MyMedR

Displaying publications 1 - 20 of 587 in total

Abstract:

Sort:

A palatability trial on rice from British Guiana

BROWNE EM

Med J Malaya, 1954 Mar;8(3):260-2.
PMID: 13164696
Matched MeSH terms: Oryza*
Fulltext Inline 3D Volumetric Measurement of Moisture Content in Rice Using Regression-Based ML of RF Tomographic Imaging

Almaleeh AA, Zakaria A, Kamarudin LM, Rahiman MHF, Ndzi DL, Ismail I

Sensors (Basel), 2022 Jan 05;22(1).
PMID: 35009947 DOI: 10.3390/s22010405

The moisture content of stored rice is dependent on the surrounding and environmental factors which in turn affect the quality and economic value of the grains. Therefore, the moisture content of grains needs to be measured frequently to ensure that optimum conditions that preserve their quality are maintained. The current state of the art for moisture measurement of rice in a silo is based on grab sampling or relies on single rod sensors placed randomly into the grain. The sensors that are currently used are very localized and are, therefore, unable to provide continuous measurement of the moisture distribution in the silo. To the authors' knowledge, there is no commercially available 3D volumetric measurement system for rice moisture content in a silo. Hence, this paper presents results of work carried out using low-cost wireless devices that can be placed around the silo to measure changes in the moisture content of rice. This paper proposes a novel technique based on radio frequency tomographic imaging using low-cost wireless devices and regression-based machine learning to provide contactless non-destructive 3D volumetric moisture content distribution in stored rice grain. This proposed technique can detect multiple levels of localized moisture distributions in the silo with accuracies greater than or equal to 83.7%, depending on the size and shape of the sample under test. Unlike other approaches proposed in open literature or employed in the sector, the proposed system can be deployed to provide continuous monitoring of the moisture distribution in silos.

Matched MeSH terms: Oryza*
Antagonistic activity of wild growing mushrooms against various fungal rice pathogen

Mohd-Baseri N, Kheirel Anuar MS, Shamsuhazli NAS, Zulkifli MAF, Wasoh H, Yusof MT

Int Microbiol, 2023 Jan;26(1):91-98.
PMID: 36089618 DOI: 10.1007/s10123-022-00275-4

Paddy is an important crop in Malaysia. There are various pathogens able to infect paddy causing a loss in yield's production. In this study, dual culture method, volatile organic compound (VOC) analysis, and non-volatile compound analysis were used to assess the ability of mushroom to control fungal rice pathogens including Curvularia lunata, Bipolaris panici-miliacei, and Nigrospora sp. Four mushroom isolates were further analysed for their antagonistic activity against rice pathogen. The highest percentage inhibition of radial growth (PIRG) was recorded between 45.55 and 73.68% observed in isolate 42b. The 4 isolates with the highest PIRG based on the dual culture analysis were then tested for their production of VOCs and non-volatile compound. Internal transcribed spacer (ITS) region analysis of the 4 mushroom isolates revealed their identity as Coprinellus disseminates (isolate 12b), Marasmiellus palmivorus (isolate 42b), Trametes maxima (isolate 56e), and Lentinus sajor-caju (isolate 60a). This study showed that mushroom isolates have the potential of antagonistic effect on various fungal rice pathogens tested by the production of secondary metabolites and mycoparasitic interaction.

Matched MeSH terms: Oryza*
Resource utilization of rice straw to prepare biochar as peroxymonosulfate activator for naphthalene removal: Performances, mechanisms, environmental impact and applicability in groundwater

Zhang JB, Dai C, Wang Z, You X, Duan Y, Lai X, et al.

