Product Yield Research Articles

The impact of planting dates and hybrid selection on sunflower seed yield and oil content

Suitable planting dates and hybrid selection are crucial in optimising yield, component traits and oil production in sunflower (Helianthus annuus L.). In South Africa, there is limited information on the effects of planting dates on currently available sunflower hybrids in the marketplace. This study aimed to investigate the impact of planting dates on sunflower seed yield, oil content and oil yield, and to discern optimal planting dates for selected sunflower hybrids. Nineteen commercial sunflower hybrids were evaluated at three planting dates and three consecutive seasons in Potchefstroom, South Africa. The study used a complete block design with three replicates, and the standard analysis of variance was conducted. Significant differences were detected among seasons, planting dates, hybrids, and their interactions. The mean seed yield varied from 1.86 (LG 5678 CLP) to 2.50 tonnes ha−1 (PAN 7160 CLP). The oil content varied from 37.23 (P 65LP 54) to 53.16% (SY 3970 CLP), and the oil yield ranged from 0.74 (AGSUN 5101 CLP) to 1.25 tonnes ha−1 (LG 5710). Planting sunflowers in November and December resulted in the highest seed yield, oil content and oil yield, while planting in January and early February showed linear declines. January planting reduced 1 to 20%, 2 to 10%, and 3 to 26% in seed yield, oil content and oil yield, respectively. February planting significantly reduced seed yield by 72%, oil content by 20% and oil yield by 77%. The study recommended November and December as optimal sunflower planting dates in South Africa.

Upgrade and Renovation of Steel Billet Scale in front of High-speed Wire Furnace

This article briefly introduces the weighing device for steel billets in front of the heating furnace of the high-speed wire rod unit, and analyzes and summarizes the problems existing in the original weighing device for steel billets in production and use. Based on on-site installation conditions, design a new weighing method, match a large range weighing sensor, upgrade the automation control of the weighing device, and remotely transmit the billet weighing data to the MES system of the group. The automatic, stable, reliable, and accurate measurement of steel billet raw materials has been achieved, providing important guarantees for the accurate measurement of production line billet and product yield.

Optimal Dynamic Regimes for CO Oxidation Discovered by Reinforcement Learning.

Metal nanoparticles are widely used as heterogeneous catalysts to activate adsorbed molecules and reduce the energy barrier of the reaction. Reaction product yield depends on the interplay between elementary processes: adsorption, activation, desorption, and reaction. These processes, in turn, depend on the inlet gas composition, temperature, and pressure. At a steady state, the active surface sites may be inaccessible due to adsorbed reagents. Periodic regime may thus improve the yield, but the appropriate period and waveform are not known in advance. Dynamic control should account for surface and atmospheric modifications and adjust reaction parameters according to the current state of the system and its history. In this work, we applied a reinforcement learning algorithm to control CO oxidation on a palladium catalyst. The policy gradient algorithm was trained in the theoretical environment, parametrized from experimental data. The algorithm learned to maximize the CO2 formation rate based on CO and O2 partial pressures for several successive time steps. Within a unified approach, we found optimal stationary, periodic, and nonperiodic regimes for different problem formulations and gained insight into why the dynamic regime can be preferential. In general, this work contributes to the task of popularizing the reinforcement learning approach in the field of catalytic science.

Quantification of species composition in grass-clover swards using RGB and multispectral UAV imagery and machine learning.

Growing grass-legume mixtures for forage production improves both yield productivity and nutritional quality, while also benefiting the environment by promoting species biodiversity and enhancing soil fertility (through nitrogen fixation). Consequently, assessing legume proportions in grass-legume mixed swards is essential for breeding and cultivation. This study introduces an approach for automated classification and mapping of species in mixed grass-clover swards using object-based image analysis (OBIA). The OBIA procedure was established for both RGB and ten band multispectral (MS) images capturedby an unmanned aerial vehicle (UAV). The workflow integrated structural (canopy heights) and spectral variables (bands, vegetation indices) along with a machine learning algorithm (Random Forest) to perform image segmentation and classification. Spatial k-fold cross-validation was employed to assess accuracy. Results demonstrated good performance, achieving an overall accuracy of approximately 70%, for both RGB and MS-based imagery, with grass and clover classes yielding similar F1 scores, exceeding 0.7 values. The effectiveness of the OBIA procedure and classification was examined by analyzing correlations between predicted clover fractions and dry matter yield (DMY) proportions. This quantification revealed a positive and strong relationship, with R2 values exceeding 0.8 for RGB and MS-based classification outcomes. This indicates the potential of estimating (relative) clover coverage, which could assist breeders but also farmers in a precision agriculture context.

