Effect of eco-physiological factors on biometric traits of green mussel Perna viridis cultured in the south-east coast of the Bay of Bengal, Bangladesh

Noor, Aysha Rahi; Shakil, Abrar; Hoque, Nayeema Ferdausy; Rahman, Moshiur; Akter, Shirin; Talukder, Avijit; Ahmad-Al-Nahid, Sk.; Wahab, Abdul; Nahiduzzaman, Md.; Rahman, Jalilur; Asaduzzaman, Md

doi:10.1016/j.aqrep.2020.100562

Cited by 6 publications

(3 citation statements)

References 39 publications

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“…The range of water temperature in the Percut Sei Tuan is between 29.73-32.17°C. In accordance with the observations of Sagita et al (2017) and Noor et al (2021), the water temperature of Green mussel cultivation during the study ranged from 27.5°C-34.0°C. The positive relationship between P. viridis density and temperature, especially at station I (points 1 and 2).…”

Section: Discussionsupporting

confidence: 92%

“…This analysis was performed using the XL Stat software in order to determine the relationship between the density of Green mussels and the physical and chemical parameters of water and sediment (Basyuni et al 2018;Noor et al 2021). There were 12 factors analyzed in PCA, including density of Green mussels, temperature, salinity, water current, pH, DO, nitrate, phosphate, C-organic, percentage of texture sand, silt, and clay.…”

Section: Principal Component Analysis (Pca)mentioning

confidence: 99%

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Density and characteristics of Green mussels (Perna viridis) in Percut Sei Tuan coastal, North Sumatra, Indonesia

et al. 2021

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Percut Sei Tuan is a coastal area on the east coast of North Sumatra which has a lot of natural resource potential, one of them which is green mussels (Perna viridis). Green mussels have many benefits, namely for consumption, cultivation and bioindicator. This study aimed to determine the density, habitat location, growth pattern, frequency distribution of green mussels, physical-chemical parameters of water, a substrate of the bottom waters, and the relationship of green clams density to water and substrate parameters. The study was conducted in July-September 2020. Data analysis included density, the relationship of total length and weight of green mussels, the frequency distribution of shell lengths, and Principal Component Analysis (PCA). The results showed that the density of green mussels at stations I, II, and III were 352 ind/m2, 3 ind/m2, and 1 ind/m2, respectively. The relationship between the length and weight of green shells shows that the growth was negative allometric. The water condition, seen from the physical, chemical, and substrate parameters, was still suitable for P. viridis. Water and substrate parameters that were positively related to the density of green mussels were water temperature, nitrate, phosphate, C-organic, percentage of silt and clay. Parameters that were negatively related were salinity, pH, and percentage of sand in the bottom substrate. The present study suggested that Station I was an appropriate area for the growth and reproduction of green mussels.

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Section: Discussionsupporting

confidence: 92%

Section: Principal Component Analysis (Pca)mentioning

confidence: 99%

Density and characteristics of Green mussels (Perna viridis) in Percut Sei Tuan coastal, North Sumatra, Indonesia

et al. 2021

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“…, and other environmental conditions(Noor et al 2021). Green mussel shell opening and meat yield, which are affected by steaming, are shown in Table1.…”

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confidence: 99%

Quality Changes of Green Mussel (Perna viridis) at Different Steaming Conditions

Endoma¹,

Baldoza²,

Gamez³

et al. 2022

Philipp J Sci

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This study investigates the effects of different steaming temperatures (80, 90, and 100 °C) and time (2, 4, and 6 min) combinations on the quality and safety of green mussels. Analyses were conducted on steamed green mussel meat to determine the optimum steaming conditions based on its morphometric, microbiological, and physico-chemical properties. Results showed that steaming at 80 °C for 2 min provides high meat yield, reduced the total APC by 90% and decreased Escherichia coli counts by 75%. However, it is important to increase the steaming temperature to 90 °C (for 6 min) or 100 °C (for 2, 4, and 6 min) in order to eliminate Salmonella spp. and Vibrio spp. in steamed mussels. Meanwhile, increasing the steaming temperature at 100 °C (for 2, 4, and 6 min) could lower the acidity of steamed mussel meat (at pH 6.8), which may increase expressible drip loss and leaching of nutrients such as lipids and proteins. The steaming method as a thermal shocking procedure to deliver minimally-processed green mussels is a practical yet crucial in achieving safe microbiological levels without compromising its yield and physico-chemical properties.

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Analytical study on users’ awareness and acceptability towards adoption of multimodal biometrics (MMB) mechanism in online transactions: a two-stage SEM-ANN approach

Purohit

Dadhich

Ajmera

2022

Multimed Tools Appl

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s The study analyses user awareness of multimodal biometrics and its acceptability for online transactions in the current dynamic world. The study was performed on the five underlying perspectives: User Acceptability, Cognizant Factors towards Biometrics, Technological factors, Perceptional Factors (Fingerprints, Iris, Face Recognition and Voice) and Data Privacy Factors. A questionnaire was prepared and circulated to the 530 biometrics users; on that basis, the corresponding answer was obtained for analysis. SEM is first employed to gauge the research model and test the prominent hypothesized predictors, which are then used as inputs in the neural network to evaluate the relative significance of each predictor variable. By considering the standardized significance of the feed-for-back-propagation of ANN algorithms, the study found a significant effect of DPF_3 (93%), DPF_2 (50%) and DPF_4 (34%) on the adoption of MMB. In the Perceptional construct, PRF_2 (49%) and PRF_3 (33%) was relatively the most important predictor, whereas, in User Acceptability, UAC_2 (37%), UAC_3 & UAC_5 (41%) was vital to be considered. Only one item, TCF_2 (35%), from Technological Factors, followed by Cognizant factors, i.e., CFG_1 (33%), confirmed the best fit model to adopt MMB. The research is a novel effort when compared to past studies as it considered cognizant and perceptual factors in the proposed model, thereby expanding the analytical outlook of MMB literature. Thus, the study also explored several new and valuable practical implications for adopting multimodal instruments of biometrics along with certain limitations.

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Effect of eco-physiological factors on biometric traits of green mussel Perna viridis cultured in the south-east coast of the Bay of Bengal, Bangladesh

Cited by 6 publications

References 39 publications

Density and characteristics of Green mussels (Perna viridis) in Percut Sei Tuan coastal, North Sumatra, Indonesia

Density and characteristics of Green mussels (Perna viridis) in Percut Sei Tuan coastal, North Sumatra, Indonesia

Quality Changes of Green Mussel (Perna viridis) at Different Steaming Conditions

Analytical study on users’ awareness and acceptability towards adoption of multimodal biometrics (MMB) mechanism in online transactions: a two-stage SEM-ANN approach

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