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Deep-sowing is an effective measure to ensure seeds absorbing water from deep soil layer and emerging normally in arid and semiarid regions. However, existing varieties demonstrate poor germination ability in deep soil layer and some key quantitative trait loci (QTL) or genes related to deep-sowing germination ability remain to be identified and analyzed. In this study, a high-resolution genetic map based on 280 lines of the intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population which comprised 6618 bin markers was used for the QTL analysis of deep-sowing germination related traits. The results showed significant differences in germination related traits under deep-sowing condition (12.5 cm) and standard-germination condition (2 cm) between two parental lines. In total, 8, 11, 13, 15, and 18 QTL for germination rate, seedling length, mesocotyl length, plumule length, and coleoptile length were detected for the two sowing conditions, respectively. These QTL explained 2.51–7.8% of the phenotypic variance with LOD scores ranging from 2.52 to 7.13. Additionally, 32 overlapping QTL formed 11 QTL clusters on all chromosomes except for chromosome 8, indicating the minor effect genes have a pleiotropic role in regulating various traits. Furthermore, we identified six candidate genes related to deep-sowing germination ability, which were co-located in the cluster regions. The results provide a basis for molecular marker assisted breeding and functional study in deep-sowing germination ability of maize.

The Yangtze River basin is one of the world's hotspots for nitrogen (N) deposition and likely plays an important role in China's riverine N output. Here we constructed a basin-scale total dissolved inorganic N (DIN) deposition (bulk plus dry) pattern based on published data at 100 observational sites between 2000 and 2014, and assessed the relative contributions of different reactive N (N) emission sectors to total DIN deposition using the GEOS-Chem model. Our results show a significant spatial variation in total DIN deposition across the Yangtze River basin (33.2 kg N ha yr on average), with the highest fluxes occurring mainly in the central basin (e.g., Sichuan, Hubei and Hunan provinces, and Chongqing municipality). This indicates that controlling N deposition should build on mitigation strategies according to local conditions, namely, implementation of stricter control of N emissions in N deposition hotspots but moderate control in the areas with low N deposition levels. Total DIN deposition in approximately 82% of the basin area exceeded the critical load of N deposition for semi-natural ecosystems along the basin. On the basin scale, the dominant source of DIN deposition is fertilizer use (40%) relative to livestock (11%), industry (13%), power plant (9%), transportation (9%), and others (18%, which is the sum of contributions from human waste, residential activities, soil, lighting and biomass burning), suggesting that reducing NH emissions from improper fertilizer (including chemical and organic fertilizer) application should be a priority in curbing N deposition. This, together with distinct spatial variations in emission sector contributions to total DIN deposition also suggest that, in addition to fertilizer, major emission sectors in different regions of the basin should be considered when developing synergistic control measures.

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Grain moisture in maize at harvest depends on the grain drying rate (GDR) after physiological maturity. The maize plants with high GDR can reduce grain moisture rapidly, which will shorten the drying time after harvest and prevent the grain to be mildew and enhance maize quality. In this study, A total of 280 recombinant inbred lines that were derived from a cross between Ji846 (high drying rate, 1.18 % day -1 ) and Ye3189 (slow drying rate, 0.39 % day -1 ) were used to construct genetic linkage map and identify QTL underlying GDR in different environments. A genetic linkage map was constructed containing 97 SSR and 49 AFLP markers, which covered 2356.8 cM of the maize genome, with an average distance of 16.1 cM. Composite interval mapping identified 14 QTL for GDR after physiological maturity located on chromosomes 2, 3, 5, 6 and 8. The additive effects of QTL were all from Ji846. The range of phenotypic variation explained by the QTL was 5.05-16.28 %. But only two QTL (qKdr-2-1, qKdr-3-6) were identified across both locations. qKdr-2-1 positioned between the markers phi090-umc1560 on chromosome 2 explained 15.59 % of the phenotypic variance, and the other qKdr-3-6 positioned between the markers phi046-bnlg1754 on chromosome 3 explained 10.28 % of the phenotypic variance.