PENILAIAN KONDISI EKOLOGI PERAIRAN UNTUK PENGEMBANGAN BUDIDAYA KERANG HIJAU (Perna viridis L.)  DI PESISIR KUALA LANGSA, ACEH

Penelitian ini bertujuan untuk menilai kondisi ekologi untuk pengembangan budidaya kerang hijau di pesisir Kuala Langsa, Aceh. Data ekologi perairan dikumpulkan di 12 titik sampling pada Agustus, September dan Oktober untuk mewakili musim hujan, serta Maret, April dan Mei untuk mewakili musim kemarau. Data dianalisis dengan analisis komponen utama (principal component analysis/PCA). Suhu perairan pesisir Kuala Langsa berkisar 25,5 – 35,6 oC dengan rata-rata 30,5 ± 1,7 oC; salinitas 25,9 – 34,0 ppt dengan rata-rata 29,9 ± 1,3 oC; pH 7,0 – 9,2 dengan rata-rata 8,1 ± 0,3; oksigen terlarut 3,9 – 6,8 mg/l dengan rata-rata 5,5 ± 0,5 mg/l; kecepatan arus berkisar 0,1 – 0,9 m/s dengan rata-rata 0,3 ± 0,1 m/s; serta kelimpahan fitoplankton berkisar 1,32 x 105 sel/m3 hingga 6,86 x 105 sel/m3 dengan rata-rata 3,88 x 105 ± 1,08 x 105 sel/ m3. PCA yang diaplikasikan pada seluruh data menghasilkan dua komponen utama, yaitu PC1 dan PC2 dengan nilai akar ciri (eigenvalue) sebesar 2,096 dan 1,770; dimana PC1 secara kumulatif dapat menjelaskan ragam seluruh data sebesar 34,9% yang dibangun oleh parameter salinitas, suhu dan plankton, sedangkan PC2 sebesar 64,4% yang dibangun oleh parameter oksigen terlarut dan salinitas. Berdasarkan analisis dengan membandingkan parameter ekologi perairan untuk budidaya kerang hijau berdasarkan literatur maka dapat disimpulkan bahwa kondisi ekologi perairan pada musim hujan dan kemarau dapat mendukung pengembangan budidaya kerang hijau di pesisir Kuala Langsa, Aceh. The research aims to assessment of waters ecology condition for the development of green mussel cultivation in coastal of Kuala Langsa, Aceh. Data of waters ecology parameters collected at 12 sampling points in August, September and October to represent the rainy season, while March, April and May to represent the dry season. Data analyzed using principal component analysis (PCA). Temperature of waters coastal Kuala Langsa ranged from 25.5 – 35.6 oC average of 30.5 ± 1.7 oC; salinity 25.9 – 34.0 ppt average of 29.9 ± 1.3 oC; pH 7.0 – 9.2 average of 8.1 ± 0.3; dissolved oxygen from 3.9 – 6.8 average of 5.5 ± 0.5 mg/l; current velocity of 0.1 – 0.9 m/s average of 0.3 ± 0.1 m/s; and abundance of fitoplankton ranged of 1.32 x 105 cell/m3 to 6.86 x 105 cell/m3. PCA applied to all data produced two principal component is PC1 and PC2 with a eigenvalue of 2.096 and 1.770; where PC1 on cumulatively can explain 34.9% of all data collected, with built by parameters of salinity, temperature and plankton, while PC2 is 64.4% with built by parameters dissolved oxygen dan salinity. Based on the analysis by comparing waters ecology parametes for green mussel culture based on the literature, it can be concluded that the waters ecology condition can support development of green mussel culture in coastal Kuala Langsa, Aceh.

Download Full-text

PARAMETER FISIKA, KIMIA, DAN BIOLOGI PENCIRI HABITAT IKAN BELIDA (Chitala lopis)

Jurnal Penelitian Perikanan Indonesia ◽

10.15578/jppi.15.1.2009.13-21 ◽

2017 ◽

Vol 15 (1) ◽

pp. 13

Author(s):

Arif Wibowo ◽

Mas Tri Djoko Sunarno ◽

Safran Makmur

Keyword(s):

