ResearchPad - wheat https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Terminal drought and heat stress alter physiological and biochemical attributes in flag leaf of bread wheat]]> https://www.researchpad.co/article/elastic_article_14475 Heat stress along with low water availability at reproductive stage (terminal growth phase of wheat crop) is major contributing factor towards less wheat production in tropics and sub-tropics. Flag leaf plays a pivotal role in assimilate partitioning and stress tolerance of wheat during terminal growth phase. However, limited is known about biochemical response of flag leaf to combined and individual heat and drought stress during terminal growth phase. Therefore, current study investigated combined and individual effect of terminal drought and heat stress on water relations, photosynthetic pigments, osmolytes accumulation and antioxidants defense mechanism in flag leaf of bread wheat. Experimental treatments comprised of control, terminal drought stress alone (50% field capacity during reproductive phase), terminal heat stress alone (wheat grown inside plastic tunnel during reproductive phase) and terminal drought stress + terminal heat stress. Individual and combined imposition of drought and heat stresses significantly (p≤0.05) altered water relations, osmolyte contents, soluble proteins and sugars along with activated antioxidant defensive system in terms of superoxide dismutase (SOD), peroxidase (POD) and ascorbate peroxidase (APX). Turgor potential, POD and APX activities were lowest under individual heat stress; however, these were improved when drought stress was combined with heat stress. It is concluded that combined effect of drought and heat stress was more detrimental than individual stresses. The interactive effect of both stresses was hypo-additive in nature, but for some traits (like turgor potential and APX) effect of one stress neutralized the other. To best of our knowledge, this is the first report on physiological and biochemical response of flag leaf of wheat to combine heat and drought stress. These results will help future studies dealing with improved stress tolerance in wheat. However, detailed studies are needed to fully understand the genetic mechanisms behind these physiological and biochemical changes in flag leaf in response to combined heat and drought stress.

]]>
<![CDATA[Use of multiple traits genomic prediction, genotype by environment interactions and spatial effect to improve prediction accuracy in yield data]]> https://www.researchpad.co/article/elastic_article_14474 Genomic selection has been extensively implemented in plant breeding schemes. Genomic selection incorporates dense genome-wide markers to predict the breeding values for important traits based on information from genotype and phenotype records on traits of interest in a reference population. To date, most relevant investigations have been performed using single trait genomic prediction models (STGP). However, records for several traits at once are usually documented for breeding lines in commercial breeding programs. By incorporating benefits from genetic characterizations of correlated phenotypes, multiple trait genomic prediction (MTGP) may be a useful tool for improving prediction accuracy in genetic evaluations. The objective of this study was to test whether the use of MTGP and including proper modeling of spatial effects can improve the prediction accuracy of breeding values in commercial barley and wheat breeding lines. We genotyped 1,317 spring barley and 1,325 winter wheat lines from a commercial breeding program with the Illumina 9K barley and 15K wheat SNP-chip (respectively) and phenotyped them across multiple years and locations. Results showed that the MTGP approach increased correlations between future performance and estimated breeding value of yields by 7% in barley and by 57% in wheat relative to using the STGP approach for each trait individually. Analyses combining genomic data, pedigree information, and proper modeling of spatial effects further increased the prediction accuracy by 4% in barley and 3% in wheat relative to the model using genomic relationships only. The prediction accuracy for yield in wheat and barley yield trait breeding, were improved by combining MTGP and spatial effects in the model.

]]>
<![CDATA[SNP markers for low molecular glutenin subunits (LMW-GSs) at the <i>Glu-A3</i> and <i>Glu-B3</i> loci in bread wheat]]> https://www.researchpad.co/article/elastic_article_13817 The content and composition of seed storage proteins is largely responsible for wheat end-use quality. They mainly consist of polymeric glutenins and monomeric gliadins. According to their electrophoretic mobility, gliadins and glutenins are subdivided into several fractions. Glutenins are classified as high molecular weight or low molecular weight glutenin subunits (HMW-GSs and LMW-GSs, respectively). LMW-GSs are encoded by multigene families located at the orthologous Glu-3 loci. We designed a set of 16 single-nucleotide polymorphism (SNP) markers that are able to detect SDS-PAGE alleles at the Glu-A3 and Glu-B3 loci. The SNP markers captured the diversity of alleles in 88 international reference lines and 27 Mexican cultivars, when compared to SDS-PAGE and STS markers, however, showed a slightly larger percent of multiple alleles, mainly for Glu-B3. SNP markers were then used to determine the Glu-1 and Glu-3 allele composition in 54 CIMMYT historical lines and demonstrated to be useful tool for breeding programs to improve wheat end product properties.

