scholarly journals Hazardous Noxious Substance Detection Based on Ground Experiment and Hyperspectral Remote Sensing

2021 ◽  
Vol 13 (2) ◽  
pp. 318
Author(s):  
Jae-Jin Park ◽  
Kyung-Ae Park ◽  
Pierre-Yves Foucher ◽  
Philippe Deliot ◽  
Stephane Le Floch ◽  
...  
Keyword(s):  
Near Infrared ◽  
Spectral Characteristics ◽  
Chemical Properties ◽  
Principal Component ◽  
Component Analysis ◽  
Noise Removal ◽  
Vertex Component Analysis ◽  
Shortwave Infrared ◽  
Spectral Mixture ◽  
Physical And Chemical

With an increase in the overseas maritime transport of hazardous and noxious substances (HNSs), HNS-related spill accidents are on the rise. Thus, there is a need to completely understand the physical and chemical properties of HNSs. This can be achieved through establishing a library of spectral characteristics with respect to wavelengths from visible and near-infrared (VNIR) bands to shortwave infrared (SWIR) wavelengths. In this study, a ground HNS measurement experiment was conducted for artificially spilled HNS by using two hyperspectral cameras at VNIR and SWIR wavelengths. Representative HNSs such as styrene and toluene were spilled into an outdoor pool and their spectral characteristics were obtained. The relative ratio of HNS to seawater decreased and increased at 550 nm and showed different constant ratios at the SWIR wavelength. Noise removal and dimensional compression procedures were conducted by applying principal component analysis on HNS hyperspectral images. Pure HNS and seawater endmember spectra were extracted using four spectral mixture techniques—N-FINDR, pixel purity index (PPI), independent component analysis (ICA), and vertex component analysis (VCA). The accuracy of detection values of styrene and toluene through the comparison of the abundance fraction were 99.42% and 99.56%, respectively. The results of this study are useful for spectrum-based HNS detection in marine HNS accidents.

Polluted aquifers: identification and characterisation by statistical analysis

2010 ◽  
Vol 61 (2) ◽  
pp. 331-337 ◽  
Author(s):  
Analía Boemo ◽  
Haydée Musso ◽  
Irene Lomniczi
Keyword(s):  
Principal Component Analysis ◽  
Hierarchical Clustering ◽  
Chemical Properties ◽  
Principal Component ◽  
Component Analysis ◽  
Underground Water ◽  
Chemical Components ◽  
Eastern Area ◽  
Western Area ◽  
Physical And Chemical

Hierarchical clustering and principal component analysis applied to chemical components and physicochemical properties of well water proved to be a useful tool for identification and characterisation of aquifers. Underground water of Lerma Valley (Salta, Argentina) was examined for its physical and chemical properties by sampling 46 wells located in two adjacent areas separated by hills, one of them polluted with boron since 1991. Hierarchical clustering splits sampled sites into two main clusters, corresponding to the two areas, establishing the fact that the aquifers should be considered as two different entities in spite of their common recharge area. Values of boron concentration in the eastern area decreased in most of the wells since the pollution sources were eradicated, while four of them experienced a substantial increase, proof of the slow self-recovery of the aquifer. The use of principal component analysis provided evidence of the incipient boron pollution of the aquifer of the western area.

scholarly journals Diversity of entomopathogenic fungi associated with Mediterranean fruit fly (C. capitata) in Moroccan Argan forests and nearby area: impact of soil factors on their distribution

2020 ◽  
Author(s):  
Ayoub HALLOUTI ◽  
Mohamed AIT HAMZA ◽  
Abdelaziz ZAHIDI ◽  
Rachid AIT HAMMOU ◽  
Rachid BOUHARROUD ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Entomopathogenic Fungi ◽  
Chemical Properties ◽  
Principal Component ◽  
Fruit Fly ◽  
Component Analysis ◽  
Organic Content ◽  
Pathogenicity Test ◽  
Factors Affecting ◽  
Physical And Chemical

