Measurement Of Moisture Content Research Articles

Prediction and visualization of moisture content in Tencha drying processes by computer vision and deep learning.

It is important to monitor and control the moisture content throughout the Tencha drying processing procedure so that its quality is ensured. Workers often rely on their senses to perceive the moisture content, leading to relative subjectivity and low reproducibility. Traditional drying methods, which are used for measuring moisture content, are destructive to samples. This research was conducted using computer vision combined with deep learning to detect moisture content during the Tencha drying process. Different color space components of Tencha drying sample images were first extracted by computer vision. The color components were preprocessed using MinMax and Z score. Subsequently, one-dimensional convolutional neural networks (1D-CNN), partial least squares, and backpropagation artificial neural networks models were built and compared. The 1D-CNN model and Z scorepreprocessing achieved superior predictive accuracy, with correlation coefficient of prediction (Rp) = 0.9548 for moisture content. The migration of moisture content during the Tencha drying process was eventually visualized by mapping its spatial and temporal distributions. The results indicated that computer vision combined with 1D-CNN was feasible for moisture prediction during the Tencha drying process. This study provides technical support for the industrial and intelligent production of Tencha. © 2024 Society of Chemical Industry.

GRU–Transformer: A Novel Hybrid Model for Predicting Soil Moisture Content in Root Zones

The accurate measurement of soil moisture content emerges as a critical parameter within the ambit of agricultural irrigation management, wherein the precise prediction of this variable plays an instrumental role in enhancing the efficiency and conservation of agricultural water resources. This study introduces an innovative, cutting-edge hybrid model that ingeniously integrates Gated Recirculation Unit (GRU) and Transformer technologies, meticulously crafted to amplify the precision and reliability of soil moisture content forecasts. Leveraging meteorological and soil moisture datasets amassed from eight monitoring stations in Hebei Province, China, over the period from 2011 to 2018, this investigation thoroughly assesses the model’s efficacy against a diverse array of input variables and forecast durations. This assessment is concurrently contrasted with a range of conventional machine learning and deep learning frameworks. The results demonstrate that (1) the GRU–Transformer model exhibits remarkable superiority across various aspects, particularly in short-term projections (1- to 2-day latency). The model’s mean square error (MSE) for a 1-day forecast is notably low at 5.22%, reducing further to a significant 2.71%, while the mean coefficient of determination (R2) reaches a high of 89.92%. Despite a gradual increase in predictive error over extended forecast periods, the model consistently maintains robust performance. Moreover, the model shows exceptional versatility in managing different soil depths, notably excelling in predicting moisture levels at greater depths, thereby surpassing its performance in shallower soils. (2) The model’s predictive error inversely correlates with the reduction in parameters. Remarkably, with a streamlined set of just six soil moisture content parameters, the model predicts an average MSE of 0.59% and an R2 of 98.86% for a three-day forecast, highlighting its resilience to varied parameter configurations. (3) In juxtaposition with prevalent models such as Support Vector Regression (SVR), K-Nearest Neighbors (KNN), Gradient Boosting Decision Tree (GBDT), XGBoost, Random Forest, and deep learning models like Deep Neural Network (DNN), Convolutional Neural Network (CNN), and standalone GRU-branch and Transformer-branch models, the GRU–Transformer framework demonstrates a significant advantage in predicting soil moisture content with enhanced precision for a five-day forecast. This underscores its exceptional capacity to navigate the intricacies of soil moisture data. This research not only provides a potent decision-support tool for agricultural irrigation planning but also makes a substantial contribution to the field of water resource conservation and optimization in agriculture, while concurrently imparting novel insights into the application of deep learning techniques in the spheres of agricultural and environmental sciences.