]]>
<![CDATA[Impacts of arbuscular mycorrhizal fungi on nutrient uptake, N2 fixation, N transfer, and growth in a wheat/faba bean intercropping system]]> https://www.researchpad.co/article/5c900d39d5eed0c48407e3a9

Arbuscular mycorrhizal fungi (AMF) can play a key role in natural and agricultural ecosystems affecting plant nutrition, soil biological activity and modifying the availability of nutrients by plants. This research aimed at expanding the knowledge of the role played by AMF in the uptake of macro- and micronutrients and N transfer (using a 15N stem-labelling method) in a faba bean/wheat intercropping system. It also investigates the role of AMF in biological N fixation (using the natural isotopic abundance method) in faba bean grown in pure stand and in mixture. Finally, it examines the role of AMF in driving competition and facilitation between faba bean and wheat. Durum wheat and faba bean were grown in pots (five pots per treatment) as sole crops or in mixture in the presence or absence of AMF. Root colonisation by AMF was greater in faba bean than in wheat and increased when species were mixed compared to pure stand (particularly for faba bean). Mycorrhizal symbiosis positively influenced root biomass, specific root length, and root density and increased the uptake of P, Fe, and Zn in wheat (both in pure stand and in mixture) but not in faba bean. Furthermore, AMF symbiosis increased the percentage of N derived from the atmosphere in the total N biomass of faba bean grown in mixture (+20%) but not in pure stand. Nitrogen transfer from faba bean to wheat was low (2.5–3.0 mg pot-1); inoculation with AMF increased N transfer by 20%. Overall, in terms of above- and belowground growth and uptake of nutrients, mycorrhization favoured the stronger competitor in the mixture (wheat) without negatively affecting the companion species (faba bean). Results of this study confirm the role of AMF in driving biological interactions among neighbouring plants.

]]>
<![CDATA[A framework for gene mapping in wheat demonstrated using the Yr7 yellow rust resistance gene]]> https://www.researchpad.co/article/N8aa5bdf2-6390-43c2-aef2-b7a76659179a

We used three approaches to map the yellow rust resistance gene Yr7 and identify associated SNPs in wheat. First, we used a traditional QTL mapping approach using a double haploid (DH) population and mapped Yr7 to a low-recombination region of chromosome 2B. To fine map the QTL, we then used an association mapping panel. Both populations were SNP array genotyped allowing alignment of QTL and genome-wide association scans based on common segregating SNPs. Analysis of the association panel spanning the QTL interval, narrowed the interval down to a single haplotype block. Finally, we used mapping-by-sequencing of resistant and susceptible DH bulks to identify a candidate gene in the interval showing high homology to a previously suggested Yr7 candidate and to populate the Yr7 interval with a higher density of polymorphisms. We highlight the power of combining mapping-by-sequencing, delivering a complete list of gene-based segregating polymorphisms in the interval with the high recombination, low LD precision of the association mapping panel. Our mapping-by-sequencing methodology is applicable to any trait and our results validate the approach in wheat, where with a near complete reference genome sequence, we are able to define a small interval containing the causative gene.

