Comparative study of the physicochemical properties of a vegan dressing-type mayonnaise and traditional commercial mayonnaise

The food industry has developed a vegan dressing-type mayonnaise due to new consumer demands. The aim of this study was to compare three commercial mayonnaise types with a vegan dressing, measuring their physicochemical properties. Four dressing samples were analyzed: vegan, homemade recipe, creamy, and light. The following properties were measured: water activity, color, droplet size, rheological properties, structural analysis, and oxidative stability. A high color difference was observed between vegan and the other samples due to the presence of chickpea protein. The size and distribution of droplets of the vegan sample were greater than the others. The rheological properties indicated that all samples are non-Newtonian pseudoplastic fluids. The FT-IR results indicated that the highest peak for vegan corresponded to its content in mono-unsaturated fat. Therefore, it showed the lowest oxidative stability. In conclusion, the mayonaise formulations were affected by physicochemical properties such as the content and composition of the oil, thickener and protein contents, along with processing technology.

GROWTH AND EARLY REPRODUCTION DEVELOPMENT OF THE FIRST GENERATION OF SHEATFISH, Ompok miostoma (Vaillant, 1902) REARED IN CONTROLLED CONCRETE TANKS

This study was conducted to observe the growth and reproductive biology of wild sheatfish in controlled concrete tanks. The research was carried out from January to November 2020 at the Research Station for Freshwater Fisheries Germplasm, Cijeruk, Bogor. Sampled fish were captured from Cilala Lake in Bogor and Cipanas River in Sumedang, West Java. The collected fish were 14.6 ± 2.24 cm in length and 21.5 ± 9.19 g in weight. Growth and reproductive biology parameters were measured every 30 days. Cortisol, estradiol, vitellogenin, testosterone, glucose, and hemoglobin were also determined as the supporting parameters for gonadal maturity. Measured water quality parameters were temperature, pH, dissolved oxygen, ammonia, and alkalinity. The results showed that sheatfish grew with a specific growth rate of 0.4 ± 0.15%/day, FCR of 3.2 ± 0.26, and survival rate of 100%. Observation on the gonad maturity found that the fish studied were in the level-I and II. There are no significant differences regarding the supporting parameters (P>0.05) on the fish examined, despite the tendency of decreasing cortisol, and increasing testosterone. Based on the results, this study concludes that the observed fish can adapt, grow, and start to mature their gonads in their new environment, with temperature as one of the possible key factors influencing its gonad development.

Comparisons of Zooplankton Community Structure between with- and without- Pesticide Applications on Rice Fields

Herbicide usage in rice fields over time may have a direct and indirect influence on the biodiversity of the fields. The impacts of herbicide usage on non-target organisms were assessed by examining the species richness and zooplankton density of two rice fields. One was 2.08 hectares in size and had been treated with pesticides during the sampling year (RF-PA). The second field, measuring 1.76 hectares, had received no pesticide treatment (RF-NPA). Every two weeks, zooplankton was quantitatively collected from ten sampling sites in each field. At each station, 20 L of measured water was filtered through a plankton net with a mesh size of 20 µm and preserved in 1% Lugol’s solution. The results revealed that RF-NPA and RF-PA had 112 and 88 species of zooplankton, respectively, with an abundance-based Jaccard index (Jabd) of 0.438. The total zooplankton density in RF-NPA was 24.4 ind./L, significantly higher than the 16.6 ind./L in RF-PA (p < 0.001). The Shannon-Wiener diversity index (H’) and evenness (J) were highest in RF-NPA at the second sampling (3.45 and 0.75, respectively). These results indicate that glyphosate application affects the diversity of species and density of zooplankton in rice fields.

Characterisation of pH variations along the Ba River in Fiji utilising the GEF R2R framework during the 2019 sugarcane season

Within Pacific Small Island Developing States (Pacific SIDS), the ridge-to-reef (R2R) approach has emerged as a framework for monitoring river connectivity between terrestrial and marine ecosystems. The study measured water quality, including pH, over 88.40 km of the Ba River in Fiji. The sampling design focused on measuring spatio-temporal variability in pH throughout the sugarcane season with three rapid sampling periods (RSP1, 2 & 3) along the Ba River, together with continuous measurement of temperature and pH using stationary data loggers at two locations upstream and downstream of the sugar mill. Spatial variability in pH and water quality was characterised before (RSP1 and RSP2) and during (RSP3) the sugarcane season. Mean pH measured before the sugarcane crushing season for RSP1 and RSP2 were 8.16 (± 0.49) and 8.20 (± 0.61) respectively. During the sugarcane crushing season (RSP3), mean pH declined by 3.06 units to 6.94 within 42 m downstream of the sugar mill (P ≤ 0.001). The 3.06 unit decline in pH for RSP3 exceeded both the mean diurnal variation in pH of 0.39 and mean seasonal variation in pH of 2.01. This decline in pH could be a potential source of acidification to downstream coastal ecosystems with implications for coral reefs, biodiversity and fishery livelihoods.

Statistical Analysis and Trend Detection of the Hydrological Extremes of the Danube River at Bratislava

The territory of the Danube River Basin is one of the most flood-endangered regions in Europe. The flow regime conditions of the Danube River are continually changing. These changes are the result of natural processes and anthropogenic activities. In the present study, we focused on the statistical analysis and trend detection of the hydrological extremes of the Danube River at Bratislava. This paper firstly analyses the changes in correlation between water levels of the Danube River at Bratislava and Kienstock. Studied period of 1991-2013 included one or three hour measured water levels of the Danube River at Bratislava and Kienstock and shorter periods (1991–1995, 1999–2002, and 2004—2013) were selected for identification of the water level changes at Bratislava. One of the factors that recall the necessity to establish empirical - regression relationships was increasing of water levels of the Danube River at Bratislava (due to sediments accumulation at Bratislava). The results of the analysis indicated an increasing of water levels corresponding to the same flood discharges observed in the past. We also can say that travel time of the Danube floods between Kienstock and Bratislava did not change significantly during the analysed period. In the second part of the paper, we have identified changes in commonly used hydrological characteristics of annual maximum discharges, annual discharges and daily discharges of the Danube River at Bratislava during the period of 1876–2019. We examined whether there is a significant trend in discharges of the Danube River at Bratislava.