Decline of a North American rocky intertidal foundation species linked to extreme dry, downslope Santa Ana winds

Foundation species are essential to ecosystem function, but their role as habitat providers is predicated on their spatial dominance. Worldwide, kelps, seagrasses, corals, and other marine foundation species have declined. This is true also for rockweeds, the canopy-forming analog of subtidal kelp forests in temperate rocky intertidal ecosystems. On the west coast of North America, dense beds of the rockweed Silvetia compressa occur across large biogeographic regions, benefitting numerous species by ameliorating physical stress caused by sun exposure, desiccation, heat, and wave disturbance. Like many rockweed species, Silvetia is long-lived, slow-growing, and short-dispersing – characteristics that reduce its resilience to disturbance. Using a generalized additive mixed-effects model with explicit spatial effects, we analyzed canopy cover data from 30 sites spanning 18 years, and we tested the hypothesis that Silvetia population trends are tightly linked to atmospheric climate conditions, particularly Santa Ana wind events (SAWs): strong, hot, and dry downslope winds that originate inland and move offshore. We found that the rockweed had declined markedly, particularly at sites south of the major biogeographic break, Point Conception (PC), including the California Channel Islands and southern California mainland, and a highly significant negative effect of dewpoint depression, a measure of moisture content in the atmosphere, on Silvetia cover across all three regions in this study. Our results suggest that any increases in the frequency or intensity of SAWs are likely to lead to large declines and possible extirpation of Silvetia, as well as the important ecological services the species provides.

Impact of Rice Husk Ash on the Compaction Characteristics of Soil

Usually, the measurement of maximum dry density (MDD) and optimum moisture content (OMC) is important for assessing the quality control of the compacted fill or earthwork constructions as the compaction parameters. Rice husk ash (RHA), plentifully available in many rice-producing countries, can be used as a building material. This study mainly tries to investigate the effect of RHA on compaction features of sandy soil classified as A-2-4 or SM for soil stabilization. Nominal to a maximal dosage of RHA addition in the soil was considered for the experiments by the standard Proctor compaction tests. The result revealed that by increasing the amount of RHA in the soil, MDD was reduced and OMC increased significantly. It can be concluded that applying a soil-RHA combination is beneficial to soil improvement. Jagannath University Journal of Science, Volume 10, Number II, Dec. 2023, pp. 87-93

Optical measurement of paper moisture content with application in paper pressing

Optical measurement of paper moisture content with application in paper pressing

Monitoring and Calibrating Building Materials Drying Kinetics with Capacitance Sensors

Building materials’ moisture content defines the overall durability and serviceability of buildings and infrastructures. Conventionally, moisture content is estimated by weighing the materials before and after drying. In this work, the results of capacitance wired sensors for measuring moisture content were investigated. These sensors facilitate in situ measurement of capacitance values, with the aid of specialized installation equipment, and the results are accessible via a cloud-based software application. In practice, the main drawback associated with the application of these sensors is related to their calibration. Thus, it is important to investigate different algorithms which convert capacitance readings into moisture content values. To address this, various specimens covering a diverse set of building materials were prepared in the laboratory. This study focused on examining two bricks, two sedimentary stones with low and high porosity values. and four different kinds of mortars (with different binders, namely hydrated lime putty, cement, natural hydraulic lime, and hydrated lime powder and pozzolan). The results indicated that a linear model can be recommended for calibrating sensor capacitance to moisture content measurements. This model can be used for the prediction of building material moisture content with high accuracy, from saturated to the dry state, covering the full range of drying kinetics.

Moisture diffusion analysis and their effects on the mechanical properties of organic particle filled natural fiber reinforced hybrid polymer composites

