Anti-corrosion behavior of olmesartan for soft-cast steel in 1 mol dm−3 HCL.

This study discusses the effects of temperature on corrosion inhibition for soft-cast steel by the pharmaceutically active drug olmesartan in 1 mol dm−3 HCl. The sufficient number of electron-rich elements and non-bonding π electrons in its structure favored a good capability for coating onto the electron-deficient steel surfaces. Theoretical and electrochemical measurements were carried out at the temperature region of 303 K to 333 K. Therefore, the experiment suggests that the inhibition efficiency of olmesartan increases with its increasing concentrations due to the adsorption. Additionally, even at a higher temperature of 333 K, the inhibitor molecules attain their stability towards corrosion resistance of steel surfaces. The adsorption of inhibitors on steel surfaces is spontaneously found to include the mixture of physisorption and chemisorption, and it obeys Temkin’s adsorption isotherm model. Theoretical and computational considerations were made using quantum chemical parameters and molecular dynamics simulations, which confirmed that the olmesartan has a suitable corrosion inhibitive capability intended for soft-cast steel in 1 mol dm−3 HCl. Additionally, scanning electron microscopic measurement was used to obtain a visual idea of the inhibitive action of the inhibitor attained by forming an adsorbed protective layer onto the steel surfaces. The minute concentration of olmesartan of about 10–50 ppm shows high inhibition efficiency of ~80%, even at elevated temperatures

Managing vulnerability to drought and enhancing livelihood resilience in sub-Saharan Africa: Technological, institutional and policy options

AbstractAgriculture and the economies of Sub-Saharan Africa (SSA) are highly sensitive to climatic variability. Drought, in particular, represents one of the most important natural factors contributing to malnutrition and famine in many parts of the region. The overall impact of drought on a given country/region and its ability to recover from the resulting social, economic and environmental impacts depends on several factors. The economic, social and environmental impacts of drought are huge in SSA and the national costs and losses incurred threaten to undermine the wider economic and development gains made in the last few decades in the region. There is an urgent need to reduce the vulnerability of countries to climate variability and to the threats posed by climate change. This paper attempts to highlight the challenges of drought in SSA and reviews the current drought risk management strategies, especially the promising technological and policy options for managing drought risks to protect livelihoods and reduce vulnerability. The review suggests the possibilities of several ex ante and ex post drought management strategies in SSA although their effectiveness depends on agro-climatic and socio-economic conditions. Existing technological, policy and institutional risk management measures need to be strengthened and integrated to manage drought ex ante and to minimize the ex post negative effects for vulnerable households and regions. A proactive approach that combines promising technological, institutional and policy solutions to manage the risks within vulnerable communities implemented by institutions operating at different levels (community, sub-national, and national) is considered to be the way forward for managing drought and climate variability

Smart breeding driven by big data, artificial intelligence, and integrated genomic-enviromic prediction

The first paradigm of plant breeding involves direct selection-based phenotypic observation, followed by predictive breeding using statistical models for quantitative traits constructed based on genetic experimental design and, more recently, by incorporation of molecular marker genotypes. However, plant performance or phenotype (P) is determined by the combined effects of genotype (G), envirotype (E), and genotype by environment interaction (GEI). Phenotypes can be predicted more precisely by training a model using data collected from multiple sources, including spatiotemporal omics (genomics, phenomics, and enviromics across time and space). Integration of 3D information profiles (G-P-E), each with multidimensionality, provides predictive breeding with both tremendous opportunities and great challenges. Here, we first review innovative technologies for predictive breeding. We then evaluate multidimensional information profiles that can be integrated with a predictive breeding strategy, particularly envirotypic data, which have largely been neglected in data collection and are nearly untouched in model construction. We propose a smart breeding scheme, integrated genomic-enviromic prediction (iGEP), as an extension of genomic prediction, using integrated multiomics information, big data technology, and artificial intelligence (mainly focused on machine and deep learning). We discuss how to implement iGEP, including spatiotemporal models, environmental indices, factorial and spatiotemporal structure of plant breeding data, and cross-species prediction. A strategy is then proposed for prediction-based crop redesign at both the macro (individual, population, and species) and micro (gene, metabolism, and network) scales. Finally, we provide perspectives on translating smart breeding into genetic gain through integrative breeding platforms and open-source breeding initiatives. We call for coordinated efforts in smart breeding through iGEP, institutional partnerships, and innovative technological support

