Determination Of Moisture Content Research Articles

Exploring the circular prospects of cashew nutshells and avocado seeds as potential adsorbents for onboard natural gas storage

Natural gas (NG), known for its eco-friendly energy attributes, faces challenges such as low volumetric density, leakage susceptibility, and explosion risks during storage and transport. To narrow this gap, this study reports on the potential of bio-based adsorbents from cashew nut shells (CNS) and avocado seeds (AVS) as an alternative approach for the onboard storage of NG. CNS and AVS were characterized to determine moisture content, volatile matter content, ash content, and fixed carbon content. Additionally, the study determined the optimal loading of activating agents to produce activated carbons (ACs). ACs were produced through a dual process involving simultaneous chemical activation and carbonization. In the chemical activation phase, a sample of either cashew nut shells (CNS) or avocado seeds (AVS) was impregnated with phosphoric acid at various ratios. Subsequently, the properties of the ACs, including surface area, pore volume, and X-ray diffraction (XRD), were evaluated. The NG adsorption capacity of the ACs was assessed, and Freundlich and Langmuir isotherm adsorption equations were derived to elucidate the NG adsorption behavior on the ACs. The results revealed that the proximate analysis of CNS and AVS showed low moisture content (6.48% and 8.91%), high volatile matter (80.21% and 73.09%), low ash content (1.48% and 4.71%), and high fixed carbon (13.65% and 15.59%), indicating suitability for AC formulations. During synthesis, adding phosphoric acid to AVS or CNS in a 1:1 ratio resulted in significantly larger surface areas and pore volumes in the produced ACs. X-ray diffraction analysis of the ACs produced from CNS or AVS with phosphoric acid added at a 1:1 ratio indicated a broad diffraction background and a predominantly amorphous structure. The performance of the ACs in the adsorption of NG demonstrated that ACs produced from 1:1 mixtures of CNS with phosphoric acid and AVS with phosphoric acid exhibited higher adsorption capacities, 0.038 g/g and 0.031 g/g, respectively, at a low pressure of 5 bar, showcasing a novelty of this study. Furthermore, the Freundlich equation test yielded a constant R² exceeding 0.9, with positive adsorption intensity and adsorption capacity values, indicating a favorable fit for the model. In contrast, the Langmuir equation test resulted in a constant R² exceeding 0.9, but the adsorption capacity exhibited negative values, leading to inconclusive explanations. These findings affirm that bio-wastes can be an effective source of adsorbents for onboard natural gas storage , suggesting a means to reduce the take-dispose model and promote a circular economy in the energy sector.

Drying Kinetics and Quality Attributes of Solar-Dried Red Peppers: A Comparative Study with Traditional and Industrial Methods

Red pepper is a valuable ingredient known for its abundance of vitamins and antioxidants. But, it usually needs to be dried for longer preservation. Hence, this research is aimed at examining the drying kinetics and quality attributes of dried red peppers utilizing various solar drying methods, in comparison with traditional open sun drying (OSD) and industrial laboratory thin layer dryers (LTLD). Analysis parameters employed include determining moisture content, measuring color properties, evaluating antioxidant capacity, analyzing capsaicinoid content, and assessing microbial presence. The drying process took place in a sunny environment with fluctuations in temperature and relative humidity as evidence of the dynamic conditions experienced within the solar dryers. It was observed that the logarithmic model was the most accurate in predicting moisture ratio over time, estimating a drying time of 25 hours to achieve 10% moisture content. The result demonstrated that direct solar dryers (DSD), indirect solar dryers (ISD), and mix mode solar dryers (MMSD) methods showed moderate changes in color parameters, with average ΔL∗, Δa∗, and Δb∗ values of -5.08, -23.71, and -13.62, respectively. The average overall color difference (ΔE) for these methods was 27.96. In addition, after comparing it to the LTLD method, which showed the highest content of phenolic compounds at 47.89%, MMSD displayed a slightly lower content of 44.71%. Similarly, MMSD exhibited higher levels of DPPH radical scavenging activity and ferric reducing power, measuring at 44.22% and 1163.75 μmol Fe2+/L, respectively. The capsaicin content remained relatively consistent across all drying methods, with MMSD, DSD, and LTLD demonstrating similar levels of approximately 31 mg/g. Although MMSD had slightly higher mold and yeast counts compared to LTLD, ISD, and DSD, it remained lower than OSD (less than 0.56 log10cfu/g). Furthermore, MMSD showed a lower total microbial count in comparison to other drying methods. These findings suggest that MMSD shows promise as a drying technique for preserving the phenolic compounds and antioxidant activity of the dried product.