This investigation explores the water intake characteristics of hybrid composite samples composed of Wood Dust as organic filler (WD), Prosopis Juliflora as fiber (PJF), and epoxy as matrix. The specimens underwent immersion in both distilled and seawater environments for a duration of 240 hours. The composite samples, with compositions of 10WD + 30PJF + 60 PF, 20WD + 20PJF + 60 PF, and 30WD + 10PJF + 60 PF, were subjected to moisture content measurements at different intervals. Mechanical properties were tested following ASTM standards for both dry and wet conditions. Results indicate that seawater immersion leads to higher moisture absorption compared to distilled (condensed) water, with the fiber (PJF)-rich composite (30PJF +10WD + 60 PF) exhibiting the greatest water absorption. The water absorption pattern exhibited by the hybrid composite of WD/PJF/PF does not adhere to a Fickian behavior. Tensile, flexural, and impact properties were evaluated, with the (10WD + 30PJF + 60 PF) specimen showcasing superior performance in dry conditions, boasting a tensile character of 51 MPa, flexural (bending) strength of 60 MPa, and impact value of 1.4 KJ/m2. However, its strength diminishes upon exposure to distilled water and seawater. SEM analysis of fractured surfaces from seawater-exposed specimens provides additional insights. In conclusion, this study sheds light on the influence of immersion on moisture absorption and mechanical properties, emphasizing the prevalence of non-Fickian behavior and the varying performance of different compositions, with the (10WD + 30PJF + 60 PF) composition demonstrating remarkable strength under dry conditions.

Unobvious geoheritage in sacral buildings: millstones in churches of NE Poland from a geological and geomorphological perspective

The article highlights the importance of medieval churches with embedded millstones as geocultural objects with a great geotouristic and educational potential. In the lowland areas of Northeastern Poland, 79 millstones and their semi-finished products were inventoried. Their sizes ranged from 70 to 100 cm in diameter. The majority of them were made of erratic boulders, mainly granitoids of Fennoscandian origin. Additionally, gneisses, sandstones, pegmatites, and basaltoid were also identified. An attempt was made to determine the degree of weathering of the millstones over several hundred years of exposure to external conditions. Measurements of moisture content and salinity of the walls surrounding 10 millstones embedded in the walls of 8 churches were taken three times (in spring, summer, and winter). Lower wall moisture was observed in the vicinity of the millstones, but only in the case of three walls, the salinity of the mortar binding the bricks and stones was at a low level. A weak but statistically significant negative correlation was found between the age of the churches and the hardness of the millstones measured with a Schmidt hammer.

A moisture detection sensor for flour based on the gas in scattering media absorption spectroscopy

AbstractFlour is an essential ingredient in human daily diet, thus it is crucial to measure its moisture content. However, current detection methods are time‐consuming and labor‐intensive, hindering quick measurement. Here we demonstrate the measurement of moisture content in flour via gas in the scattering media absorption spectroscopy (GASMAS) technique. A compact sensor that includes distributed feedback laser driver, cuvette, photodetector, analog lock‐in amplifier, and analysis processing module is developed. We measure the equivalent mean path length of various flour samples, and verify the measurement sensitivity of GASMAS by studying its dependence on moisture content. A linear relationship between path length and moisture content is established by least‐squares curve fitting, corresponding to a correlation coefficient of 0.996. Compared to the drying method, our method shows a maximum error range of 6.1% for all samples, providing a highly accurate and reliable measurement of water content in flour.

Non-destructive method of small sample sets for the maize moisture content measurement during filling based on NIRS

Non-destructive method of small sample sets for the maize moisture content measurement during filling based on NIRS

Exploring moisture content measurement using an open-ended coaxial sensor: A method of moments approach

Continuous measurement of the material's relative moisture content (m.c) is an important duty in industrial process control. However, current techniques only provide the absolute amount of water in the sample container, and (m.c of corn) is obtained from an extra mass measurement. The investigation of the dielectric behavior of moist matter at microwave frequencies using an open-ended coaxial sensor, as well as the relationship of reflection coefficient and moisture content for frequencies ranging from 1 GHz to 5 GHz via MOM and measurement, and thus the comparison of results, confirms the superiority of Method of Moment (MOM), due to benefits such as low cost and non-harmful to the sample materials. The basic concept is explored, and the results of experiments using maize as the medium are shown.