1,6-Nucleophilic Di- and Trifluoromethylation of para-Quinone Methides with Me3SiCF2H/Me3SiCF3 Facilitated by CsF/18-Crown-6.

The direct 1,6-nucleophilic difluoromethylation, trifluoromethylation, and difluoroalkylation of para-quinone methides (p-QMs) with Me3SiRf (Rf = CF2H, CF3, CF2CF3, CF2COOEt, and CF2SPh) under mild conditions are described. Although Me3SiCF2H shows lower reactivity than Me3SiCF3, it can react with p-QMs promoted by CsF/18-Crown-6 to give structurally diverse difluoromethyl products in good yields. The products can then be further converted into fluoroalkylated para-quinone methides and α-fluoroalkylated diarylmethanes.

Advances in organocatalyzed synthesis of organic compounds.

The recent advancements in utilizing organocatalysts for the synthesis of organic compounds have been described in this review by focusing on their simplicity, effectiveness, reproducibility, and high selectivity which lead to excellent product yields. The organocatalytic methods for various derivatives, such as indoles, pyrazolones, anthrone-functionalized benzylic amines, maleimide, polyester, phthalimides, dihydropyrimidin, heteroaryls, N-aryl benzimidazoles, stilbenoids, quinazolines, quinolines, and oxazolidinones have been specifically focused. The review provides more understanding by delving into potential reaction mechanisms. We anticipate that this collection of data and findings on successful synthesis of diverse compound derivatives will serve as valuable resources and stimulating current and future research efforts in organocatalysis and industrial chemistry.

Reaction engineering for high yield electrosynthesis: Unraveling the impact of reaction conditions and conversion on methanol oxidation to formate

Electrochemical processes offer defossilized alternatives to conventional routes. Key processes, such as hydrogen evolution and electrochemical CO2 reduction, are typically paired with the anodic oxygen evolution reaction (OER). However, the generated oxygen holds little value and the electrical costs associated with energy-intensive OER pose a significant economic barrier. The methanol oxidation reaction (MOR) to formate is a promising alternative to OER, requiring less energy and providing a value-added product. Extensive research focuses on MOR regarding high Faraday efficiencies, but conversion and product yields are mostly neglected. However, high conversion with sufficient yield is a prerequisite to transition from lab-scale catalysis towards feasible industrial applications. In this work, we investigated the selectivity of MOR to formate with progressing conversion at high current densities of up to 200mA/cm2 on hierarchically structured copper(II) oxide electrodes. We assessed the impact of the reaction conditions, including current density, temperature, flow rate, electrolyte composition, and membrane type. We found a positive influence of low current density and high temperature on the FE. Through tailored reaction conditions, we achieved a formate yield of 70% at 100mA/cm2 with an anodic potential of 1.33V vs. RHE. The anodic potential remained below typical OER potentials even at high conversion. For the first time, we demonstrated that MOR can achieve significant formate yields at high current density. Our results reveal the impact of conversion, reaction conditions and ion balance on selectivity and provide valuable insights for operating MOR at high yield in paired processes, e.g., with hydrogen evolution or CO2 reduction.

Improving the genetic stability of bacterial growth control for long-term bioproduction.

