Efficient Processing Technology Research Articles

Novel strategies for enhancing quality stability of edible flower during processing using efficient physical fields: A review

Edible flowers are an exotic part of the human diet due to their distinct sensorial properties and health benefits. Due to consumers demand edible flowers and their products with natural freshness and high nutritional value, there is increasing research on the application of green and efficient edible flower processing technologies. This paper reviews the application of a number of physical fields including ultrasound, microwave, infrared, ultraviolet, ionizing radiation, pulse electric field, high hydrostatic pressure, and reduced pressure aiming to improve the processing and product quality of edible flowers. The mechanism of action, influencing factors, and status on application of each physical energy field are critically evaluated. In addition, the advantages and disadvantages of each of these energy fields are evaluated, and trends on their future prospects are highlighted. Future research is expected to focus on gaining greater understanding of the mechanism action of physical field-based technologies when applied to processing of edible flowers and to provide the basis for broaden the application of physical field-based technologies in industrial realm.

DESIGN AND BUILD A COCONUT HUSK CHOPPER MACHINE USING AN 8 HP GASOLINE ENGINE

The coconut frond cutter or coconut frond shredder is a device used to transform coconut fronds into small pieces, even turning them into a finely textured material. This study examines the design and development of a coconut-chopping machine that uses an 8 HP combustion motor. Structural analysis was performed on the machine frame by considering the maximum and minimum Von Mises Stresses. The analysis results show that the maximum Von Mises Stress in the frame is 1.670e+06 N/mm², while the minimum stress is 2.338e+04 N/mm². The displacement of the frame was observed at 2.642e-02 mm to 1.000e-30 mm. The safety factor of the frame was found to be 1.366e+02, indicating an adequate level of safety. Next, this study analyzed the shredding capacity of the machine. The analysis showed that the largest shredding capacity was 3619.30 kg/hour, which occurred at a high rotation of young fronds, producing fine shreds. Meanwhile, the smallest shredding capacity of 612.66 kg/hour occurs at low rotation of old fronds and produces coarse shreds. These results provide essential insights into using coconut shredding machines based on the rotation level and the processed material. This research contributes to the development of efficient and effective coconut processing technology.

Magnetic γ-Fe2O3/ZnO@CNTs synthesized by a green precipitation method for the degradation of aniline through photocatalysis coupling catalytic ozonation

Aniline is highly toxic and difficult to degrade by conventional biological treatment processes. Thus, more efficient processing technology needs to be developed. Photocatalysis coupling catalytic ozonation (PCO) could be a solution. In this study, a green precipitation method was used to synthesize a γ-Fe2O3/ZnO@CNT catalyst, which exhibits high activity for aniline PCO degradation and strong magnetic properties for rapid separation. Under the optimal conditions, the aniline removal rate reached 93.5%. After 5 reaction cycles, the γ-Fe2O3/ZnO@CNT catalysts can be separated easily with a magnet, and a 91% aniline removal rate can be maintained. Furthermore, there are at least 4 kinds of advanced oxidation processes (AOPs) in this system, i.e., (1) photocatalytic oxidation; (2) catalytic ozonation; (3) photocatalytic ozone; and (4) Fenton oxidation. Thus, a novel stable and magnetically separable catalyst was developed, and new insight were provided for the role of PCO processes in the treatment of aniline.

Effect of extrusion cooking on the chemical and nutritional properties of instant flours: a review

Satisfying the nutritional requirements of consumers has made food industries focus on the development of safe, innocuous, easy-to-prepare products with high nutritional quality through efficient processing technologies. Extrusion cooking has emerged as a prominent technology associated with the nutritional and functional attributes of food products. This review aims to establish a theoretical framework concerning the influence of extrusion parameters on the functional and nutritional properties of precooked or instant flours, both as end-products and ingredients. It highlights the pivotal role of process parameters within the extruder, including temperature, screw speed, and raw materials moisture content, among others, and elucidates their correlation with the modifications observed in the structural composition of these materials. Such modifications subsequently induce notable changes in the ultimate characteristics of the food product. Detailed insights into these transformations are provided within the subsequent sections, emphasizing their associations with critical phenomena such as nutrient availability, starch gelatinization, protein denaturation, enhanced in vitro digestibility, reduction in the content of antinutritional factors (ANFs), and the occurrence of Maillard reactions during specific processing stages. Drawing upon insights from available literature, it is concluded that these effects represent key attributes intertwined with the nutritional properties of the end-product during the production of instant flours.