]]>
<![CDATA[Modified shape index for object-based random forest image classification of agricultural systems using airborne hyperspectral datasets]]> https://www.researchpad.co/article/5c8acce5d5eed0c484990263

This paper highlights the importance of optimized shape index for agricultural management system analysis that utilizes the contiguous bands of hyperspectral data to define the gradient of the spectral curve and improve image classification accuracy. Currently, a number of machine learning methods would resort to using averaged spectral information over wide bandwidths resulting in loss of crucial information available in those contiguous bands. The loss of information could mean a drop in the discriminative power when it comes to land cover classes with comparable spectral responses, as in the case of cultivated fields versus fallow lands. In this study, we proposed and tested three new optimized novel algorithms based on Moment Distance Index (MDI) that characterizes the whole shape of the spectral curve. The image classification tests conducted on two publicly available hyperspectral data sets (AVIRIS 1992 Indian Pine and HYDICE Washington DC Mall images) showed the robustness of the optimized algorithms in terms of classification accuracy. We achieved an overall accuracy of 98% and 99% for AVIRIS and HYDICE, respectively. The optimized indices were also time efficient as it avoided the process of band dimension reduction, such as those implemented by several well-known classifiers. Our results showed the potential of optimized shape indices, specifically the Moment Distance Ratio Right/Left (MDRRL), to discriminate between types of tillage (corn-min and corn-notill) and between grass/pasture and grass/trees, tree and grass under object-based random forest approach.

]]>
<![CDATA[Genome-wide analysis, expansion and expression of the NAC family under drought and heat stresses in bread wheat (T. aestivum L.)]]> https://www.researchpad.co/article/5c897798d5eed0c4847d30f2

The NAC family is one of the largest plant-specific transcription factor families, and some of its members are known to play major roles in plant development and response to biotic and abiotic stresses. Here, we inventoried 488 NAC members in bread wheat (Triticum aestivum). Using the recent release of the wheat genome (IWGS RefSeq v1.0), we studied duplication events focusing on genomic regions from 4B-4D-5A chromosomes as an example of the family expansion and neofunctionalization of TaNAC members. Differentially expressed TaNAC genes in organs and in response to abiotic stresses were identified using publicly available RNAseq data. Expression profiling of 23 selected candidate TaNAC genes was studied in leaf and grain from two bread wheat genotypes at two developmental stages in field drought conditions and revealed insights into their specific and/or overlapping expression patterns. This study showed that, of the 23 TaNAC genes, seven have a leaf-specific expression and five have a grain-specific expression. In addition, the grain-specific genes profiles in response to drought depend on the genotype. These genes may be considered as potential candidates for further functional validation and could present an interest for crop improvement programs in response to climate change. Globally, the present study provides new insights into evolution, divergence and functional analysis of NAC gene family in bread wheat.

]]>
<![CDATA[Analysis of genetic control and QTL mapping of essential wheat grain quality traits in a recombinant inbred population]]> https://www.researchpad.co/article/5c897730d5eed0c4847d2663

Wheat cultivars are genetically crossed to improve end-use quality for traits as per demands of baking industry and broad consumer preferences. The processing and baking qualities of bread wheat are influenced by a variety of genetic make-ups, environmental factors and their interactions. Two wheat cultivars, WL711 and C306, derived recombinant inbred lines (RILs) with a population of 206, were used for phenotyping of quality-related traits. The genetic analysis of quality traits showed considerable variation for measurable quality traits, with normal distribution and transgressive segregation across the years. From the 206 RILs, few RILs were found to be superior to those of the parental cultivars for key quality traits, indicating their potential use for the improvement of end-use quality and suggesting the probability of finding new alleles and allelic combinations from the RIL population. Mapping analysis identified 38 putative QTLs for 13 quality-related traits, with QTLs explaining 7.9–16.8% phenotypic variation spanning over 14 chromosomes, i.e., 1A, 1B, 1D, 2A, 2D, 3B, 3D, 4A, 4B, 4D, 5D, 6A, 7A and 7B. In-silico analysis based on homology to the annotated wheat genes present in database, identified six putative candidate genes within QTL for total grain protein content, qGPC.1B.1 region. Major QTL regions for other quality traits such as TKW have been identified on 1B, 2A, and 7A chromosomes in the studied RIL population. This study revealed the importance of the combination of stable QTLs with region-specific QTLs for better phenotyping, and the QTLs presented in our study will be useful for the improvement of wheat grain and bread-making quality.