Water Res, 2023 Oct 01;244:120555.
PMID: 37666149 DOI: 10.1016/j.watres.2023.120555

Herein, biochar was prepared using rice straw, and it served as the peroxymonosulfate (PMS) activator to degrade naphthalene (NAP). The results showed that pyrolysis temperature has played an important role in regulating biochar structure and properties. The biochar prepared at 900°C (BC900) had the best activation capacity and could remove NAP in a wide range of initial pH (5-11). In the system of BC900/PMS, multi-reactive species were produced, in which 1O2 and electron transfer mainly contributed to NAP degradation. In addition, the interference of complex groundwater components on the NAP removal rate must get attention. Cl- had a significant promotional effect but risked the formation of chlorinated disinfection by-products. HCO3-, CO32-, and humic acid (HA) had an inhibitory effect; surfactants had compatibility problems with the BC900/PMS system, which could lead to unproductive consumption of PMS. Significantly, the BC900/PMS system showed satisfactory remediation performance in spiked natural groundwater and soil, and it could solve the problem of persistent groundwater contamination caused by NAP desorption from the soil. Besides, the degradation pathway of NAP was proposed, and the BC900/PMS system could degrade NAP into low or nontoxic products. These suggest that the BC900/PMS system has promising applications in in-situ groundwater remediation.

Matched MeSH terms: Oryza*
Synergy of RHA and silica sand on physico-mechanical and tribological properties of waste plastic-reinforced thermoplastic composites as floor tiles

Soni A, Das PK, Yusuf M, Pasha AA, Irshad K, Bourchak M

Environ Sci Pollut Res Int, 2023 Dec;30(60):124566-124584.
PMID: 35599290 DOI: 10.1007/s11356-022-20915-6

The usage of waste for the development of sustainable building materials has received an increasing attention in socio-eco-environment spheres. The rice husk ash (RHA) produced during burning of rice husk and the ever-increasing plastic wastes are useless causing detrimental effects on the environment. This research supports the idea of sustainability and circular economy via utilization of waste to produce value-added products. This research explores the potential of waste plastics, RHA, and silica sand as thermoplastic composite materials. The different composite samples were prepared through waste plastics which includes low- and high-density polyethylene and polypropylene with incorporation of RHA and silica sand in proportions. The study investigates the effect of filler/polymer in 30/70, 20/80, and 10/90 (wt. %) on the workability of the developed composite materials. The workability of the composites was found to improve with filler reinforcement. The experimental results showed the maximum density of 1.676 g/cm3 and mechanical strength of 26.39, 4.89, and 3.25 MPa as compressive, flexural, and tensile strengths, respectively. The minimum percentage of water absorption was 0.052%. The wear tests resulted in a minimum abrasive and sliding wear rate of 0.03759 (cm3) and 0.00692 × 10-6 kg/m. The correlations between wear mechanisms and responses were morphologically analyzed. The developed composites verify the feasibility of RHA and plastics waste as a cost effective and environmentally competent product. The results and discussions provided a direction for the future research on sustainable polymeric composite materials.

Matched MeSH terms: Oryza*
Fulltext Stochastic Frontier approach and Data Envelopment Analysis to Total Factor Productivity and efficiency measurement of Bangladeshi rice

Hossain MK, Kamil AA, Baten MA, Mustafa A

PLoS One, 2012;7(10):e46081.
PMID: 23077500 DOI: 10.1371/journal.pone.0046081

The objective of this paper is to apply the Translog Stochastic Frontier production model (SFA) and Data Envelopment Analysis (DEA) to estimate efficiencies over time and the Total Factor Productivity (TFP) growth rate for Bangladeshi rice crops (Aus, Aman and Boro) throughout the most recent data available comprising the period 1989-2008. Results indicate that technical efficiency was observed as higher for Boro among the three types of rice, but the overall technical efficiency of rice production was found around 50%. Although positive changes exist in TFP for the sample analyzed, the average growth rate of TFP for rice production was estimated at almost the same levels for both Translog SFA with half normal distribution and DEA. Estimated TFP from SFA is forecasted with ARIMA (2, 0, 0) model. ARIMA (1, 0, 0) model is used to forecast TFP of Aman from DEA estimation.

Matched MeSH terms: Oryza*
Uncertainty estimation approach in catalytic fast pyrolysis of rice husk: Thermal degradation, kinetic and thermodynamic parameters study

Loy ACM, Yusup S, How BS, Yiin CL, Chin BLF, Muhammad M, et al.

