Field application of star polymer-delivered chitosan to amplify plant defense against potato late blight

2021 ◽  
Vol 417 ◽  
pp. 129327
Author(s):  
Xiaodan Wang ◽  
Kangkai Zheng ◽  
Wenyu Cheng ◽  
Jie Li ◽  
Xiangxiu Liang ◽  
...  
2018 ◽  
Vol 34 (6) ◽  
pp. 4-11
Author(s):  
V.K. Chizhik ◽  
◽  
E.A. Sokolova ◽  
V.V. Martynov ◽  
M.A. Kuznetsova ◽  
...  

2014 ◽  
Vol 20 (12) ◽  
pp. 3621-3631 ◽  
Author(s):  
Adam H. Sparks ◽  
Gregory A. Forbes ◽  
Robert J. Hijmans ◽  
Karen A. Garrett

2014 ◽  
Vol 13 (8) ◽  
pp. 2101-2113 ◽  
Author(s):  
Harold J. G. Meijer ◽  
Francesco M. Mancuso ◽  
Guadalupe Espadas ◽  
Michael F. Seidl ◽  
Cristina Chiva ◽  
...  

Plant Disease ◽  
2012 ◽  
Vol 96 (7) ◽  
pp. 935-942 ◽  
Author(s):  
Toky Rakotonindraina ◽  
Jean-Éric Chauvin ◽  
Roland Pellé ◽  
Robert Faivre ◽  
Catherine Chatot ◽  
...  

The Shtienberg model for predicting yield loss caused by Phytophthora infestans in potato was developed and parameterized in the 1990s in North America. The predictive quality of this model was evaluated in France for a wide range of epidemics under different soil and weather conditions and on cultivars different than those used to estimate its parameters. A field experiment was carried out in 2006, 2007, 2008, and 2009 in Brittany, western France to assess late blight severity and yield losses. The dynamics of late blight were monitored on eight cultivars with varying types and levels of resistance. The model correctly predicted relative yield losses (efficiency = 0.80, root mean square error of prediction = 13.25%, and bias = –0.36%) as a function of weather and the observed disease dynamics for a wide range of late blight epidemics. In addition to the evaluation of the predictive quality of the model, this article provides a dataset that describes the development of various late blight epidemics on potato as a function of weather conditions, fungicide regimes, and cultivar susceptibility. Following this evaluation, the Shtienberg model can be used with confidence in research and development programs to better manage potato late blight in France.


2017 ◽  
Vol 2 (1) ◽  
pp. 90-91
Author(s):  
Virupaksh U. Patil ◽  
G. Vanishree ◽  
Debasis Pattanayak ◽  
Sanjeev Sharma ◽  
Vinay Bhardwaj ◽  
...  

1992 ◽  
Vol 69 (10) ◽  
pp. 635-644 ◽  
Author(s):  
J. M. Parker ◽  
H. D. Thurston ◽  
M. J. Villarreal-Gonzalez ◽  
W. E. Fry

2010 ◽  
Vol 100 (11) ◽  
pp. 1146-1161 ◽  
Author(s):  
Peter Skelsey ◽  
Walter A. H. Rossing ◽  
Geert J. T. Kessel ◽  
Wopke van der Werf

Strategic spatial patterning of crop species and cultivars could make agricultural landscapes less vulnerable to plant disease epidemics, but experimentation to explore effective disease-suppressive landscape designs is problematic. Here, we present a realistic, multiscale, spatiotemporal, integrodifference equation model of potato late blight epidemics to determine the relationship between spatial heterogeneity and disease spread, and determine the effectiveness of mixing resistant and susceptible cultivars at different spatial scales under the influence of weather. The model framework comprised a landscape generator, a potato late blight model that includes host and pathogen life cycles and fungicide management at the field scale, and an atmospheric dispersion model that calculates spore dispersal at the landscape scale. Landscapes consisted of one or two distinct potato-growing regions (6.4-by-6.4-km) embedded within a nonhost matrix. The characteristics of fields and growing regions and the separation distance between two growing regions were investigated for their effects on disease incidence, measured as the proportion of fields with ≥1% severity, after inoculation of a single potato grid cell with a low initial level of disease. The most effective spatial strategies for suppressing disease spread in a region were those that reduced the acreage of potato or increased the proportion of a resistant potato cultivar. Clustering potato cultivation in some parts of a region, either by planting in large fields or clustering small fields, enhanced the spread within such a cluster while it delayed spread from one cluster to another; however, the net effect of clustering was an increase in disease at the landscape scale. The planting of mixtures of a resistant and susceptible cultivar was a consistently effective option for creating potato-growing regions that suppressed disease spread. It was more effective to mix susceptible and resistant cultivars within fields than plant some fields entirely with a susceptible cultivar and other fields with a resistant cultivar, at the same ratio of susceptible to resistant potato plants at the landscape level. Separation distances of at least 16 km were needed to completely prevent epidemic spread from one potato-growing region to another. Effects of spatial placement of resistant and susceptible potato cultivars depended strongly on meteorological conditions, indicating that landscape connectivity for the spread of plant disease depends on the particular coincidence between direction of spread, location of fields, distance between the fields, and survival of the spores depending on the weather. Therefore, in the simulation of (airborne) pathogen invasions, it is important to consider the large variability of atmospheric dispersion conditions.


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