Tillage Effects on Soil Moisture and Sulfur use Efficiency by Sesame (Sesamum indicum L.) on Vertisol of North Ethiopia

Sesame, produced in Humera is among the highest quality seeds grown in Ethiopia and even in the world. However, its productivity is by far less than the production potential due to nutrient depletion, moisture stress and lack of crop response to applied fertilizer. An experiment was conducted to evaluate the effects of tillage practices and sulfur fertilizer rates on moisture conservation and agronomic sulfur use efficiency of sesame crop in 2015. The treatments were tied ridges (M1) and flatbed tillage practices combined with five rates of sulfur fertilizer at a split plot design with three replications. M1 and flatbed treatments were assigned to the main plots, while sulfur fertilizer rates were assigned to the sub-plots. Measurements of soil moisture content at 0-20 cm, 20–40 cm and 40–60 cm depth were conducted throughout the growing season at an interval of 13 days using the gravimetric method. The results showed that M1 increased the soil moisture content up to 44% compared to the flatbed. The highest amount of agronomic sulfur use efficiency 14.4 kg kg-1 was also obtained from M1 tillage at 10 kg S ha-1. On the other hand, the highest amount of agronomic sulfur use efficiencies under flatbed tillage was 9.5 kg kg-1 at 10 kg S ha-1. M1 increased agronomic sulfur use efficiency by 51.6%. Tied ridging is the best option to significantly increased soil moisture availability in the root zone and as a consequence it increased agronomic sulfur use efficiency of the sesame. Therefore, in-situ moisture conservation using tillage practices like M1 at farm level should be demonstrated at farmer’s field in the semi-arid Humera areas for improving sulfur fertilizer use efficiency.

Tillage and Crop Residue Effects on Soil Carbon and Moisture for Wheat (Triticum aestivum L.) Productivity in Semiarid Regions of Tigray, Ethiopia

Soil tillage is one of the basic agriculture operations. However, the appropriate tillage type, tillage time, and tillage frequency for effective moisture harvesting and sustainable soil fertility were not investigated for Tigray. A field experiment was conducted during 2016 to 2018 in Enderta district. It was done with the objective of evaluating the effect of different tillage practices on wheat productivity. The treatments were (I) permanent bed+ crop residue,(II) three times tillage with furrow, (III) two times tillage with furrow, and (IV) farmer’s practice tillage. A randomized complete block design with three replications was set up. Measurement of soil moisture content was conducted using the gravimetric method. Agronomic parameters were collected and analyzed using GenStat. Marginal rate of return was also estimated from the total revenue and total variable cost. Positive effect was found on soil fertility, soil moisture content, and grain yield due to the tillage practice and crop residue. Permanent bed+ crop residues and three tillage furrow increased soil moisture content, organic carbon, and total nitrogen, as well as the yield and yield components at the second and third year of experimentation. The highest grain yield 2952 kg ha-1 and biomass yield 8582 kg ha-1 were recorded at the three tillage furrow in the third year of experimentation. The 59,056 ETB was the highest net revenue recorded at three times tillage with furrows. From this result, it can be concluded that without adding any additional input instead of changing agricultural operation techniques, the economic benefit of farmers’ could be improved by 48%. Therefore, three tillage practices with furrow is the most economically feasible technology for farmers to increase wheat productivity in the semiarid area of Enderta district.

Moisture content online measurement in the sludge by ultrasonic reflection method

Moisture content is an important parameter of solid waste degradation in landfill. The traditional gravimetric method used for determining the moisture content of sludge is very time-consuming and cannot achieve online measurement of sludge moisture content. This paper proposes an ultrasonic reflection method to measure the moisture content of sludge on-line, the sludge only needs to be dried once, and then the online measurement can be realized. The specific process is as follows: by analyzing the ultrasonic characteristic parameter under different moisture content, the quantitative relationship between them can be obtained, and then the sludge moisture content can be deduced by the ultrasonic characteristic parameter. In this paper, the relationship between the ultrasonic characteristic parameter of the three sludge and the moisture content was analyzed, and the quantitative relationship was determined. The sludge moisture content calculated by this method is very close to the actual value. This method provides a new research idea for the online measurement of sludge moisture content.