Using microorganisms for bioproduction requires the reorientation of metabolic fluxes from biomass synthesis to the production of compounds of interest. We previously engineered a synthetic growth switch in Escherichia coli based on inducible expression of theβ- and β'-subunits of RNA polymerase. Depending on the level of induction, the cells stop growing or grow at a rate close to that of the wild-type strain. This strategy has been successful in transforming growth-arrested bacteria into biofactories with a high production yield, releasing cellular resources from growth towards biosynthesis. However, high selection pressure is placed on a growth-arrested population, favoring mutations that allow cells to escape from growth control. Accordingly, we made the design of the growth switch more robust by building in genetic redundancy. More specifically, we added the rpoA gene, encoding for the α-subunit of RNA polymerase, under the control of a copy of the same inducible promoter used for expression control of ββ'. The improved growth switch is much more stable (escape frequency <10-9), while preserving the capacity to improve production yields. Moreover, after a long period of growth inhibition the population can be regenerated within a few generations. This opens up the possibility to alternate biomass accumulation and product synthesis over a longer period of time and is an additional step towards the dynamical control of bioproduction.

Efficient Trifluoromethylation of Halogenated Hydrocarbons Using Novel [(bpy)Cu(O2CCF2SO2F)2] Reagent.

This study introduces a novel trifluoromethylating reagent, [(bpy)Cu(O2CCF2SO2F)2], notable for not only its practical synthesis from cost-effective starting materials and scalability but also its nonhygroscopic nature. The reagent demonstrates high efficiency in facilitating trifluoromethylation reactions with various halogenated hydrocarbons, yielding products in good yields and exhibiting broad functional group compatibility. The development of [(bpy)Cu(O2CCF2SO2F)2] represents an advancement in the field of organic synthesis, potentially serving as a valuable addition to the arsenal of existing trifluoromethylating agents.

Efficient photocatalytic CO2 reduction to CH4 via electric field-regulated d-band center on Ga2S3/CuS S-type heterojunction interface structures

Photocatalytic CO2 reduction is an excellent method for the resource utilization of CO2. However, challenges such as inferior product yields and poor selectivity still exist. In this investigation, a novel composite catalyst of S-type heterojunction Ga2S3/CuS was formulated and synthesized using a facile two-step hydrothermal method. The CH4 product yield of 30 wt% Ga2S3/CuS reached 18.8 μmol·g−1·h−1. The reaction pathways were investigated through in-situ DRIFTS and DFT calculations, revealing the internal built-in electric field at the S-type heterojunction induces migration of the Cu atomic d-band center towards the Fermi energy level. The elevation of the Cu d orbital energy levels enables electron contributions from the dxz orbital to facilitate the formation of π* bonds with CO2, thereby promoting the adsorption of both CO2 and intermediate species to produce CH4. This study emphasizes the influence of the intrinsic electric field at the interface on product yield and selectivity.

Benefits from co-pyrolysis of biomass and refuse derived fuel for biofuels production: Experimental investigations

The application of renewable fuels and waste for energy production is crucial environmentally and economically. Co-pyrolysis of biomass and refuse derived fuel (RDF) offers a promising pathway for valuable products that combine various benefits including enhanced energy recovery, waste valorisation, improved product quality, and environmental sustainability. Consideration of specific feedstocks and optimization of process parameters are necessary to maximise the efficiency and effectiveness of the co-pyrolysis process. This work presents investigations of the co-pyrolysis process of lignocellulosic biomass wastes (rye straw and agriculture grass) and RDF. These biomasses ensure efficient decomposition. The RDF, high in carbon (78.5 %) and hydrogen (11.8 %), was predominantly plastic based. Based on Py-GC-MS studies at 600 °C, it was observed that the addition of RDF to biomass caused a significant decrease in the share of organic oxygen compounds among the released decomposition products. Laboratory tests were performed in a fixed-bed reactor for raw biomass and RDF and 1:1 and 3:1 biomass to RDF mass ratio. The results demonstrated that the yield of char production decreased with the addition of RDF, which promoted the bio-oil yield. Despite, RDF pyrolysis meets problems, it was proved that co-pyrolysis of biomass and RDF is a good solution for their utilization.

Cobalt-based Polymerized Porphyrinic Network for Visible-light-driven CO2 Reduction.