Rapid assessment of vanilla (Vanilla planifolia) quality parameters using portable near-infrared spectroscopy combined with random forest

The determination of moisture and vanillin content significantly influences the quality of vanilla. Currently, conventional chemical methods employed for assessing these parameters are time-consuming, involve complex sample preparation, are expensive, and environmentally unfriendly due to the use of chemical solutions. Portable Near-Infrared (NIR) spectroscopy emerges as a promising alternative, characterized by smaller dimensions and lower costs. This study investigates the performance of two portable NIR spectrometers with distinct wavelengths at 740–1070 nm and 1350–2550 nm, in conjunction with Random Forest (RF) and Partial Least Square (PLS) regression, and preprocessing techniques including min-max normalization, 1st derivative, standard normal variate (SNV), multiplicative scatter correction (MSC), 1st derivative + SNV, and 1st derivative + MSC for predicting moisture and vanillin content. At the wavelength range of 1350–2550 nm, RF coupled with 1st derivative produced the best moisture content prediction model with an R2 of 0.971, and RF paired with 1st derivative+SNV yielded the best vanillin content prediction with an R2 of 0.983. This work highlights that the integration of portable NIR and RF allows for rapid and non-destructive detection of moisture and vanillin content. This methodology provides a novel regression method for predicting vanilla qualities.

Determination of moisture content in coal using pulsed fast thermal neutron activation technique

The quality of coal is greatly influenced by the residual moisture content, which in turn affects the Gross Calorific Value (GCV) by limiting the maximum energy that can be extracted from a given mass of coal. Various methods have been developed to measure this residual moisture, including gravimetric techniques, near-infrared spectroscopy, microwave, and infrared moisture meters. Amongst these, neutron-based techniques offer distinct advantages for bulk and rapid characterization, making them suitable for online monitoring. This article presents the use of a Pulsed Fast Thermal Neutron Activation technique to determine moisture content in various coal samples acquired from Indian coal mines. A 14.1 MeV D-T neutron source coupled with a Bismuth Germanate (BGO) detector and associated electronics have been used. The hydrogen content in the sample has been used as an indicator for the moisture and the technique has been calibrated with samples of known moisture content. The results obtained for the coal samples demonstrate a remarkable agreement with the findings of proximate analysis. A minimum quantity of 2% moisture by weight has been detected with a relative error of 0.4%.

Electrical Properties for Non-destructive Determination of Free Fatty Acid and Moisture Content in Oil Palm Fruit