Comparative assessment of Nanotrap and polyethylene glycol-based virus concentration in wastewater samples.

Wastewater-based epidemiology is now widely used in many countries for the routine monitoring of SARS-CoV-2 and other viruses at a community level. However, efficient sample processing technologies are still under investigation. In this study, we compared the performance of the novel Nanotrap® Microbiome Particles (NMP) concentration method to the commonly used polyethylene glycol (PEG) precipitation method for concentrating viruses from wastewater and their subsequent quantification and sequencing. For this, we first spiked wastewater with SARS-CoV-2, influenza and measles viruses and norovirus and found that the NMP method recovered 0.4%-21% of them depending on virus type, providing consistent and reproducible results. Using the NMP and PEG methods, we monitored SARS-CoV-2, influenza A and B viruses, RSV, enteroviruses and norovirus GI and GII and crAssphage in wastewater using quantitative PCR (qPCR)-based methods and next-generation sequencing. Good viral recoveries were observed for highly abundant viruses using both methods; however, PEG precipitation was more successful in the recovery of low-abundance viruses present in wastewater. Furthermore, samples processed with PEG precipitation were more successfully sequenced for SARS-CoV-2 than those processed with the NMP method. Virus recoveries were enhanced by high sample volumes when PEG precipitation was applied. Overall, our results suggest that the NMP concentration method is a rapid and easy virus concentration method for viral targets that are abundant in wastewater, whereas PEG precipitation may be more suited to the recovery and analysis of low-abundance viruses and for next generation sequencing.

The Effect of MoS2 and MWCNTs Nanomicro Lubrication on the Process of 7050 Aluminum Alloy

Nanofluid Minimum Quantity Lubrication (NMQL) is a resource-saving, environmentally friendly, and efficient green processing technology. Therefore, this study employs Minimum Quantity Lubrication (MQL) technology to conduct milling operations on aerospace 7050 aluminum alloy using soybean oil infused with varying concentrations of MoS2 and MWCNTs nanoparticles. By measuring cutting forces, cutting temperatures, and surface roughness under three different lubrication conditions (dry machining, Minimum Quantity Lubrication, and nanofluid minimum quantity lubrication), the optimal lubricating oil with the best lubrication performance is selected. Under the conditions of hybrid nanofluid minimum quantity lubrication (NMQL), as compared to dry machining and Minimum Quantity Lubrication (MQL) processing, surface roughness was reduced by 48% and 36% respectively, cutting forces were decreased by 35% and 29% respectively, and cutting temperatures were lowered by 44% and 40%, respectively. Under the conditions of hybrid nanofluid minimum quantity lubrication, the optimal parameter combination is cutting speed (Vc) of 199.93 m/min, feed rate (f) of 0.18 mm, cutting depth (ap) of 0.49 mm, and nanofluid mass fraction (wt) of 0.51%. The hybrid nanofluid can significantly enhance heat exchange capacity and lubrication performance, thereby improving machining characteristics.

Application of steam explosion for preparing high value-added antioxidants from eggshell membrane waste

Eggshell membrane (ESM) is primary considered as food industry discard due to its highly insoluble structure. In this study, steam explosion was exploited to improve the utilization of ESM and convert it into high-valued antioxidants. An increase in dissolution rate of ESM to 66.67%–219.05% was detected, along with decrease in disulfide bonds and cysteine/cystine level induced by the steam explosion. After steam explosion pretreatment, DPPH radical scavenging rate and total antioxidant capacity of ESM hydrolysate (ESMH) were maximally increased by 87.48% and 103.09%, respectively, indicating an overwhelming advantage than unpretreated hydrolysate. Furthermore, ESMH exerted strong synergistic antioxidant activity with gallic acid (GA). Importantly, ESMH-GA mixture protected UVB-injured L929 cells by reducing reactive oxygen species and could be potentially used as antioxidant ingredients in cosmeceutical foods. This finding provided an efficient recycling strategy and direction for ESM utilization. Industrial relevanceSteam explosion is a new green and efficient processing technology. ESM with low solubility is an underutilized byproduct. This study applied steam explosion to ESM and significantly improved antioxidant activity of its hydrolysates (ESMH). ESMH protected UVB-injured L929 cells by reducing reactive oxygen species and could be potentially used as antioxidant ingredients in cosmeceutical foods. Steam explosion has the potential to be used to high-value utilization of ESM.

Novel Optical Kerr Switching Photonic Device Based on Nonlinear Carbon Material.