Principal Component Analysis ◽

Discriminant Analysis ◽

Dissolved Oxygen ◽

Air Temperature ◽

Oxygen Demand ◽

Principal Component ◽

Environmental Parameters ◽

Component Analysis ◽

Biological Oxygen Demand ◽

Total Dissolved Solid

Penelitian mengenai parameter fisika, kimia, dan biologi penciri habitat ikan belida (Chitala lopis) dilakukan tahun 2005 - 2006 di perairan umum daratan di Sumatera, Kalimantan, dan Jawa. Tujuan nya adalah untuk mendapatkan informasi parameter lingkungan yang menjadi karakteristik habitat ikan belida dari berbagai badan air di Jawa, Sumatera, dan Kalimantan. Metode survei dan kegiatan laboratorium digunakan dalam penelitian ini. Parameter lingkungan yang diamati meliputi suhu udara, suhu air, Total Dissolved Solid (TDS), Daya Hantar Listrik (DHL), klorofil-a, kecepatan arus, Biological Oxygen Demand (BOD), oksigen terlarut, pH, alkalinitas, CO2 bebas, kedalaman air, dan kecerahan pada 116 lokasi pengambilan yang ditentukan secara sengaja di Sungai Tulang Bawang (Provinsi Lampung), Sungai Kampar, Sungai Siak (Provinsi Riau), Sungai Musi (Provinsi Sumatera Selatan), Sungai Citarum (Provinsi Jawa Barat), Sungai Kapuas (Provinsi Kalimantan Barat), dan Waduk Riam Kanan (Provinsi Kalimantan Selatan). Analisis data menggunakan pendekatan analisis multivariabel regresi berganda Metode Backward yang didasarkan pada Analisis Komponen Utama (Principal Component Analysis) dan pembeda (Discriminant Analysis), serta korespondensi analisis (correspondency analysis). Hasil penelitian menunjukkan habitat ikan belida dapat dibedakan menjadi tiga tipe, yaitu tipe yang menyerupai sungai utama, waduk, dan anak sungai. Pembeda utama sekaligus parameter lingkungan utama adalah parameter TDS yang paling besar, dan selanjutnya parameterparameter DHL, suhu udara, klorofil-a, kecepatan arus, BOD, Oksigen terlarut, pH, alkalinitas, dan CO2 bebas menyumbang yang paling sedikit. Kehadiran plankton genus Ulothrix dan Mytilina secara tidak langsung teridentifikasi sebagai penciri habitat spesifik ikan belida. Research on physical, chemical, and biological parameters indicating specific habitat of clown knife fish (Chitala lopis) was carried out at 2005 - 2006 in inlands waters of Sumatera, Borneo, and Java. This study purposed to obtain information of environmental parameters indicating habitat characteristic of the knife fish in various inland waters bodies in Sumatera, Borneo, and Java. Survey method and laboratory activities were employed in this research. Environmental parameters observed were air temperature, water temperature, Total Dissolved Solid (TDS), conductivity, water velocity, Biological Oxygen Demand (BOD), dissolved oxygen, pH, alkalinity, free C02, water depth, and water transparancy taken on 116 sampling stations distributing in Tulang Bawang River (Lampung Province), Kampar and Siak River (Riau Province), Musi River (South Sumatera Province), Kapuas River (West Kalimantan Province), Riam Kanan Reservoar (South Kalimantan Province), and Citarum River (West Java Province). Data analysis used multivariate approach of multiple regression of Backward Method such as Principal Component Analysis, Discriminant Analysis, and Corre spondency Analysis. The results showed that the clown knife fish habitats could be divided by three types of specific habitat, namely water bodies similar with main rivers, reservoir, and tributaries. Parameter of TDS indicated the primary differentization as well as habitat characteristics of the clown knife fish.Whilst the parameters of conductivity, air temperature, chlorophyill-a, water current, BOD, dissolved oxygen, pH, alcalinity, and free CO2 contributed less significance. The existence of plankton from genus Ulothrix and Mytilina was identified indirectly as the specific habitat of the clown knife fish.

