Estimation of moisture content in dry-cured beef ham by measuring the impedance of the surface.

Dry-cured beef ham quality is determined by moisture content; however, it is hard to do non-destructive monitoring. We investigated whether the internal moisture content of dry-cured beef ham could be determined from the impedance of the surface, which is removed at the time of eating. Supraspinatus muscle samples from Japanese Shorthorn steers were dried for different periods. The samples were then divided into the parts to be removed (surface) and edible parts. Their respective impedance and moisture content were measured, and the correlation between these two parameters was investigated. A negative correlation was observed between the impedance and moisture content of the surface and the shallow and deep sections of the edible part. There was also a negative correlation between the impedance of the surface and the moisture content of the shallow and deep sections of the edible part. Therefore, the results of this study indicate that during drying, the moisture content in the shallow and deep sections of dry-cured hams can be estimated by measuring the impedance of the surface. This non-destructive method of measuring the moisture content of dry-cured hams can help in regulating the moisture content during drying to produce high-quality dry-cured hams.

Visual analysis of sea buckthorn fruit moisture content based on deep image processing technology.

The effect of moisture content changes during drying processing on the appearance of sea buckthorn was studied. Using computer vision methods and various image processing methods to collect and analyze images during the drying process of sea buckthorn fruit. Sea buckthorn is dried in a drying oven at a temperature of 65 °C and Level 1 wind speed conditions. The images of the entire drying process of sea buckthorn fruit were collected at 30-min intervals. Deep mining and transformation of image information through various image processing methods. By calibrating and modeling the color components, real-time online detection of the moisture content of sea buckthorn fruit can be achieved. After modeling, this article attempted to use LSTM (Long Short Term Memory) to predict the appearance of sea buckthorn fruit with supercritical moisture content. Different agricultural products adapt to different color spaces, but after standard modeling with a certain amount of data, applying color components to detect moisture content is a very good method.

The use of image analysis to study the effect of moisture content on the physical properties of grains.

Designing machines and equipment for post-harvest operations of agricultural products requires information about their physical properties. The aim of the work was to evaluate the possibility of introducing a new approach to predict the moisture content in bean and corn seeds based on measuring their dimensions using image analysis using artificial neural networks (ANN). Experimental tests were carried out at three levels of wet basis moisture content of seeds: 9, 13 and 17%. The analysis of the results showed a direct relationship between the wet basis moisture content and the main dimensions of the seeds. Based on the statistical analysis of the seed material, it was shown that the characteristics examined have a normal or close to normal distribution, and the seed material used in the investigation is representative. Furthermore, the use of artificial neural networks to predict the wet basis moisture content of seeds based on changes in their dimensions has an efficiency of 82%. The results obtained from the method used in this work are very promising for predicting the moisture content.

Nondestructive Detection of Sunflower Seed Vigor and Moisture Content Based on Hyperspectral Imaging and Chemometrics.

Sunflower is an important crop, and the vitality and moisture content of sunflower seeds have an important influence on the sunflower's planting and yield. By employing hyperspectral technology, the spectral characteristics of sunflower seeds within the wavelength range of 384-1034 nm were carefully analyzed with the aim of achieving effective prediction of seed vitality and moisture content. Firstly, the original hyperspectral data were subjected to preprocessing techniques such as Savitzky-Golay smoothing, standard normal variable correction (SNV), and multiplicative scatter correction (MSC) to effectively reduce noise interference, ensuring the accuracy and reliability of the data. Subsequently, principal component analysis (PCA), extreme gradient boosting (XGBoost), and stacked autoencoders (SAE) were utilized to extract key feature bands, enhancing the interpretability and predictive performance of the data. During the modeling phase, random forests (RFs) and LightGBM algorithms were separately employed to construct classification models for seed vitality and prediction models for moisture content. The experimental results demonstrated that the SG-SAE-LightGBM model exhibited outstanding performance in the classification task of sunflower seed vitality, achieving an accuracy rate of 98.65%. Meanwhile, the SNV-XGBoost-LightGBM model showed remarkable achievement in moisture content prediction, with a coefficient of determination (R2) of 0.9715 and root mean square error (RMSE) of 0.8349. In conclusion, this study confirms that the fusion of hyperspectral technology and multivariate data analysis algorithms enables the accurate and rapid assessment of sunflower seed vitality and moisture content, providing robust tools and theoretical support for seed quality evaluation and agricultural production practices. Furthermore, this research not only expands the application of hyperspectral technology in unraveling the intrinsic vitality characteristics of sunflower seeds but also possesses significant theoretical and practical value.

