3D monitoring spatio - temporal effects of herbicide on a whole plant using combined range and chlorophyll a fluorescence imaging

2009 ◽  
Vol 36 (11) ◽  
pp. 874 ◽  
Author(s):  
Atsumi Konishi ◽  
Akira Eguchi ◽  
Fumiki Hosoi ◽  
Kenji Omasa
Keyword(s):  
Chlorophyll Fluorescence ◽  
Fluorescence Imaging ◽  
Chlorophyll A ◽  
Chlorophyll A Fluorescence ◽  
Structural Parameters ◽  
Leaf Age ◽  
Temporal Effects ◽  
Whole Plant ◽  
Fluorescence Images ◽  
Spatio Temporal

Spatio–temporal effects of herbicide including 3-(3,4 dichlorophenyl)-1,1-dimethylurea (DCMU) on a whole melon (Cucumis melo L.) plant were three-dimensionally monitored using combined range and chlorophyll a fluorescence imaging. The herbicide was treated to soil in a pot and the changes in chlorophyll a fluorescence images of the plant were captured over time. The time series of chlorophyll fluorescence images were combined with 3D polygon model of the whole plant taken by a high-resolution portable scanning lidar. From the produced 3D chlorophyll fluorescence model, it was observed that the increase of chlorophyll fluorescence appeared along veins of leaves and gradually expanded to mesophylls. In addition, it was found by detailed analysis of the images that the invisible herbicide injury on the mature leaves occurred earlier and more severely than on the young and old leaves. The distance from veins, whole leaf area and leaf inclination influenced the extent of the injury within the leaves. These results indicated difference in uptake of herbicide in the plant from soil depends on structural parameters of leaves and the microenvironments as well as leaf age. The findings showed that 3D monitoring using combined range and chlorophyll a fluorescence imaging can be utilised for understanding spatio-temporal changes of herbicide effects on a whole plant.

CLASSIFYING APPLES BY THE MEANS OF FLUORESCENCE IMAGING

2004 ◽  
Vol 18 (02) ◽  
pp. 157-174 ◽  
Author(s):  
MARIUS C. CODREA ◽  
OLLI S. NEVALAINEN ◽  
ESA TYYSTJÄRVI ◽  
MARTIN VANDEVEN ◽  
ROLAND VALCKE
Keyword(s):  
Neural Networks ◽  
Fluorescence Imaging ◽  
Chlorophyll A ◽  
Blue Light ◽  
Chlorophyll A Fluorescence ◽  
Classification Method ◽  
Test Material ◽  
Fluorescence Images

Classification of harvested apples when predicting their storage potential is an important task. This paper describes how chlorophyll a fluorescence images taken in blue light through a red filter, can be used to classify apples. In such an image, fluorescence appears as a relatively homogenous area broken by a number of small nonfluorescing spots, corresponding to normal corky tissue patches, lenticells, and to damaged areas that lower the quality of the apple. The damaged regions appear more longish, curved or boat-shaped compared to the roundish, regular lenticells. We propose an apple classification method that employs a hierarchy of two neural networks. The first network classifies each spot according to geometrical criteria and the second network uses this information together with global attributes to classify the apple. The system reached 95% accuracy using a test material classified by an expert for "bad" and "good" apples.

scholarly journals FLIP: FLuorescence Imaging Pipeline for field-based chlorophyll fluorescence images

SoftwareX ◽  
2021 ◽  
Vol 14 ◽  
pp. 100685
Author(s):  
Matthew T. Herritt ◽  
Jacob C. Long ◽  
Mike D. Roybal ◽  
David C. Moller ◽  
Todd C. Mockler ◽  
...  
Keyword(s):  
Chlorophyll Fluorescence ◽  
Fluorescence Imaging ◽  
Fluorescence Images

scholarly journals Temporal Variation of Chlorophyll-a Concentrations in Highly Dynamic Waters from Unattended Sensors and Remote Sensing Observations

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2699 ◽  
Author(s):  
Jian Li ◽  
Liqiao Tian ◽  
Qingjun Song ◽  
Zhaohua Sun ◽  
Hongjing Yu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Chlorophyll Fluorescence ◽  
Chlorophyll A ◽  
Temporal Variations ◽  
Lake Area ◽  
Short Term ◽  
Chl A ◽  
Spatio Temporal

