A Study of Apple Bruise Detection by Using Chlorophyll Fluorescence Image

2011 ◽  
Author(s):  
Yi-Chich Chiu ◽  
Mu-Te Chen
Keyword(s):  
Chlorophyll Fluorescence ◽  
Fluorescence Image

Chilling Injury Segmentation of Tomato Leaves Based on Fluorescence Images and Improved k-Means++ Clustering

2021 ◽  
Vol 64 (1) ◽  
pp. 13-22
Author(s):  
Zhenfen Dong ◽  
Yuheng Men ◽  
Zhengming Li ◽  
Zhenzhen Liu ◽  
Jianwei Ji
Keyword(s):  
Chlorophyll Fluorescence ◽  
Fluorescence Imaging ◽  
Chilling Injury ◽  
Color Space ◽  
Clustering Method ◽  
Fluorescence Image ◽  
Target Region ◽  
Fuzzy C Means Clustering ◽  
The Mean ◽  
Injury Area

HighlightsChlorophyll fluorescence imaging can be used to evaluate chilling injury.Chilling injury area heterogeneity in the L*a*b* color space is significant.Improved k-means++ clustering has a good segmentation effect on chilling injury.Abstract. The application of fluorescence imaging in the detection of tomato chilling injury was investigated. With the segmentation of the chilling injury area serving as the experimental target, an algorithm based on chlorophyll fluorescence image analysis and improved k-means++ clustering was proposed. First, the extraction of lateral heterogeneity values algorithm was used to analyze the horizontal heterogeneity in five color spaces of the fluorescence images of tomato seedling leaves, and it was found that the chilling injury area was significant in the L*a*b* color space. Second, the fluorescence image was converted from the RGB color space to the L*a*b* color space, and the k-means++ algorithm was used to cluster the two-dimensional data of the a*b* space. Third, insertion sorting was used to reorder the different label regions obtained by the k-means++ clustering algorithm, and the region with the largest value was used as the target region. Finally, the binary image of the target region was filtered using a morphological noise filter, and the cold-damaged area was outputted by the mask operation. The results showed that the cold-damaged area was well segmented when the fluorescence imaging contained yellow cold traces. The mean match rate of the proposed algorithm was 37.08%, 13.52%, and 0.96% higher than that based on the HSV model and watershed algorithm, the fuzzy C-means clustering method, and the k-means clustering method, respectively. Similarly, the mean error rate was 13.69%, 5.56%, and 0.16% lower than that based on the HSV model and watershed algorithm, the fuzzy C-means clustering method, and the k-means clustering method, respectively. These findings provide a foundation for research on early warning of chilling injury by identifying the chilling injury status of tomato leaves using a computer vision method. Keywords: Chlorophyll fluorescence, Fluorescence image, Image segmentation, k-Means++.

scholarly journals Phenoplant: a web resource for the exploration of large chlorophyll fluorescence image datasets

Plant Methods ◽  
2015 ◽  
Vol 11 (1) ◽  
Author(s):  
Céline Rousseau ◽  
Gilles Hunault ◽  
Sylvain Gaillard ◽  
Julie Bourbeillon ◽  
Gregory Montiel ◽  
...  
Keyword(s):  
Chlorophyll Fluorescence ◽  
Fluorescence Image ◽  
Web Resource ◽  
Image Datasets

scholarly journals High throughput quantitative phenotyping of plant resistance using chlorophyll fluorescence image analysis

Plant Methods ◽  
2013 ◽  
Vol 9 (1) ◽  
pp. 17 ◽  
Author(s):  
Céline Rousseau ◽  
Etienne Belin ◽  
Edouard Bove ◽  
David Rousseau ◽  
Frédéric Fabre ◽  
...  
Keyword(s):  
Image Analysis ◽  
Chlorophyll Fluorescence ◽  
High Throughput ◽  
Plant Resistance ◽  
Fluorescence Image

Quantification of small-scale heterogeneity in aquatic aminopeptidase activity

2020 ◽  
Vol 84 ◽  
pp. 127-140
Author(s):  
BM Gaas ◽  
JW Ammerman
Keyword(s):  
Chlorophyll Fluorescence ◽  
Leucine Aminopeptidase ◽  
Hudson River ◽  
Aminopeptidase Activity ◽  
Small Scale ◽  
Analysis Instrument ◽  
Sequential Samples ◽  
Degree Of Confidence ◽  
The Mean ◽  
Hydrolysis Of

Leucine aminopeptidase (LAP) is one of the enzymes involved in the hydrolysis of peptides, and is sometimes used to indicate potential nitrogen limitation in microbes. Small-scale variability has the potential to confound interpretation of underlying patterns in LAP activity in time or space. An automated flow-injection analysis instrument was used to address the small-scale variability of LAP activity within contiguous regions of the Hudson River plume (New Jersey, USA). LAP activity had a coefficient of variation (CV) of ca. 0.5 with occasional values above 1.0. The mean CVs for other biological parameters—chlorophyll fluorescence and nitrate concentration—were similar, and were much lower for salinity. LAP activity changed by an average of 35 nmol l-1 h-1 at different salinities, and variations in LAP activity were higher crossing region boundaries than within a region. Differences in LAP activity were ±100 nmol l-1 h-1 between sequential samples spaced <10 m apart. Variogram analysis indicated an inherent spatial variability of 52 nmol l-1 h-1 throughout the study area. Large changes in LAP activity were often associated with small changes in salinity and chlorophyll fluorescence, and were sensitive to the sampling frequency. This study concludes that LAP measurements in a sample could realistically be expected to range from zero to twice the average, and changes between areas or times should be at least 2-fold to have some degree of confidence that apparent patterns (or lack thereof) in activity are real.

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