]]>
<![CDATA[Analysis of transcriptional responses in root tissue of bread wheat landrace (Triticum aestivum L.) reveals drought avoidance mechanisms under water scarcity]]> https://www.researchpad.co/article/5c89770fd5eed0c4847d238d

In this study, high-throughput sequencing (RNA-Seq) was utilized to evaluate differential expression of transcripts and their related genes involved in response to terminal drought in root tissues of bread wheat landrace (L-82) and drought-sensitive genotype (Marvdasht). Subsets of 460 differentially expressed genes (DEGs) in drought-tolerant genotype and 236 in drought-sensitive genotype were distinguished and functionally annotated with 105 gene ontology (GO) terms and 77 metabolic pathways. Transcriptome profiling of drought-resistant genotype “L-82” showed up-regulation of genes mostly involved in Oxidation-reduction process, secondary metabolite biosynthesis, abiotic stress response, transferase activity and heat shock proteins. On the other hand, down-regulated genes mostly involved in signaling, oxidation-reduction process, secondary metabolite biosynthesis, auxin-responsive protein and lipid metabolism. We hypothesized that the drought tolerance in “L-82” was a result of avoidance strategies. Up-regulation of genes related to the deeper root system and adequate hydraulic characteristics to allow water uptake under water scarcity confirms our hypothesis. The transcriptomic sequences generated in this study provide information about mechanisms of acclimation to drought in the selected bread wheat landrace, “L-82”, and will help us to unravel the mechanisms underlying the ability of crops to reproduce and keep its productivity even under drought stress.

]]>
<![CDATA[Combining biophysical parameters, spectral indices and multivariate hyperspectral models for estimating yield and water productivity of spring wheat across different agronomic practices]]> https://www.researchpad.co/article/5c897762d5eed0c4847d2b85

Manipulating plant densities under different irrigation rates can have a significant impact on grain yield and water use efficiency by exerting positive or negative effects on ET. Whereas traditional spectral reflectance indices (SRIs) have been used to assess biophysical parameters and yield, the potential of multivariate models has little been investigated to estimate these parameters under multiple agronomic practices. Therefore, both simple indices and multivariate models (partial least square regression (PLSR) and support vector machines (SVR)) obtained from hyperspectral reflectance data were compared for their applicability for assessing the biophysical parameters in a field experiment involving different combinations of three irrigation rates (1.00, 0.75, and 0.50 ET) and five plant densities (D1: 150, D2: 250, D3: 350, D4: 450, and D5: 550 seeds m-2) in order to improve productivity and water use efficiency of wheat. Results show that the highest values for green leaf area, aboveground biomass, and grain yield were obtained from the combination of D3 or D4 with 1.00 ET, while the combination of 0.75 ET and D3 was the best treatment for achieving the highest values for water use efficiency. Wheat yield response factor (ky) was acceptable when the 0.75 ET was combined with D2, D3, or D4 or when the 0.50 ET was combined with D2 or D3, as the ky values of these combinations were less than or around one. The production function indicated that about 75% grain yield variation could be attributed to the variation in seasonal ET. Results also show that the performance of the SRIs fluctuated when regressions were analyzed for each irrigation rate or plant density specifically, or when the data of all irrigation rates or plant densities were combined. Most of the SRIs failed to assess biophysical parameters under specific irrigation rates and some specific plant densities, but performance improved substantially for combined data of irrigation rates and some specific plant densities. PLSR and SVR produced more accurate estimations of biophysical parameters than SRIs under specific irrigation rates and plant densities. In conclusion, hyperspectral data are useful for predicting and monitoring yield and water productivity of spring wheat across multiple agronomic practices.