Bioresour Technol, 2019 Dec;294:122089.
PMID: 31526932 DOI: 10.1016/j.biortech.2019.122089

The aim of this study was to understand the influence of catalyst in thermal degradation behavior of rice husk (RH) in catalytic fast pyrolysis (CFP) process. An iso-conversional Kissinger kinetic model was introduced into this study to understand the activation energy (EA), pre-exponential value (A), Enthalpy (ΔH), Entropy (ΔS) and Gibb's energy (ΔG) of non-catalytic fast pyrolysis (NCFP) and CFP of RH. The study revealed that the addition of natural zeolite catalyst enhanced the rate of devolatilization and decomposition of RH associated with lowest EA value (153.10 kJ/mol) compared to other NCFP and CFP using nickel catalyst. Lastly, an uncertainty estimation was applied on the best fit non-linear regression model (MNLR) to identify the explanatory variables. The finding showed that it had the highest probability to obtain 73.8-74.0% mass loss in CFP of rice husk using natural zeolite catalyst.

Matched MeSH terms: Oryza*
Effect of rain on the feeding of the Malaysian rice-field rat

HARRISON JL

Nature, 1949 Oct 29;164(4174):746.
PMID: 15400253
Matched MeSH terms: Oryza*
An LCA-Based Environmental Performance of Rice Production for Developing a Sustainable Agri-Food System in Malaysia

Harun SN, Hanafiah MM, Aziz NIHA

Environ Manage, 2021 Jan;67(1):146-161.
PMID: 33001258 DOI: 10.1007/s00267-020-01365-7

This study aims to assess the environmental impacts of conventional and organic rice cultivations and proposes a sustainable conceptual framework of rice farming based on the life cycle assessment (LCA) approach. A cradle-to-gate LCA was performed by using the ReCiPe 2016 method and SimaPro 8.5 software. The functional unit was one ton of rice grains harvested. Primary data were obtained from the farmer, while secondary data were collected from Ecoinvent 3.0, the Agri Footprint 3.0 database and the literature. The total characterization factors for global warming potential (GWP), water consumption potential (WCP) and fossil fuel depletion potential (FFP) were 457.89 kg CO2-eq, 98.18 m3 and 84.56 kg oil-eq, respectively, at the midpoint level for conventional rice, while the impacts for organic rice were 140.55 kg CO2-eq, 29.45 m3 and 22.25 kg oil-eq, respectively. At the endpoint level, the total characterization factors for human health damage (HH), ecosystem damage (ED) and resource availability (RA) for conventional rice were 9.63 × 10-4 DALY, 5.54 × 10-6 species.year and 30.98 Dollar, respectively, while for organic rice, the impacts were 2.60 × 10-4 DALY, 2.28 × 10-6 species.year and 8.44 Dollar, respectively. Rice cultivation impacted the environment, particularly in relation to three impact categories: GWP, WCP and FFP. The cultivation phase of rice production was the main contributor to environmental impacts due to the production and application of fertilizer and pesticides. It can be concluded that the application of LCA in agricultural sector is able to provide information and responses for policy makers in understanding the potential environmental impacts at various spatial levels.

Matched MeSH terms: Oryza*
Crop photoperiodism model 2.0 for the flowering time of sorghum and rice that includes daily changes in sunrise and sunset times and temperature acclimation

Clerget B, Sidibe M, Bueno CS, Grenier C, Kawakata T, Domingo AJ, et al.