Effect of moisture on the edgewise flexural properties of acetylated and unmodified birch plywood: a comparison of strength, stiffness and brittleness properties

Birch plywood has superior mechanical properties compared with that made from most softwoods. However, durability-related issues still limit the application of birch plywood in outdoor structures. A means to enhance its durability is to acetylate birch veneers before processing them into plywood. An earlier study showed that such acetylated birch plywood has equivalent mechanical properties to unmodified ones. However, there is a need to better understand the moisture effect on the mechanical properties of unmodified and acetylated birch plywood for a better design of structural birch plywood elements. Moreover, due to the pronounced in-plane anisotropy of plywood, extra concern should be given to the weakest load angle due to the weakest chain theory. In this study, acetylated and unmodified birch plywood specimens were conditioned in climate chambers under three different environments with a temperature of 20 °C and increasing relative humidity (RH) from 35 to 65% to 95%. Thereafter, their in-plane edgewise flexural properties with load-to-face grain angles of 0, 45, and 90 degrees were tested. The influence of both RH and measured moisture contents on bending strength and stiffness are then presented. Prediction formulas of mechanical properties with moisture contents are derived by performing linear regressions among test results. Variations of brittleness factors and brittleness indexes under various RH conditions and load-face grain angles were also studied.

Wheat Quantity Monitoring Methods Based on Inventory Measurement and SVR Prediction Model

Due to the influences of the storage environment, water content change, particle settlement, natural loss, and other factors, the distribution density of wheat and the volume of grain pile in the storage process are gradually changed so that the single weight calculation method cannot objectively evaluate the storage quantity of wheat and also causes difficulties to the regular inspection of the quantity of wheat stock. To meet the practical needs of wheat inventory monitoring, a wheat inventory monitoring method based on inventory measurement and the support vector machine regression (SVR) prediction model is proposed. By collecting the working papers for the physical inspection of wheat in grain warehouses in Shanxi province, Hebei province, Henan province, Jiangsu province, and other places, the storage time, storage weight, storage moisture content, measured moisture content, measured volume weight, measured net volume, and measured weight for inspection were selected as training samples for the SVR prediction model, and kernel function selection and parameter optimization were carried out. We developed an optimal prediction model for the amount of wheat in the grain depots. In the actual grain store measurement process, the net volume of wheat in the current grain store was obtained by a laser volumetric measuring apparatus, the actual bulk density of wheat was sampled, and the actual moisture content of wheat was measured by sampling. The three samples, their storage time, their storage moisture content, and their storage weight were fed into the trained SVR prediction model as new samples, and the predicted weight of the wheat in the current grain store was obtained from the output. The error rate calculation procedure was introduced to achieve an anomalous judgment error rate for grain depots. The experimental results showed that the SVR prediction model based on the linear kernel function had a very low mean squared error and high determination coefficient, and the average prediction accuracy of the grain stock error rate reached 93.2 percent, which can meet the requirements of wheat quantity monitoring in grain warehouses.

Effect of Glycerol Concentrations on the Characteristics of Cellulose Films from Cattail (Typha angustifolia L.) Flowers.

