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97 results for “Chickpea”
Chickpea flowering, carbon isotope, seed weight in a factorial of 20 genotypes and 8 environments
<p>Chickpea was phenotyped for time to flowering, carbon isotope composition at peak biomass, and seed weight at maturity in a factorial combining 20 genotypes, 2 sowing dates, 2 sowing regimes over two seasons. </p>
Figure 5 in Biochemical, physiological, and growth evaluation of different chickpea genotypes under varying salinity regimes
Figure 5. Effect of salinity stress on stomatal conductance (a), and transpiration rate (b) of chickpea genotypes: salinity levels=S0: 0 mM NaCl, S1: 50 mM NaCl, S2:100 mM NaCl, S3: 150 mM NaCl. Genotypes= KK-2, Bhakkar-2011, Bittle-98, Punjab-2008, CM-98. Error bar shows standard error.
Figure 2 in Biochemical, physiological, and growth evaluation of different chickpea genotypes under varying salinity regimes
Figure 2. Effect of salinity stress yield (a), and R:S (b) of chickpea genotypes: salinity levels=S0: 0 mM NaCl, S1: 50 mM NaCl, S2:100 mM NaCl, S3: 150 mM NaCl. Genotypes= KK-2, Bhakkar-2011, Bittle-98, Punjab-2008, CM-98. Data labels represnts the level of significance for multiple comparison between all combination of treatments @ 0.05 probability level. Error bar shows standard error.
Figure 4 in Biochemical, physiological, and growth evaluation of different chickpea genotypes under varying salinity regimes
Figure 4. Effect of salinity stress on crude protein content (a), Reducing sugars (b) and total carbohydrates (c) of chickpea genotypes: salinity levels=S0: 0 mM NaCl, S1: 50 mM NaCl, S2:100 mM NaCl, S3: 150 mM NaCl. Genotypes= KK-2, Bhakkar-2011, Bittle-98, Punjab-2008, CM-98. Data labels represnts the level of significance for multiple comparison between all combination of treatments @ 0.05 probability level. Error bar shows standard error.
Figure 3 in Biochemical, physiological, and growth evaluation of different chickpea genotypes under varying salinity regimes
Figure 3. Effect of salinity stress on proline content (a), lipid peroxidation (b) and H 2 O 2 (c) of chickpea genotypes: salinity levels=S0: 0 mM NaCl, S1: 50 mM NaCl, S2:100 mM NaCl, S3: 150 mM NaCl. Genotypes= KK-2, Bhakkar-2011, Bittle-98, Punjab-2008, CM-98. Data labels represnts the level of significance for multiple comparison between all combination of treatments @ 0.05 probability level. Error bar shows standard error.
Figure 1 in Biochemical, physiological, and growth evaluation of different chickpea genotypes under varying salinity regimes
Figure 1. Effect of salinity stress on SL (a) and RL (b) of chickpea genotypes: salinity levels=S0: 0 mM NaCl, S1: 50 mM NaCl, S2:100 mM NaCl, S3: 150 mM NaCl. Genotypes= KK-2, Bhakkar-2011, Bittle-98, Punjab-2008, CM-98. Data labels represnts the level of significance for multiple comparison between all combination of treatments @ 0.05 probability level. Error bar shows standard error.
Figure 2 in Response of Rhizobacterial strains and organic amendments on chickpea growth
Figure 2. Soil organic matter as affected by Rhizobacterial strains. T: control. T: Enterobactor asburiae. T: Enterobacter mori. T: 1 2 3 4 rhizobiu ceceri. T5: Pesodomonas aeruginosa. T6: Pesodomonas putida.
Figure 1 in Response of Rhizobacterial strains and organic amendments on chickpea growth
Figure 1. Soil Nitrogen as affected by Rhizobacterial strains. T 1: control. T 2: Enterobactor asburiae. T 3: Enterobacter mori. T 4: rhizobiu ceceri. T 5: Pesodomonas aeruginosa. T: Pesodomonas putida.
Figure 1 in Antioxidant status and their enhancements strategies for water stress tolerance in chickpea
Figure 1. (a) Influence of exogenous application of osmoprotectants on crop growth rate (g m-2 day-1) of chickpea genotypes in Bahawalpur; (b) Influence of exogenous application of osmoprotectants on crop growth rate (g m-2 day-1) of chickpea genotypes in Cholistan. Whereas D1= well watered; D2= Drought at flowering+ pod formation + grain filling stage; D3= Drought at flowering stage; DAS, Days after sowing.
