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Xianchun Xia

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Xianchun Xia
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Xianchun Xia
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0000-0003-2071-197X

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2008 - 200912010 - 20182
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Keyword: Bread Wheat × Item Type: Publication ×

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Now showing 1 - 3 of 3
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    Rapid separation and characterization of grain water-soluble proteins in bread wheat cultivars (Triticum aestivum L.) by capillary electrophoresis
    (Canadian Science Publishing, 2008) Aili Wang; Yu-he Pei; Xiaohui Li; Yan-zhen Zhang; Qian Zhang; He Zhonghu; Xianchun Xia; Appels, R.; Wujun Ma; Xiu-Qiang Huang; Yueming Yan
    Publication
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    Characterization of Fusarium head blight resistance gene fhb1 and its putative ancestor in Chinese wheat germplasm
    (Institute of Crop Sciences, 2018) Zhanwang Zhu; Dengan Xu; Cheng Shun-He; Chunbao Gao; Xianchun Xia; Yuanfeng Hao; He Zhonghu
    Enhancing resistance to Fusarium head blight (FHB) has become one of important breeding objectives in the major wheat-growing regions in China. A prominent locus Fhb1 conferring stable FHB resistance with the largest effect is the major source of resistance in wheat breeding. Understanding the distribution and putative donor of Fhb1 in Chinese wheat cultivars will facilitate the application of this gene and thus benefit FHB resistance breeding in China. Haplotype analysis of PFT (pore-forming toxin-like), HC (HCBT-like defense response protein) and His (histidine-rich calcium-binding protein) genes in the Fhb1 region of 229 wheat cultivars and advanced lines indicated that PFT-I/His-I was a resistant haplotype. Both pedigree and marker (or sequence) information revealed that Fhb1 in Chinese wheat cultivars was mainly derived from Sumai 3 and Ningmai 9, in which Ningmai 9 was the major donor. The Fhb1 diagnostic markers PFT-CAPS and His-InDel developed in this study can be used effectively in marker-assisted selection for improving FHB resistance.
    Publication
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    Time-series multispectral indices from unmanned aerial vehicle imagery reveal senescence rate in bread wheat
    (MDPI, 2018) Hassan, M.A.; Mengjiao Yang; Rasheed, A.; Xiuliang Jin; Xianchun Xia; Yonggui Xiao; He Zhonghu
    Detection of senescence's dynamics in crop breeding is time consuming and needs considerable details regarding its rate of progression and intensity. Normalized difference red-edge index (NDREI) along with four other spectral vegetative indices (SVIs) derived from unmanned aerial vehicle (UAV) based spatial imagery, were evaluated for rapid and accurate prediction of senescence. For this, 32 selected winter wheat genotypes were planted under full and limited irrigation treatments. Significant variations for all five SVIs: green normalize difference vegetation index (GNDVI), simple ratio (SR), green chlorophyll index (GCI), red-edge chlorophyll index (RECI), and normalized difference red-edge index (NDREI) among genotypes and between treatments, were observed from heading to late grain filling stages. The SVIs showed strong relationship (R2 = 0.69 to 0.78) with handheld measurements of chlorophyll and leaf area index (LAI), while negatively correlated (R2 = 0.75 to 0.77) with canopy temperature (CT) across the treatments. NDREI as a new SVI showed higher correlations with ground data under both treatments, similarly as exhibited by other four SVIs. There were medium to strong correlations (r = 0.23-0.63) among SVIs, thousand grain weight (TGW) and grain yield (GY) under both treatments. Senescence rate was calculated by decreasing values of SVIs from their peak values at heading stage, while variance for senescence rate among genotypes and between treatments could be explained by SVIs variations. Under limited irrigation, 10% to 15% higher senescence rate was detected as compared with full irrigation. Principle component analysis corroborated the negative association of high senescence rate with TGW and GY. Some genotypes, such as Beijing 0045, Nongda 5181, and Zhongmai 175, were selected with low senescence rate, stable TGW and GY in both full and limited irrigation treatments, nearly in accordance with the actual performance of these cultivars in field. Thus, SVIs derived from UAV appeared as a promising tool for rapid and precise estimation of senescence rate at maturation stages.
    Publication