Plastic waste has become a big problem for the environment globally. Biodegradable polymers are a potential replacement for plastics that can have a positive outcome both environmentally and economically. In this work, we used acid hydrolysis and alkaline treatment to extract cellulose fibers from cattails. The obtained cellulose was used as a substrate for the fabrication of cellulose film using a casting technique on plastic plates. Different concentrations of the plasticizer, glycerol, were used to prepare films for comparison, and its effects on the film's characteristics were observed. The morphology, chemical structure, and thermal stability of the cattail cellulose (CTC) films were studied using techniques such as scanning electron microscopy (SEM), attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR), and thermogravimetric analysis (TGA), respectively. Measurements of transparency, moisture content (MC), water solubility (MS), and water contact angle (WCA) were also performed. Introducing glycerol into the films increased the transparency, MC, and WS values, as well as the gap width between film textures. However, it resulted in a decrease in the WCA of the films, showing that the hydrophilicity of the films is increased by the addition of glycerol. The interaction between the functional groups of cellulose and glycerol was established from the ATR-FTIR and XRD data. The obtained results indicated that glycerol affected the thermal stability and the degree of crystallinity of the produced films. Accordingly, the hydrophilicity of the cellulose film was increased by increasing the glycerol content; therefore, cattail cellulose films can be used as a biodegradable alternative to plastic in the future.

Polycaprolactone/cress seed mucilage based bilayer antibacterial films containing ZnO nanoparticles with superabsorbent property for the treatment of exuding wounds

In this research, a novel double-layer film based on polycaprolactone and cress seed mucilage containing zinc oxide nanoparticles (0.5–2 %) was synthesized using solution casting technique, as an interactive multi-functional wound dressing. The bilayer films were characterized by measuring moisture content, contact angle parameter, porosity, water vapor transmission rate (WVTR), color attributes and opacity, swelling, degradation, mechanical properties, cell viability, and antimicrobial activity, as well as using scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD). The results indicated that the film containing 1.5 % zinc oxide nanoparticles had the best performance, with high swelling ability (3600 %) and 25 % degradation within 24 h of placement in a wound simulator solution. Its mechanical properties, including tensile strength and elongation at break, were 9 MPa and 5.53 %, respectively. In investigating the antimicrobial activity of the optimal film against Escherichia coli and Staphylococcus aureus, the diameter of the inhibition zone was observed to be 39.33 and 42 mm, respectively. Moreover, increasing the number of ZnO-NPs hindered the growth of NIH/3T3 cells, but the 1.5 % ZnO-NP loaded film showed a high percentage of cell viability in 1 day (90 %) and 3 days (93 %), which is suitable for biomedical applications.

Modern methods and means for online measurement of moisture content in natural gas

Moisture-in-gas content is an important quality parameter in production, transportation and processing of both natural and associated petroleum gas. Reliable and accurate measurement of this parameter is required at all stages: from the well to gas processing plant and, further, to consumer, – and influence significantly the efficiency of technological processes. The article presents modern methods and means for online measurement of moisture content in natural gas, their advantages and disadvantages as well as the most effective applications. The article makes it possible to reasonably choose one or another online moisture-in-gas analyzer for each stage of the technological cycle: from natural gas production to processing into a sales gas and its transportation.

Effect of soil moisture content on thermal performance of ground source heat exchangers: An electromagnetism topology-based analysis

Ground source heat pump (GSHP) technology has gained significant attention as a viable solution for the heating, ventilation, and air conditioning (HVAC) of buildings. One of the factors that can impact the performance of GSHP systems is the soil moisture content. In this study, an innovative approach, referred to as soil impedance topology, is introduced as an alternative to traditional methods for measuring soil moisture content in geothermal heat pump systems. This method is inspired by pipeline grid utilizes impedance measurement, which provides a direct measurement of soil moisture content without the need for sensors. The study also proposes a changing rule of impedance with varying moisture content, where capacitance increases and resistance decreases when the soil moisture content is less than 20% but stabilizes beyond a water content of 20%. The accuracy of the topological mechanism prediction method is high, as demonstrated through the verification of the Smith circle and measured data. However, it is noted that the performance may be insufficient in the high frequency band and high soil moisture content. The use of impedance topology provides a more accurate and reliable method for measuring soil moisture content as well as for modeling and predicting heat transfer rates and system performance. This technology has strong potential to improve efficiency, reduce energy costs, and enhance the environmental sustainability of geothermal heat pump systems.