Visible-light-driven conversion of carbon dioxide to valuable compounds and fuels is an important but challenging task due to the inherent stability of the CO2 molecules. Herein, we report a series of cobalt-based polymerized porphyrinic network (PPN) photocatalysts for CO2 reduction with high activity. The introduction of organic groups results in the addition of more conjugated electrons to the networks, thereby altering the molecular orbital levels within the networks. This integration of functional groups effectively adjusts the levels of the lowest unoccupied molecular orbital (LUMO) and the highest occupied molecular orbital (HOMO). The PPN(Co)-NO2 exhibits outstanding performance, with a CO evolution rate of 12 268 μmol/g/h and 85.8% selectivity, surpassing most similar photocatalyst systems. The performance of PPN(Co)-NO2 is also excellent in terms of apparent quantum yield (AQY) for CO production (5.7% at 420 nm). Density functional theory (DFT) calculations, time-resolved photoluminescence (TRPL), and electrochemical tests reveal that the introduction of methyl and nitro groups leads to a narrower energy gap, facilitating a faster charge transfer. The coupling reaction in this study enables the formation of stable C-C bonds, enhancing the structural regulation, active site diversity, and stability of the catalysts for photocatalytic CO2 reduction. This work offers a facile strategy to develop reliable catalysts for efficient CO2 conversion.

Palladium-Catalyzed O-Glycosylation through π-π Interactions.

A stereodivergent synthesis of β- and α-O-glycosides using 3-O-quinaldoyl glucals was developed by palladium catalysis at 60 and 110 °C respectively. Various alcohols, monosaccharides, and amino acid were glycosylated to form β- and α- products in good yields with high stereoselectivity. Mechanistic studies indicated no classic Pd-N (quinoline) coordination, but π-π stacking interactions promoted the anomeric stereodiversity. The practicality was demonstrated by glycosylating natural products/drugs and synthesizing a complex tetrasaccharide.

Enhancing Water Management in Jordan: A Fresh Tomato Water Footprint Analysis

Water footprint (WF) analysis is crucial for comprehending agricultural water usage patterns. This study aims to determine the total WF for tomatoes in Jordan from 1994 to 2023, covering both summer and winter seasons, to inform decision-making regarding tomato cultivation practices in the area. Despite inconsistencies in data recording, particularly regarding fertilizer application and sunshine, the WF serves as a valuable tool for estimating seasonal variations in water requirements and facilitating comparisons between different approaches to water usage for tomatoes. Comparative studies globally suggest variability in WFs due to factors such as climate, irrigation methods, and soil conditions influencing results. In this study, the CROPWAT 8.0 model was employed to analyze input data obtained from the Department of Statistics, NASA POWER, and local farmers near the Baqoura, Deir Alla, and Ghour Alsafi stations. The analysis aimed to determine the green WF (rainfall), blue WF (irrigation), and gray WF (water required to dilute pollutants) at these stations. The results revealed that the total WF during winter was approximately 7217.62, 8417.65, and 14061.42 m3/ton for the Baqoura, Deir Alla, and Ghour Alsafi stations. In summer, the respective values were around 3107.67, 6026.52, and 11847.35 m3/ton. Significant findings include ET green, evapotranspiration (ET) blue, crop water use (CWU) green and blue, and production yield for 2023. The nitrogen application per dunum was also calculated as 368 kg/30 dunum, equating to 123 kg/ha. The significance of these results lies in their potential to inform and optimize water management practices in tomato cultivation, promoting sustainability and resource efficiency.

A quantitative assessment of Geant4 for predicting the yield and distribution of positron-emitting fragments in ion beam therapy

Objective. To compare the accuracy with which different hadronic inelastic physics models across ten Geant4 Monte Carlo simulation toolkit versions can predict positron-emitting fragments produced along the beam path during carbon and oxygen ion therapy. Approach. Phantoms of polyethylene, gelatin, or poly(methyl methacrylate) were irradiated with monoenergetic carbon and oxygen ion beams. Post-irradiation, 4D PET images were acquired and parent 11C, 10C and 15O radionuclides contributions in each voxel were determined from the extracted time activity curves. Next, the experimental configurations were simulated in Geant4 Monte Carlo versions 10.0 to 11.1, with three different fragmentation models—binary ion cascade (BIC), quantum molecular dynamics (QMD) and the Liege intranuclear cascade (INCL++) - 30 model-version combinations. Total positron annihilation and parent isotope production yields predicted by each simulation were compared between simulations and experiments using normalised mean squared error and Pearson cross-correlation coefficient. Finally, we compared the depth of the maximum positron annihilation yield and the distal point at which the positron yield decreases to 50% of peak between each model and the experimental results. Main results. Performance varied considerably across versions and models, with no one version/model combination providing the best prediction of all positron-emitting fragments in all evaluated target materials and irradiation conditions. BIC in Geant4 10.2 provided the best overall agreement with experimental results in the largest number of test cases. QMD consistently provided the best estimates of both the depth of peak positron yield (10.4 and 10.6) and the distal 50%-of-peak point (10.2), while BIC also performed well and INCL generally performed the worst across most Geant4 versions. Significance. The best predictions of the spatial distribution of positron annihilations and positron-emitting fragment production along the beam path during carbon and oxygen ion therapy was obtained using Geant4 10.2.p03 with BIC or QMD. These version/model combinations are recommended for future heavy ion therapy research.

