Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Junchan Wang"'
Autor:
Xujiang Wu, Junchan Wang, Di Wu, Wei Jiang, Zhifu Gao, Dongsheng Li, Rongling Wu, Derong Gao, Yong Zhang
Publikováno v:
Frontiers in Plant Science, Vol 13 (2022)
IntroductionWheat sharp eyespot caused by Rhizoctonia cerealis is a serious pathogenic disease affecting plants. The effective strategy for controlling this disease is breeding resistant cultivar. However, to date, no wheat varieties are fully resist
Externí odkaz:
https://doaj.org/article/34b8fb4c48df4e63b018fb4279494776
Autor:
Wenjing Hu, Derong Gao, Hongya Wu, Jian Liu, Chunmei Zhang, Junchan Wang, Zhengning Jiang, Yeyu Liu, Dongsheng Li, Yong Zhang, Chengbin Lu
Publikováno v:
BMC Plant Biology, Vol 20, Iss 1, Pp 1-13 (2020)
Abstract Background Fusarium head blight (FHB), primarily caused by Fusarium graminearum, is a major threat to wheat production and food security worldwide. Breeding stably and durably resistant cultivars is the most effective approach for managing a
Externí odkaz:
https://doaj.org/article/0fb0a498728c44f4abecdb229f4a83b5
Autor:
Hongya Wu, Zunjie Wang, Xiao Zhang, Junchan Wang, Wenjing Hu, Hui Wang, Derong Gao, Edword Souza, Shunhe Cheng
Publikováno v:
Plants, Vol 11, Iss 23, p 3370 (2022)
Weak-gluten wheat is the main raw material for crisp and soft foods such as cookies, cakes, and steamed breads in China. However, it remains challenging to find an appropriate fertilization regime to balance the yield and quality of wheat for special
Externí odkaz:
https://doaj.org/article/e24f8b8c31514bbcb40f17cbff3e2f30
Publikováno v:
Remote Sensing, Vol 14, Iss 6, p 1338 (2022)
Tiller are an important biological characteristic of wheat, a primary food crop. Accurate estimation of tiller number can help monitor wheat growth and is important in forecasting wheat yield. However, because of leaf cover and other factors, it is d
Externí odkaz:
https://doaj.org/article/b7cdc4a1b2644110b29e5134fbdd4c03
Autor:
Xujiang Wu, Junchan Wang, Lei Li, Xiao Zhang, Wei Jiang, Man Li, Derong Gao, Boqiao Zhang, Chengbin Lu
Publikováno v:
Journal of Plant Pathology. 104:1383-1396
Bread wheat (Triticum aestivum L.) is the most widely grown crop in the world. Rhizoctonia cerealis, the causal agent of wheat sharp eyespot disease, has 21 become epidemic in many countries. In the present study, we performed transcriptome analysis
Autor:
Tao Liu, Yuanyuan Zhao, Fei Wu, Junchan Wang, Chen Chen, Yuzhuang Zhou, Chengxin Ju, Zhongyang Huo, Xiaochun Zhong, Shengping Liu, Chengming Sun
Publikováno v:
Precision Agriculture. 24:353-374
Autor:
Wenjing Hu, Derong Gao, Hongya Wu, Liu, Jian, Chunmei Zhang, Junchan Wang, Zhengning Jiang, Yeyu Liu, Dongsheng Li, Zhang, Yong, Chengbin Lu
Additional file 1: Table S1 171 wheat accessions used in the genome-wide association study (GWAS) for FHB severities and their origins, Table S2 Marker-trait associations (MTAs) for FHB resistance in 171 wheat accessions identified by the Tassel v5.0
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7be69453ca962267387df0b1bec62293
Publikováno v:
IFIP Advances in Information and Communication Technology
11th International Conference on Computer and Computing Technologies in Agriculture (CCTA)
11th International Conference on Computer and Computing Technologies in Agriculture (CCTA), Aug 2017, Jilin, China. pp.31-44, ⟨10.1007/978-3-030-06179-1_4⟩
Computer and Computing Technologies in Agriculture XI ISBN: 9783030061784
CCTA (2)
11th International Conference on Computer and Computing Technologies in Agriculture (CCTA)
11th International Conference on Computer and Computing Technologies in Agriculture (CCTA), Aug 2017, Jilin, China. pp.31-44, ⟨10.1007/978-3-030-06179-1_4⟩
Computer and Computing Technologies in Agriculture XI ISBN: 9783030061784
CCTA (2)
International audience; Biomass and the chlorophyll content are important indicators to measure the growth and development of grasslands. Modeling using hyperspectral data is an important means to monitor grassland growth and development. In this pap
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2d100186a6e4ae8d5ac946336b369fbd
https://hal.inria.fr/hal-02111540/document
https://hal.inria.fr/hal-02111540/document
Publikováno v:
IFIP Advances in Information and Communication Technology
11th International Conference on Computer and Computing Technologies in Agriculture (CCTA)
11th International Conference on Computer and Computing Technologies in Agriculture (CCTA), Aug 2017, Jilin, China. pp.452-461, ⟨10.1007/978-3-030-06137-1_41⟩
Computer and Computing Technologies in Agriculture XI ISBN: 9783030061364
CCTA (1)
11th International Conference on Computer and Computing Technologies in Agriculture (CCTA)
11th International Conference on Computer and Computing Technologies in Agriculture (CCTA), Aug 2017, Jilin, China. pp.452-461, ⟨10.1007/978-3-030-06137-1_41⟩
Computer and Computing Technologies in Agriculture XI ISBN: 9783030061364
CCTA (1)
International audience; In order to alleviate the difficulties in collecting indexes for the analysis of farmland weed communities, we implemented a computer vision technology-based method for the identification of farmland weeds at the species level
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d99b5827181161d5294244c2fd873c7d
https://hal.inria.fr/hal-02124257/file/478291_1_En_41_Chapter.pdf
https://hal.inria.fr/hal-02124257/file/478291_1_En_41_Chapter.pdf
Publikováno v:
2011 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC).
The purpose of this study is to further improve the accuracy of predicting winter wheat grain quality with remote sensing, and to enhance the prediction mechanism. In order to predict grain starch content (GSC) in winter wheat using HJ-1A/1B images,