Figure 2 in Exogenously applied nutrients can improve the chickpea productivity under water stress conditions by modulating the antioxidant enzyme system
Figure 2. Effect of foliar application of nutrients on relative growth rate (g g-1 day-1) of chickpea genotypes in Bahawalpur (a) and Cholistan (b). Whereas D1= well watered; D2= Drought at flowering+ pod formation + grain filling stage; D3= Drought at flowering stage; DAS= days after sowing.
Figure 1 in Exogenously applied nutrients can improve the chickpea productivity under water stress conditions by modulating the antioxidant enzyme system
Figure 1. Effect of foliar application of nutrients on crop growth rate (g m-2 day-1) of chickpea genotypes in Bahawalpur (a) and Cholistan (b). Whereas D1= well watered; D2=Drought at flowering+ pod formation + grain filling stage; D3= Drought at flowering stage; DAS= days after sowing.
Novel Genomic Regions linked to Ascochyta blight Resistance in two differentially resistant cultivars of chickpea
<p><em>Ascochyta</em> blight (AB) caused by the fungal pathogen <em>Ascochyta rabiei</em> is a devastating foliar disease of chickpea (<em>Cicer arietinum</em> L.). Genotyping-by-sequencing (GBS) has been used in the current study for the identification of AB associated quantitative trait loci (QTLs) and their gene(s). We evaluated genotyping-by-sequencing (GBS)-based approach for mapping QTLs associated with AB resistance in chickpea using two recombinant inbred lines populations (AB<sub>3279</sub> and AB<sub>482</sub>) derived from two crosses ILC 1929 X ILC 3279 and ILC 1929 X ILC 482, under six different environments. In total, twenty-one different genomic regions were identified on linkage groups CalG02 and CalG04 pertaining to AB resistance in both populations AB<sub>3279</sub> and AB<sub>482</sub>. Four genomic regions were detected on CalG02 in the population AB<sub>3279</sub> and nine major genomic regions were associated with AB resistance on CaLG04, five out of them were common to both resistant parents ‘ILC3279’ and ‘ILC482’, and eight minor genomic regions with two out of them common between both populations. These regions contain 1,118 SNPs significantly associated (p ≤ 0.001) with AB resistance. Gene ontology (GO) assigned these QTLs to 319 genes, many of which were associated with stress and disease resistance, with most important genes belonging to resistance gene families including Leucine-Rich Repeat (LRR), and transcription factors families. Our results may refer to the flowering-associated gene GIGANTEA as a possible key factor in AB resistance in chickpea. The results have narrowed the AB resistance associated regions on the chickpea physical map and the associated markers will help in breeding programs for chickpea improvement.</p>
Chickpea genetic variants with dbSNP and pseudoDB
<p>Chickpea genetic variants with dbSNP and pseudoDB</p>
Chickpea pseudo database
<p>Chickpea pseudo database</p>
Chickpea flowering, carbon isotope, seed weight in a factorial of 20 genotypes and 8 environments
Open the record for dataset details and reuse information.
