December
2013
, Volume
103
, Number
12
Pages
1,235
-
1,242
Authors
F. Workneh,
D. C. Henne,
J. A. Goolsby,
J. M. Crosslin,
S. D. Whipple,
J. D. Bradshaw,
A. Rashed,
L. Paetzold,
R. M. Harveson, and
C. M. Rush
Affiliations
First, eighth, and tenth authors: Texas A&M AgriLife Research, Bushland 79012; second author: Texas A&M AgriLife Research, Weslaco 78596; third author: United States Department of Agriculture–Agricultural Research Service (USDA-ARS), Edinburg, TX 78596; fourth author: USDA-ARS, Prosser, WA 99350; fifth, sixth, and ninth authors: University of Nebraska, Panhandle Research and Extension Center, Scottsbluff 69361; and seventh author: University of Idaho, R&E Center, Aberdeen 83210.
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RelatedArticle
Accepted for publication 8 July 2013.
Abstract
ABSTRACT
Potato zebra chip (ZC), caused by the bacterial pathogen ‘Candidatus Liberibacter solanacearum’, which is vectored by the potato psyllid (Bactericera cockerelli), has caused widespread damage to U.S. potato production ever since its first discovery in south Texas in 2000. To determine the influence of environmental factors and management practices on ZC occurrence, data on management and meteorological variables, field locations, and psyllid counts were collected over a 3-year period (2010 to 2012) from six locations across the central United States (south Texas to Nebraska). At these locations, ZC-symptomatic plants were counted in 26 fields from systematically established 20 m × 30 m plots around the field edges and field interiors. Mean numbers of symptomatic plants per plot were classified into two intensity classes (ZC ≤ 3 or ZC > 3) and subjected to discriminant function and logistic regression analyses to determine which factors best distinguish between the two ZC intensity classes. Of all the variables, location, planting date, and maximum temperature were found to be the most important in distinguishing between ZC intensity classes. These variables correctly classified 88.5% of the fields into either of the two ZC-intensity classes. Logistic regression analysis of the individual variables showed that location accounted for 90% of the variations, followed by planting date (86%) and maximum temperature (70%). There was a low but significant (r = –0.44983, P = 0.0211) negative correlation between counts of psyllids testing positive for pathogen and latitudinal locations, indicating a south-to-north declining trend in counts of psyllids testing positive for the pathogen. A similar declining trend also was observed in ZC occurrence (r = –0.499, P = 0.0094).
JnArticleKeywords
Additional keywords:
α-proteobacterium, ROC curve.
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© 2013 The American Phytopathological Society