Tert‐Butyl as a Functional Group: Non‐Directed Catalytic Hydroxylation of Sterically Congested Primary C−H Bonds

AbstractThe tert‐butyl group is a common aliphatic motif extensively employed to implement steric congestion and conformational rigidity in organic and organometallic molecules. Because of the combination of a high bond dissociation energy (~100 kcal mol−1) and limited accessibility, in the absence of directing groups, neither radical nor organometallic approaches are effective for the chemical modification of tert‐butyl C−H bonds. Herein we overcome these limits by employing a highly electrophilic manganese catalyst, [Mn(CF3bpeb)(OTf)2], that operates in the strong hydrogen bond donor solvent nonafluoro‐tert‐butyl alcohol (NFTBA) and catalytically activates hydrogen peroxide to generate a powerful manganese‐oxo species that effectively oxidizes tert‐butyl C−H bonds. Leveraging on the interplay of steric, electronic, medium and torsional effects, site‐selective and product chemoselective hydroxylation of the tert‐butyl group is accomplished with broad reaction scope, delivering primary alcohols as largely dominant products in preparative yields. Late‐stage hydroxylation at tert‐butyl sites is demonstrated on 6 densely functionalized molecules of pharmaceutical interest. This work uncovers a novel disconnection approach, harnessing tert‐butyl as a potential functional group in strategic synthetic planning for complex molecular architectures.

Tert-Butyl as a Functional Group: Non-Directed Catalytic Hydroxylation of Sterically Congested Primary C-H Bonds.

The tert-butyl group is a common aliphatic motif extensively employed to implement steric congestion and conformational rigidity in organic and organometallic molecules. Because of the combination of a high bond dissociation energy (~ 100 kcal mol-1) and limited accessibility, in the absence of directing groups, neither radical nor organometallic approaches are effective for the chemical modification of tert-butyl C-H bonds. Herein we overcome these limits by employing a highly electrophilic manganese catalyst, [Mn(CF3bpeb)(OTf)2], that operates in the strong hydrogen bond donor solvent nonafluoro-tert-butyl alcohol (NFTBA) and catalytically activates hydrogen peroxide to generate a powerful manganese-oxo species that effectively oxidizes tert-butyl C-H bonds. Leveraging on the interplay of steric, electronic, medium and torsional effects, site-selective and product chemoselective hydroxylation of the tert-butyl group is accomplished with broad reaction scope, delivering primary alcohols as largely dominant products in preparative yields. Late-stage hydroxylation at tert-butyl sites is demonstrated on 6 densely functionalized molecules of pharmaceutical interest. This work uncovers a novel disconnection approach, harnessing tert-butyl as a potential functional group in strategic synthetic planning for complex molecular architectures.

Integrated microalgae cultivation and sustainable biofuel production from pretreated food waste

Repurposing of food waste (FW) affords an alternate waste management strategy and sustainable product yield. Thus, this study proposed an integrated biorefinery approach, repurposing pretreated FW hydrolysate for microalgae cultivation and utilizing residual solids for biomethane recovery. FW biomass with different solubilization ranging from (10–15 to 60–65%) obtained during surfactant coupled disperser pretreatment was used as a substrate for microalgae (Chlorella vulgaris) cultivation. A higher microalgae biomass productivity of 0.87 ± 0.003 g/g substrate was obtained from the FW hydrolysate with 40–45% solubilization. The microalgae cultivated in FW hydrolysate with 40–45% solubilization yielded a higher protein, carbohydrate, and lipid accumulation of 380 ± 20 mg/g, 480 ± 30 mg/g and 360 ± 15 mg/g. Besides, the methanogenesis process showed a higher methane yield of 0.294 ± 0.003 L/g COD utilizing residual solids of pretreated food waste as substrate. This integrated biorefinery provides a sustainable platform for completely valorizing food waste biomass and recovery of multiple products.