Download Full-text

Water quality assessment of an urban river receiving tail water using the single-factor index and principal component analysis

Water Science & Technology Water Supply ◽

10.2166/ws.2018.107 ◽

2018 ◽

Vol 19 (2) ◽

pp. 603-609 ◽

Cited By ~ 4

Author(s):

Weiwei Lu ◽

Juan Wu ◽

Zhu Li ◽

Naxin Cui ◽

Shuiping Cheng

Keyword(s):

Water Quality ◽

Principal Component Analysis ◽

Principal Component ◽

Component Analysis ◽

Urban River ◽

Single Factor ◽

Sampling Points ◽

Factor Index ◽

Tail Water

Abstract Tail water from wastewater treatment plants (WWTP) serves as a major supplementary water source for scenic water bodies, whose water quality is one of the major focuses of public and scientific inquiries. This study investigated the temporal and spatial variations in water quality of Tangxihe River, a eutrophic urban river receiving tail water from a nearby WWTP in Hefei City, using the single-factor index (SFI) and principal component analysis (PCA). The results of SFI indicated that the most important parameters responsible for low water quality were total nitrogen (TN) and ammonia (NH4+-N). PCA showed that tail water from the WWTP greatly reduced water quality, as demonstrated by the significantly increased SFIs and integrated principal component values (F values) of the sampling points around the drain outlet of the WWTP (T3, T4 and T5). The sampling points located at the upstream of the river (T1) and up the water-gate of Chaohu Lake (T6) had negative F values, indicating relatively higher water quality. In addition, the season had a significant effect on the water quality of the river. Moreover, we discuss measures to improve the water quality of urban rivers in order to maintain their ecological functions.

Download Full-text

Site selection for new green mussel culture area expansion in Buguey estuary, Cagayan, Philippines.

10.31220/osf.io/3nb6w ◽

2018 ◽

Author(s):

Eunice A. Layugan ◽

John Philip B. Tabasin ◽

Marlon Alejos ◽

Lorebelle E. Pidoy ◽

Jomar F. Rabajante ◽

...

Keyword(s):

Dissolved Oxygen ◽

Water Temperature ◽

Major Effect ◽

The Philippines ◽

Perna Viridis ◽

Limited Data ◽

Green Mussel ◽

Mussel Culture ◽

Area Expansion ◽

Marketable Size

Abstract Currently, there is limited data on the suitability of estuaries in Cagayan province, Philippines for aquaculture. In this brief report, we discuss the overall assessment score of Buguey estuary in the municipality of Buguey, Cagayan as potential spot for the culture of green mussel (Perna viridis), locally known in the Philippines as "tahong". The score is mainly based on salinity and water temperature. We also present the condition of dissolved oxygen and pH levels in the estuary but these factors do not have major effect on mussel growth compared to salinity and water temperature. The reference ideal values for a suitable culture site are 27 to 35 psu for salinity; 27 to 30°C for water temperature; >5 mg/L for dissolved oxygen; and 7.7 to 8.4 for pH. Based on this reference values, areas in Buguey estuary have acceptable possibility of success for green mussel culture, which is qualitatively equivalent to having "good" suitability. This translates to a production estimate of 81% to 90% of cultured mussels will have a marketable size. However, these ratings may vary due to competition with existing oyster farming, water depth of the chosen site (since several areas in Buguey estuary are shallow), and other factors.

Download Full-text

Evaluation of Water Quality and Benthic Macrointervebrates Fauna Relationship Using Principal Component Analysis (PCA): A Case Study of Cameron Highlands Malaysia

Environmental Management and Sustainable Development ◽

10.5296/emsd.v5i1.9399 ◽

2016 ◽

Vol 5 (1) ◽

pp. 187 ◽

Cited By ~ 1

Author(s):

Kok Weng Tan ◽

Weng Chee Beh

Keyword(s):