In the context of current communication systems, there is an urgent demand for more efficient and higher-speed optical signal processing technologies. Researchers are actively exploring new materials and devices to harness nonlinear optical phenomena, seeking advancements in this field. Nonlinear carbon materials, especially promising 2D materials, have garnered attention for their potential interaction with light and have become integral to the development of all-optical signal processing devices. This study focuses on utilizing a photonic device based on a nonlinear Au/CB composite material for optical Kerr switching. The application of Au/CB as a nonlinear material in the Kerr switch represents a noteworthy advancement, demonstrating its capability to modulate optical signals. By appropriately applying a pump light, the study achieves optical Kerr switching with an extinction ratio of approximately 15 dB in the fully off state of the signal light carrying a 10 GHz analog signal, marking a pioneering achievement in the field to the best of our knowledge. The experimental results, encompassing extinction ratios, signal control, and stability, not only validate the feasibility of this technology but also underscore its potential applicability within optical communication systems. The successful modulation and control of a 10 GHz analog signal showcase the practicality and effectiveness of the Au/CB-based optical Kerr switch. This progress contributes to the continuous evolution of optical Kerr switching, a crucial component in modern optical communication systems. Therefore, we believe that the Au/CB-based optical Kerr switch is an exceptionally promising and stable all-optical signal processing device. As the contemporary communication landscape evolves, the integration of this technology holds the potential to enhance the efficiency and speed of optical signal processing.

An Image Recognition Method Based on Correct Parking of Intelligent Medical Vehicles

This paper introduces a circular object recognition method based on image processing technology. With the continuous development of robot technology, there is an increasing demand for efficient and accurate image processing technology in the fields of robot vision navigation and automated production. Therefore, this paper aims to propose an image processing method that can effectively recognize circular targets, and provide technical support for applications in the fields of robot vision navigation and automated production. The method first reads the image and converts it to a binary image, then constructs and closes the graph structure elements and fills the holes. By calculating the area and perimeter of the circular target, the method of threshold matching is used to determine the circular target. In this paper, the red and green circular targets are taken as examples to identify them respectively and judge whether the recognition is successful through logical operations. The experimental results show that the method can effectively identify circular targets under different clearing conditions, and has high accuracy and robustness. This technology can be applied in the fields of robot visual navigation, automatic production, etc., and provides technical support for realizing intelligent and efficient production and service. At the same time, the research method of this paper also provides reference and references for the solution of other object recognition problems.

Research on an epoxy resin magnetoelastic abrasive: Application in tool edge preparation

Magnetoelastic abrasive grains have low elastic modulus and magnetism, which can create magnetic brushes in magnetic fields. When magnetoelastic abrasive particles come into contact with a workpiece, they can cause deformation, which increases the effective contact surface area and improves machining quality and efficiency. A method for preparing epoxy resin magnetoelastic abrasives was proposed first. The magnetic particle micromorphology was detected through scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS). Secondly, based on the theory of particle-filled composite materials and mechanics, the representative volume element (RVE) model was developed using the finite element software ABAQUS. The size ratio of iron and silicon carbide filler particles, particle shape, and arrangement of stress and strain were found to further improve the magnetoelastic abrasive preparation process. To investigate the effect of time, abrasive size, tool speed, disc speed, and disc spacing on the flank face value, rake face value, and shape factor, double disc magnetic preparation was subjected to magnetoelastic abrasive. Compared to traditional drag finishing methods, the magnetoelastic abrasive demonstrated high efficiency and quality. Exploring the application of magnetoelastic abrasives, new technology and methods of edge preparation, and promoting progress in magnetic efficient processing and magnetic optical finishing technology is of great theoretical and practical value.

Review On Synthetic Vs Herbal Drugs, Its Various Extraction Methods And Animal Models Related To Depression

Depression is a neuropsychiatric disorder The focus of the current review article is on the most recent antidepressants drugs , their mechanisms of action, their pathophysiology, their side effects, and the methods for preventing drug-induced toxicity. There is also a description of phytochemicals that have been found to have antidepressant effects. Widely used synthetic drugs are, i. tricyclic antidepression ii. Selective serotonin reuptake inhibitors iii. monoamine oxidase inhibitors, iv. Serotonin-Norepinephrine Reuptake Inhibitors (SNRI) It has been reported that most antidepressants have negative health effects. An account of phytochemicals found to be acting as antidepressant is also included. Their beneficial effects to the human body have been attributed to the presence of active phytochemical ingredients with some efficiency for disease treatment as well as for beauty and health enhancement. Public awareness on the adverse effects of synthetic chemical products also increased the demand for herbal products. Highly efficient herbal processing and extraction technologies have been developed to obtain the optimal amounts of active ingredients from herbs Soxhlet extraction, supercritical fluid extraction cold Maceration Extraction, steam distillation, Hot Water Extraction, microwave assisted extraction. This review focuses on recent findings regarding some of the most widely employed animal models used currently to predict antidepressant potential. Here we, studies the assessment behavioral test by using various animal models force swimming test, tail suspension Test, rotarod test. In that for study of synthetic and herbal drugs in treatment of depression. Their advantageous effects on the human body have been related to the existence of active phytochemical components that are effective in treating certain diseases as well as enhancing attractiveness and health. The demand for herbal items increased as a result of growing public knowledge of the negative consequences of synthetic chemical products.

