Maternal dietary diversity and micronutrient adequacy during pregnancy and related factors in East Gojjam Zone, Northwest Ethiopia, 2016.

BackgroundMonotonous and less diversified diets are associated with micronutrient deficiency. Evidence on maternal dietary intakes during pregnancy is essential to achieve the 2025 global nutrition target and reduce maternal and child mortalities. This study assessed pregnant women's dietary diversity and identified factors associated with inadequate dietary diversity in East Gojjam Zone.MethodsWe conducted a community-based cross-sectional study between April and June 2016. Eight hundred thirty-four pregnant women were randomly sampled. The Women Dietary Diversity Score tool developed by the Food and Agricultural Organization (FAO) and Food and Nutrition Technical Assistance (FANTA) was used. Data were entered into EpiData with double entry verification, and analysis was done using IBM SPSS version 20. Level of significance was set to P ResultsThe mean (±SD) dietary diversity score was 3.68 (±2.10). Inadequate dietary diversity was prevalent in 55% [95% CI (52.3-59.3%)] of pregnant women, or indirectly micronutrient was inadequate in more than half of the pregnant women. Commonly consumed dietary groups were legumes, nuts, and seeds (85.5%) followed by starchy staples (64.7%). Inadequate dietary diversity was higher among non-educated [Adjusted Odds Ratio (AOR) = 7.30, 95% CI (2.35-22.68)] compared to college and above completed women. Wealth index had significant association with dietary diversity, in which women in the poorest [AOR = 8.83, 95% CI, (1.60-48.61)], poorer [AOR = 6.34, 95% CI (1.16-34.65)], poor [AOR = 8.46, 95% CI (1.56-45.70)], and richer [AOR = 6.57, 95% CI (2.16-20.01)] had higher odds of inadequate dietary diversity. Those who had not received dietary counseling had three folds [AOR = 3.31, 95% CI (1.49-7.35)] of inadequate dietary diversity compared to their counterparts. Less likelihood of inadequate dietary diversity was among women with an increased meal frequency [AOR = 0.53, 95% CI (0.38-0.74)].ConclusionConsumption of less diversified food during pregnancy is common in the study area. Adequacy of micronutrients is insufficient for more than half of the studied pregnant women. We conclude that being non-educated affects pregnant women to depend on less diversified diet. Providing dietary counseling during pregnancy can improve nutritional practice for pregnant women

Centrality dependence of pTp_{T} spectra for identified hadrons in Au+Au and Cu+Cu collisions at sNN=200\sqrt{s_{NN}}= 200 GeV

The centrality dependence of transverse momentum spectra for identified hadrons at midrapidity in Au+Au collisions at $\sqrt{s_{NN}}= 200$ GeV is systematically studied in a quark combination model. The $\mathrm{{p}_{T}}$ spectra of $\pi^{\pm}$, $K^{\pm}$, $p(\bar{p})$ and $\Lambda(\bar{\Lambda})$ in different centrality bins and the nuclear modification factors ($R_{CP}$) for these hadrons are calculated. The centrality dependence of the average collective transverse velocity $$ for the hot and dense quark matter is obtained in Au+Au collisions, and it is applied to a relative smaller Cu+Cu collision system. The centrality dependence of $\mathrm{{p}_{T}}$ spectra and the $R_{CP}$ for $\pi^{0}$, $K_{s}^{0}$ and $\Lambda$ in Cu+Cu collisions at $\sqrt{s_{NN}}= 200$ GeV are well described. The results show that $<\beta (r)>$ is only a function of the number of participants $N_{part}$ and it is independent of the collision system.Comment: 7 pages, 6 figure

Genome-Wide Association Analysis and Genomic Prediction for Adult-Plant Resistance to Septoria Tritici Blotch and Powdery Mildew in Winter Wheat

Septoria tritici blotch (STB) caused by the fungal pathogen Zymoseptoria tritici and powdery mildew (PM) caused by Blumeria graminis f.sp tritici (Bgt) are among the forefront foliar diseases of wheat that lead to a significant loss of grain yield and quality. Resistance breeding aimed at developing varieties with inherent resistance to STB and PM diseases has been the most sustainable and environment-friendly approach. In this study, 175 winter wheat landraces and historical cultivars originated from the Nordic region were evaluated for adult-plant resistance (APR) to STB and PM in Denmark, Estonia, Lithuania, and Sweden. Genome-wide association study (GWAS) and genomic prediction (GP) were performed based on the adult-plant response to STB and PM in field conditions using 7,401 single-nucleotide polymorphism (SNP) markers generated by 20K SNP chip. Genotype-by-environment interaction was significant for both disease scores. GWAS detected stable and environment-specific quantitative trait locis (QTLs) on chromosomes 1A, 1B, 1D, 2B, 3B, 4A, 5A, 6A, and 6B for STB and 2A, 2D, 3A, 4B, 5A, 6B, 7A, and 7B for PM adult-plant disease resistance. GP accuracy was improved when assisted with QTL from GWAS as a fixed effect. The GWAS-assisted GP accuracy ranged within 0.53-0.75 and 0.36-0.83 for STB and PM, respectively, across the tested environments. This study highlights that landraces and historical cultivars are a valuable source of APR to STB and PM. Such germplasm could be used to identify and introgress novel resistance genes to modern breeding lines

Reference soil groups map of Ethiopia based on legacy data and machine learning-technique: EthioSoilGrids 1.0

Up-to-date digital soil resource information and its comprehensive understanding are crucial to supporting crop production and sustainable agricultural development. Generating such information through conventional approaches consumes time and resources, and is difficult for developing countries. In Ethiopia, the soil resource map that was in use is qualitative, dated (since 1984), and small scaled (1 : 2 M), which limit its practical applicability. Yet, a large legacy soil profile dataset accumulated over time and the emerging machine-learning modeling approaches can help in generating a high-quality quantitative digital soil map that can provide better soil information. Thus, a group of researchers formed a Coalition of the Willing for soil and agronomy data-sharing and collated about 20 000 soil profile data and stored them in a central database. The data were cleaned and harmonized using the latest soil profile data template and 14 681 profile data were prepared for modeling. Random forest was used to develop a continuous quantitative digital map of 18 World Reference Base (WRB) soil groups at 250 m resolution by integrating environmental covariates representing major soil-forming factors. The map was validated by experts through a rigorous process involving senior soil specialists or pedologists checking the map based on purposely selected district-level geographic windows across Ethiopia. The map is expected to be of tremendous value for soil management and other land-based development planning, given its improved spatial resolution and quantitative digital representation.</p