Experimental analysis of moisture uptake and dry-out in CLT end-grain exposed to free water

This paper presents the results of a series of laboratory tests of CLT end-grain moisture uptake and dry-out. We put CLT test details (TDs) in direct water contact from the end-grain edge and then left the TDs to dry for two weeks in the laboratory and in an outside shelter. Half of the TDs had their wet sides attached to another CLT detail. Fibre saturation point was quickly reached in the bottom part of the TDs during the seven-day water contact. A tendency of increasing moisture content (MC) was up to 90 mm from the wet edges, but we did not record MC levels above the critical level at that height. However, MC exceeded critical levels at 60 mm from the water level. The measured water absorption coefficient Aw was 3.51×10−3 kg/m2-s0’5. Drying was negligible for the TDs which were in contact with another CLT detail. Thus, moisture dry-out is very complicated in joints where the CLT end-grain is covered, such as the exterior wall to foundation or intermediate ceiling connection. The dry-out of CLT is not expected in a cold and humid outdoor environment once the CLT end-grain has absorbed moisture even with wet edges exposed to air.

Prediction research on sedimentation balance of Three Gorges Reservoir under new conditions of water and sediment

Influenced by climate change and human activities, especially the completion and operation of cascade reservoirs in the middle and lower reaches of Jinsha River since 2012, new changes have taken place in the water and sediment characteristics of the Three Gorges Reservoir (TGR) in recent years. In this paper, a one-dimensional unsteady water and sediment mathematical model of the main and tributary rivers of the TGR is established, and the main calculation parameters of the model are calibrated with the measured water and sediment data from January 1, 2008 to December 31, 2017. In view of the different combinations of inflow water and sediment that may occur in the TGR under the condition of new water and sediment, the long-term changes of sediment erosion and deposition and the balance of reservoir deposition in the TGR are studied using the model. The results show that: (1) Under the new conditions of water and sediment, the amount of sediment in the TGR accounts for only 14.8% and 35.8% of that in 1956–1990 and 2003–2012, respectively; (2) The variation process of water level, discharge and sediment concentration of each station along the route calculated by the model is basically consistent with the measured results, and the calculated values of total deposition amount and deposition distribution are also basically consistent with the measured results. The verification results of the model are in accordance with the measured values; (3) Under the water-sediment conditions during 1961–1970 and 1991–2000, the model predicted the estimates of 320 and 430 years for the TGR to reach a sedimentation balance, respectively. Under the new water-sediment conditions, it takes 560 years at most and 450 years at least to reach the sedimentation balance for the TGR, and the corresponding condition is the typical year with less water-less sediment and more water-more sediment, respectively. The research results of this paper can provide a new reference for the long-term safe operation and operation optimization of the TGR.

The Water Polymorphism and the Liquid–Liquid Transition from Transport Data

NMR spectroscopic literature data are used, in a wide temperature-pressure range (180–350 K and 0.1–400 MPa), to study the water polymorphism and the validity of the liquid–liquid transition (LLT) hypothesis. We have considered the self-diffusion coefficient DS and the reorientational correlation time τθ (obtained from spin-lattice T1 relaxation times), measured, respectively, in bulk and emulsion liquid water from the stable to well inside the metastable supercooled region. As an effect of the hydrogen bond (HB) networking, the isobars of both these transport functions evolve with T by changing by several orders of magnitude, whereas their pressure dependence become more and more pronounced at lower temperatures. Both these transport functions were then studied according to the Adam–Gibbs model, typical of glass forming liquids, obtaining the water configurational entropy and the corresponding specific heat contribution. The comparison of the evaluated CP,conf isobars with the experimentally measured water specific heat reveals the full consistency of this analysis. In particular, the observed CP,conf maxima and its diverging behaviors clearly reveals the presence of the LLT and with a reasonable approximation the liquid–liquid critical point (LLCP) locus in the phase diagram.

Machine learning for manually-measured water quality prediction in fish farming

Monitoring variables such as dissolved oxygen, pH, and pond temperature is a key aspect of high-quality fish farming. Machine learning (ML) techniques have been proposed to model the dynamics of such variables to improve the fish farmer’s decision-making. Most of the research on ML in aquaculture has focused on scenarios where devices for real-time data acquisition, storage, and remote monitoring are available, making it easy to develop accurate ML techniques. However, fish farmers do not necessarily have access to such devices. Many of them prefer to use equipment to manually measure these variables limiting the amount of available data to process. In this work, we study the use of random forests, multivariate linear regression, and artificial neural networks in scenarios with limited amount of measurements to analyze data from water-quality variables that are commonly measured in fish farming. We propose a methodology to build models in two scenarios: i) estimation of unobserved variables based on the observed ones, and ii) forecasting when a low amount of data is available for training. We show that random forests can be used to forecast dissolved oxygen, pond temperature, pH, ammonia, and ammonium when the water pond variables are measured only twice per day. Moreover, we showed that these prediction models can be implemented on a mobile-based information system and run in an average smartphone that fish farmers can afford.