Evaluation of fungal pathogens with hyperspectral imaging (Conference Presentation)

2019 ◽  
Author(s):  
Paul Williams
Keyword(s):  
Hyperspectral Imaging ◽  
Fungal Pathogens

Single stain hyperspectral imaging for accurate fungal pathogens identification and quantification

Nano Research ◽  
2021 ◽  
Author(s):  
Yongqiang Zhang ◽  
Kunxing Liu ◽  
Jingkun Yu ◽  
Haifeng Chen ◽  
Rui Fu ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Fungal Pathogens ◽  
Identification And Quantification

Hyperspectral Imaging Remote Sensing

2016 ◽  
Author(s):  
Dimitris Manolakis ◽  
Ronald Lockwood ◽  
Thomas Cooley
Keyword(s):  
Remote Sensing ◽  
Hyperspectral Imaging

SOOTY MOULD DISEASES OF SOME TREES FROM AURANGABAD DISTRICT, MAHARASHTRA (INDIA)

2017 ◽  
Vol 23 (2) ◽  
Author(s):  
NAVALSINGH J. TODAWAT
Keyword(s):  
Surface Area ◽  
Fungal Pathogens ◽  
Leaf Surface ◽  
Severity Of Disease ◽  
Sooty Mould ◽  
Leaf Surface Area

Sooty mould diseases of Tress from Aurangabad district were surveyed. During the survey of tress, 5 species were found infected by fungal pathogens causing sooty mould diseases. Disease is easily identifiable by the presence of a black, velvety growth covering the leaf surface area. The fungus produces mycelium which is superficial and dark grows on the flowers, leaf, stem and sometime on fruits also. The severity of disease depends on the honeydew secretions by insects. The diseases were found to be caused by 5 species of fungi viz. Capnodium anonae, C. ramosum, Capnodium sp., Meliola bangalorensis and Meliola ranganthii.

Hyperspectral Imaging for Beef Tenderness Assessment

2015 ◽  
Vol 2 (2) ◽  
pp. 18-25 ◽  
Author(s):  
M. Ngadi ◽  
◽  
F. Saadatian ◽  
L. Liu
Keyword(s):  
Hyperspectral Imaging ◽  
Beef Tenderness

A Supervised Learning Approach for Dynamic Sampling (SLADS) in Raman Hyperspectral Imaging

2018 ◽  
Vol 2018 (15) ◽  
pp. 132-1-1323
Author(s):  
Shijie Zhang ◽  
Zhengtian Song ◽  
G. M. Dilshan P. Godaliyadda ◽  
Dong Hye Ye ◽  
Atanu Sengupta ◽  
...  
Keyword(s):  
Supervised Learning ◽  
Hyperspectral Imaging ◽  
Learning Approach ◽  
Dynamic Sampling

Airborne Hyperspectral Imaging of Laurentian Great Lakes: Operational Challenges

2010 ◽  
Author(s):  
John Lekki ◽  
R. Anderson ◽  
Q.-V. Nguyen ◽  
J. Demers ◽  
J. Flatico ◽  
...  
Keyword(s):  
Great Lakes ◽  
Hyperspectral Imaging ◽  
Laurentian Great Lakes

Diseases of the kumara crop

2009 ◽  
Vol 62 ◽  
pp. 402-402
Author(s):  
S.L. Lewthwaite ◽  
P.J. Wright
Keyword(s):  
Fungal Pathogens ◽  
Ipomoea Batatas ◽  
Mechanical Damage ◽  
Soft Rot ◽  
Economic Loss ◽  
Root Surface ◽  
Black Rot ◽  
Rhizopus Stolonifer ◽  
Ceratocystis Fimbriata ◽  
Pink Rot

The predominant diseases of the commercial kumara (Ipomoea batatas) or sweetpotato crop are caused by fungal pathogens The field disease pink rot results from infection by the fungus Sclerotinia sclerotiorum Lesions form on vines but may spread down stems to the roots The widespread nature of this disease in sweetpotato appears peculiar to New Zealand Scurf is a disease caused by Monilochaetes infuscans which occurs in the field but may proliferate amongst stored roots The disease causes a superficial discolouration of the root surface which is mainly cosmetic but can also increase root water loss in storage Infection by Ceratocystis fimbriata produces a disease known as black rot The disease can be transmitted amongst plants at propagation but is particularly rampant amongst roots in storage This disease is readily transmitted and can cause severe economic loss Fusarium oxysporum causes surface rots in stored roots characterised by light to dark brown lesions that tend to be firm dry and superficial The lesions may be circular and centred on wounds caused by insects or mechanical damage at harvest Soft rot caused by Rhizopus stolonifer generally occurs in roots after they are washed and prepared for the market Fungal infection occurs through wounds or bruised tissue producing distinctive tufts of white fungal strands and black spores

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