]]>
<![CDATA[Nitrogen- and phosphorus-starved Triticum aestivum show distinct belowground microbiome profiles]]> https://www.researchpad.co/article/5c76fe27d5eed0c484e5b5dd

Many plants have natural partnerships with microbes that can boost their nitrogen (N) and/or phosphorus (P) acquisition. To assess whether wheat may have undiscovered associations of these types, we tested if N/P-starved Triticum aestivum show microbiome profiles that are simultaneously different from those of N/P-amended plants and those of their own bulk soils. The bacterial and fungal communities of root, rhizosphere, and bulk soil samples from the Historical Dryland Plots (Lethbridge, Canada), which hold T. aestivum that is grown both under N/P fertilization and in conditions of extreme N/P-starvation, were taxonomically described and compared (bacterial 16S rRNA genes and fungal Internal Transcribed Spacers—ITS). As the list may include novel N- and/or P-providing wheat partners, we then identified all the operational taxonomic units (OTUs) that were proportionally enriched in one or more of the nutrient starvation- and plant-specific communities. These analyses revealed: a) distinct N-starvation root and rhizosphere bacterial communities that were proportionally enriched, among others, in OTUs belonging to families Enterobacteriaceae, Chitinophagaceae, Comamonadaceae, Caulobacteraceae, Cytophagaceae, Streptomycetaceae, b) distinct N-starvation root fungal communities that were proportionally enriched in OTUs belonging to taxa Lulworthia, Sordariomycetes, Apodus, Conocybe, Ascomycota, Crocicreas, c) a distinct P-starvation rhizosphere bacterial community that was proportionally enriched in an OTU belonging to genus Agrobacterium, and d) a distinct P-starvation root fungal community that was proportionally enriched in OTUs belonging to genera Parastagonospora and Phaeosphaeriopsis. Our study might have exposed wheat-microbe connections that can form the basis of novel complementary yield-boosting tools.

]]>
<![CDATA[Training set optimization of genomic prediction by means of EthAcc]]> https://www.researchpad.co/article/5c75ac8dd5eed0c484d08a24

Genomic prediction is a useful tool for plant and animal breeding programs and is starting to be used to predict human diseases as well. A shortcoming that slows down the genomic selection deployment is that the accuracy of the prediction is not known a priori. We propose EthAcc (Estimated THeoretical ACCuracy) as a method for estimating the accuracy given a training set that is genotyped and phenotyped. EthAcc is based on a causal quantitative trait loci model estimated by a genome-wide association study. This estimated causal model is crucial; therefore, we compared different methods to find the one yielding the best EthAcc. The multilocus mixed model was found to perform the best. We compared EthAcc to accuracy estimators that can be derived via a mixed marker model. We showed that EthAcc is the only approach to correctly estimate the accuracy. Moreover, in case of a structured population, in accordance with the achieved accuracy, EthAcc showed that the biggest training set is not always better than a smaller and closer training set. We then performed training set optimization with EthAcc and compared it to CDmean. EthAcc outperformed CDmean on real datasets from sugar beet, maize, and wheat. Nonetheless, its performance was mainly due to the use of an optimal but inaccessible set as a start of the optimization algorithm. EthAcc’s precision and algorithm issues prevent it from reaching a good training set with a random start. Despite this drawback, we demonstrated that a substantial gain in accuracy can be obtained by performing training set optimization.

]]>
<![CDATA[Averting wheat blast by implementing a ‘wheat holiday’: In search of alternative crops in West Bengal, India]]> https://www.researchpad.co/article/5c76fe4ad5eed0c484e5b82c

The emergence of wheat-blast in Bangladesh in the 2015–16 wheat (Triticum aestivum L.) crop threatens the food security of South Asia. A potential spread of the disease from Bangladesh to India could have devastating impacts on India’s overall food security as wheat is its second most important staple food crop. West Bengal state in eastern India shares a 2,217 km-long border with Bangladesh and has a similar agro-ecology, enhancing the prospects of the disease entering India via West Bengal. The present study explores the possibility of a ‘wheat holiday’ policy in the nine border districts of West Bengal. Under the policy, farmers in these districts would stop wheat cultivation for at least two years. The present scoping study assesses the potential economic feasibility of alternative crops to wheat. Of the ten crops considered, maize, gram (chickpea), urad (black gram), rapeseed and mustard, and potatoes are found to be potentially feasible alternative crops. Any crop substitution would need support to ease the transition including addressing the challenges related to the management of alternative crops, ensuring adequate crop combinations and value chain development. Still, as wheat is a major staple, there is some urgency to support further research on disease epidemiology and forecasting, as well as the development and dissemination of blast-resistant wheat varieties across South Asia.