FFA content is one of the essential qualities of oil palm fruit. FFA content exceeding 5% is considered unsuitable for human consumption. Commonly, FFA content is determined by chemical methods in the laboratory, but it is destructive, time-consuming, and costly. Several non-destructive methods have been investigated, but a maturity prediction approach has been primarily used with no direct relation to FFA content. Thus, there is a pressing need for a non-destructive framework to assess the FFA levels in the oil palm fruit directly. An attempt has been explored using a non-destructive palm fruit quality assessment that relied on electrical properties (impedance, admittance, resistance, and capacitance) in the frequency range from 50 Hz to 5 MHz was investigated to predict FFA and moisture content directly. Two statistical analyses were employed: stepwise multiple linear regressions (MLR) and artificial neural networks (ANN) to calibrate and validate electrical properties with FFA and moisture content. The best-performing models ANN showcased significant results: r= 0.96, R2=0.92, SEC at 0.86%, SEP at 0.97%, CV at 19.45%, consistency at 88.54, and RPD at 3.43 for FFA prediction, and r= 0.99, R2=0.98, SEC at 3.09 %, SEP at 3.46 %, CV at 5.44 %, consistency at 89.08 and RPD at 7.02 for predicting moisture content. In modeling oil palm quality determination, applying the ANN method significantly improved model performances, demonstrating its efficacy in predicting non-destructively both FFA levels based on admittance and moisture content based on impedance.

Spatial variability of heavy metals concentrations in soil of auto-mechanic workshop clusters in Nsukka, Nigeria

The indiscriminate disposal of spent engine oils and other hazardous waste at auto mechanic workshops clusters in Nsukka, Enugu State, Nigeria is an environmental concern. This study examines the concentration of heavy metals in the soil inside the workshop cluster and in the unpolluted soil outside the workshop cluster at approximately 100 m. Ten sampling points were randomly selected from within the cluster and another ten from outside the cluster. Using a hand-held Global Positioning System, the coordinates of the selected points were established and used to create a digital map. Soil samples at depths of 0–30 cm and 30–60 cm, were analyzed for Cu, Fe, Zn, Pb, As and Cd using Spectrophotometer. Moisture content determination and particle size analysis were also done on the samples. Spatial variability of heavy metals concentrations of the studied site was also mapped with ArcGIS 10.2.2 using interpolation methods. Results showed that the soil ranged from sandy loam to sandy clay loam. Cadmium and Zinc had the lowest and highest concentration, respectively, in the studied area. Comparing the concentrations of heavy metals in soils within and outside the auto mechanic cluster revealed notable differences across various depths (0–30 cm and 30–60 cm). The analysis results for soil samples within the cluster exhibited concentration levels (mg/kg) ranging from 0.716–0.751 (Cu), 2.981–3.327 (Fe), 23.464–30.113 (Zn), 1.115–1.21 (Pb), 2.6–2.912 (As), and 0.133–0.365 (Cd) demonstrating a variation pattern in the order of Zn > Fe > As > Pb > Cu > Cd. Conversely, for soil samples outside the cluster, concentration levels (mg/kg) ranged from 0.611–0.618 (Cu), 2.233–2.516 (Fe), 12.841–15.736 (Zn), 0.887–0.903 (Pb), 1.669–1.911 (As), and 0.091–0.091 (Cd). To assess the disparity in heavy metal concentration levels between samples collected within and outside the clusters, ANOVA test was performed. The test showed significant difference in heavy metal concentrations between samples within and outside the auto mechanic cluster (p < 0.05), implying auto mechanic activities significantly impact heavy metal levels within the cluster compared to outside areas. The assessment of soil pollution utilized indices including the Geo-accumulation Index (Igeo), Contamination factor (Cf), and anthropogenic metal concentration (QoC). Zinc, Cadmium, and Arsenic showed the highest contamination factors, indicating significant soil contamination likely due to anthropogenic activities. The concentrations of the metals analyzed were within WHO permissible limits while the metals concentrations were also observed to decrease as depth was increased. Using ArcGIS 10.2.2, spatial maps showing heavy metal distribution were developed, with the Kriging method proving superior. This study suggests that heavy metal levels in the soil at the area be monitored on a regular basis.