Water Quality ◽

Principal Component Analysis ◽

Dissolved Oxygen ◽

Oxygen Demand ◽

Principal Component ◽

Component Analysis ◽

Ammonia Nitrogen ◽

Average Density ◽

Class Iii ◽

Cameron Highlands

This study applies the Principal Component Analysis (PCA) to evaluate and interpret the relationship between water quality and benthic macro-invertebrates fauna data obtained from Pauh River, Cameron Highlands. Samples were collected once every two months (in February, April, June, August and October 2013) with six chosen sampling stations. Six water quality parameters namely dissolved oxygen (DO), pH, biological oxygen demand (BOD5), chemical oxygen demand (COD), ammonia-nitrogen (NH3-N), total suspended solid (TSS) and heavy metals contents were analyzed according to American Public Health Association (APHA), Standard Methods for Examination of Water and Wastewater (1998). Macro-invertebrates were also sampled using Surber sampler and were identified until their family level. Water Quality Index (WQI) values for all stations were class II except for the station 6 which was recorded as class III. Both the diversity and biotic indices showed decreasing value from the upstream (Station 1) to downstream (Station 6). A total 28 to 31 taxa have been found in Station 1, 2, 3 and 5 (upstream to middle stream). However, only 7 taxa found at station 6 (downstream). Total 31 taxa with an average density 368.28 ind/m2 were found in Station 4 which was highest number of taxa among the monitoring stations. The principal component analysis (PCA) was applied on the dataset, which explained 72.15 % of the total variance of the variables. Three components were extracted in this study. First component was classified as benthic macroinvertebrates which tolerated to low water quality condition and high loading of organic matters. The benthic macro-invertebrates families loaded in second component were sensitive to water environment such as NH3-N, dissolved oxygen (DO), organic matter and stream flow. The benthic macroinvertebrate families loaded in third component were recognized as species which might not tolerate low concentration of dissolved oxygen.

Download Full-text

Evaluation of the quality of superficial sediment using principal components analysis of the physical–chemical attributes of the Mearim River – Brazil

Ciência e Natura ◽

10.5902/2179460x41267 ◽

2020 ◽

Vol 42 ◽

pp. e5

Author(s):

Neuriane Silva Lima ◽

Darlan Ferreira da Silva ◽

Wallace Ribeiro Nunes Neto ◽

Delmo Matos da Silva ◽

Leila Cristina Almeida de Sousa ◽

...

Keyword(s):

Principal Component Analysis ◽

Principal Components ◽

Rainy Season ◽

Principal Component ◽

Component Analysis ◽

Dry Period ◽

Data Set ◽

Inorganic Matter ◽

Sampling Points

The Mearim River is one of the main rivers of Maranhão, which, over the years, has been affected from pollution caused by human activities such as deforestation, disposal of domestic effluents, and agricultural activities, among others. The objective of this research was to evaluate the environmental quality of the Mearim River through the study of the sediment in different periods. In order to investigate this question, four sampling points (P1- Balneário, P2-Cais, P3-Trizidela, and P4-Matadouro) were submitted to particle size analysis (clay, silt, and fine sand) and physico-chemical analyses (pH, organic matter, and inorganic and organic carbon). Two principal components were generated in principal component analysis, explaining 73% of the total variance among the parameters within the studied periods. The overall analysis of the data set by principal component analysis highlighted two clusters: one relating the attributes to three sampling points analyzed in the rainy season and another relating the attributes to four sampling points analyzed in the dry period. Multivariate analysis of the data showed that the organic matter, clay, and pH parameters were directly correlated with the dry period (correlation coefficients 0.41), and inorganic matter (correlation coefficient = | 0,414) was more sensitive in the rainy season.

Download Full-text

Dimension Reduction of Machine Learning-based Forecasting Models Employing Principal Component Analysis

10.20944/preprints202007.0397.v1 ◽

2020 ◽

Author(s):

Yinghui Meng ◽

Sultan Noman Qasem ◽

Manouchehr Shokri ◽

S Shamshirband

Keyword(s):

Water Quality ◽

Principal Component Analysis ◽

Dissolved Oxygen ◽

Dimension Reduction ◽

Principal Component ◽

Component Analysis ◽

Computational Time ◽

Aquatic Life ◽

Ann Models ◽

Input Variables

In this research, an attempt was made to reduce the dimension of wavelet-ANFIS/ANN (artificial neural network/adaptive neuro-fuzzy inference system) models toward reliable forecasts as well as to decrease computational cost. In this regard, the principal component analysis was performed on the input time series decomposed by a discrete wavelet transform to feed the ANN/ANFIS models. The models were applied for dissolved oxygen (DO) forecasting in rivers which is an important variable affecting aquatic life and water quality. The current values of DO, water surface temperature, salinity, and turbidity have been considered as the input variable to forecast DO in a three-time step further. The results of the study revealed that PCA can be employed as a powerful for dimension reduction of input variables and also to detect inter-correlation of input variables. Results of the PCA-Wavelet-ANN models are compared with those obtained from Wavelet-ANN models while the earlier one has the advantage of less computational time than the later models. Dealing with ANFIS models, PCA is more beneficial to avoid Wavelet-ANFIS models creating too many rules which deteriorate the efficiency of the ANFIS models. Moreover, manipulating the Wavelet-ANFIS models utilizing PCA leads to a significant decreasing in computational time. Finally, it was found that the PCA-Wavelet-ANN/ANFIS models can provide reliable forecasts of dissolved oxygen as an important water quality indicators in rivers.

