Plant derived natural products have found uses in medicine, food, and other settings. For example, taxol (an anticancer drug), artemisinin (antimalaria drug), and vanillin (flavoring agent and spice) are all plant derived. Despite the importance of natural products, the enzymes responsible for making them are unknown in many cases. Therefore, scientists extract the natural products directly from plants or use chemical synthesis. These methods, while effective, face drawbacks. A possible solution is biosynthetic engineering of the desired product in chassis organisms. For biosynthetic engineering, the pathway genes must be known. One notable plant derived compound, which serves as a pollinator attractor and as an antifungal, is benzaldehyde. Because of its almond-like smell and taste, benzaldehyde has many uses in the cosmetic and flavor industries. After much effort, the enzyme responsible for benzaldehyde production, benzaldehyde synthase, was identified in 2022, allowing for production of benzaldehyde in organisms such as S. cerevisiae. In this work, we design a S. cerevisiae strain that can produce benzaldehyde from phenylalanine by expressing the on-path genes from Petunia hybrida cv. Mitchell flowers. Producing benzaldehyde using an engineered yeast strain can provide scientists with a method that is scalable, results in high-yields, and is environmentally friendly.
This study investigates a sustainable, zero-waste method for extracting antimicrobial biomaterials from Finnish maple (Acer platanoides) and birch (Betula pendula) leaves harvested in the fall, with potential applications in the textile industry. Three extraction methods were employed: subcritical acidified water extraction (40 bar), autoclave extraction (10 bar), and hot solvent extraction (1 bar), using varying temperatures (60°C–180°C) and solvents (70% ethanol and 15% acetic acid). The resulting extracts were tested for antimicrobial efficacy against Staphylococcus aureus microbes. Maple leaf extracts exhibited the largest inhibition zones (10–14 mm), especially when processed under acidified water with low pressures and temperatures, suggesting a high concentration of active antimicrobial compounds. This activity was linked to the phenolic compounds, including rutin, gallic acid, quercetin,tannic acid, and carboxylic acids, identified through FT-IR analysis. In contrast, birch leaf extracts demonstrated much lower antimicrobial activity, corresponding to a lower concentration of phenolic compounds and a less intense phenolic profile compared to maple leaves, which explains their reduced effectiveness. The extraction process follows a zero-waste model, where the feedstock is biomass from agricultural waste and the solid residual from the extraction can be converted into biofuel pellets, supporting a circular bioeconomy. The antimicrobial fractions derived from maple leaves offer a natural alternative for textile applications, serving both as antibacterial agents and natural colorants, reducing the need for synthetic chemicals. The use of abundant biomass ensures a scalable and sustainable solution that can be applied beyond Finland, contributing to global sustainability goals. The high-performance, eco-friendly textile solution offered by maple leaf extracts encourages the shift to circular, bio-based economies and supports industry sustainability.
Climate change is an universal upheaval having impact to the environment as well as health. The chemicals in the air in the form of aerosols, mist and fog often are a result of continuous photochemical interactions. The radiative forcing and the protective blanket shielding the human habitation is under constant threat due to accelerated development. The aim of this paper is to embark light upon the distinct properties of greenhouse gases which under alternative measures with dissolved solutes and solvents can reduce emissions, reduce global temperature by balancing heating and cooling.
The aim of this paper is to determine wheat and corn volume based geometric parameters L (length), width (W), and T(thickness). Wheat and corn represent random factors. The sample size included 100 seeds for each group and the grain measurement. A digital caliper was used to measure the geometric parameters for each single grain. In this data set, the means of each objective crop was calculated. The V(volume) of each grain was calculated based on formula. These characteristics were manipulated to create a mathematical model based on each crop and a mathematical model develop based on the two crops to determine the seed volume. SAS used to analysis data and Origin 2018 used to great 3D model graph. The results show that the overall for seed volume based one wheat and corn was highly significant F=(3,196), =5892.34 P value <0.0001, R-Square was 0.9890, Adj R-Sq=0.9889, and RMSE=6.89130, and R-Square for each variables were 0.9441, 0.9419, and 0.8755 for W,T, and L. Furthermore, the R-Square for the interaction was higher than 0.95. Wheat Volume=130.63+12.041W+25.869T+8.6016L. The mathematical approach for wheat was F=(3,199),=3540.03 P value <0.0001, R-Square was 0.9910, Adj R-Sq=0.9908, and RMSE=0.5423. Wheat equitation Volume=-47.375+8.0457W+10.2T+3.6013L. The mathematical approach for corn was F(3,99)=6016.82, P value <0.0001, R-Square was 0.9947, Adj R-Sq=0.9945, and RMSE=1.7085. Corn equitation Volume=-293.34+21.479W+31.306T+16.742L. The mathematical approach based on wheat and corn may help farmer and designer engineering in Iraq to get better idea when design storage bin and seed planter. Further studies need to be applied by using different seed crops.