3D photogrammetric reconstructions of individual chickpea plants
<p>3D point clouds and meshed models of individual chickpea plants were reconstructed using photogrammetry. This dataset serves as a companion to the article “Open source 3D phenotyping of chickpea plant architecture across plant development” uploaded as a preprint to <em>BioRxiv</em> (<a href="https://doi.org/10.1101/2020.09.08.288530">https://doi.org/10.1101/2020.09.08.288530</a>).</p> <p><strong>Description of the dataset</strong></p> <p>Individual chickpea plants were imaged using a low-cost, automated turntable and camera set up. Dense point clouds were generated in <a href="http://ccwu.me/vsfm/">VisualSFM</a>, these point clouds were cleaned (denoised and non-plant points removed), scaled and then meshed using a ball-pivoting algorithm. More information on the imaging and reconstruction workflow can be found in our <em>BioRxiv</em> preprint (<a href="https://doi.org/10.1101/2020.09.08.288530">https://doi.org/10.1101/2020.09.08.288530</a>). Scaled, clean point clouds and meshed models are provided in this dataset. All files are in the .PLY format and can be viewed using most 3D imaging software packages, including <a href="https://github.com/cnr-isti-vclab/meshlab">Meshlab</a>.</p> <p>Files are named using the following convention:<br> "GENOTYPE_PLANTIDNUMBER_GROUNDTRUTHINGORWEEKS_POINTCLOUDORMESHED"<br> Where:<br> GENOTYPE is the chickpea genotype.<br> PLANTIDNUMBER is the unique identifier for each plant.<br> GROUNDTRUTHINGORWEEKS refers to whether the plant was used for validation against ground truthing measurements or if growth was tracked after germination.<br> POINTCLOUDORMESHED refers to if the .ply file is a dense point cloud or a meshed 3D model.</p> <p><strong>Plant material</strong></p> <p>Three commercial Australian chickpea cultivars (Genesis Kalkee, PBA Hattrick and PBA Slasher) were grown in pots in a glasshouse and were imaged once per week for five weeks after germination. Three genotypes selected from local and international sources (ICC5878, SonSla and PUSA76) were grown in pots outdoors and were imaged once at five weeks post germination.</p>
Contrasting patterns in biomass allocation, root morphology and mycorrhizal symbiosis for phosphorus acquisition among 20 chickpea genotypes with different amounts of rhizosheath carboxylates
<p>1. Adjustments in root biomass allocation, root morphology, carboxylate exudation and mycorrhizal symbiosis are well-known strategies for plants to cope with phosphorus (P) deficiency. Large genotypic variation in these functional traits has been demonstrated within numerous species. Yet, whether these functional traits are coordinated differently among genotypes of a species to enhance P acquisition remains unknown.</p> <p>2. We characterised 11 root functional traits associated with P acquisition in 20 chickpea genotypes with contrasting amounts of rhizosheath carboxylates, grown in a glasshouse with severely limiting insoluble (10 mg kg<sup>–1</sup> FePO<sub>4</sub>), moderately limiting soluble (10 mg kg<sup>–1</sup> KH<sub>2</sub>PO<sub>4</sub>), and adequate (50 mg kg<sup>–1</sup> KH<sub>2</sub>PO<sub>4</sub>) P supply.</p> <p>3. Substantial variation was found among genotypes in root functional traits associated with P acquisition. Genotypes with a large amount of carboxylates (HRC) had thinner roots, and a lower root mass fraction and root mass density, but higher specific root length and colonisation by arbuscular mycorrhizal fungi (AMF) than genotypes with a small amount of rhizosheath carboxylates.</p> <p>4. In response to soil P availability, chickpea genotypes showed large plasticity in root biomass allocation, rhizosheath pH, carboxylate amount, and colonisation by AMF, but a limited response in most root morphological traits (i.e. mean root diameter, root mass density and specific root length). Shoot P content was strongly correlated with different root functional traits in the three P treatments.</p> <p>5. Our findings suggest a range of predictable relationships between root functional traits among chickpea genotypes; those with HRC tended to have relatively thinner roots with lower cost of root construction, while allocating more resources to carboxylate exudation and colonisation by AMF. The shift in the relationships between shoot P content and root functional traits indicates that <span class="fontstyle01"><span>root traits and/or trait combinations in chickpea vary in a manner that enhances P acquisition under specific soil P conditions (i.e. P sources/ levels)</span></span>. Such knowledge provides valuable information for chickpea genotype breeding and our understanding of evolution of traits with improved root/rhizosphere functioning.</p> <p> </p>
Data - Krieg et al. Greater ecophysiological stress tolerance in the core environment than in extreme environments of wild chickpea (Cicer reticulatum)
<p>Data used in analyses and code to produce figures.</p>
Potential of chickpea flours with different microstructures as multifunctional ingredient in an instant soup application
<p>The data used for the graphs in the paper: Noordraven LEC, Kim H-J, Hoogland H, Grauwet T, Van Loey AM. Potential of Chickpea Flours with Different Microstructures as Multifunctional Ingredient in an Instant Soup Application. <em>Foods</em>. 2021; 10(11):2622. https://doi.org/10.3390/foods10112622.</p>
Flavour Stability of Sterilised Chickpeas Stored in Pouches
<p>Final data used for figures in the paper Noordraven, L. E.C., Petersen, M. A., Van Loey, A. M., & Bredie, W. L. (2021). Flavour stability of sterilised chickpeas stored in pouches. <em>Current Research in Food Science</em>.: <a href="https://doi.org/10.1016/j.crfs.2021.10.011?_ga=2.250986822.1988728626.1635610214-937081454.1617605331">https://doi.org/10.1016/j.crfs.2021.10.011</a></p>
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