Ann Bot, 2021 07 28;128(1):97-113.
PMID: 33821947 DOI: 10.1093/aob/mcab048

BACKGROUND AND AIMS: Daylength determines flowering dates. However, questions remain regarding flowering dates in the natural environment, such as the synchronous flowering of plants sown simultaneously at highly contrasting latitudes. The daily change in sunrise and sunset times is the cue for the flowering of trees and for the synchronization of moulting in birds at the equator. Sunrise and sunset also synchronize the cell circadian clock, which is involved in the regulation of flowering. The goal of this study was to update the photoperiodism model with knowledge acquired since its conception.
METHODS: A large dataset was gathered, including four 2-year series of monthly sowings of 28 sorghum varieties in Mali and two 1-year series of monthly sowings of eight rice varieties in the Philippines to compare with previously published monthly sowings in Japan and Malaysia, and data from sorghum breeders in France, Nicaragua and Colombia. An additive linear model of the duration in days to panicle initiation (PI) and flowering time using daylength and daily changes in sunrise and sunset times was implemented.
KEY RESULTS: Simultaneous with the phyllochron, the duration to PI of field crops acclimated to the mean temperature at seedling emergence within the usual range of mean cropping temperatures. A unique additive linear model combining daylength and daily changes in sunrise and sunset hours was accurately fitted for any type of response in the duration to PI to the sowing date without any temperature input. Once calibrated on a complete and an incomplete monthly sowing series at two tropical latitudes, the model accurately predicted the duration to PI of the concerned varieties from the equatorial to the temperate zone.
CONCLUSIONS: Including the daily changes in sunrise and sunset times in the updated photoperiodism model largely improved its accuracy at the latitude of each experiment. More research is needed to ascertain its multi-latitudinal accuracy, especially at latitudes close to the equator.

Matched MeSH terms: Oryza*
Esterification of residual palm oil using solid acid catalyst derived from rice husk

Balan WS, Janaun J, Chung CH, Semilin V, Zhu Z, Haywood SK, et al.

J Hazard Mater, 2021 02 15;404(Pt B):124092.
PMID: 33091694 DOI: 10.1016/j.jhazmat.2020.124092

In this study, carbon-silica based acid catalysts derived from rice husks (RH) were successfully synthesised using microwave (MW) technology. The results showed that MW sulphonation produced Sulphur (S) content of 17.2-18.5 times higher than in raw RH. Fourier-transform Infrared Spectroscopy (FTIR) showed peak at 1035 cm-1 which corresponded to O˭S˭O stretching of sulphonic (-SO3H) group. XRD showed sulfonated RH catalysts (SRHCs) have amorphous structure, and through SEM, broadening of the RH voids and also formation of pores is observed. RH600 had the highest surface area of 14.52 m2/g. SRHCs showed high catalytic activity for esterification of oleic acid with methanol with RH600 had the highest initial formation rate (6.33 mmolL-1min-1) and yield (97%). The reusability of the catalyst showed gradually dropped yield of product for every recycle, which might be due to leaching of -SO3H. Finally, esterification of oil recovered from palm oil mill effluent (POME) with methanol achieved a conversion of 87.3% free fatty acids (FFA) into fatty acid methyl esters (FAME).

Matched MeSH terms: Oryza*
Thermogravimetric kinetic modelling of in-situ catalytic pyrolytic conversion of rice husk to bioenergy using rice hull ash catalyst

Loy ACM, Gan DKW, Yusup S, Chin BLF, Lam MK, Shahbaz M, et al.

Bioresour Technol, 2018 Aug;261:213-222.
PMID: 29665455 DOI: 10.1016/j.biortech.2018.04.020

The thermal degradation behaviour and kinetic parameter of non-catalytic and catalytic pyrolysis of rice husk (RH) using rice hull ash (RHA) as catalyst were investigated using thermogravimetric analysis at four different heating rates of 10, 20, 50 and 100 K/min. Four different iso conversional kinetic models such as Kissinger, Friedman, Kissinger-Akahira-Sunose (KAS) and Ozawa-Flynn-Wall (OFW) were applied in this study to calculate the activation energy (EA) and pre-exponential value (A) of the system. The EA of non-catalytic and catalytic pyrolysis was found to be in the range of 152-190 kJ/mol and 146-153 kJ/mol, respectively. The results showed that the catalytic pyrolysis of RH had resulted in a lower EA as compared to non-catalytic pyrolysis of RH and other biomass in literature. Furthermore, the high Gibb's free energy obtained in RH implied that it has the potential to serve as a source of bioenergy production.