Effects of Lime on Bagasse Ash-Stabilised Expansive Soils

Management of agricultural wastes and improvement of construction soils have become increasingly necessary for sustainable development. This study therefore stabilised selected expansive soils using bagasse ash (BA) and lime, with a view to determining the effect of lime on BA-stabilised soils. Two soil samples (identified as Sample A and Sample B) were collected from two identified locations characterised with expansive soils in Ile-Ife, Osun State, Southwestern Nigeria. Using standard procedures, the following preliminary and geotechnical tests were conducted on the soil samples in their natural state: moisture content determination, particle size analysis, specific gravity, Atterberg limits, compaction and unconfined compressive strength (UCS). BA was then introduced to the soils in 5 %, 10 % and 15 % proportions by weight of dry soil. Thereafter, Atterberg limits and UCS tests were conducted on the BA-stabilised soils. Also 2.5 % lime was introduced to each proportion of BA earlier used. Atterberg limits and UCS tests were then conducted on the BA-lime stabilised soils. Results showed that the two soils in their natural state have high plasticity and they both belong to the A-2-7 group. For both BA and BA-lime stabilised soil samples, plasticity reduced with increase in the stabilisers, which implies an improvement in the soil properties. Also, UCS of both BA and BA-lime stabilised soil samples increased with optimum values at 10 % BA content. Expectedly, addition of lime increased the values of UCS for each combination of stabilisers. It was concluded that BA could be used to improve the properties of expansive soils and that the addition of certain proportions of lime does not have a negative impact on the stabilisation properties of BA, but rather improves it.

An Adjusted Waveguide Antenna with A Woodpile-Shaped EBG for Eucalyptus Wood Moisture Content Measurement

An Adjusted Waveguide Antenna with A Woodpile-Shaped EBG for Eucalyptus Wood Moisture Content Measurement

Determining Moisture Content of Basil Using Handheld Near-Infrared Spectroscopy

Accurate and rapid determination of moisture content is essential in crop production and decision-making for irrigation. Near-infrared (NIR) spectroscopy has been shown to be a promising method for determining moisture content in various agricultural products, including herbs and vegetables. This study tested the hypothesis that NIR spectroscopy is effective in accurately measuring the moisture content of Genovese basil (Ocimum basilicum L.), with the objective of developing a respective calibration model. Spectral data were obtained from a total of 120 basil leaf samples over a period of six days. These included freshly harvested and detached leaves, as well as those left in ambient air for 1–6 days. Five spectra were taken from each leaf using a handheld NIR spectrophotometer, which covers the first and second overtones of the NIR spectral region: 950–1650 nm. After the spectral acquisition, the leaves were weighed for fresh mass and then put in an oven for 72 h at 80 °C to determine the dry weight and calculate the reference moisture content. The calibration model was developed using multivariate analysis in MATLAB, including preprocessing and regression modeling. The data obtained from 75% of the samples were used for model training and 25% for validation. The final model demonstrates strong performance metrics. The root mean square error of calibration (RMSEC) is 2.9908, the root mean square error of cross-validation (RMSECV) is 3.2368, and the root mean square error of prediction (RMSEP) reaches 2.4675. The coefficients of determination for calibration (R2C) and cross-validation (R2CV) are consistent, with values of 0.829 and 0.80, respectively. The model’s predictive ability is indicated by a coefficient of determination for prediction (R2P) of 0.86. The range error ratio (RER) stands at 11.045—highlighting its predictive performance. Our investigation, using handheld NIR spectrophotometry, confirms NIR’s usefulness in basil moisture determination. The rapid determination offers valuable insights for irrigation and crop management.

Near infrared spectroscopy for determination of moisture content in lyophilized formulation

A non-invasive near infrared (NIR) spectroscopic method was developed for the quantitative moisture determination in a lyophilized injection formulation. The calibration samples were prepared by exposing lyophilized samples at different temperatures and relative humidity. The samples from different scales and different process parameters were considered for adding robustness to the model. The NIR spectra were collected using a Fourier-transform (FT) NIR with a diffuse reflectance probe and the same samples were further analyzed by the Karl Fisher (KF) method for moisture content. The pre-treated NIR spectra were used for quantitative method development for moisture content. Partial least squares regression was used to develop calibrations in the 5600-4950 cm−1 region with calibration coefficient of determination (R2) of 0.96 and root mean square error of calibration (RMSEC) of 0.149. The model was cross-validated internally using the Kernel algorithm with r2 = 0.96 and RMSECV = 0.15. The accuracy of the NIR method against the KF method, precision, and reproducibility were good and the model was robust in predicting different external validation samples. This work allowed NIR as an alternative measurement for moisture analysis as well as facilitate 100% monitoring before packaging and save the cost of sample and time of KF analysis.