Effect of extrusion cooking on the chemical and nutritional properties of instant flours: a review.

Satisfying the nutritional requirements of consumers has made food industries focus on the development of safe, innocuous, easy-to-prepare products with high nutritional quality through efficient processing technologies. Extrusion cooking has emerged as a prominent technology associated with the nutritional and functional attributes of food products. This review aims to establish a theoretical framework concerning the influence of extrusion parameters on the functional and nutritional properties of precooked or instant flours, both as end-products and ingredients. It highlights the pivotal role of process parameters within the extruder, including temperature, screw speed, and raw materials moisture content, among others, and elucidates their correlation with the modifications observed in the structural composition of these materials. Such modifications subsequently induce notable changes in the ultimate characteristics of the food product. Detailed insights into these transformations are provided within the subsequent sections, emphasizing their associations with critical phenomena such as nutrient availability, starch gelatinization, protein denaturation, enhanced in vitro digestibility, reduction in the content of antinutritional factors (ANFs), and the occurrence of Maillard reactions during specific processing stages. Drawing upon insights from available literature, it is concluded that these effects represent key attributes intertwined with the nutritional properties of the end-product during the production of instant flours.

Application of Entity-BERT model based on neuroscience and brain-like cognition in electronic medical record entity recognition.

In the medical field, electronic medical records contain a large amount of textual information, and the unstructured nature of this information makes data extraction and analysis challenging. Therefore, automatic extraction of entity information from electronic medical records has become a significant issue in the healthcare domain. To address this problem, this paper proposes a deep learning-based entity information extraction model called Entity-BERT. The model aims to leverage the powerful feature extraction capabilities of deep learning and the pre-training language representation learning of BERT(Bidirectional Encoder Representations from Transformers), enabling it to automatically learn and recognize various entity types in medical electronic records, including medical terminologies, disease names, drug information, and more, providing more effective support for medical research and clinical practices. The Entity-BERT model utilizes a multi-layer neural network and cross-attention mechanism to process and fuse information at different levels and types, resembling the hierarchical and distributed processing of the human brain. Additionally, the model employs pre-trained language and sequence models to process and learn textual data, sharing similarities with the language processing and semantic understanding of the human brain. Furthermore, the Entity-BERT model can capture contextual information and long-term dependencies, combining the cross-attention mechanism to handle the complex and diverse language expressions in electronic medical records, resembling the information processing method of the human brain in many aspects. Additionally, exploring how to utilize competitive learning, adaptive regulation, and synaptic plasticity to optimize the model's prediction results, automatically adjust its parameters, and achieve adaptive learning and dynamic adjustments from the perspective of neuroscience and brain-like cognition is of interest. Experimental results demonstrate that the Entity-BERT model achieves outstanding performance in entity recognition tasks within electronic medical records, surpassing other existing entity recognition models. This research not only provides more efficient and accurate natural language processing technology for the medical and health field but also introduces new ideas and directions for the design and optimization of deep learning models.

Effect of anisotropy on deformation and crack formation under the brittle removal of 6H-SiC during SPDT process