Matched MeSH terms: Oryza*
Synergistic effect on co-pyrolysis of rice husk and sewage sludge by thermal behavior, kinetics, thermodynamic parameters and artificial neural network

Naqvi SR, Hameed Z, Tariq R, Taqvi SA, Ali I, Niazi MBK, et al.

Waste Manag, 2019 Feb 15;85:131-140.
PMID: 30803566 DOI: 10.1016/j.wasman.2018.12.031

This study investigates the thermal decomposition, thermodynamic and kinetic behavior of rice-husk (R), sewage sludge (S) and their blends during co-pyrolysis using thermogravimetric analysis at a constant heating rate of 20 °C/min. Coats-Redfern integral method is applied to mass loss data by employing seventeen models of five major reaction mechanisms to calculate the kinetics and thermodynamic parameters. Two temperature regions: I (200-400 °C) and II (400-600 °C) are identified and best fitted with different models. Among all models, diffusion models show high activation energy with higher R2(0.99) of rice husk (66.27-82.77 kJ/mol), sewage sludge (52.01-68.01 kJ/mol) and subsequent blends (45.10-65.81 kJ/mol) for region I and for rice husk (7.31-25.84 kJ/mol), sewage sludge (1.85-16.23 kJ/mol) and blends (4.95-16.32 kJ/mol) for region II, respectively. Thermodynamic parameters are calculated using kinetics data to assess the co-pyrolysis process enthalpy, Gibbs-free energy, and change in entropy. Artificial neural network (ANN) models are developed and employed on co-pyrolysis thermal decomposition data to study the reaction mechanism by calculating Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and coefficient of determination (R2). The co-pyrolysis results from a thermal behavior and kinetics perspective are promising and the process is viable to recover organic materials more efficiently.

Matched MeSH terms: Oryza*
Computer Vision and Machine Learning Analysis of Commercial Rice Grains: A Potential Digital Approach for Consumer Perception Studies

Aznan A, Gonzalez Viejo C, Pang A, Fuentes S

Sensors (Basel), 2021 Sep 23;21(19).
PMID: 34640673 DOI: 10.3390/s21196354

Rice quality assessment is essential for meeting high-quality standards and consumer demands. However, challenges remain in developing cost-effective and rapid techniques to assess commercial rice grain quality traits. This paper presents the application of computer vision (CV) and machine learning (ML) to classify commercial rice samples based on dimensionless morphometric parameters and color parameters extracted using CV algorithms from digital images obtained from a smartphone camera. The artificial neural network (ANN) model was developed using nine morpho-colorimetric parameters to classify rice samples into 15 commercial rice types. Furthermore, the ANN models were deployed and evaluated on a different imaging system to simulate their practical applications under different conditions. Results showed that the best classification accuracy was obtained using the Bayesian Regularization (BR) algorithm of the ANN with ten hidden neurons at 91.6% (MSE = <0.01) and 88.5% (MSE = 0.01) for the training and testing stages, respectively, with an overall accuracy of 90.7% (Model 2). Deployment also showed high accuracy (93.9%) in the classification of the rice samples. The adoption by the industry of rapid, reliable, and accurate methods, such as those presented here, may allow the incorporation of different morpho-colorimetric traits in rice with consumer perception studies.

Matched MeSH terms: Oryza*
Fulltext Rice Crop Counting Using Aerial Imagery and GIS for the Assessment of Soil Health to Increase Crop Yield

Hassan SI, Alam MM, Zia MYI, Rashid M, Illahi U, Su'ud MM

Sensors (Basel), 2022 Nov 07;22(21).
PMID: 36366269 DOI: 10.3390/s22218567

Rice is one of the vital foods consumed in most countries throughout the world. To estimate the yield, crop counting is used to indicate improper growth, identification of loam land, and control of weeds. It is becoming necessary to grow crops healthy, precisely, and proficiently as the demand increases for food supplies. Traditional counting methods have numerous disadvantages, such as long delay times and high sensitivity, and they are easily disturbed by noise. In this research, the detection and counting of rice plants using an unmanned aerial vehicle (UAV) and aerial images with a geographic information system (GIS) are used. The technique is implemented in the area of forty acres of rice crop in Tando Adam, Sindh, Pakistan. To validate the performance of the proposed system, the obtained results are compared with the standard plant count techniques as well as approved by the agronomist after testing soil and monitoring the rice crop count in each acre of land of rice crops. From the results, it is found that the proposed system is precise and detects rice crops accurately, differentiates from other objects, and estimates the soil health based on plant counting data; however, in the case of clusters, the counting is performed in semi-automated mode.

