Genomic prediction for grain zinc and iron concentrations in spring wheat.

KEY MESSAGE: Predictability estimated through cross-validation approach showed moderate to high level; hence, genomic selection approach holds great potential for biofortification breeding to enhance grain zinc and iron concentrations in wheat. Wheat (Triticum aestivum L.) is a major staple crop, providing 20 % of dietary energy and protein consumption worldwide. It is an important source of mineral micronutrients such as zinc (Zn) and iron (Fe) for resource poor consumers. Genomic selection (GS) approaches have great potential to accelerate development of Fe- and Zn-enriched wheat. Here, we present the results of large-scale genomic and phenotypic data from the HarvestPlus Association Mapping (HPAM) panel consisting of 330 diverse wheat lines to perform genomic predictions for grain Zn (GZnC) and Fe (GFeC) concentrations, thousand-kernel weight (TKW) and days to maturity (DTM) in wheat. The HPAM lines were phenotyped in three different locations in India and Mexico in two successive crop seasons (2011-12 and 2012-13) for GZnC, GFeC, TKW and DTM. The genomic prediction models revealed that the estimated prediction abilities ranged from 0.331 to 0.694 for Zn and from 0.324 to 0.734 for Fe according to different environments, whereas prediction abilities for TKW and DTM were as high as 0.76 and 0.64, respectively, suggesting that GS holds great potential in biofortification breeding to enhance grain Zn and Fe concentrations in bread wheat germplasm.

Political determinants of health: (re) examining the role of governance in reducing maternal mortality.

Given change in the universal developmental agenda and the quality of governance in the last two decades, this paper re-examines the relationship between governance, health expenditure and maternal mortality using panel data for 184 countries from 1996 to 2019. By employing the 'dynamic panel data regression model', the study reveals that a one-point improvement in the governance index decreases maternal mortality by 10-21%. We also find that good governance can better translate health expenditure into improved maternal health outcomes through effective allocation and equitable distribution of available resources. These results are robust to alternative instruments, alternative dependent variables (such as infant mortality rate and life expectancy), estimation by different governance dimensions and at the sub-national level. Additional findings using 'Quantile regression' estimates show that the quality of governance matters more than the health expenditure in countries with a higher level of maternal mortality. While the 'Path regression' analysis exhibits the specific direct and indirect mechanisms through which the causal inference operates between governance and maternal mortality.