significant effect for most of the type traits had the farm size, interaction of the year and the season of evaluation, age at linear evaluation, lactation stage and a genetic group formed by the year and country of bull/sires birth. The total type traits score (final score), which represents an evaluation of the overall primiparous cow exterior, is calculated for the 24226 linearly evaluated primiparous cows. Estimation of variance components and heritability coefficient calculation is done in the software package WOMBAT. Heritability coefficient values for the primiparous cow's type traits in the Province of Vojvodina were low to middle, ranged from 0.08 for the rear legs - side view up to 0.38 for the stature. Due to the fact that the value of the heritability coefficient depends on the variability of the traits and previous selection, lower heritability may be a consequence of the low genetic variability, or, a higher degree of variability which is a consequence of the effect of the systematic factors. Heritability coefficients indicate a genetic variability of the type traits, and its evaluation is important for the breeding value estimation for the type traits.

Estimation of variance components for bodyweight of grasscutters using expectation maximization algorithm of restricted maximum likelihood

The objective of this study was to estimate the variance components and heritability of bodyweight of grasscutters at 4, 6 and 8 months of age using EM algorithm of REML procedures. The data used for the study were obtained from the bodyweight records of 20 grasscutters from four families at 4, 6 and 8 months of age. The heritability of bodyweight of grasscutters at 4, 6 and 8 months of age were 0.14, 0.10 and 0.12 respectively. This implies that about 10 – 14 % of the phenotypic variability of body weight in this grasscutter population was accounted by additive genetic variance while environmental and gene combination variance made a larger contribution. The implication is that selection of grasscutters in this population should not be based on the information on the animals alone but also information fromits relatives.