Matched MeSH terms: Oryza*
The diversity of rhizospheric bacterial communities associated with Trichoderma-treated rice fields

Abdullah NS, Doni F, Chua KO, Mispan MS, Saiman MZ, Mohd Yusuf Y, et al.

Lett Appl Microbiol, 2022 Dec;75(6):1645-1650.
PMID: 36073093 DOI: 10.1111/lam.13832

Microbial-based fertilizer has been widely used as a healthier and better alternative to agrochemical products. However, the effects of biofertilizers on the rhizospheric microbiota has rarely been investigated. Thus, the aim of this study was to investigate the effects of symbiotic fungus Trichoderma asperellum SL2-based inoculant on the soil bacterial population through next generation sequencing using a metabarcoding approach. The treatment plots were treated with T. asperellum SL2 spore suspension, while the control plots were treated with sterilized distilled water. The results showed similar bacterial microbiome profiles in the soil of control and T. asperellum SL2-treated plots. In conclusion, the application of the T. asperellum SL2 inoculant had not exerted a negative impact towards the bacterial population as similar observation was reflected in control plots. Nonetheless, future research should be conducted to investigate the effects of repeated application of T. asperellum SL2 over a longer period on the rice microbiota communities.

Matched MeSH terms: Oryza*
Fulltext Rapid Detection of Fraudulent Rice Using Low-Cost Digital Sensing Devices and Machine Learning

Aznan A, Gonzalez Viejo C, Pang A, Fuentes S

Sensors (Basel), 2022 Nov 09;22(22).
PMID: 36433249 DOI: 10.3390/s22228655

Rice fraud is one of the common threats to the rice industry. Conventional methods to detect rice adulteration are costly, time-consuming, and tedious. This study proposes the quantitative prediction of rice adulteration levels measured through the packaging using a handheld near-infrared (NIR) spectrometer and electronic nose (e-nose) sensors measuring directly on samples and paired with machine learning (ML) algorithms. For these purposes, the samples were prepared by mixing rice at different ratios from 0% to 100% with a 10% increment based on the rice's weight, consisting of (i) rice from different origins, (ii) premium with regular rice, (iii) aromatic with non-aromatic, and (iv) organic with non-organic rice. Multivariate data analysis was used to explore the sample distribution and its relationship with the e-nose sensors for parameter engineering before ML modeling. Artificial neural network (ANN) algorithms were used to predict the adulteration levels of the rice samples using the e-nose sensors and NIR absorbances readings as inputs. Results showed that both sensing devices could detect rice adulteration at different mixing ratios with high correlation coefficients through direct (e-nose; R = 0.94-0.98) and non-invasive measurement through the packaging (NIR; R = 0.95-0.98). The proposed method uses low-cost, rapid, and portable sensing devices coupled with ML that have shown to be reliable and accurate to increase the efficiency of rice fraud detection through the rice production chain.

Matched MeSH terms: Oryza*
Carbonized rice husk coated solar absorber for clean water generation from seawater with a solar still

Karen WMJ, Wong CY, Wang Z, Liew WYH, Melvin GJH

Environ Technol, 2023 Jan;44(3):326-333.
PMID: 34407722 DOI: 10.1080/09593330.2021.1970820

