Volatile organic compounds (VOC) are important precursors of secondary organic aerosols (SOA). The pollution processes in Beijing were investigated from 18th October to 6th November 2013 to study the ...characteristics, SOA formation potential and contributing factors of VOC during hazy episodes. The mean concentrations of VOC were 67.4 ± 33.3 μg m−3 on clear days and have 5–7-fold increase in polluted periods. VOC concentrations rapidly increased at a visibility range of 4–5 km with the rate of 25%/km in alkanes, alkenes and halocarbons and the rate of 45%/km in aromatics. Analysis of the mixing layer height (MLH); wind speed and ratios of benzene/toluene (B/T), ethylbenzene/m,p-xylene (E/X), and isopentane/n-pentane (i/n) under different visibility conditions revealed that the MLH and wind speed were the 2 major factors affecting the variability of VOC during clear days and that local emissions and photochemical reactions were main causes of VOC variation on polluted days. Combined with the fractional aerosol coefficient (FAC) method, the SOA formation potentials of alkanes, alkenes and aromatics were 0.3 ± 0.2 μg m−3, 1.1 ± 1.0 μg m−3 and 6.5 ± 6.4 μg m−3, respectively. As the visibility deteriorated, the SOA formation potential increased from 2.1 μg m−3 to 13.2 μg m−3, and the fraction of SOA-forming aromatics rapidly increased from 56.3% to 90.1%. Initial sources were resolved by a positive matrix factorization (PMF) model. Vehicle-related emissions were an important source of VOC at all visibility ranges, accounting for 23%–32%. As visibility declined, emissions from solvents and the chemical industry increased from 13.2% and 6.3% to 34.2% and 23.0%, respectively. Solvents had the greatest SOA formation ability, accounting for 52.5% on average on hazy days, followed by vehicle-related emissions (20.7%).
•The variation characteristics of VOCs during haze process were investigated.•Initial concentration and SOA potentials of VOCs were estimated at different pollution stages.•Initial emission source were resolved during different pollution conditions.•52.5% SOA come from solvents source on pollution days.
Volatile organic compounds (VOCs) play a very important role in the formation of ozone and secondary organic aerosols. The concentrations, compositions, and variability of VOCs were measured from ...2005 to 2008 at Dinghu Mountain Forest Ecosystem Research Station, a remote station in Southeast China. Weekly samples were collected in the Dinghu Mountain area and were analysed via gas chromatography–mass spectrometry. The results revealed that the total VOC concentrations decreased continuously and that the dominant VOC components were alkanes (43%) and aromatics (33%), followed by halo-hydrocarbons (12%) and alkenes (12%). The general trend of seasonal variation indicated higher concentrations in spring and lower concentrations in summer. The positive matrix factorization model was used to identify the sources of the VOCs. Seven sources were resolved by the PMF model: (1) vehicular emissions, which contributed 25% of the total VOC concentration; (2) industrial sources and regional transportation, contributing 17%; (3) paint solvent use, contributing 17%; (4) fuel evaporation, contributing 13%; (5) stationary combustion sources, contributing 12%; (6) biogenic emissions, contributing 10%; and aged VOCs, contributing only 6%. The HYSPLIT model was used to analyse the effect of pollutant transport, and the results indicated that the transport of pollutants from cities cannot be ignored. Finally, the OH radical loss rates and ozone formation potentials (OFPs) were calculated, and the results indicated isoprene to have the highest OH radical loss rate and toluene to be the largest contributor to the OFP at the Dinghu Mountain site.
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•First time Continuous observation of VOCs at the Dinghu Mountain site.•The total VOC concentrations decreased continually during the period of observation.•BTEX were at a high level compared with other regional remote stations.•Anthropogenic sources are the most important sources at the Dinghu Mountain site.•Isoprene and toluene were the largest contributor to reactivity and OFP.
The mixing ratio, composition and variability of volatile organic compounds (VOCs) were measured from 2008 through 2011 at Gongga Mountain Forest Ecosystem Research Station (102°00′E, 29°33′N, ...elevation 1640 m), a remote station in southwest China. Weekly samples were collected in the Gongga Mountain area and were analyzed using a three-stage preconcentration method coupled with GC–MS. An advance receptor model positive matrix factorization (PMF) was applied to identify and apportion the sources of VOCs. The results show that the measured VOC mixing ratio at Gongga Mountain is dominated by aromatics (35.7%) and alkanes (30.8%), followed by halocarbons (21.6%) and alkenes (11.9%). The general trend of seasonal variation shows higher mixing ratios in spring and lower mixing ratios in autumn. The effect of alkanes and aromatics on the seasonal variation of total volatile organic compounds (TVOCs) is significant. Five sources were resolved by the PMF model: (1) gasoline-related emission (the combination of gasoline exhaust and gas vapor), which contributes 35.1% of the measured VOC mixing ratios; (2) solvent use, contributing 21.8%; (3) fuel combustion, contributing 29.1%; (4) biogenic emission, contributing 5.2%; and (5) industrial, commercial and domestic sources, contributing 8.7%. The effect on this area of the long-range transport of air pollutants from highly polluted areas is significant.