]]>
<![CDATA[Drought stress affects the protein and dietary fiber content of wholemeal wheat flour in wheat/Aegilops addition lines]]> https://www.researchpad.co/article/5c633936d5eed0c484ae624e

Wild relatives of wheat, such as Aegilops spp. are potential sources of genes conferring tolerance to drought stress. As drought stress affects seed composition, the main goal of the present study was to determine the effects of drought stress on the content and composition of the grain storage protein (gliadin (Gli), glutenin (Glu), unextractable polymeric proteins (UPP%) and dietary fiber (arabinoxylan, β-glucan) components of hexaploid bread wheat (T. aestivum) lines containing added chromosomes from Ae. biuncialis or Ae. geniculata. Both Aegilops parents have higher contents of protein and β-glucan and higher proportions of water-soluble arabinoxylans (determined as pentosans) than wheat when grown under both well-watered and drought stress conditions. In general, drought stress resulted in increased contents of protein and total pentosans in the addition lines, while the β-glucan content decreased in many of the addition lines. The differences found between the wheat/Aegilops addition lines and wheat parents under well-watered conditions were also manifested under drought stress conditions: Namely, elevated β-glucan content was found in addition lines containing chromosomes 5Ug, 7Ug and 7Mb, while chromosomes 1Ub and 1Mg affected the proportion of polymeric proteins (determined as Glu/Gli and UPP%, respectively) under both well-watered and drought stress conditions. Furthermore, the addition of chromosome 6Mg decreased the WE-pentosan content under both conditions. The grain composition of the Aegilops accessions was more stable under drought stress than that of wheat, and wheat lines with the added Aegilops chromosomes 2Mg and 5Mg also had more stable grain protein and pentosan contents. The negative effects of drought stress on both the physical and compositional properties of wheat were also reduced by the addition of these. These results suggest that the stability of the grain composition could be improved under drought stress conditions by the intraspecific hybridization of wheat with its wild relatives.

]]>
<![CDATA[Protein fortification with mealworm (Tenebrio molitor L.) powder: Effect on textural, microbiological, nutritional and sensory features of bread]]> https://www.researchpad.co/article/5c5df30cd5eed0c484580bee

In the present study, inclusion of mealworm (Tenebrio molitor L.) powder into bread doughs at 5 and 10% substitution level of soft wheat (Triticum aestivum L.) flour was tested to produce protein fortified breads. The addition of mealworm powder (MP) did not negatively affect the technological features of either doughs or breads. All the tested doughs showed the same leavening ability, whereas breads containing 5% MP showed the highest specific volume and the lowest firmness. An enrichment in protein content was observed in experimental breads where the highest values for this parameter were recorded in breads containing 10% MP. Breads fortified with 10% MP also exhibited a significant increase in the content of free amino acids, and especially in the following essential amino acids: tyrosine, methionine, isoleucine, and leucine. By contrast, no differences in nutritional quality of lipids were seen between fortified and control breads. Results of sensory analyses revealed that protein fortification of bread with MP significantly affected bread texture and overall liking, as well as crust colour, depending on the substitution level. Overall, proof of concept was provided for the inclusion of MP into bread doughs started with different leavening agents (sourdough and/or baker’s yeast), at 5 or 10% substitution level of soft wheat flour. Based on the Technology Readiness Level (TRL) scale, the proposed bread making technology can be situated at level 4 (validation in laboratory environment), thus suggesting that the production of breads with MP might easily be scaled up at industrial level. However, potential spoilage and safety issues that need to be further considered were highlighted.