Impact of CGIAR maize germplasm in sub-Saharan Africa

Open Access ArticleThis study reports on the adoption and impacts of CGIAR-related maize varieties in 18 major maize-producing countries in sub-Saharan Africa (SSA) during 1995–2015. Of the 1345 maize varieties released during this timeframe, approximately 60% had a known CGIAR parentage. About 34% (9.5 million ha) of the total maize area in 2015 was cultivated with ’new’ CGIAR-related maize varieties released between 1995 and 2015. In the same year, an additional 13% of the maize area was cultivated with ’old’ CGIAR-related maize varieties released before 1995. The aggregate annual economic benefit of using new CGIAR-related maize germplasm for yield increase in SSA was estimated at US$1.1–1.6 billion in 2015, which we attributed equally to co-investments by CGIAR funders, public-sector national research and extension programs, and private sector partners. Given that the annual global investment in CGIAR maize breeding at its maximum was US$30 million, the benefit-cost ratios for the CGIAR investment and CGIAR-attributable portion of economic benefits varied from 12:1–17:1, under the assumption of a 5-year lag in the research investment to yield returns. The study also discusses the methodological challenges involved in large-scale impact assessments. Post-2015 CGIAR tropical maize breeding efforts have had a strong emphasis on stress tolerance

Molecular breeding for nutritionally enriched maize: status and prospects

Open Access Journal; Published online: 21 Feb 2020Maize is a major source of food security and economic development in sub-Saharan Africa (SSA), Latin America, and the Caribbean, and is among the top three cereal crops in Asia. Yet, maize is deficient in certain essential amino acids, vitamins, and minerals. Biofortified maize cultivars enriched with essential minerals and vitamins could be particularly impactful in rural areas with limited access to diversified diet, dietary supplements, and fortified foods. Significant progress has been made in developing, testing, and deploying maize cultivars biofortified with quality protein maize (QPM), provitamin A, and kernel zinc. In this review, we outline the status and prospects of developing nutritionally enriched maize by successfully harnessing conventional and molecular marker-assisted breeding, highlighting the need for intensification of efforts to create greater impacts on malnutrition in maize-consuming populations, especially in the low- and middle-income countries. Molecular marker-assisted selection methods are particularly useful for improving nutritional traits since conventional breeding methods are relatively constrained by the cost and throughput of nutritional trait phenotyping

Increasing Seed Viability of Maize Haploid Inducing Lines by Genetic and Non-Genetic Approaches

Some haploid inducing lines used in the production of maize doubled haploids (DHs), express germination problems and reduced vigor. In this study, haploid inducing lines RWS, RWK-76 and their reciprocal hybrids RWS/RWK-76 and RWK-76/RWS were examined for viability by Tetrazolium (TZ) and germination ability by standard germination tests. Evaluation based on TZ tests showed that 59% of the seed of RWK-76/RWS were not viable, compared with only 12% dead seed in RWS/RWK-76. Similarly, the percentage and speed of germination in RWK- 76/RWS (25%, 1.53) was lower than for RWS/RWK-76 (74%, 4.30). In an effort to develop a quick method for assessing seed viability in these lines, the TZ test was repeated in a different way. Seed from each genotype was placed in beakers containing distilled water.Seed would either float or sink. Subsequent TZ testing confirmed that seed that floated was dead, and seed that sank was alive, although some of them had defective embryos. The dead seed in both genotypes failed to develop an embryo, leaving an empty cavity that would fill with air and cause seed to float on water. This feature can be exploited for a simple and practical method to separate living from dead seed. In addition, we surveyed theig1 (indeterminate gametophyte) gene as a candidate for germination problems in inducer lines.Sequencing data from theig1 region showed that RWS and RWK-76 differed in one nucleotide and amino acidin the firstexon of ig1.Segregation of ig1 alleles from RWS and RWK-76 wassignificantly (P=0.01) distortedin the respectiveF2 population relative to the expected Mendelian segregation ratio (1:2:1). Thus, either ig1 or a linked gene in the ig1 region affect seed viability