Abstract Background: Studying the ecology of biocontrol-agents is a prerequisite to effectively control medfly (C. capitata) with entomopathogenic fungi. In this context, factors affecting the occurrence and distribution of medfly-associated entomopathogenic-fungi were studied. Soil samples (22) were collected from natural and cultivated areas of Souss-region Morocco. Results: A total of 260 fungal isolates belonging to 22 species and 10 genera were obtained by using medfly pupae as bait. Medfly-associated fungi were detected in all studied soils and pupae infection percentages ranged from 3.33% to 48%. Two genera, Fusarium and Beauveria were the most frequent with 83 isolates (32%) and 50 isolates (19.23%) respectively. Pathogenicity test of isolated species against medfly pupae showed high mortality rates up to 91% for some strains. Principal component analysis (PCA) demonstrated strong influence of origin, physical and chemical properties of soil on the abundance of these fungi. In general, medfly-associated fungi were more abundant in soils with moderate pH (7.5 to 8) having high sand and organic content. High relative humidity negatively influenced the abundance of these fungi. Both factors directly affected the fungal infection percentages in pupae. The response of fungi to these parameters varied among species. According to principal component analysis (PCA) the soils of argan fields and forests were more suitable for the development of medfly-associated fungi than citrus orchards. Conclusions: These results provide guidance on identifying suitable soils for effective application of entomopathogenic fungi as biological control agents. In summary, isolated indigenous strains seem to be a promising option to control C. capitata.

scholarly journals Aplikasi Principle Component Analysis dan Directed Principal Component untuk Pemetaan Alterasi Hidrotermal menggunakan Citra ASTER di Kecamatan Kokap, Kulon Progo

2019 ◽  
Vol 20 (3) ◽  
pp. 119
Author(s):  
Bayu Raharja ◽  
Agung Setianto ◽  
Anastasia Dewi Titisari
Keyword(s):  
Principle Component Analysis ◽  
Near Infrared ◽  
Confusion Matrix ◽  
Principal Component ◽  
Component Analysis ◽  
Principle Component ◽  
Shortwave Infrared

Endapan emas di daerah Kokap, Kabupaten Kulon Progo yang berasosiasi dengan endapan tipe epitermal terbentuk akibat adanya proses alterasi hidrotermal. Pemanfaatan data penginderaan jauh untuk pemetaan alterasi telah berhasil dilakukan diberbagai lokasi. Penelitian ini bertujuan untuk mengkaji kemampuan citra ASTER saluran visible near infrared (VNIR) dan saluran shortwave infrared (SWIR) dalam memetakan jenis alterasi menggunakan metode Principle Component Analysis (PCA) dan Directed Principal Component (DPC). Klasifikasi multispektral selanjutnya dilakukan untuk membedakan tipe alterasi hidrotermal menggunakan kombinasi saluran hasil PCA dan DPC. Keberhasilan pemetaan alterasi hidrotermal dievaluasi secara statistik menggunakan confusion matrix. Tingkat akurasi yang dapat diterima adalah sebesar 85% dengan koefisien kappa lebih besar dari 0.8. Hasil penelitian menunjukkan metode DPC memiliki akurasi lebih baik dari PCA dalam memetakan tipe alterasi meskipun tingkat akurasi keduanya dibawah batas yang ditentukan. Saluran ASTER yang paling baik digunakan untuk memetakan tipe alterasi hidrotermal di lokasi penelitian adalah 1, 2, 4, dan 6.

scholarly journals Non-Destructive Classification of Fruits Based on Vis-nir Spectroscopy and Principal Component Analysis

2019 ◽  
Vol 4 (1) ◽  
pp. 89-95 ◽  
Author(s):  
Kusumiyati Kusumiyati ◽  
Yuda Hadiwijaya ◽  
Ine Elisa Putri
Keyword(s):  
Principal Component Analysis ◽  
Fruit Quality ◽  
Near Infrared ◽  
Chemical Properties ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Component Analysis ◽  
Internal Quality ◽  
Fruit Samples ◽  
Non Destructive

Fruits are one of the sources of nutrition needed for health. Fruit quality is generally assessed by physical and chemical properties. Measurement of fruit internal quality is usually done by destructive techniques. Ultraviolet, visible and near-infrared (UV-Vis-NIR) spec-troscopy is a non-destructive technique to measure fruit quality. This technique can rapidly measure the fruit quality, the measured fruit still remains intact, and can be marketed. Besides, UV-Vis-NIR spectrosco-py can also be used to classify fruits. The study aimed to classify var-ious types of fruits using UV-Vis-NIR spectroscopy with wavelengths of 300-1041 nm and Principal Component Analysis (PCA). First de-rivative savitzky-golay with 9 smoothing points (dg1) and multiplica-tive scatter correction (MSC) were applied to correct the spectra. The results showed that the use of uv-vis-nir spectroscopy and PCA com-bined with spectra pre-treatment of the MSC method were able to clas-sify various types of fruits with 100% success rate in all fruit samples including sapodilla, ridge gourd, mango, guava, apple and zucchini. 