•This is the first time to study the VOCs in the remote station in southwest China.•Aromatics and alkanes are the major components of VOC.•The seasonal variation shows higher value in spring and lower value in autumn.•Anthropogenic sources are the most important sources in the remote area.
Key message
A tiller inhibition gene,
TIN4
, was mapped to an approximately 311 kb genomic interval on chromosome arm 2DL of wheat.
The tiller is one of the key components of plant morphological ...architecture and a central agronomic trait affecting spike number in wheat. Low tiller number has been proposed as a major component of crop ideotypes for high yield potential. In this study, we characterized the development of tillering in near-isogenic lines (NIL7A and NIL7B), indicating that the TIN4 gene inhibited the growth of tillering buds and negatively regulated tiller number. Low-tillering was controlled by a single gene (TIN4) located on chromosome 2DL by genetic analysis and bulked segregant RNA-seq analysis. A total of 17 new polymorphic markers were developed in this study, and 61 recombinants were identified in the secondary F2 population containing 4,266 individuals. TIN4 was finally mapped on a 0.35 cM interval, co-segregated with molecular marker M380, within a 311 kb genomic interval of the wheat cultivar Chinese Spring reference genome sequence that contained twelve predicted genes. Yield experiments showed that the yield of low-tillering lines was higher than that of high-tillering lines at a higher density. Overall, this study provides a foundation for the construction of a low-tillering ideotype for improving wheat yield and further cloning TIN4 by map-based cloning approach.
Key message
We identified and validated two stable grain filling rate (GFR) quantitative trait loci (QTL) in wheat that positively influenced several yield-related traits. Among them,
QGfr.sicau
-
...7D.1
was a novel GFR QTL.
The grain filling rate (GFR) plays a crucial role in determining grain yield. To advance the current understanding of the genetic characteristics underlying the GFR in common wheat, three recombinant inbred line populations were used to map and validate GFR quantitative trait loci (QTL). Using a high-density genetic linkage map, 10 GFR QTL were detected. They were located on chromosomes 2D, 4A, 4B, 5B, 6D, 7A and 7D, explained 4.99–12.62% of the phenotypic variation. Two of them,
QGfr.sicau
-
6D
and
QGfr.sicau
-
7D.1
, were detected in all four environments tested and their genetic effect was validated by closely linked kompetitive allele specific PCR (KASP) markers in different genetic backgrounds. The effects of these two GFR QTL on other yield-related traits were also estimated.
QGfr.sicau
-
6D
had a significant positive influence (
p
< 0.01) on thousand kernel weight, kernel width, kernel volume, and kernel surface area.
QGfr.sicau
-
7D.1
had a significant positive influence (
p
< 0.01) on thousand kernel weight and kernel length. Furthermore,
QGfr.sicau
-
7D.1
was a completely novel QTL for GFR; several genes associated with grain growth and development were predicted in its physical interval. These results will facilitate molecular marker-assisted selection of wheat with high-confidence QTL for GFR and fine mapping of genes associated with GFR, thereby contributing to yield improvement.
Spike-layer uniformity (SLU), the consistency of the spike distribution in the vertical space, is an important trait. It directly affects the yield potential and appearance. Revealing the genetic ...basis of SLU will provide new insights into wheat improvement. To map the SLU-related quantitative trait loci (QTL), 300 recombinant inbred lines (RILs) that were derived from a cross between H461 and Chinese Spring were used in this study. The RILs and parents were tested in fields from two continuous years from two different pilots. Phenotypic analysis showed that H461 was more consistent in the vertical spatial distribution of the spike layer than in Chinese Spring. Based on inclusive composite interval mapping, four QTL were identified for SLU. There were two major QTL on chromosomes 2BL and 2DL and two minor QTL on chromosomes 1BS and 2BL that were identified. The additive effects of
,
and
were all from the parent, H461. The major QTL,
and
, were detected in each of the conducted trials. Based on the best linear unbiased prediction values, the two loci explained 23.97% and 15.98% of the phenotypic variation, respectively. Compared with previous studies, the two major loci were potentially novel and the two minor loci were overlapped. Based on the kompetitive allele-specific PCR (KASP) marker, the genetic effects for
were validated in an additional RIL population. The genetic effects ranged from 26.65% to 32.56%, with an average value of 30.40%. In addition,
showed a significant (
0.01) and positive influence on the spike length, spikelet number, and thousand kernel weight. The identified QTL and the developed KASP marker will be helpful for fine-mapping these loci, finally contributing to wheat breeding programs in a marker-assisted selection way.
Phosphorus deficiency is a major limiting factors for affecting crop production globally. To understand the genetic variation of phosphorus-deficiency-tolerance, a total of 15 seedling traits were ...evaluated among 707 Chinese wheat landraces under application of phosphorus (AP) and non-application of phosphorus (NP). A total of 18,594 single-nucleotide polymorphisms and 38,678 diversity arrays technology sequencing markers were used to detect marker-trait associations under AP and NP.