Effect of Ripening and Extraction Method on the Physicochemical Properties of Pectin Extracted from Peels of Apem and Apantu Plantain Cultivars in Ghana

Fruit waste has emerged as a significant environmental issue in recent years, adding to the global burden. In Ghana, the extensive use of plantains at various stages of ripeness results in substantial waste during each processing stage, leading to disposal challenges. Interestingly, these wastes often hold considerable economic value and can be repurposed as a source of valuable raw materials or products. Given the broad range of uses for plantains and the significant pollution problems associated with their processing, finding new uses for this organic waste has become a pressing necessity. This study investigated the impact of the method of extraction and ripening stages on the physicochemical characteristics of pectin obtained from two different cultivars of plantains, namely, Apem (M) and Apantu (T), which are indigenous to Ghana. Pectin samples were extracted from different stages of ripening (matured-green (G), half-ripe (H), and full-ripe (R)) by the utilization of acidic (D) and alkaline (L) extraction methods. The analyses conducted on the extracted pectin included proximate composition and moisture content determination, assessment of mineral/elemental composition, and solubility testing. Phytochemical investigations were performed to determine the phytoconstituents present in these pectin extracts. The pectin samples were characterized by determining their equivalent weight, methoxyl and anhydrouronic acid content, and the degree of esterification. The pectin yields obtained from the samples ranged from 10.01% to 46.55%. The moisture levels of all the pectins were below 20%. All pectin samples had swelling indexes between 37.5 ± 0.01% and 185.71 ± 0.02%. The equivalent weight (EW) of the pectin samples ranged from 1351.00 ± 0.6 g/mol to 10000.00 ± 0.07 g/mol. The methoxyl content (MeO) fell within the range of 6.2 ± 0.07% to 14.88 ± 0.14%, while the anhydrouronic acid content (AUA) varied between 38.72 ± 0.28% and 86.59 ± 0.21%. The degree of esterification (DE) ranged from 81.22 ± 0.21% to 97.56 ± 0.14%. Furthermore, the result of the micronutrient and mineral analysis indicated compliance with nutritional requirements. The levels of heavy metals were also within acceptable thresholds, thereby adhering to existing regulatory requirements. These findings highlight the significance of both the extraction technique and the ripening stage on the physicochemical properties of the extracted pectins. Generally, the extracted pectins possess excellent nutritional quality and physicochemical properties, rendering them a very valuable resource that holds promising potential for use in the food and pharmaceutical sectors.

Determination of hydration kinetic of pinto beans: A hyperspectral images application

Hydration is a typical operation applied to legumes before cooking, reducing time and the associated energy cost. To monitor the process, mass balance method is the most used methodology, despite this method is destructive, repetitive, and time-consuming. For that reason. hyperspectral techniques are presented as an alternative for assessing the hydration process since it is a noninvasive method. Therefore, the objective of this work was to evaluate the technique of hyperspectral imaging for studying the hydration kinetics of pinto beans. For this purpose, a sample of pinto beans was hydrated in distilled water, determining moisture content during the process and taking hyperspectral images by reflectance mode, in the range 400 to 800 nm until constant mass. The moisture content was modelled using Peleg and a sigmoidal model. Next, the images were pre-treated and the median spectral profile for each bean was obtained. Then, a regression model was fitted, using the wavelength that maximized the coefficient of determination (R2) and minimized the root mean square error (RMSE). The results show that Peleg model fit experimental data with R2 in the range of 0.974 to 0.989 while sigmoidal model of 0.997 to 0.999. On other hand, mean spectral profiles at 632 nm and sigmoidal model give the higher metrics 0.997 and 38.3 for R2 and RMSE respectively. The results showed that hyperspectral imaging in reflectance mode is a tool capable of measuring the hydration level of beans with higher performance at 632 nm, with a determination coefficient R2 higher than 0.98.