scholarly journals Diversity of entomopathogenic fungi associated with Mediterranean fruit fly (C. capitata) in Moroccan Argan forests and nearby area: impact of soil factors on their distribution

2020 ◽  
Author(s):  
Ayoub HALLOUTI ◽  
Mohamed AIT HAMZA ◽  
Abdelaziz ZAHIDI ◽  
Rachid AIT HAMMOU ◽  
Rachid BOUHARROUD ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Entomopathogenic Fungi ◽  
Chemical Properties ◽  
Principal Component ◽  
Fruit Fly ◽  
Component Analysis ◽  
Organic Content ◽  
Pathogenicity Test ◽  
Factors Affecting ◽  
Physical And Chemical

Abstract Background: Studying the ecology of biocontrol-agents is a prerequisite to effectively control medfly (Ceratitis capitata (Diptera: Tephritidae)) with entomopathogenic fungi. In this context, factors affecting the occurrence and distribution of medfly-associated entomopathogenic-fungi were studied. Soil samples (22) were collected from natural and cultivated areas of Souss-region Morocco. Results: A total of 260 fungal isolates belonging to 22 species and 10 genera were obtained by using medfly pupae as bait. Medfly-associated fungi were detected in all studied soils and pupae infection percentages ranged from 3.33% to 48%. Two genera, Fusarium and Beauveria were the most frequent with 83 isolates (32%) and 50 isolates (19.23%) respectively. Pathogenicity test of isolated species against medfly pupae showed high mortality rates up to 91% for some strains. Principal component analysis (PCA) demonstrated a strong influence of origin, physical, and chemical properties of soil on the abundance of these fungi. In general, medfly-associated fungi were more abundant in soils with moderate pH (7.5 to 8) having high sand and organic content. High relative humidity negatively influenced the abundance of these fungi. Both factors directly affected the fungal infection percentages in pupae. The response of fungi to these parameters varied among species. According to principal component analysis (PCA), the soils of argan fields and forests were more suitable for the development of medfly-associated fungi than citrus orchards.Conclusions: These results guide identifying suitable soils for the effective application of entomopathogenic fungi as biological control agents. In summary, isolated indigenous strains seem to be a promising option to control C. capitata.

scholarly journals Aplikasi Principle Component Analysis dan Directed Principal Component untuk Pemetaan Alterasi Hidrotermal menggunakan Citra ASTER di Kecamatan Kokap, Kulon Progo

2019 ◽  
Vol 20 (3) ◽  
pp. 119
Author(s):  
Bayu Raharja ◽  
Agung Setianto ◽  
Anastasia Dewi Titisari
Keyword(s):  
Principle Component Analysis ◽  
Near Infrared ◽  
Confusion Matrix ◽  
Principal Component ◽  
Component Analysis ◽  
Principle Component ◽  
Shortwave Infrared

Endapan emas di daerah Kokap, Kabupaten Kulon Progo yang berasosiasi dengan endapan tipe epitermal terbentuk akibat adanya proses alterasi hidrotermal. Pemanfaatan data penginderaan jauh untuk pemetaan alterasi telah berhasil dilakukan diberbagai lokasi. Penelitian ini bertujuan untuk mengkaji kemampuan citra ASTER saluran visible near infrared (VNIR) dan saluran shortwave infrared (SWIR) dalam memetakan jenis alterasi menggunakan metode Principle Component Analysis (PCA) dan Directed Principal Component (DPC). Klasifikasi multispektral selanjutnya dilakukan untuk membedakan tipe alterasi hidrotermal menggunakan kombinasi saluran hasil PCA dan DPC. Keberhasilan pemetaan alterasi hidrotermal dievaluasi secara statistik menggunakan confusion matrix. Tingkat akurasi yang dapat diterima adalah sebesar 85% dengan koefisien kappa lebih besar dari 0.8. Hasil penelitian menunjukkan metode DPC memiliki akurasi lebih baik dari PCA dalam memetakan tipe alterasi meskipun tingkat akurasi keduanya dibawah batas yang ditentukan. Saluran ASTER yang paling baik digunakan untuk memetakan tipe alterasi hidrotermal di lokasi penelitian adalah 1, 2, 4, dan 6.