Monitoring of water quality changes in highly dynamic inland lakes is frequently impeded by insufficient spatial and temporal coverage, for both field surveys and remote sensing methods. To track short-term variations of chlorophyll fluorescence and chlorophyll-a concentrations in Poyang Lake, the largest freshwater lake in China, high-frequency, in-situ, measurements were collected from two fixed stations. The K-mean clustering method was also applied to identify clusters with similar spatio-temporal variations, using remote sensing Chl-a data products from the MERIS satellite, taken from 2003 to 2012. Four lake area classes were obtained with distinct spatio-temporal patterns, two of which were selected for in situ measurement. Distinct daily periodic variations were observed, with peaks at approximately 3:00 PM and troughs at night or early morning. Short-term variations of chlorophyll fluorescence and Chl-a levels were revealed, with a maximum intra-diurnal ratio of 5.1 and inter-diurnal ratio of 7.4, respectively. Using geostatistical analysis, the temporal range of chlorophyll fluorescence and corresponding Chl-a variations was determined to be 9.6 h, which indicates that there is a temporal discrepancy between Chl-a variations and the sampling frequency of current satellite missions. An analysis of the optimal sampling strategies demonstrated that the influence of the sampling time on the mean Chl-a concentrations observed was higher than 25%, and the uncertainty of any single Terra/MODIS or Aqua/MODIS observation was approximately 15%. Therefore, sampling twice a day is essential to resolve Chl-a variations with a bias level of 10% or less. The results highlight short-term variations of critical water quality parameters in freshwater, and they help identify specific design requirements for geostationary earth observation missions, so that they can better address the challenges of monitoring complex coastal and inland environments around the world.

scholarly journals Chlorophyll a fluorescence imaging of soya bean leaflets infected by Corynespora cassiicola

2018 ◽  
Vol 166 (11-12) ◽  
pp. 782-789
Author(s):  
Alessandro A. Fortunato ◽  
Daniel Debona ◽  
Carlos E. Aucique-Pérez ◽  
Emerson Fialho Corrêa ◽  
Fabrício A. Rodrigues
Keyword(s):  
Fluorescence Imaging ◽  
Chlorophyll A ◽  
Chlorophyll A Fluorescence ◽  
Soya Bean ◽  
Corynespora Cassiicola

Chlorophyll a fluorescence study revealing effects of flooding in canola hybrids

Biologia ◽  
2012 ◽  
Vol 67 (2) ◽  
Author(s):  
Anelise Perboni ◽  
Daniela Cassol ◽  
Fabio Silva ◽  
Diolina Silva ◽  
Marcos Bacarin
Keyword(s):  
Chlorophyll Fluorescence ◽  
Chlorophyll A ◽  
Chlorophyll A Fluorescence ◽  
Cell Metabolism ◽  
Brassica Napus L ◽  
Soil Flooding ◽  
Performance Indexes ◽  
Chlorophyll A Fluorescence Transient ◽  
The Difference ◽  
Kinetics Of

AbstractBy generating stress conditions soil flooding can induce alterations in the cell metabolism and thus is detrimental to plant growth. This study was done under the greenhouse conditions to determine the effect of soil flooding on the chlorophyll fluorescence of some hybrids of canola (Brassica napus L.). Fifty five days old plants were subjected to flooding for six days. There was no difference in the parameters modulate chlorophyll fluorescence, in contrast, some the parameters related to the energy flux in photosystem II varied due to flooding stress. At the end of the six days, the performance indexes (PItotal and PIABS) decreased, in all hybrids except in ‘Hyola 420’. The difference kinetics of the chlorophyll a fluorescence transient showed different effects on different sites of the photosynthetic machinery. It could be concluded that compared to the other hybrids, ‘Hyola 420’ was less sensitive to flooding.

Effects of Epoxiconozale and Pyraclostrobin Fungicides in the Infection Process of Hemileia vastatrix on Coffee Leaves as Determined by Chlorophyll a Fluorescence Imaging

2015 ◽  
Vol 163 (11-12) ◽  
pp. 968-977 ◽  
Author(s):  
Jaime Honorato Júnior ◽  
Laércio Zambolim ◽  
Henrique Silva Silveira Duarte ◽  
Carlos Eduardo Aucique-Pérez ◽  
Fabrício Ávila Rodrigues
Keyword(s):  
Fluorescence Imaging ◽  
Chlorophyll A ◽  
Chlorophyll A Fluorescence ◽  
Infection Process ◽  
Hemileia Vastatrix
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