Contamination and persistence of polycyclic aromatic hydrocarbons (PAHs) in rice grains after drying in direct-fired dryer.

The objective of this work was to study PAHs contamination in rice grains subjected to different milling types, after drying at different air temperatures in a direct-fired dryer and using firewood with different moisture contents as a heating source. In addition to verifying the persistence of these compounds after storage. Drying of rice grains was performed in a cross-flow dryer at air temperatures of 55 and 65 ºC. As heating source firewood containing different moisture contents was used. The presence of nine PAHs was detected. The drying air temperature, as well as the storage time, did not significantly influence the PAHs contamination of grains. The highest PAHs contamination was observed in grains from the brown subgroup. Grain polishing promoted a reduction in the PAH concentration. The grains subjected to parboilization showed a higher PAHs concentration. The use of firewood with higher moisture content promoted greater PAHs contamination in the grains.

Study on Characteristics of Failure and Energy Evolution of Different Moisture-Containing Soft Rocks under Cyclic Disturbance Loading.

During the coal mining process in soft rock mines with abundant water, the rock mass undergoes cyclic loading and unloading at low frequencies due to factors such as excavation. To investigate the mechanical characteristics and energy evolution laws of different water-containing rock masses under cyclic disturbance loading, a creep dynamic disturbance impact loading system was employed to conduct cyclic disturbance experiments on various water-containing soft rocks (0.00%, 1.74%, 3.48%, 5.21%, 6.95%, and 8.69%). A comparative analysis was conducted on the patterns of input energy density, elastic energy density, dissipated energy density, and damage variables of different water-containing soft rocks during the disturbance process. The results indicate that under the influence of disturbance loading, the peak strength of specimens, except for fully saturated samples, is generally increased to varying degrees. Weakness effects on the elastic modulus were observed in samples with 6.95% water content and saturated samples, while strengthening effects were observed in others. The input energy density of samples is mostly stored in the form of elastic strain energy within the samples, and different water-containing samples adapt to external loads within the first 100 cycles, with almost identical trends in energy indicators. Damage variables during the disturbance process were calculated using the maximum strain method, revealing the evolution of damage in the samples. From an energy evolution perspective, these experimental results elucidate the fatigue damage characteristics of water-containing rock masses under the influence of disturbance loading.

Design and preparation of a novel pullulan hard capsule formulation: A promising green candidate and study of crucial capsule features.

Plant-based hard capsules have gained considerable attention because of their great properties. Accordingly, designing and developing of these kinds of capsules will be a difficult task. Herein, an innovative pullulan-based hard capsule formulation was prepared for the first time. A series of characterization approaches, including Fourier transform infrared, field emission scanning electron microscope, and rheology analysis, were utilized to figure out the straightforward preparation of a designed hard capsule. Many tests and experiments were performed to achieve the optimum capsule formulation. Based on the obtained results, specifications such as uniform downfall and non-desirable adhesion, and other ideal characteristics of the capsule display the critical function. The gelling promoter of divalent cationic salts is more beneficial than its single-valent counterparts. With respect to the key role of gelling promoter, the presence of chosen MgSO4.7H2O salt and the source of selected carrageenan are important parameters to achieve optimal formulation. Moreover, field emission scanning electron microscope images illustrate that the weight ratio of 3.5 (gelling agent to salt) displays uniform surface morphology without any impurities or other foreign materials. Likewise, the outcomes of the rheology test also illustrated that the weight ratio of 3.5 is preferable. Considering the different weight ratios, the benefits of a weight ratio of 3.5 outweigh the other investigated ratios. Overall, the current research addresses substantial information about developing pullulan-based hard capsules for target usage.

