Simultaneous Extraction and Fractionation of Fish Oil from Tuna By-Product Using Supercritical Carbon Dioxide (SC-CO2)

ABSTRACT

Fish oil was extracted and simultaneously collected into six fractions based on molecular weight and the chain length of triglycerides in terms of fatty acid constituents without splitting of the triglycerides, using supercritical carbon dioxide (SC-CO₂) at optimized conditions of 40 MPa, 65°C, and a flow rate 3 mL min^?1. In each type of fractionation, the first fraction (F1) was rich in saturated fatty acids (SFA; 52.57 to 61.26%), followed by monounsaturated fatty acids (MUFA; 22.17 to 23.22%) and polyunsaturated fatty acids (PUFA; (0.54 to 20.37%); the sixth fraction (F6) was rich in PUFA (48.93%), followed by MUFA (33.59%) and SFA (13.61%). It was obvious that short-chain fatty acids were extracted at an earlier fraction; therefore, the latter fractions were dominant in long-chain fatty acids, especially MUFA and PUFA. Thus, omega-3 fish oil (last three fractions) was successfully separated to be used as a value-added health product.     

A REVIEW OF PRODUCTION FRONTIER RESEARCH IN AQUACULTURE (2001–2011)

Most research works on the production frontier in aquaculture focus on efficiency measurement using either Stochastic Production Frontier (SPF) or Data Envelopment Analysis (DEA). The studies on productivity growth in aquaculture were limited, perhaps due to lack of time-series data. Nevertheless, total factor productivity analysis (TFP) in fish farms has started gaining popularity in recent years. In addition, the majority of the efficiency studies have centered on technical efficiency analysis but substantial increases in the output levels can be fully realized through improving overall economic efficiency. Therefore, this review suggests that future research should estimate all three efficiency indices (i.e., technical, allocative and economic efficiencies).     

Visible-Light-Driven Photocatalytic N-Doped TiO<Subscript>2</Subscript> for Degradation of Bisphenol A (BPA) and Reactive Black 5 (RB5) Dye

Bisphenol A (BPA) and reactive black 5 (RB5) dye are among the most persistent and non-biodegradable contaminants in water which require an urgent need for the development of effective removal method. The ubiquitous existence of both contaminants could interfere with the human health and aquatic environmental balance. Photocatalytic process as one of advanced oxidation processes (AOPs) has shown high performance for degradation of organic compounds to the harmless materials under sensible condition. Therefore, this study aims to develop a visible-light-driven photocatalyst that can efficiently degrade BPA and RB5 present in household water. N-doped TiO₂ were successfully synthesized via simple and direct sol–gel method. The prepared TiO₂ nanoparticles were characterized by field emission scanning microscope (FE-SEM), X-ray diffraction (XRD), Fourier transform infrared (FTIR), and Brunauere Emmette Teller (BET) analysis. The incorporation of nitrogen in TiO₂ lattice exhibited excellent optical responses to visible region as revealed by UV–Vis–NIR spectroscopy absorption capability at 400–600 nm. The photocatalytic activity of the N-doped TiO₂ nanoparticles was measured by photocatalytic degradation of BPA and RB5 in an aqueous solution under visible-light irradiations. Degradation of BPA and RB5 was 91.3% and 89.1%, respectively after 360 min illumination. The degradation of BPA and RB5 by N-doped TiO₂ was increased up to 89.8% and 88.4%, respectively under visible-light irradiation as compared to commercial TiO₂ P25. This finding clearly shows that N-doped TiO₂ exhibits excellent photocatalytic degradation of BPA and RB5 under visible irradiation, hence have a promising potential in removing various recalcitrant contaminants for water treatment to fulfill the public need to consume clean water.

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Response Surface Methodology for Modeling Bisphenol A Removal Using Ultrafiltration Membrane System

In this work, the effects of various operating parameters (pressure, pH, BPA concentration, and filtration time) toward bisphenol A (BPA) removal via ultrafiltration (UF) membrane system were investigated using response surface methodology (RSM). Historical data design of RSM was used to obtain the interaction between variables and response as well as optimizing the process. The analysis of variance (ANOVA) showed that the third-order polynomial model was significant in which pH and filtration time were identified as significant terms that influence BPA removal. The 3D response surface plots revealed the two-factor interaction between independent and dependent variables. The optimization process of the model predicted optimum conditions of 99.61% BPA removal at 1 bar, pH 6.7, 10 μg/L BPA concentration, and 10-min filtration time. The predicted optimum conditions for BPA removal were consistent with the obtained experimental values, indicating reliable application of historical data design RSM for modeling BPA removal in UF membrane system.     

Comparative Studies on the Role of Organic Biostimulant in Resistant and Susceptible Cultivars of Rice Grown under Saline Stress - Organic Biostimulant Alleviate Saline Stress in Tolerant and Susceptible Cultivars of Rice