Comparative analysis of the effect of different drying methods on the quality parameters of tomato powder

This study investigates the impact of different drying systems on the quality parameters of tomato powder. The objective of this research is to evaluate and compare the effects of different drying methods on the quality parameters of tomato powder. Fresh matured and ripped tomatoes were procured, sorted, graded, washed and sliced with the thickness of 3 mm. The tomatoes were dried by three different methods viz. oven drying at 60°C, tent drying and open sun drying, milled into powder using kitchen blender and packed into air tight nylon bags for moisture content and quality parameters determination. The relevant test methods were used to determine quality parameters of the tomato powder. The relevant test methods were used to determine the results of the study showed that the samples have significant differences on the proximate and minerals content but between the samples. The findings show that there is no significant difference at 95% confidence interval. The R-square value of 0.535 and 0.980 for both proximate and minerals respectively are a measure of goodness of fit. It means the model explains 53 and 98% variation embedded in the response variable. There was no statistically significant difference between the samples (oven, sun and tent drying at p &gt; 0.05. This suggests that any of the drying mediums can serve as a good source of drying for tomato powder production. However, since tent drying has the highest nutrients by composition, this study suggests the use of tent drying for production of tomato powder. Further research is needed in order to optimize the drying process of tomato powder and improve its quality parameters.

Assessment of microwave drying for rapid and convenient analysis of medicinal plants for quality assurance.

The safety and quality of many medicinally important herbs are compromised since farmers and small organizations are involved in the cultivation, aggregation, and primary processing of these herbs. Such organizations often lack adequate quality control facilities. To improve the safety and quality of herbal products, simple, rapid, and affordable quality control systems are required. The aim of this study was to assess the suitability of microwave oven-drying for moisture content (MC) determination and sample preparation of herbs in small organizations. Microwave oven-drying (720 W) and convective oven-drying at 105°C for MC determination were compared. The effects of three different drying methods (microwave oven-drying, low-temperature convective drying, and freeze-drying) on in vitro antioxidant and polyphenol oxidase (PPO) activity were determined, similarity analysis was conducted using HPLC signature spectra, and validation was performed with LC-MS focusing on one herb. Microwave oven-drying at 720 W significantly reduced the drying time (from hours to minutes), whereas the spatial variationof temperature in convective ovens set at 105°C can cause about 10% underestimation of MC. Microwave oven-dryingshowed similar macro-properties like freeze-drying and higher extractability (10%-20%) and in vitro antioxidant capacity (33%-66%) and lower PPO activity compared to low-temperature convective drying. HPLC signature spectra revealed strongsimilarity ofsoluble components between freeze-dried and microwave oven-dried herbs. LC-MS analysis demonstrated more common compounds between freeze-driedand microwave oven-driedCentella asiatica extracts, whereas convective tray-dried samples had fewer compounds common with samples obtained by freeze-drying or microwave oven-drying. Microwave oven-drying is rapid (tens of min) and shows small batch-to-batch variation compared to oven-drying at 105°C. The in vitro antioxidant assays and signature spectra can be used for assessing the source and purity or quality of a specific herb variety.

