VARIATION AMONG AGRONOMIC TRAITS AND MINERAL CONTENTS IN 15 ACCESSIONS OF GARDEN EGG PLANT (Solanum aethiopicum) IN SOUTHWEST OF NIGERIA

Throughout Africa, S. aethiopicum is very popular and plays a vital role in many human diets. Despite the fact that there are previous reports on yield characteristics and nutrition of the crop, there is a need to assess the crop for variations in mineral properties. This study aimed at determining the amount of genetic variability and level of heritability of agronomic and mineral contents of S. aethiopicum accessions. Fifteen accessions of S.aethiopicum were evaluated in an RBCD experimental design to generate data for use. Data were collected for agronomic, morphological and mineral contents. Data collected were subjected to ANOVA and the significant means were also separated using Duncan Multiple Range Test (DMRT) at 5% probability level. Variance component method was used to estimate phenotypic and genotypic variations as well as heritability. Significant differences were observed among accessions for the various morphological and mineral nutritional traits evaluated. High heritability estimates, Phenotypic and Genotypic variances were observed for mineral content and fruit yield. Genotypic and phenotypic variances ranged between 0.31 and 11078.85 for the agronomic traits. The hierarchical cluster analyses revealed five distinct clusters at similarity index of 85%. The first cluster included 6 accessions; the second included accessions NHS 101A, and OG 03; the third were NHS 104 and OG 01; the fourth included NHS 105; and the fifth included NHS 106, NHS 108, OS 02 and OS 03. Accessions OS 01 and OS 03 appear unique based on the traits for which the accessions were assessed.This study revealed that substantial variation exists within the accessions of S.aethiopicum evaluated, hence, it will help in breeding process of good quality genotypes for higher yields and mineral content.

Determination of homogenous GRACE FOLLOW-ON monthly displacements based on available solutions

<p>Presently, Gravity Recovery and Climate Experiment (GRACE) mission data is widely used in various fields of science. The longest satellite gravimetric mission regularly explored changes of the gravity field from April 2002 to October 2017. Nowadays, its follow-on mission (GRACE-FO) observes gravity changes from May 2018, providing new greater research opportunities. In the following research, we present a completely new vertical deformations changes model of the first 14 months GRACE-FO observations. The study’s aim is to reduce the signal noise left after Gauss spatial smoothing. In this study, we use monthly gravity field in spherical harmonics form up to degree and order 96, provided by three different centers, i.e. the NASA’s Jet Propulsion Laboratory (JPL), the German Research Center for Geosciences (GFZ) and the Center for Space Research (CSR). In following study, we use all sets of data (JPL, GFZ and CSR) to test three various algorithms: (1) coefficient-wise and (2) field-wise non-iterative weighting methods and further, (3) estimation by iterative variance component method.  Finally, we obtain joined spherical harmonics changes by a weighted average scheme, which are converted to Earth crust vertical deformations. The used weighting methods reduce root mean square scatter of monthly deformation fields by nearly 5% for continental areas (excluding Amazon basin and Hudson Bay region) and by 10-15% changes for the ocean areas. However, with respect to each new-created model, differences in monthly deformation changes are in the range from ±3 mm to ±6 mm depending on the data center (JPL, GFZ or CSR). Furthermore, the analysis of signal information contained in each degree allows us to assess the quality of the created models. The highest signal variations in our models occur up to the degree and order 25. Additionally, the high differences in the signal are obtained for sectoral harmonics up to the maximum degree. Analysis showed that the applied field-wise weights much more effectively remove remaining noise after spatial averaging than per-order/degree weighting. Whereas, the obtained results indicate that observations provided by GFZ center have the smallest weights for each algorithm.</p>

Genetic and Common Environmental Contributions to Familial Resemblances in Plasma Carotenoid Concentrations in Healthy Families

Carotenoids have shown an interindividual variability that may be due to genetic factors. The only study that has reported heritability of serum α- and β-carotene has not considered the environmental component. This study aimed to estimate the contribution of both genetic and common environmental effects to the variance of carotenoid concentrations and to test whether their phenotypic correlations with cardiometabolic risk factors are explained by shared genetic and environmental effects. Plasma carotenoid concentrations (α-carotene, β-carotene, β-cryptoxanthin, lutein, lycopene, zeaxanthin, and total carotenoids) of 48 healthy subjects were measured. Heritability estimates of carotenoid concentrations were calculated using the variance component method. Lutein and lycopene showed a significant familial effect (p = 6 × 10−6 and 0.0043, respectively). Maximal heritability, genetic heritability, and common environmental effect were computed for lutein (88.3%, 43.8%, and 44.5%, respectively) and lycopene (45.2%, 0%, and 45.2%, respectively). Significant phenotypic correlations between carotenoid concentrations and cardiometabolic risk factors were obtained for β-cryptoxanthin, lycopene, and zeaxanthin. Familial resemblances in lycopene concentrations were mainly attributable to common environmental effects, while for lutein concentrations they were attributable to genetic and common environmental effects. Common genetic and environmental factors may influence carotenoids and cardiometabolic risk factors, but further studies are needed to better understand the potential impact on disease development.

Genetic and Environmental Influences on General Skin Traits: Healthy Twins and Families in Korea

Family study can provide estimates of overall genetic influences on a particular trait because family relationships provide accurate measures of average genetic sharing. However, evidence of genetic contributions to skin phenotypes is limited, which may preclude genetic studies to identify genetic variants or to understand underlying molecular biology of skin traits. This study aimed to estimate genetic and environmental contributions to selected dermatologic phenotypes, that is, to melanin index, sebum secretion, and skin humidity level in a Korean twin-family cohort. We investigated more than 2,000 individuals from 486 families, including 388 monozygotic twin pairs and 82 dizygotic twin pairs. Variance component method was used to estimate genetic influences in terms of heritability. Heritability of skin melanin index, sebum secretion, and skin humidity (arm and cheek) were estimated to be 0.44 [95% CI 0.38–0.49], 0.21 [95% CI 0.16–0.26], 0.13 [95% CI 0.07–0.18], and 0.11 [95% CI 0.06–0.16] respectively, after adjusting for confounding factors. Our findings suggest that genetics play a major role on skin melanin index, but only mild roles on sebum secretion and humidity. Sebum secretion and skin humidity are controlled predominantly by environmental factors notably on shared environments among family members. We expect that our findings add insight to determinants of common dermatologic traits, and serve as a reference for biologic studies.