scholarly journals Aplikasi Principle Component Analysis dan Directed Principal Component untuk Pemetaan Alterasi Hidrotermal menggunakan Citra ASTER di Kecamatan Kokap, Kulon Progo

2019 ◽  
Vol 20 (3) ◽  
Author(s):  
Bayu Raharja ◽  
Agung Setianto ◽  
Anastasia Dewi Titisari
Keyword(s):  
Principle Component Analysis ◽  
Near Infrared ◽  
Confusion Matrix ◽  
Principal Component ◽  
Component Analysis ◽  
Principle Component ◽  
Shortwave Infrared

Endapan emas di daerah Kokap, Kabupaten Kulon Progo yang berasosiasi dengan endapan tipe epitermal terbentuk akibat adanya proses alterasi hidrotermal. Pemanfaatan data penginderaan jauh untuk pemetaan alterasi telah berhasil dilakukan diberbagai lokasi. Penelitian ini bertujuan untuk mengkaji kemampuan citra ASTER saluran visible near infrared (VNIR) dan saluran shortwave infrared (SWIR) dalam memetakan jenis alterasi menggunakan metode Principle Component Analysis (PCA) dan Directed Principal Component (DPC). Klasifikasi multispektral selanjutnya dilakukan untuk membedakan tipe alterasi hidrotermal menggunakan kombinasi saluran hasil PCA dan DPC. Keberhasilan pemetaan alterasi hidrotermal dievaluasi secara statistik menggunakan confusion matrix. Tingkat akurasi yang dapat diterima adalah sebesar 85% dengan koefisien kappa lebih besar dari 0.8. Hasil penelitian menunjukkan metode DPC memiliki akurasi lebih baik dari PCA dalam memetakan tipe alterasi meskipun tingkat akurasi keduanya dibawah batas yang ditentukan. Saluran ASTER yang paling baik digunakan untuk memetakan tipe alterasi hidrotermal di lokasi penelitian adalah 1, 2, 4, dan 6.

scholarly journals Influence of environmental factors on the detection of blood in sheep faeces using visible–near-infrared spectroscopy as a measure of Haemonchus contortus infection

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Elise A. Kho ◽  
Jill N. Fernandes ◽  
Andrew C. Kotze ◽  
Glen P. Fox ◽  
Maggy T. Sikulu-Lord ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Haemonchus Contortus ◽  
Prediction Accuracy ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Component Analysis ◽  
Diagnostic Methods ◽  
Calibration Models ◽  
Good Prediction Accuracy

Abstract Background Existing diagnostic methods for the parasitic gastrointestinal nematode, Haemonchus contortus, are time consuming and require specialised expertise, limiting their utility in the field. A practical, on-farm diagnostic tool could facilitate timely treatment decisions, thereby preventing losses in production and flock welfare. We previously demonstrated the ability of visible–near-infrared (Vis–NIR) spectroscopy to detect and quantify blood in sheep faeces with high accuracy. Here we report our investigation of whether variation in sheep type and environment affect the prediction accuracy of Vis–NIR spectroscopy in quantifying blood in faeces. Methods Visible–NIR spectra were obtained from worm-free sheep faeces collected from different environments and sheep types in South Australia (SA) and New South Wales, Australia and spiked with various sheep blood concentrations. Spectra were analysed using principal component analysis (PCA), and calibration models were built around the haemoglobin (Hb) wavelength region (387–609 nm) using partial least squares regression. Models were used to predict Hb concentrations in spiked faeces from SA and naturally infected sheep faeces from Queensland (QLD). Samples from QLD were quantified using Hemastix® test strip and FAMACHA© diagnostic test scores. Results Principal component analysis showed that location, class of sheep and pooled versus individual samples were factors affecting the Hb predictions. The models successfully differentiated ‘healthy’ SA samples from those requiring anthelmintic treatment with moderate to good prediction accuracy (sensitivity 57–94%, specificity 44–79%). The models were not predictive for blood in the naturally infected QLD samples, which may be due in part to variability of faecal background and blood chemistry between samples, or the difference in validation methods used for blood quantification. PCA of the QLD samples, however, identified a difference between samples containing high and low quantities of blood. Conclusion This study demonstrates the potential of Vis–NIR spectroscopy for estimating blood concentration in faeces from various types of sheep and environmental backgrounds. However, the calibration models developed here did not capture sufficient environmental variation to accurately predict Hb in faeces collected from environments different to those used in the calibration model. Consequently, it will be necessary to establish models that incorporate samples that are more representative of areas where H. contortus is endemic.

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