]]>
<![CDATA[Genome-wide association mapping of grain yield in a diverse collection of spring wheat (Triticum aestivum L.) evaluated in southern Australia]]> https://www.researchpad.co/article/5c61e8c8d5eed0c48496f180

Wheat landraces, wild relatives and other ‘exotic’ accessions are important sources of new favorable alleles. The use of those exotic alleles is facilitated by having access to information on the association of specific genomic regions with desirable traits. Here, we conducted a genome-wide association study (GWAS) using a wheat panel that includes landraces, synthetic hexaploids and other exotic wheat accessions to identify loci that contribute to increases in grain yield in southern Australia. The 568 accessions were grown in the field during the 2014 and 2015 seasons and measured for plant height, maturity, spike length, spike number, grain yield, plant biomass, HI and TGW. We used the 90K SNP array and two GWAS approaches (GAPIT and QTCAT) to identify loci associated with the different traits. We identified 17 loci with GAPIT and 25 with QTCAT. Ten of these loci were associated with known genes that are routinely employed in marker assisted selection such as Ppd-D1 for maturity and Rht-D1 for plant height and seven of those were detected with both methods. We identified one locus for yield per se in 2014 on chromosome 6B with QTCAT and three in 2015, on chromosomes 4B and 5A with GAPIT and 6B with QTCAT. The 6B loci corresponded to the same region in both years. The favorable haplotypes for yield at the 5A and 6B loci are widespread in Australian accessions with 112 out of 153 carrying the favorable haplotype at the 5A locus and 136 out of 146 carrying the favorable haplotype at the 6A locus, while the favorable haplotype at 4B is only present in 65 out of 149 Australian accessions. The low number of yield QTL in our study corroborate with other GWAS for yield in wheat, where most of the identified loci have very small effects.

]]>
<![CDATA[Rainfall affects leaching of pre-emergent herbicide from wheat residue into the soil]]> https://www.researchpad.co/article/5c5df35fd5eed0c4845811ca

No-tillage with stubble retention is a widely used cropping system for its conservation and yield benefits. The no-tillage farming system in southern Australia relies heavily on herbicides for weed management, but heavy crop residues may have a negative impact on the activity of pre-emergent herbicides applied. Any herbicide intercepted by the crop residue may not reach the soil surface without timely rainfall and may dissipate due to volatilisation, photo-degradation and/or microbial activity. Two experiments were carried out to investigate the interception of prosulfocarb, pyroxasulfone, and trifluralin herbicides by wheat residue and retention following simulated rainfall. For the first experiment, there were four simulated rainfall amounts (0, 5, 10, and 20 mm), three intensities (5, 10, and 20 mm h–1) and five application times (immediately after spraying herbicide, 6 h, 1, 7, and 14 days after spraying). In the second experiment, 20 mm of rainfall was applied at 10 mm h–1 in either 4 × 5 mm rainfall events over two days, 2 × 10 mm rainfall events over one day, or a single 20 mm rainfall event, with a no-rainfall control treatment. Bioassays were used to assess the herbicide activity/availability in the soil and remaining on the residue, using cucumber (Cucumis sativus L.) and Italian ryegrass (Lolium multiflorum Lam.) as indicator plants. At higher rainfall amounts, most of the herbicide leached from the stubble into the soil soon after application; more so with rain in one event rather than multiple events. However, the intensity of rainfall had no effect. Pyroxasulfone leached easily from the residue to the soil to potentially offer good weed control, prosulfocarb had an intermediary leaching effect, while only a small amount of trifluralin leached from stubble after rain. Therefore, in no-tillage situations with large amounts of crop residue present on the soil surface, herbicides that leach easily from the residue should be considered, like pyroxasulfone.

]]>
<![CDATA[Metabarcoding targeting the EF1 alpha region to assess Fusarium diversity on cereals]]> https://www.researchpad.co/article/5c42436cd5eed0c4845e0155