Stem moisture content prediction model for Larix olgensis based on beta regression.

To investigate the longitudinal variation patterns of sapwood, heartwood, bark and stem moisture content along the trunk of artificial Larix olgensis, we constructed mixed effect models of moisture content based on beta regression by combining the effects of sampling plot and sample trees. We used two sampling schemes to calibrate the model, without limiting the relative height (Scheme Ⅰ) and with a limiting height of less than 2 m (Scheme II). The results showed that sapwood and stem moisture content increased gradually along the trunk, heartwood moisture content decreased slightly and then increased along the trunk, and bark moisture content increased along the trunk and then levelled off before increasing. Relative height, height to crown base, stand area at breast height per hectare, age, and stand dominant height were main factors driving moisture content of L. olgensis. Scheme Ⅰ showed the stable prediction accuracy when randomly sampling moisture content measurements from 2-3 discs to calibrate the model, with the mean absolute percentage error (MAPE) of up to 7.2% for stem moisture content (randomly selected 2 discs), and the MAPE of up to 7.4%, 10.5% and 10.5% for sapwood, heartwood and bark moisture content (randomly selected 3 discs), respectively. Scheme Ⅱ was appropriate when sampling moisture content measurements from discs of 1.3 and 2 m height and the MAPE of sapwood, heartwood, bark and stem moisture content reached 7.8%, 11.0%, 10.4% and 7.1%, respectively. The prediction accuracies of all mixed effect beta regression models were better than the base model. The two-level mixed effect beta regression models, considering both plot effect and tree effect, would be suitable for predicting moisture content of each part of L. olgensis well.

[Application of microwave vacuum drying with process management in extract drying of personalized traditional Chinese medicine preparations].

Extracts are important intermediates in the production of traditional Chinese medicines preparations. The drying effect of extracts will directly affect the subsequent production process and the quality of the preparation. To meet the requirements of high drug loading, short time consumption, and simple production process of personalized traditional Chinese medicine preparations, this study explored the application of multi-program microwave vacuum drying process in the extract drying of personalized traditional Chinese medicine preparations. The influencing factors of microwave vacuum drying process were investigated for 5 excipients and 40 prescriptions. Taking the feasibility of drying, drying rate, drying time, and dried extract status as indicators, this study investigated the feeding requirements of microwave vacuum drying. With the dried extract status as the evaluation indicator, the three drying programs(A, B, and C) were compared to obtain the optimal drying condition. The experimental results showed that the optimal feeding conditions for microwave vacuum drying were material layer thickness of 2 cm and C program(a total of 7 drying processes), which solved the problem of easy scorching in microwave drying with process management. Furthermore, the preset moisture content of the dried extract in microwave drying should be 4%-5%, so that the dried extract of traditional Chinese medicine preparation had uniform quality, complete drying, and no scorching. This study lays a foundation for the application of microwave drying in the production of traditional Chinese medicine preparations, promoting the high-quality development of personalized traditional Chinese medicine preparations.

Biodrying of municipal solid waste-correlations between moisture content, organic content, and end of the biodrying process time.

Biodrying refers to the decomposition of organic municipal solid waste (MSW) under aerobic conditions. This process usually lasts 14 days and requires large amounts of air to be injected into the waste matrix. The efficiency of the biodrying process depends on several geotechnical parameters, including initial moisture content, initial organic content, bulk density, dry density, solid particle density, and porosity. To examine the potential influence of these parameters on the biodrying process, we analyzed 13 biodried MSW samples. The results revealed a strong positive linear relationship between the initial moisture content and the mass loss percentage. In the first three days of the biodrying process, the waste mass rapidly decreased; afterwards, the daily mass loss occurred at a less rapid, more constant rate. The established average mass removal ratio between the volatile solids and water was 1:6.38 with a standard deviation of 1.06. Dry and solid particle densities were preserved in all 13 experiments; thus, the corresponding void ratio remained unchanged. This finding suggests that the settlement and degradation of MSW that occur during the biodrying process did not significantly influence the airflow rate.