IntroductionMonocrystal SiC is representative of the third generation semiconductor materials, the efficient process technology of 6H-SiC wafer have always been a hot topic. Developing a SPDT processing method based on brittle removal mode with controllable surface/subsurface damage is an important approach to solve the processing difficulties of 6H-SiC. ObjectivesThis work aims to analyze the brittle removal process and fully explain the brittle separation behavior and deformation mechanism of 6H-SiC. The micro-scale crack propagation and the effect of anisotropy on crack distribution during machining process are investigated. MethodsLarge-scale molecular dynamics simulation was used in this work. ResultsUnder the condition of brittle removal, shear fracture occurs in the front area of tool tip. Shear plane is high-index surface, independent of slip system. The location of tensile fracture is the cleavage plane of hexagonal system, and the fracture surface is composed of step-like joint planes or perfect plane structures. Cracks with self-healing capability appear in the area behind the tool when the surface to be machined is basal plane. When the surface to be machined is not basal plane, a large number of dislocations or cracks remain in subsurface region. Under brittle removal mode, a large amount of plastic deformation appears as well, and deformation mode is related to processing scheme. ConclusionThe brittle removal behavior of 6H-SiC under SPDT process has obvious anisotropy. Basal plane is more suitable for brittle removal of 6H-SiC without residual damage such as sub-surface cracks. The crack behind the tool generated by cleavage fracture can be repaired by itself. Fracture behavior is not related to dislocation. The processing method parallel to the c-axis can cause the generation of a large number of surface cracks. The (011¯0)/[21¯1¯0] and (112¯0)/[11¯00] mode is the best way to achieve plastic removal of 6H-SiC during SPDT process.

ACID HELIOMICROBIOLOGICAL METHOD FOR OIL CONTAMINATED SOILS IN WESTERN KAZAKHSTAN FIELDS

The article presents promising methods of cleaning oil-contaminated soils. Oil pollution causes serious damage to the environment. Under normal conditions, work on the purification of oil waste and oil-contaminated soils is not carried out due to the lack of equipment and efficient processing technology. It is emphasized the need to develop promising methods for cleaning oil-contaminated soils and the possibility of using oil-contaminated soils as an organic retaining material for fixing the soil layer in road construction, as well as building materials. According to laboratory studies, with a moisture content of 30%, oil sludge is transported in the form of brittle plates. At the same time, oil sludge does not gather dust, has thixotropic properties, passes more than 1-3% of moisture into the lower soil layer. Thus, dry oil sludge is convenient and safe for transportation and storage in warehouses. The humidity of dry oil sludge averages 15-20%. The composition of the dry sludge is mostly stable: petroleum products 15-25%; mechanical impurities 70-75%; water 5-8%. In recent years, a number of studies have been conducted to eliminate oil pollution to solve the problem of cleaning oil-contaminated soils. Various classifications of landfills and methods of waste disposal during the construction of landfills of oil production waste are described: sludge collectors. However, currently none of the methods of removing oil-contaminated soils is widely used, each of these methods has its advantages and disadvantages. The ways of the microbiological method aimed at preventing or reducing pollution by oil and petroleum products trapped in the soil layer are shown. The object of research in the article is the Zhanazholskoye field, one of the West Kazakhstan fields, and the situation of applying the new technology to the heliomicrobiological method of acidification of oil-contaminated soils is presented.

Deconstruction of Related Technologies of Ground Image Processing Based on High-Resolution Satellite Remote Sensing Images

The Earth observation system heavily relies on sophisticated remotely sensed satellites, an important means to obtain global high-precision geospatial products and an important strategic area for the world’s major scientific and technological powers to develop. Although China’s satellites currently have real-time or quasi-real-time observations with a high temporal resolution, there are still a lot of gaps between their positioning accuracy and the world’s advanced level. This essay aims to study an efficient ground image processing technology and apply it to high-resolution satellite remote sensing images. The convolutional neural network is an efficient deep learning method for image recognition and feature extraction. In this essay, people use a convolutional neural network (CNN) to identify ground images, use a support vector machine (SVM) to classify and summarize images, and then use a Kalman filter for noise reduction, so as to obtain sophisticated remotely sensed images. In the experiment, 100 satellite remote sensing images in the GeoImageDB database were selected for the simulation test, the images were divided into 5 types, and their recognition accuracy, classification accuracy, image signal-to-noise ratio, and resolution were analyzed. The results show that the accuracy of CNN’s recognition of different types of images is up to about 94%, and the lowest is about 85%. The accuracy of the SVM for image classification is above 80%, and the highest is about 95%. The SNR of the image after noise reduction is basically above 6.5, and some even reach above 8.0. The resolution of the image is basically above 800ppi, and the highest even reaches an ultra-high resolution of 1400ppi. Overall, the processed images are of high quality. This shows that this essay uses CNN for image recognition and then uses an SVM for classification, and finally, the method of denoising the image has certain feasibility and has achieved good results through experiments.

