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 Detection of Chilling Injury in Pickling Cucumbers Using Dual-Band Chlorophyll Fluorescence Imaging

Foods ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 1094
Author(s):  
Yuzhen Lu ◽  
Renfu Lu
Keyword(s):  
Chlorophyll Fluorescence ◽  
Fluorescence Imaging ◽  
Chilling Injury ◽  
Economic Loss ◽  
Dual Band ◽  
Chlorophyll Fluorescence Imaging ◽  
Support Vector ◽  
Feature Selection Technique ◽  
Pickling Cucumbers ◽  
Fluorescence Images

Pickling cucumbers are susceptible to chilling injury (CI) during postharvest refrigerated storage, which would result in quality degradation and economic loss. It is, thus, desirable to remove the defective fruit before they are marketed as fresh products or processed into pickled products. Chlorophyll fluorescence is sensitive to CI in green fruits, because exposure to chilling temperatures can induce detectable alterations in chlorophylls of tissues. This study evaluated the feasibility of using a dual-band chlorophyll fluorescence imaging (CFI) technique for detecting CI-affected pickling cucumbers. Chlorophyll fluorescence images at 675 nm and 750 nm were acquired from pickling cucumbers under the excitation of ultraviolet-blue light. The raw images were processed for vignetting corrections through bi-dimensional empirical mode decomposition and subsequent image reconstruction. The fluorescence images were effective for ascertaining CI-affected tissues, which appeared as dark areas in the images. Support vector machine models were developed for classifying pickling cucumbers into two or three classes using the features extracted from the fluorescence images. Fusing the features of fluorescence images at 675 nm and 750 nm resulted in overall accuracies of 96.9% and 91.2% for two-class (normal and injured) and three-class (normal, mildly and severely injured) classification, respectively, which are statistically significantly better than those obtained using the features at a single wavelength, especially for the three-class classification. Furthermore, a subset of features, selected based on the neighborhood component feature selection technique, achieved the highest accuracies of 97.4% and 91.3% for the two-class and three-class classification, respectively. This study demonstrated that dual-band CFI is an effective modality for CI detection in pickling cucumbers.

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.

scholarly journals Automatic measurement of traditional Chinese costume from its silhouette through Fuzzy c-means clustering method

2020 ◽  
Vol 15 ◽  
pp. 155892502097832
Author(s):  
Jiaqin Zhang ◽  
Jingan Wang ◽  
Le Xing ◽  
Hui’e Liang
Keyword(s):  
Industrial Application ◽  
Clustering Algorithm ◽  
Color Space ◽  
Automatic Measurement ◽  
Feature Point ◽  
Feature Points ◽  
Point Location ◽  
Fuzzy C Means ◽  
Fuzzy C Means Clustering ◽  
Environmental Robustness

As the precious cultural heritage of the Chinese nation, traditional costumes are in urgent need of scientific research and protection. In particular, there are scanty studies on costume silhouettes, due to the reasons of the need for cultural relic protection, and the strong subjectivity of manual measurement, which limit the accuracy of quantitative research. This paper presents an automatic measurement method for traditional Chinese costume dimensions based on fuzzy C-means clustering and silhouette feature point location. The method is consisted of six steps: (1) costume image acquisition; (2) costume image preprocessing; (3) color space transformation; (4) object clustering segmentation; (5) costume silhouette feature point location; and (6) costume measurement. First, the relative total variation model was used to obtain the environmental robustness and costume color adaptability. Second, the FCM clustering algorithm was used to implement image segmentation to extract the outer silhouette of the costume. Finally, automatic measurement of costume silhouette was achieved by locating its feature points. The experimental results demonstrated that the proposed method could effectively segment the outer silhouette of a costume image and locate the feature points of the silhouette. The measurement accuracy could meet the requirements of industrial application, thus providing the dual value of costume culture research and industrial application.

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 Fluorescence Image-Guided Surgery for Thyroid Cancer: Utility for Preventing Hypoparathyroidism

Cancers ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 3792
Author(s):  
Marco Stefano Demarchi ◽  
Barbara Seeliger ◽  
Jean-Christophe Lifante ◽  
Pier Francesco Alesina ◽  
Frédéric Triponez
Keyword(s):  
Thyroid Cancer ◽  
Fluorescence Imaging ◽  
Thyroid Surgery ◽  
Parathyroid Glands ◽  
Review Of The Literature ◽  
Inclusion Criteria ◽  
Fluorescence Image ◽  
Guided Surgery ◽  
Fluorescence Guided Surgery

Background: Hypoparathyroidism is one of the most frequent complications of thyroid surgery, especially when associated with lymph node dissection in cases of thyroid cancer. Fluorescence-guided surgery is an emerging tool that appears to help reduce the rate of this complication. The present review aims to highlight the utility of fluorescence imaging in preserving parathyroid glands during thyroid cancer surgery. Methods: We performed a systematic review of the literature according to PRISMA guidelines to identify published studies on fluorescence-guided thyroid surgery with a particular focus on thyroid cancer. Articles were selected and analyzed per indication and type of surgery, autofluorescence or exogenous dye usage, and outcomes. The Methodological Index for Non-Randomized Studies (MINORS) was used to assess the methodological quality of the included articles. Results: Twenty-five studies met the inclusion criteria, with three studies exclusively assessing patients with thyroid cancer. The remaining studies assessed mixed cohorts with thyroid cancer and other thyroid or parathyroid diseases. The majority of the papers support the potential benefit of fluorescence imaging in preserving parathyroid glands in thyroid surgery. Conclusions: Fluorescence-guided surgery is useful in the prevention of post-thyroidectomy hypoparathyroidism via enhanced early identification, visualization, and preservation of the parathyroid glands. These aspects are notably beneficial in cases of associated lymphadenectomy for thyroid cancer.

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