Genetic Variability and Population Structure of Salvia lachnostachys: Implications for Breeding and Conservation Programs

The genetic diversity and population structure of Salvia lachnostachys Benth were assessed. Inter Simple Sequence Repeat (ISSR) molecular markers were used to investigate the restricted distribution of S. lachnostachys in Parana State, Brazil. Leaves of 73 individuals representing three populations were collected. DNA was extracted and submitted to PCR-ISSR amplification with nine tested primers. Genetic diversity parameters were evaluated. Our analysis indicated 95.6% polymorphic loci (stress value 0.02) with a 0.79 average Simpson’s index. The Nei-Li distance dendrogram and principal component analysis largely recovered the geographical origin of each sample. Four major clusters were recognized representing each collected population. Nei’s gene diversity and Shannon’s information index were 0.25 and 0.40 respectively. As is typical for outcrossing herbs, the majority of genetic variation occurred at the population level (81.76%). A high gene flow (Nm = 2.48) was observed with a correspondingly low fixation index. These values were generally similar to previous studies on congeneric species. The results of principal coordinate analysis (PCA) and of arithmetic average (UPGMA) were consistent and all three populations appear distinct as in STRUCTURE analysis. In addition, this analysis indicated a majority intrapopulation genetic variation. Despite the human pressure on natural populations our study found high levels of genetic diversity for S. lachnostachys. This was the first molecular assessment for this endemic species with medicinal proprieties and the results can guide for subsequent bioprospection, breeding programs or conservation actions.     

Bioactive Phytochemicals from Wild Arbutus unedo L. Berries from Different Locations in Portugal: Quantification of Lipophilic Components

The lipophilic composition of wild Arbutus unedo L. berries, collected from six locations in Penacova (center of Portugal), as well as some general chemical parameters, namely total soluble solids, pH, titratable acidity, total phenolic content and antioxidant activity was studied in detail to better understand its potential as a source of bioactive compounds. The chemical composition of the lipophilic extracts, focused on the fatty acids, triterpenoids, sterols, long chain aliphatic alcohols and tocopherols, was investigated by gas chromatography–mass spectrometry (GC–MS) analysis of the dichloromethane extracts. The lipophilic extractives of the ripe A. unedo berries ranged from 0.72% to 1.66% (w/w of dry weight), and consisted mainly of triterpenoids, fatty acids and sterols. Minor amounts of long chain aliphatic alcohols and tocopherols were also identified. Forty-one compounds were identified and among these, ursolic acid, lupeol, α-amyrin, linoleic and α-linolenic acids, and β-sitosterol were highlighted as the major components. To the best of our knowledge the current research study provides the most detailed phytochemical repository for the lipophilic composition of A. unedo, and offers valuable information for future valuation and exploitation of these berries.     

Strategy for a Scale‐up Correlation in a Dissolved Air Flotation Chamber

Beginning with a laboratory‐scale physical model, a scale‐up correlation for a pilot unit project was determined based on the analysis of dynamic similarity correlations involving the predominant phenomena of a dissolved air flotation (DAF) chamber. The implantation costs of pilot units require special strategies due to the lack of correlations of this type, as novel flotation methods have been considered strictly from an economic standpoint. With the aid of computational fluid dynamics and videos of microbubble and floc flow, inertia and gravity were identified as the predominant phenomena in a DAF chamber. The strategy described herein is simple and reduces the likelihood of future risks in scale‐up investments.     

Kinetics of Soybean Oil Hydrolysis on Niobium Catalysts

The catalytic hydrolysis of soybean oil was used as an alternative for the production of monoglycerides (MG) and diglycerides (DG). The reactions were conducted in a stainless-steel tubular reactor in the temperature range of 240–290 °C, on niobium phosphate (NBP) and niobium oxide (NBO) as catalysts. In the hydrolysis reactions at 270 °C, the maximum selectivities of the products of interest were obtained at 22 % MG and 48 % DG for the reaction with NBP, and 7 % MG and 33 % DG with NBO, for 59 % and 36 % of triglyceride conversion in 10 min, respectively. The proposed kinetic model presented a good fit of the theoretical model with the experimental data, showing that the previous hypotheses considered for the mechanism development are suitable for describing the kinetics of soybean oil hydrolysis.     