Varietal Differences in Juice, Pomace and Root Biochemical Characteristics of Four Rhubarb (Rheum rhabarbarum L.) Cultivars

The complex evaluation of varietal biochemical differences in rhubarb juice, pomace and roots is highly useful to develop an efficient processing technology. Research was carried out to compare four rhubarb cultivars (Malakhit, Krupnochereshkovy, Upryamets and Zaryanka) in terms of the quality and antioxidant parameters of juice, pomace and roots. The laboratory analyses showed a high juice yield (75-82%) with a relatively high content of ascorbic acid (125-164 mg L-1) and other organic acids (16-21 g L-1). Citric, oxalic and succinic acids accounted for 98% of the total acids amount. The juice of the cultivar Upryamets demonstrated high levels of the natural preservatives sorbic (36.2 mg L-1) and benzoic acids (11.7 mg L-1), which are highly valuable in juice production. The juice pomace proved to be an excellent source of pectin and dietary fiber, whose concentrations reached 21-24% and 59-64%, respectively. The total antioxidant activity decreased according to the following sequence: root pulp (161-232 mg GAE g-1 d.w.) > root peel (115-170 mg GAE g-1 d.w.) > juice pomace (28.3-34.4 mg GAE g-1 d.w.) > juice (4.4-7.6 mg GAE g-1 f.w.), suggesting that root pulp is a highly valuable antioxidant source. The results of this research highlight the interesting prospects of the complex rhubarb plant processing for the production of juice, containing a wide spectrum of organic acids and natural stabilizers (sorbic and benzoic acids), dietary fiber and pectin (juice pomace) and natural antioxidants (roots).

Processing properties and pyrolysis behavior of novolak-hexamethylenetetramine mixtures

This work investigates the influence of the hexamethylenetetramine (hexa) content on the rheological features, pyrolysis reactions, mass-loss kinetics and char yield for two phenolic resins, each with different novolak-hexa mixtures from 0 wt.-% to 15 wt.-%. Curing and viscosity of resins was studied using a rheometer. Pyrolysis, evolved gases and char yield were investigated with TG-FTIR-GC/MS. The obtained results show that the curing of resins shifts to lower temperatures whereas the viscosity and the residual carbon amount both increase with increasing hexa-contents. The presented data suggests a hexa-induced microgel formation for phenolic resins. Models for viscosity and char yield were developed and present a valuable tool to tailor the resin-hardener mixture for the desired application, enable a more efficient processing technology and contribute to a deeper understanding of the pyrolysis of novolak resins.

Effect of SiC/SiC composites density on nanosecond-laser machining behaviors

For highly efficient processing technology of hard and brittle material such as SiC/SiC composites, laser machining has always been the focus of current research. In this work, the effect of composites density on the nanosecond pulse laser machining behaviors was systemically studied. The results revealed that the composites density will largely affect the morphology of laser machining, especially for the micro-hole inlet ablation condition and outlet circle degree. Besides, the roughness of the cutting surface is highly related with density, while the generated oxides and melting substances making the cutting surface smoother in high density samples. Finally, the laser machining induced products exhibited less relationship with density but high relationship with machining time. This paper provides a clear image that how intrinsic properties affects the laser machining behaviors and processing quality.

Bamboo flattening technology ebables efficient and value-added utilization of bamboo in the manufacture of furniture and engineered composites

Bamboo flattening, a novel and efficient bamboo processing and utilization technology, can effectively flatten bamboo culms into crack-free board. The technology enables the efficient and value-added utilization of bamboo in the manufacture of furniture and engineered composites. In this study, we compared the effects of three types of flattening technologies on the macro-mechanical, macro-physical, micro-morphology, and micro-mechanical properties of untreated, softened a flattened bamboo samples. As expected, the hemicellulose and cellulose concentrations of the saturated steam treated sample (18.05% and 38.9%, respectively) were less than those the untreated sample (21.3% and 40.1%, respectively). Moreover, scanning electron microscopy (SEM) analysis showed that the notched flattening technology (NFT) inserted indents and grooves on the bamboo surface. However, the “non-notched flattening technology (NNFT)” only compressed the bamboo tissue. The flattening process increased the equilibrium moisture content and density of bamboo. The enhanced density, lignin content, and cellulose crystallinity index enhanced the bamboo cell wall properties. The non-notched-flattened bamboo board exhibited a higher cell wall modulus of elasticity and hardness (20.1 and 0.89 GPa, respectively) than the untreated bamboo samples (13.7 and 0.49 GPa, respectively). The enhanced bamboo cell wall mechanical properties of the non-notched-flattened bamboo board. Finally, we explored the practical applications, economic benefits, and limitations of the current “Non-notched bamboo flattening technology”.