Download Full-text

Dimension Reduction of Machine Learning-Based Forecasting Models Employing Principal Component Analysis

Mathematics ◽

10.3390/math8081233 ◽

2020 ◽

Vol 8 (8) ◽

pp. 1233

Author(s):

Yinghui Meng ◽

Sultan Noman Qasem ◽

Manouchehr Shokri ◽

Shahab S

Keyword(s):

Water Quality ◽

Principal Component Analysis ◽

Dissolved Oxygen ◽

Dimension Reduction ◽

Principal Component ◽

Component Analysis ◽

Computational Time ◽

Aquatic Life ◽

Ann Models ◽

Input Variables

In this research, an attempt was made to reduce the dimension of wavelet-ANFIS/ANN (artificial neural network/adaptive neuro-fuzzy inference system) models toward reliable forecasts as well as to decrease computational cost. In this regard, the principal component analysis was performed on the input time series decomposed by a discrete wavelet transform to feed the ANN/ANFIS models. The models were applied for dissolved oxygen (DO) forecasting in rivers which is an important variable affecting aquatic life and water quality. The current values of DO, water surface temperature, salinity, and turbidity have been considered as the input variable to forecast DO in a three-time step further. The results of the study revealed that PCA can be employed as a powerful tool for dimension reduction of input variables and also to detect inter-correlation of input variables. Results of the PCA-wavelet-ANN models are compared with those obtained from wavelet-ANN models while the earlier one has the advantage of less computational time than the later models. Dealing with ANFIS models, PCA is more beneficial to avoid wavelet-ANFIS models creating too many rules which deteriorate the efficiency of the ANFIS models. Moreover, manipulating the wavelet-ANFIS models utilizing PCA leads to a significant decreasing in computational time. Finally, it was found that the PCA-wavelet-ANN/ANFIS models can provide reliable forecasts of dissolved oxygen as an important water quality indicator in rivers.

Download Full-text

A German version of the Intermittent Claudication Questionnaire (ICQ): cultural adaptation and validation

VASA ◽

10.1024/0301-1526/a000218 ◽

2012 ◽

Vol 41 (5) ◽

pp. 333-342 ◽

Cited By ~ 3

Author(s):

Kirchberger ◽

Finger ◽

Müller-Bühl

Keyword(s):

Principal Component Analysis ◽

Intermittent Claudication ◽

Completion Time ◽

Short Form ◽

Principal Component ◽

Component Analysis ◽

German Version ◽

Average Completion Time ◽

Sf 36 ◽

Related Quality

Background: The Intermittent Claudication Questionnaire (ICQ) is a short questionnaire for the assessment of health-related quality of life (HRQOL) in patients with intermittent claudication (IC). The objective of this study was to translate the ICQ into German and to investigate the psychometric properties of the German ICQ version in patients with IC. Patients and methods: The original English version was translated using a forward-backward method. The resulting German version was reviewed by the author of the original version and an experienced clinician. Finally, it was tested for clarity with 5 German patients with IC. A sample of 81 patients were administered the German ICQ. The sample consisted of 58.0 % male patients with a median age of 71 years and a median IC duration of 36 months. Test of feasibility included completeness of questionnaires, completion time, and ratings of clarity, length and relevance. Reliability was assessed through a retest in 13 patients at 14 days, and analysis of Cronbachs alpha for internal consistency. Construct validity was investigated using principal component analysis. Concurrent validity was assessed by correlating the ICQ scores with the Short Form 36 Health Survey (SF-36) as well as clinical measures. Results: The ICQ was completely filled in by 73 subjects (90.1 %) with an average completion time of 6.3 minutes. Cronbachs alpha coefficient reached 0.75. Intra-class correlation for test-retest reliability was r = 0.88. Principal component analysis resulted in a 3 factor solution. The first factor explained 51.5 of the total variation and all items had loadings of at least 0.65 on it. The ICQ was significantly associated with the SF-36 and treadmill-walking distances whereas no association was found for resting ABPI. Conclusions: The German version of the ICQ demonstrated good feasibility, satisfactory reliability and good validity. Responsiveness should be investigated in further validation studies.

Download Full-text