Characterization of Soil Properties Influencing Flash Flood-Related Road Damage in North-Eastern Regions of Bangladesh

Flash floods in the North-Eastern region of Bangladesh pose a severe threat to road infrastructure, causing extensive damage and disruptions. This study focuses on the comprehensive characterization of soil properties that play a pivotal role in exacerbating flash flood-related road damage. The North-Eastern region, characterized by diverse geological formations, including the Surma Basin and the Meghalaya Plateau, experiences recurrent flash floods during the monsoon season. The undulating topography and a network of rivers contribute to the complexity of the hydrogeological system, influencing soil properties and their impact on road infrastructure.&#x0D; Field surveys were conducted to identify flash flood-prone areas, focusing on elevation, slope, and proximity to water bodies. Soil samples were collected at various depths and locations within vulnerable road sections, considering different land uses and topographical features. Laboratory analyses included particle size distribution, moisture content determination, soil classification, and cohesion tests. The results of this study highlight specific road sections vulnerable to flash floods, providing a foundation for targeted soil characterization. Key soil properties influencing road damage include high clay content, poor drainage characteristics, and low cohesion. The results also revealed the correlation between vulnerable road sections and specific combinations of soil properties, allowing for the identification of hotspots prone to flash flood-related damage.&#x0D; Finally, this study contributes to an enhanced understanding of the soil properties influencing flash flood-related road damage in the North-Eastern region. The identified key soil characteristics offer valuable insights for road infrastructure planning and design, emphasizing the need for mitigation measures such as improved drainage systems and the use of appropriate roadbed materials to enhance overall road resilience in flood-prone areas.

Quantitative determination of wheat moisture content based on microwave detection technique combined with multivariate data analysis

In this study, a new method is proposed for the quantitative detection of wheat moisture content based on double heterodyne mixing microwave transmission technique. First of all, the microwave detection device received the command from the computer and detected the wheat in the frequency domain of 2.5 GHz–11.5 GHz, while acquiring the transmission index corresponding to each frequency point. Then, competitive adaptive reweighted sampling (CARS) was used for coarse feature selection of the transmission index after least partial squares filtering, and Genetic Algorithm (GA) was used for secondary feature refinement of the coarse selected feature variables, and they were sorted and combined according to their weights. Finally, Support vector regression (SVR) was used to establish quantitative models with different combinations of feature variables to achieve rapid detection of wheat moisture content. The results showed that the CARS-GA-SVR model had better detection performance for wheat moisture content determination compared to the CARS-SVR model. Among them, the CARS-GA-SVR model had the best detection effect when the combination of feature variables is 6-dimensional, with coefficient of determination (RP2) of 0.9756 and relative prediction deviation (RPD) of 6.3234. Compared to the SVR model established by the full transmission index, the RPD improved from 3.7089 to 6.3234. The results reveal that rapid and high-precision detection of wheat moisture content can be achieved by using a self-made miniaturized microwave device combined with a suitable chemometric method.

Determination of composite fuel parameters in the operation of technogenic deposits of coal mining enterprises

The research provides the determining of the parameters for composite fuel in the operation of technogenic deposits at coal mining enterprises. The qualitative characteristics of technogenic raw materials are determined, and the parameters of technological processes to produce composite fuel are established: preparation (screening or grinding), physical and chemical influence on the state of raw materials, mixing, production, and drying (if necessary) to obtain suitable fuel. Based on the particle size distribution (as well as sedimentation analysis for waste fractions up to 50 μm) and chemical composition (with the determination of moisture, volatile matter, ash, and sulphur content) it was found that the physicochemical parameters for each type of industrial waste, when preparing them for use in the production of composite fuels, have been established. A technological classification of technogenic materials has been developed, which makes it possible to systematize technical issues in the implementation of preparation processes, physical and chemical influences, mixing, production, and drying to obtain suitable fuel.