Soft Cheese-Making with Buttermilk: Physico-chemical, Sensory, Textural Properties, and Microstructure Characterization

Background: Buttermilk, a significant by-product of the dairy industry, is acknowledged as a beneficial food due to its content of water-soluble vitamins, polar lipids, and milk fat globule membranes. This research is focused on investigating the potential of buttermilk as a substitute in the production of a novel soft cheese type ‘‘camembert’’. Methods: A total of 12 cheese samples of camembert cheese, both with and without buttermilk, were prepared and subjected to a series of physico-chemical analyses in October 2023 to measure protein, fat, total solids, pH, and production yield. Texture Profile Analysis was applied to evaluate textural characteristics, and the microstructure was examined using Scanning Electron Microscopy. A hedonic scale was employed in sensory evaluation to measure taste intensity. Results: The sample containing 90% cow's milk and 10% buttermilk exhibited the most significant (p≤0.05) physico-chemical characteristics as production yield of 45.33%±0.710, protein content of 28.9%±0.58, fat content of 24.88%±0.026, total solids of 54.62±0.23, and a pH of 6.42±0.58. Sensory evaluations demonstrated that camembert samples containing buttermilk were distinguished by high sensory quality and satisfactory taste profiles. In addition, a dense and tightly fused protein matrix was observed in the microstructure of the buttermilk fortified cheese. The results also emphasized that the acidic nature of buttermilk significantly affected the production yield, total solids content, and textural characteristics, evidenced by a hardness of 3.36 N and fracturability of 1.75 N. Conclusion: The results validate the use of buttermilk as an effective alternative in the production of a new type of soft cheese, manifesting improved sensory, structural, and physico-chemical characteristics. This investigation supports the innovative utilization of buttermilk in cheese production, potentially offering a valuable avenue for dairy industry by-products.

Isolation and characterization of piceatannol producing bacteria from soil in Erzurum, Turkey.

Piceatannol, resveratrol's derivative, and a valuable polyphenol has managed to become one of the most remarkable candidate molecules for drug development research, with its high bioactive properties and higher stability. On the other hand, the very low amount of piceatannol in plants which are its natural source increases the cost and limits the commercialization possibilities of the product. To overcome this bottleneck, a limited number of studies have recently shown that it is possible to produce piceatannol from the resveratrol precursor much cheaper by regioselective hydroxylation catalyzed by bacteria isolated from the soil, and the search for new bacteria of similar nature in new ecosystems has gained popularity. The aim of our study, which was prepared within this framework, is the bacterial isolate with regioselective hydroxylation potential obtained as a result of selective isolation steps; determination of resveratrol hydroxylation potentials and piceatannol product yields, investigation of possibilities to increase piceatannol yield with optimization trials and identification of isolates with the highest yield. For this purpose, 200 bacterial isolates capable of resveratrol hydroxylation were obtained from soil samples taken from Erzurum (Turkey) and its surroundings by using selective media. In the continuation of the study; resveratrol hydroxylation trials were carried out with these isolates and 55 active isolates capable of producing piceatannol by regioselective hydroxylation were selected. Then, yield improvement studies of active isolates were carried out by using different carbon sources and optimizing the culture conditions. As a result, a culture collection was created by identifying the 6 most active bacterial isolates with commercialization potential using conventional and molecular methods. These are 4 Gram-positive (Rhodococcus sp., Rhodococcus erythropolis, Paeniglutamicibacter sp., Arthrobacter sp.) and 2 Gram-negative (Shinella sp., Ensifer adhaerens) bacterial isolates. As a result of the optimization studies, three of these isolates used phenol as a biocatalyst, while the other three increased the production yield of piceatannol by using 4-hydroxyphenylacetic acid.