Grapevine yellows diseases and their phytoplasma agents : biology and detection /

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Bibliographic Details
Imprint:	Cham : Springer, 2017.
Description:	1 online resource (105 pages)
Language:	English
Series:	SpringerBriefs in agriculture SpringerBriefs in agriculture.
Subject:	Grapes -- Diseases and pests. Agricultural science. Microbiology (non-medical) Plant pathology & diseases. NATURE -- Reference. SCIENCE -- Life Sciences -- Biology. SCIENCE -- Life Sciences -- General. GARDENING -- Fruit. TECHNOLOGY & ENGINEERING -- Agriculture -- General. Grapes -- Diseases and pests. Electronic book. Electronic books.
Format:	E-Resource Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/11271574

Hidden Bibliographic Details
Other authors / contributors:	Dermastia, Marina. Bertaccini, Assunta. Constable, Fiona. Mehle, Nataša.
ISBN:	9783319506487 331950648X 9783319506470 3319506471
Digital file characteristics:	text file PDF
Notes:	Includes bibliographical references and index. Print version record.
Summary:	This work is to compile our current knowledge on GY phytoplasma biology at the genomic, transcriptomics, proteomics and metabolomics level, as well as to summarize the approaches for their detection. Phytoplasma are the most poorly characterized plant pathogenic bacteria from the Mollicutes class. In recent years new biostatistics and bioinformatics approaches have improved our understanding of their biology and interactions with host grapevines and a great improvement has been made toward their molecular detection, both in laboratories and on-site. They have a broad range of plant hosts among the monocots and dicots, and diseases of many important crops are associated with these pathogens. At least ten taxonomically unrelated phytoplasmas, one of them a quarantine pest in Europe, have been associated with grapevine yellows diseases (GY), which have great economic impact on viticulture worldwide.
Other form:	Print version: Dermastia, Marina. Grapevine Yellows Diseases and Their Phytoplasma Agents : Biology and Detection. Cham : Springer International Publishing, ©2017 9783319506470
Standard no.:	10.1007/978-3-319-50648-7

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