Microstrip and Metamaterial Embedded Patch Antenna Sensors for Determination of Moisture in Rice, Wheat, and Pulse Grains

Moisture Content determination inside the grains is essential for grain processing activities including harvesting, storing, inspecting, and transporting. In this paper, microstrip and metamaterial embedded patch sensors were developed to determine the moisture content and mean relative error (MRE) of rice, wheat, and pulse. The sensors were simulated in HFSS, prototypes were fabricated and the measurement was done using VNA and anechoic chamber. The Microstrip sensor was operating at a frequency of 5.2 GHz and the metamaterial-embedded sensor was operating at 4.5 GHz. Calibration equations were obtained by using the values of reflection coefficients and moisture content ranging from 11.76% to 25%. For analyzing the efficacy of designed sensors, predicted moisture content (PMC) and actual moisture content (AMC) have been compared and the lowest mean relative error has been determined. The analysis shows that the metamaterial embedded sensor has better sensitivity and accuracy than the microstrip sensor. The lowest mean relative error in moisture prediction for metamaterial sensor was 1.07% for rice, 1.13% for wheat, and 1.47% for pulse respectively. A comparison of the proposed metamaterial embedded sensor with earlier designed sensor in literature was also presented in this work and it was found that the proposed sensor had more accuracy and sensitivity than earlier designs.

Standardization Studies of Momordica charantia Seed with Physicochemical and Preliminary Phytochemical Accounts

Momordica charantia Linn also known as Karela or bitter guard is commonly used vegetable of Cucurbitaceae family. Phytochemical constituent present in seeds contains oil, and sterols possesses the anti bacterial anti microbial and anti inflammatory properties which makes it one of the oldest plant used is natural Indian medicinal system. Present study was aimed to study organoleptic characterization, determination of moisture, total ash, acid-insoluble, water-soluble ash and protein contents, Loss on drying, heavy metals and microbial profile of Momordica charantia seed without seed coat. Furthermore qualitative test for secondary metabolites were performed for bitters, saponine, terpenoids, phenolic acids, glycosides, carbohydrates and reducing sugars were marked in preliminary tests. In final standardization extracts were taken for UV spectroscopy (at 270nm wavelength) at different concentrations against standard for quantitative analysis. After preparing different compositions mobile phase containing ethylene acetate: water: formic acid (7.7:1.3:0.9) was selected for TLC of chlorogenic acid marking in aqueous extract of Momordica charantia seed and gallic acid was run using mobile phase using toluene: formic acid: methanol (3.3: 0.8: 0.2) showed the presence of markers against standard. The plates were prepared and developed in mobile phase and Rf value was calculated. Photography of plates was done under UV visible mode. The above findings can be helpful in further research to reveal the reverse pharmacology of Momordica charantia seeds reported in traditional uses with significant way to design newer outcomes in diseases related with inflammatory and immune markers.

An Assessment of the Elemental Compositions of Neem (Azadirachta indica A. Juss) Products for Biofertilizer Production

The use of soil-nutrients enhancers is crucial to crop and vegetable farmers. However, with increasing costs of mineral fertilizers, seeking alternatives in the form of biofertilizers may help to alleviate farmers concerns. Neem (Azadirachta indica A. Juss) products - seeds, tree bark, and leaves - have been documented in the literature to have soil enriching properties. This study examines the elemental compositions of neem tree bark, leaves, and mixture (leaves and bark) to suggest the most suitable for biofertilizer production. Fresh neem leaves (young and old leaves were discarded) and tree bark (harvested 0.4 – 1.70 m above ground) were harvested. chopped into bits, air-dried under the shade for 7 days, milled into powder using a mortar and pestle, sieved (with a 1.7 mm sieve) and packed into air tight nylon bags for moisture content and elemental composition determinations. The relevant test methods were used to determine the elemental compositions of the samples of neem leaves, tree bark, and mixture of bark and leaves. The results revealed that there was no statistically significant difference between the samples at p&gt;0.05.This suggests that any of the samples can serve as a good source for biofertilizer production. Since neem leaves had the highest nutritional elements by composition and relatively easier to obtain, this suggests that neem leaves can be recommended as a green fertilizer to support crop and vegetable growth. However, its use as a straight fertilizer may require further investigations.