Top ten genotypes with extremely tolerance and bottommost ten genotypes with extremely sensitivity were selected from 707 Chinese wheat landraces for future breeding and genetic analysis. A total of 55 significant markers (81 marker-trait associations) for 13 traits by both CMLM and SUPER method. These were distributed on chromosomes 1A, 1B, 2A, 2B, 2D, 3A, 4B, 5A, 5B, 6A, 6B, 6D, 7A and 7B. Considering the linkage disequilibrium decay distance, 25 and 12 quantitative trait loci (QTL) were detected under AP and NP, respectively (9 QTL were specific to NP).
The extremely tolerant landraces could be used for breeding phosphorus-deficiency-tolerant cultivars. The QTL could be useful in wheat breeding through marker-assisted selection. Our findings provide new insight into the genetic analysis of P-deficiency-tolerance, and will be helpful for breeding P-deficiency-tolerant cultivars.
Industrial pollution has a significant effect on aerosol properties in Changsha City, a typical city of central China. Therefore, year-round measurements of aerosol optical, radiative and chemical ...properties from 2012 to 2014 at an urban site in Changsha were analyzed. During the observation period, the energy structure was continuously optimized, which was characterized by the reduction of coal combustion. The aerosol properties have obvious seasonal variations. The seasonal average aerosol optical depth (AOD) at 500 nm ranged from 0.49 to 1.00, single scattering albedo (SSA) ranged from 0.93 to 0.97, and aerosol radiative forcing at the top of the atmosphere (TOA) ranged from −24.0 to 3.8 W m
−2
. The chemical components also showed seasonal variations. Meanwhile, the scattering aerosol, such as organic carbon, SO
4
2−
, NO
3
−
, and NH
4
+
showed a decrease, and elemental carbon increased. Compared with observation in winter 2012, AOD and TOA decreased by 0.14 and −1.49 W m
−2
in winter 2014. The scattering components, SO
4
2−
, NO
3
−
and NH
4
+
, decreased by 12.8 µg m
−3
(56.8%), 9.2 µg m
−3
(48.8%) and 6.4 µg m
−3
(45.2%), respectively. The atmospheric visibility and pollution diffusion conditions improved. The extinction and radiative forcing of aerosol were significantly controlled by the scattering aerosol. The results indicate that Changsha is an industrial city with strong scattering aerosol. The energy structure optimization had a marked effect on controlling pollution, especially in winter (strong scattering aerosol).
Fusarium crown rot (FCR), caused by various
Fusarium
species, is a primary fungal disease in most wheat-growing regions worldwide.
A. tauschii
, the diploid wild progenitor of the D-genome of common ...wheat, is a reservoir of genetic diversity for improving bread wheat biotic and abiotic resistance/tolerance. A worldwide collection of 286
A. tauschii
accessions was used to evaluate FCR resistance. Population structure analysis revealed that 115 belonged to the
A. tauschii
ssp.
strangulata
subspecies, and 171 belonged to the
A. tauschii
ssp.
tauschii
subspecies. Five accessions with disease index values lower than 20 showed moderate resistance to FCR. These five originated from Afghanistan, China, Iran, Uzbekistan, and Turkey, all belonging to the
tauschii
subspecies. Genome-wide association mapping using 6,739 single nucleotide polymorphisms (SNPs) revealed that two SNPs on chromosome 2D and four SNPs on chromosome 7D were significantly associated with FCR resistance. Almost all FCR resistance alleles were presented in accessions from the
tauschii
subspecies, and only 4, 11, and 19 resistance alleles were presented in accessions from the
strangulata
subspecies. Combining phenotypic correlation analysis and genome-wide association mapping confirmed that FCR resistance loci were independent of flowering time, heading date, and plant height in this association panel. Six genes encoding disease resistance-related proteins were selected as candidates for further validation. The identified resistant
A. tauschii
accessions will provide robust resistance gene sources for breeding FCR-resistant cultivars. The associated loci/genes will accelerate and improve FCR in breeding programs by deploying marker-assisted selection.
From the perspective of wheat yield improvement, the coleoptile is vital for successful crop establishment, and long coleoptile lengths (CLs) are preferred in wheat-growing regions where deep ...planting is practiced. To determine the genetic basis of CL, we performed a genome-wide association study on a set of 707 Chinese wheat landraces using 18,594 single-nucleotide polymorphisms and 38,678 diversity array technology sequencing markers. We accordingly detected a total of 29 significant markers -log
> 4.76 distributed on chromosomes 2B, 2D, 3A, 4A, 5A, 6A, 6B, 6D, and 7B. Based on linkage disequilibrium decay distance, we identified a total of 17 quantitative trait loci associated with CL, among which
, located at 508.17-509.26 Mb on chromosome 6B, was recognized as a novel major locus. We subsequently developed a high-resolution melt marker for
, which was validated in an
population. Our findings provide important insights into the genetic mechanisms underlying coleoptile growth and could be applied to marker-assisted wheat selection.
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