Fusarium head blight (FHB) is a major cereal disease caused by a complex of Fusarium species. These species vary in importance depending on climatic conditions, agronomic factors or host genotype. In addition, Fusarium species can release toxic secondary metabolites. These mycotoxins constitute a significant food safety concern as they have health implications in both humans and animals. The Fusarium species involved in FHB differ in their pathogenicity, ability to produce mycotoxins, and fungicide sensitivity. Accurate and exhaustive identification of Fusarium species in planta is therefore of great importance. In this study, using a new set of primers targeting the EF1α gene, the diversity of Fusarium species on cereals was evaluated using Illumina high-throughput sequencing. The PCR amplification parameters and bioinformatic pipeline were optimized with mock and artificially infected grain communities and further tested on 65 field samples. Fusarium species were retrieved from mock communities and good reproducibility between different runs or PCR cycle numbers was be observed. The method enabled the detection of as few as one single Fusarium-infected grain in 10,000. Up to 17 different Fusarium species were detected in field samples of barley, durum and soft wheat harvested in France. This new set of primers enables the assessment of Fusarium diversity by high-throughput sequencing on cereal samples. It provides a more exhaustive picture of the Fusarium community than the currently used techniques based on isolation or species-specific PCR detection. This new experimental approach may be used to show changes in the composition of the Fusarium complex or to detect the emergence of new Fusarium species as far as the EF1α sequence of these species show a sufficient amount of polymorphism in the portion of sequence analyzed. Information on the distribution and prevalence of the different Fusarium species in a given geographical area, and in response to various environmental factors, is of great interest for managing the disease and predicting mycotoxin contamination risks.

]]>
<![CDATA[Imputation accuracy of wheat genotyping-by-sequencing (GBS) data using barley and wheat genome references]]> https://www.researchpad.co/article/5c3d0126d5eed0c484038b91

Genotyping-by-sequencing (GBS) provides high SNP coverage and has recently emerged as a popular technology for genetic and breeding applications in bread wheat (Triticum aestivum L.) and many other plant species. Although GBS can discover millions of SNPs, a high rate of missing data is a major concern for many applications. Accurate imputation of those missing data can significantly improve the utility of GBS data. This study compared imputation accuracies among four genome references including three wheat references (Chinese Spring survey sequence, W7984, and IWGSC RefSeq v1.0) and one barley reference genome by comparing imputed data derived from low-depth sequencing to actual data from high-depth sequencing. After imputation, the average number of imputed data points was the highest in the B genome (~48.99%). The D genome had the lowest imputed data points (~15.02%) but the highest imputation accuracy. Among the four reference genomes, IWGSC RefSeq v1.0 reference provided the most imputed data points, but the lowest imputation accuracy for the SNPs with < 10% minor allele frequency (MAF). The W7984 reference, however, provided the highest imputation accuracy for the SNPs with < 10% MAF.

]]>
<![CDATA[Cereal aphids differently affect benzoxazinoid levels in durum wheat]]> https://www.researchpad.co/article/5c0ed77bd5eed0c484f14221

Aphids are major pests in cereal crops that cause direct and indirect damage leading to yield reduction. Despite the fact that wheat provides 20% of the world’s caloric and protein diet, its metabolic responses to aphid attack, in general, and specifically its production of benzoxazinoid defense compounds are poorly understood. The objective of this study was to compare the metabolic diversity of durum wheat seedlings (Triticum turgidum ssp. durum) under attack by three different cereal aphids: i) the English grain aphid (Sitobion avenae Fabricius), ii) the bird cherry-oat aphid (Rhopalosiphum padi L.), and iii) the greenbug aphid (Schizaphis graminum Rondani), which are some of the most destructive aphid species to wheat. Insect progeny bioassays and metabolic analyses using chromatography/Q-Exactive/mass spectrometry non-targeted metabolomics and a targeted benzoxazinoid profile were performed on infested leaves. The insect bioassays revealed that the plants were susceptible to S. graminum, resistant to S. avenae, and mildly resistant to R. padi. The metabolic analyses of benzoxazinoids suggested that the predominant metabolites DIMBOA (2,4-dihydroxy-7-methoxy-1,4-benzoxazin- 3-one) and its glycosylated form DIMBOA-glucoside (Glc) were significantly induced upon both S. avenae, and R. padi aphid feeding. However, the levels of the benzoxazinoid metabolite HDMBOA-Glc (2-hydroxy-4,7-dimethoxy-1,4-benzoxazin-3-one glucoside) were enhanced due to the feeding of S. avenae and S. graminum aphids, to which Svevo was the most resistant and the most susceptible, respectively. The results showed a partial correlation between the induction of benzoxazinoids and aphid reproduction. Overall, our observations revealed diverse metabolic responses of wheat seedlings to cereal aphid feeding.

]]>