This study demonstrated the generation of clean water from seawater collected at the beach coast in Universiti Malaysia Sabah, Malaysia, with carbonized rice husk coated melamine sponge as solar absorber by a solar still. Melamine sponge was utilized as a seawater transportation medium since its porous structure is excellent in channelling the seawater. Whereas carbonized rice husk was used as the photothermal conversion material for its efficient heat absorption due to its black colour and porous structure. Implementing air gap between the seawater body and solar absorber, and restricted water pathway assisted in localizing heat on the top surface of the solar absorber. Clean water was generated under direct solar radiation during the day at an open space with average solar intensity around 1.1∼1.2 kW/m2 (slightly higher than 1 sun) for about 4 h. Efficiency of the solar absorber was calculated, while the quality of the generated clean water was observed in terms of salinity and pH value. Insulated solar still with carbon-coated sponge showed the highest efficiency at about 54.74%. Salinity of the collected clean water significantly reduced to consumable level which was approximately 55 ppm, and the pH value at about 6.73 where it was within the safe limit of the drinkable water pH.

Matched MeSH terms: Oryza*
Short-term analysis on the combined use of sugarcane bagasse ash and rice husk ash as supplementary cementitious material in concrete production

Channa SH, Mangi SA, Bheel N, Soomro FA, Khahro SH

Environ Sci Pollut Res Int, 2022 Jan;29(3):3555-3564.
PMID: 34387820 DOI: 10.1007/s11356-021-15877-0

Globally, concrete is widely implemented as a construction material and is progressively being utilized because of growth in urbanization. However, limited resources and gradual depravity of the environment are forcing the research community to obtain alternative materials from large amounts of agro-industrial wastes as a partial replacement for ordinary cement. Cement is a main binding resource in concrete production. To reduce environmental problems associated with waste, this study considered the recycling of agro-industrial wastes, such as sugarcane bagasse ash (SCBA), rice husk ash (RHA), and others, into cement, and to finally bring sustainable and environmental-friendly concrete. This study considered 5%, 10%, and 15% of SBCA and RHA individually to replace ordinary Portland cement (OPC) by weight method then combined both ashes as 10%, 20%, and 30% to replace OPC to produce sustainable concrete. It was experimentally declared that the strength performance of concrete was reduced while utilizing SCBA and RHA individually and combined as supplementary cementitious material (SCM) at 7, 28, 56, and 90 days, respectively. Moreover, the initial and final setting time is increased as the quantity of replacement level of OPC with SCBA and RHA separates and together as SCM in the mixture. Based on experimental findings, it was concluded that the use of 5% of SCBA and 5% of RHA as cement replacement material individually or combined in concrete could provide appropriate results for structural applications in concrete.

Matched MeSH terms: Oryza*
Bibliometric analysis of the research landscape on rice husks gasification (1995-2019)

Nyakuma BB, Wong S, Mong GR, Utume LN, Oladokun O, Wong KY, et al.

Environ Sci Pollut Res Int, 2021 Sep;28(36):49467-49490.
PMID: 34355317 DOI: 10.1007/s11356-021-15761-x

The processing of rice (Oryza sativa L.) generates large quantities of lignocellulosic wastes termed rice husks (RH). Numerous researchers have proposed biomass gasification as the panacea to the waste disposal and management challenges posed by RH. However, a comprehensive analysis of RH gasification is required to examine the research landscape and future directions on the area. The research landscape and global developments on RH gasification from 1995 to 2019 are examined through bibliometric analysis of 228 publications extracted from the Web of Science. Bioresource Technology is considered the most influential journal on the topic, whereas China is the most productive nation due to government policies and research funding. The most productive organization is the Harbin Institute of Technology, which is due to the significant contributions of Zhao YiJun and co-workers. Keyword analysis revealed three crucial research themes: gasification, biomass, and rice husks. The literature revealed that the syngas yield, distribution, and performance of RH gasification are significantly influenced by temperature, equivalence ratio, selected reactor, and gasifying medium. The techno-economic analysis of RH gasification revealed that government interventions such as high sales rates and low investment costs could enhance the commercial viability of the technology. Furthermore, the integration of RH gasification with carbon capture utilization and storage could promote the decarbonization of power plants, negative emissions, and net-zero climate goals. Overall, the paper provides valuable information for future researchers to identify strategic collaborators, journal publications, and research frontiers yet unexplored.

Matched MeSH terms: Oryza*

Filters

Please provide feedback to Administrator ([email protected])

External Links