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Mineral nutrient malnutrition, especially deficiency of selenium (Se) affects the health of approximately one billion people worldwide. Wild emmer wheat (Triticum turgidum ssp. dicoccoides), the progenitor of common wheat, harbors a rich genetic diversity for mineral nutrients. The study was conducted on two wild emmer wheat genotypes differing in Se tolerance (R113, Se-sensitive; R171, Se-tolerant) with 2 Se application methods and 3 Se levels (foliar rates of 0, 11.5 and 23 mg.L-1; fertigation rates of 0, 5 and 10 mg.kg-1) in 2017 having 5 replications, at an experimental farm, Sichuan Province, China. It evaluated the effects of Se application on wild emmer wheat growth, grain yield and quality, and 14 other trace elements absorption and translocation in sink-source organs (flag leaves, husks and grains). The results showed that both foliar Se and fertigated Se application methods increased Se contents in sink-source organs, wheat health benefits and yield, while the foliar application was more effective than fertigation. Moreover, two Se application methods decreased toxic trace elements (Pb, Al, As, Li and Cd) contents in wheat, indicating a possible antagonistic effect. Accordingly, this study provided useful information concerning agronomic biofortification of wheat, indicating that it is feasible to apply Se in fertilization programmes to inhibit the heavy metal elements contents and improve yield and quality in agricultural crops. The higher Se, Fe, Zn and Mo contents found in R171 suggested that its germplasm conferred higher abilities for mineral uptake and accumulation, which can be used for genetic studies of wheat nutritional value and for further improvement of domesticated cereals. [ABSTRACT FROM AUTHOR]

Earthquake prediction is an extraordinarily stochastic process. Determining the occurrence time, location of epicenter and magnitude of a coming earthquake in the following month is an extremely difficult task. Nowadays, some geophysical, statistical and machine learning methods are adopted to predict earth-quakes, however, for the insufficient medium-large seismic data, their results are not satisfactory. Due to there is no obvious empirical relationship between seismicity features, magnitude and location of a coming earthquake in a particular time window, an earthquake prediction approach based on danger theory is proposed in this paper. It extracts eight indicators calculated from earthquake data for recent years in Sichuan and surroundings by Gutenberg-Richter(GR) inverse power-law, and predicts quakes with magnitude lager than 4.5 during the following month by numerical differential based Dendritic Cell Algorithm (ndDCA). We compare this approach with six state-of-art earthquake prediction algorithms. Overall our algorithm yields the encouraging results in all the qualified parameters assessed, and it provides technical support for the application of earthquake prediction. [ABSTRACT FROM AUTHOR]