scholarly journals Metro Maps of Plant Disease Dynamics—Automated Mining of Differences Using Hyperspectral Images

PLoS ONE ◽  
2015 ◽  
Vol 10 (1) ◽  
pp. e0116902 ◽  
Author(s):  
Mirwaes Wahabzada ◽  
Anne-Katrin Mahlein ◽  
Christian Bauckhage ◽  
Ulrike Steiner ◽  
Erich-Christian Oerke ◽  
...  
Plant Methods ◽  
2019 ◽  
Vol 15 (1) ◽  
Author(s):  
Koushik Nagasubramanian ◽  
Sarah Jones ◽  
Asheesh K. Singh ◽  
Soumik Sarkar ◽  
Arti Singh ◽  
...  

2012 ◽  
Vol 8 (4) ◽  
pp. 685-688 ◽  
Author(s):  
Takefumi Nakazawa ◽  
Takehiko Yamanaka ◽  
Satoru Urano

Plants are subject to diseases caused by pathogens, many of which are transmitted by herbivorous arthropod vectors. To understand plant disease dynamics, we studied a minimum hybrid model combining consumer–resource (herbivore–plant) and susceptible–infected models, in which the disease is transmitted bi-directionally between the consumer and the resource from the infected to susceptible classes. Model analysis showed that: (i) the disease is more likely to persist when the herbivore feeds on the susceptible plants rather than the infected plants, and (ii) alternative stable states can exist in which the system converges to either a disease-free or an endemic state, depending on the initial conditions. The second finding is particularly important because it suggests that the disease may persist once established, even though the initial prevalence is low (i.e. the R 0 rule does not always hold). This situation is likely to occur when the infection improves the plant nutritive quality, and the herbivore preferentially feeds on the infected resource (i.e. indirect vector–pathogen mutualism). Our results highlight the importance of the eco-epidemiological perspective that integration of tripartite interactions among host plant, plant pathogen and herbivore vector is crucial for the successful control of plant diseases.


2018 ◽  
Author(s):  
N. Anggriani ◽  
M. Z. Ndii ◽  
N. Istifadah ◽  
A. K. Supriatna

2018 ◽  
Author(s):  
N. Anggriani ◽  
M. Z. Ndii ◽  
D. Arumi ◽  
N. Istifadah ◽  
A. K. Supriatna

2021 ◽  
Vol 30 ◽  
pp. 104821
Author(s):  
Shumaila Azam ◽  
Nauman Ahmed ◽  
Ali Akgül ◽  
Muhammad Sajid Iqbal ◽  
Muhammad Rafiq ◽  
...  

2018 ◽  
Vol 4 (12) ◽  
pp. 143 ◽  
Author(s):  
Jan Behmann ◽  
David Bohnenkamp ◽  
Stefan Paulus ◽  
Anne-Katrin Mahlein

The characterization of plant disease symptoms by hyperspectral imaging is often limited by the missing ability to investigate early, still invisible states. Automatically tracing the symptom position on the leaf back in time could be a promising approach to overcome this limitation. Therefore we present a method to spatially reference time series of close range hyperspectral images. Based on reference points, a robust method is presented to derive a suitable transformation model for each observation within a time series experiment. A non-linear 2D polynomial transformation model has been selected to cope with the specific structure and growth processes of wheat leaves. The potential of the method is outlined by an improved labeling procedure for very early symptoms and by extracting spectral characteristics of single symptoms represented by Vegetation Indices over time. The characteristics are extracted for brown rust and septoria tritici blotch on wheat, based on time series observations using a VISNIR (400–1000 nm) hyperspectral camera.


Author(s):  
Karen K. Baker ◽  
David L. Roberts

Plant disease diagnosis is most often accomplished by examination of symptoms and observation or isolation of causal organisms. Occasionally, diseases of unknown etiology occur and are difficult or impossible to accurately diagnose by the usual means. In 1980, such a disease was observed on Agrostis palustris Huds. c.v. Toronto (creeping bentgrass) putting greens at the Butler National Golf Course in Oak Brook, IL.The wilting symptoms of the disease and the irregular nature of its spread through affected areas suggested that an infectious agent was involved. However, normal isolation procedures did not yield any organism known to infect turf grass. TEM was employed in order to aid in the possible diagnosis of the disease.Crown, root and leaf tissue of both infected and symptomless plants were fixed in cold 5% glutaraldehyde in 0.1 M phosphate buffer, post-fixed in buffered 1% osmium tetroxide, dehydrated in ethanol and embedded in a 1:1 mixture of Spurrs and epon-araldite epoxy resins.


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