Plants are sessile organisms that experience various abiotic stresses during their lifespan and try to adapt to these environmental stresses by manipulating their physiological, biochemical, cellular, and molecular mechanisms. Salinity is one of the important abiotic stress that affects the metabolism and physiology of plant cells that leads to serious damage to crops and productivity. We investigated the response of two contrasting (salt susceptible and tolerant) cultivars during saline stress by modulating its effect with the application of an important natural biostimulant panchagavya (PG). The results showed that the salinity stress greatly influenced and negatively affects the plant growth, biochemical attributes, and induces the expression of various genes in both cultivars. Furthermore, we assessed the effect of PG alone and by amending with NaCl to alleviate the saline stress which showed a significant enhancement of biochemical and physiological characteristics in both cultivars. Furthermore, we assessed the response of seven autophagy associated gene (ATG1, ATG3, ATG4, ATG6, ATG7, ATG8, and ATG9), BAX Inhibitor -1 (BI-1), Mitogen activated Protein Kinase–1 (MAPK-1), WRKY53, Catalase -1 (CAT-1), Superoxide Dismutase (SOD), and Glutathione Peroxidase (GPX) genes in rice that displayed the differential expression pattern during saline stress in both cultivars. We concluded that saline stress can be manipulated by the application of PG and positively regulate the physiological, biochemical, and gene expression response in salt-susceptible and -tolerant rice cultivars. Furthermore, the current study also suggested that salinity is a mutifactorial and multigenic response. Autophagy and programmed cell death regulated along with salinity and was helpful in adapting the tolerance against the stress condition.     

Exogenous Calcium Supplementation Improves Salinity Tolerance in BRRI Dhan28; a Salt-Susceptible High-Yielding Oryza Sativa Cultivar

Journal of Crop Science and Biotechnology - Salinity is one of the most brutal abiotic stressors, commencing a great stumbling block in the way of attaining food security in Bangladesh. Cultivation...     

Sulfur uptake and translocation in maize (zea mays) grown in a high pH soil treated with elemental sulfur

A glasshouse experiment was conducted to elucidate the influence of elemental sulfur (S) application rates (0, 0.5, 1.0, and 2.0 g S kg^?1 soil) on the release and uptake of S at 0, 20, and 40 days after incubation. Results showed that there was a progressive upward trend in maize leaves, stem, and root S content with application of elemental S. However, maize production followed a nonlinear model. Plants grown in untreated soils suffer from S deficiency and addition of elemental S at a rate of 0.5 g S kg^?1 soil alleviated S deficiency. The decrease in maize performance due to the highest S application rate was not related to S toxicity. The greatest leave, stem, and root productions were obtained at S concentrations of 0.41, 0.58, and 0.2%, respectively. Overall, application of elemental S at a rate of 0.5 g S kg^?1 soil is recommended for maize performance improvement.     

An in silico approach for characterization of encoded protein from Rdr1, a black spot resistance gene in Rosa multiflora

Journal of Plant Diseases and Protection - Black spot disease is the most common diseases of landscape roses and is caused by Diplocarpon rosae Wolf. In Rosa multiflora, the screening of black...     

The potential of hyperspectral images and partial least square regression for predicting total carbon,total nitrogen and their isotope composition in forest litterfall samples

Purpose

The main objective of this study was to examine the potential of using hyperspectral image analysis for prediction of total carbon (TC), total nitrogen (TN) and their isotope composition (δ¹³C and δ¹⁵N) in forest leaf litterfall samples.

Materials and methods

Hyperspectral images were captured from ground litterfall samples of a natural forest in the spectral range of 400–1700 nm. A partial least-square regression model (PLSR) was used to correlate the relative reflectance spectra with TC, TN, δ¹³C and δ¹⁵N in the litterfall samples. The most important wavelengths were selected using β coefficient, and the final models were developed using the most important wavelengths. The models were, then, tested using an external validation set.

Results and discussion

The results showed that the data of TC and δ¹³C could not be fitted to the PLSR model, possibly due to small variations observed in the TC and δ¹³C data. The model, however, was fitted well to TN and δ¹⁵N. The cross-validation R² _cv of the models for TN and δ¹⁵N were 0.74 and 0.67 with the RMSE_cv of 0.53% and 1.07‰, respectively. The external validation R² _ex of the prediction was 0.64 and 0.67, and the RMSE_ex was 0.53% and 1.19 ‰, for TN and δ¹⁵N, respectively. The ratio of performance to deviation (RPD) of the predictions was 1.48 and 1.53, respectively, for TN and δ¹⁵N, showing that the models were reliable for the prediction of TN and δ¹⁵N in new forest leaf litterfall samples.

Conclusions

The PLSR model was not successful in predicting TC and δ¹³C in forest leaf litterfall samples using hyperspectral data. The predictions of TN and δ¹⁵N values in the external litterfall samples were reliable, and PLSR can be used for future prediction.

     

Phytoremediation Potential of Vetiver Grass (<Emphasis Type="Italic">Vetiveria zizanioides</Emphasis>) for Treatment of Metal-Contaminated Water

Phytoremediation using vetiver grass (Vetiveria zizanioides) has been regarded as an effective technique for removing contaminants in polluted water. This study was conducted to assess the removal efficiency of heavy metals (Cu, Fe, Mn, Pb, Zn) using vetiver grass (VG) at different root lengths and densities and to determine metals uptake rate by plant parts (root and shoot) between treatments (low and high concentration). Removal efficiency for heavy metals in water by VG is ranked in the order of Fe>Pb>Cu>Mn>Zn. Results showed that VG was effective in removing all the heavy metals, but removals greatly depend on root length, plant density and metal concentration. Longer root length and higher density showed greater removals of heavy metals due to increased surface area for metal absorption by plant roots. Results also demonstrated significant difference of heavy metals uptake in plant parts at different concentrations indicating that root has high tolerance towards elevated concentration of heavy metals. However, the effects were less significant in plant shoot suggesting that metals uptake were generally higher in root than in shoot. The findings have shown potential of VG in phytoremediation for heavy metals removal in water thus providing significant implication for treatment of metal-contaminated water.