Improving weld formability by a novel dual-rotation bobbin tool friction stir welding

A novel dual-rotation bobbin tool friction stir welding (DBT-FSW) was developed, in which the upper shoulder (US) and lower shoulder (LS) have different rotational speeds. This process was tried to weld 3.2 mm thick aluminum-lithium alloy sheets. The metallographic analysis and torque measurement were carried out to characterize the weld formability. Experimental results show that compared to conventional bobbin tool friction stir welding, the DBT-FSW has an excellent process stability, and can produce the defect-free joints in a wider range of welding parameters. These can be attributed to the significant improvement of material flow caused by the formation of a staggered layer structure and the unbalanced force between the US and LS during the DBT-FSW process.     

Genomic studies of milk-related traits in water buffalo (Bubalus bubalis) based on single-step genomic best linear unbiased prediction and random regression models

Genomic selection has been widely implemented in many livestock breeding programs, but it remains incipient in buffalo. Therefore, this study aimed to (1) estimate variance components incorporating genomic information in Murrah buffalo; (2) evaluate the performance of genomic prediction for milk-related traits using single- and multitrait random regression models (RRM) and the single-step genomic best linear unbiased prediction approach; and (3) estimate longitudinal SNP effects and candidate genes potentially associated with time-dependent variation in milk, fat, and protein yields, as well as somatic cell score (SCS) in multiple parities. The data used to estimate the genetic parameters consisted of a total of 323,140 test-day records. The average daily heritability estimates were moderate (0.35 ± 0.02 for milk yield, 0.22 ± 0.03 for fat yield, 0.42 ± 0.03 for protein yield, and 0.16 ± 0.03 for SCS). The highest heritability estimates, considering all traits studied, were observed between 20 and 280 d in milk (DIM). The genetic correlation estimates at different DIM among the evaluated traits ranged from ?0.10 (156 to 185 DIM for SCS) to 0.61 (36 to 65 DIM for fat yield). In general, direct selection for any of the traits evaluated is expected to result in indirect genetic gains for milk yield, fat yield, and protein yield but also increase SCS at certain lactation stages, which is undesirable. The predicted RRM coefficients were used to derive the genomic estimated breeding values (GEBV) for each time point (from 5 to 305 DIM). In general, the tuning parameters evaluated when constructing the hybrid genomic relationship matrices had a small effect on the GEBV accuracy and a greater effect on the bias estimates. The SNP solutions were back-solved from the GEBV predicted from the Legendre random regression coefficients, which were then used to estimate the longitudinal SNP effects (from 5 to 305 DIM). The daily SNP effect for 3 different lactation stages were performed considering 3 different lactation stages for each trait and parity: from 5 to 70, from 71 to 150, and from 151 to 305 DIM. Important genomic regions related to the analyzed traits and parities that explain more than 0.50% of the total additive genetic variance were selected for further analyses of candidate genes. In general, similar potential candidate genes were found between traits, but our results suggest evidence of differential sets of candidate genes underlying the phenotypic expression of the traits across parities. These results contribute to a better understanding of the genetic architecture of milk production traits in dairy buffalo and reinforce the relevance of incorporating genomic information to genetically evaluate longitudinal traits in dairy buffalo. Furthermore, the candidate genes identified can be used as target genes in future functional genomics studies.     

Facing Losses of Telemetric Signal in Real Time Forecasting of Water Level using Artificial Neural Networks

Water Resources Management - Real-time forecasting plays a valuable role in the early warning system framework by reducing damage. However, signal loss in telemetric monitoring networks tends to...