Moisture content online detection system based on multi-sensor fusion and convolutional neural network.

To monitor the moisture content of agricultural products in the drying process in real time, this study applied a model combining multi-sensor fusion and convolutional neural network (CNN) to moisture content online detection. This study built a multi-sensor data acquisition platform and established a CNN prediction model with the raw monitoring data of load sensor, air velocity sensor, temperature sensor, and the tray position as input and the weight of the material as output. The model's predictive performance was compared with that of the linear partial least squares regression (PLSR) and nonlinear support vector machine (SVM) models. A moisture content online detection system was established based on this model. Results of the model performance comparison showed that the CNN prediction model had the optimal prediction effect, with the determination coefficient (R2) and root mean square error (RMSE) of 0.9989 and 6.9, respectively, which were significantly better than those of the other two models. Results of validation experiments showed that the detection system met the requirements of moisture content online detection in the drying process of agricultural products. The R2 and RMSE were 0.9901 and 1.47, respectively, indicating the good performance of the model combining multi-sensor fusion and CNN in moisture content online detection for agricultural products in the drying process. The moisture content online detection system established in this study is of great significance for researching new drying processes and realizing the intelligent development of drying equipment. It also provides a reference for online detection of other indexes in the drying process of agricultural products.

Thermo-Hydric Study of Wood-Based Materials under Thermal Comfort Conditions.

This paper tackles the issue of moisture variation in wood-based materials, explicitly focusing on melamine-coated particleboard (hereafter referred to as melamine) and medium-density fiberboard (MDF) used in the third phase of wood industry transformation. The approach involves a comprehensive strategy for predicting moisture content variation, incorporating numerical simulation, experimental testing, and the application of artificial neural network (ANN) technology to enhance accuracy in furniture manufacturing. The developed ANN models are tailored to predict moisture content changes under specific thermal comfort conditions. Remarkably, these models demonstrate high precision, with an average error margin of only 1.40% for 8% moisture content (MC) and 2.85% for 12% MC in melamine, as well as 1.42% for 8% MC and 2.25% for 12% MC in MDF. These levels of precision surpass traditional models, emphasizing this study's novelty and practical relevance to the industrial context. The findings indicate that ANN models adapt to diverse environmental conditions, presenting a robust tool for optimizing moisture management in wood-based materials. This research contributes valuable insights for improving the reliability and efficiency of moisture content predictions in the wood industry.

Rapid and Non-Destructive Prediction of Moisture Content in Maize Seeds Using Hyperspectral Imaging.

The moisture content of corn seeds is a crucial indicator for evaluating seed quality and is also a fundamental aspect of grain testing. In this experiment, 80 corn samples of various varieties were selected and their moisture content was determined using the direct drying method. The hyperspectral imaging system was employed to capture the spectral images of corn seeds within the wavelength range of 1100-2498 nm. By utilizing seven preprocessing techniques, including moving average, S-G smoothing, baseline, normalization, SNV, MSC, and detrending, we preprocessed the spectral data and then established a PLSR model for comparison. The results show that the model established using the normalization preprocessing method has the best prediction performance. To remove spectral redundancy and simplify the prediction model, we utilized SPA, CASR, and UVE algorithms to extract feature wavelengths. Based on three algorithms (PLSR, PCR, and SVM), we constructed 12 predictive models. Upon evaluating these models, it was determined that the normalization-SPA-PLSR algorithm produced the most accurate prediction. This model boasts high RC2 and RP2 values of 0.9917 and 0.9914, respectively, along with low RMSEP and RMSECV values of 0.0343 and 0.0257, respectively, indicating its exceptional stability and predictive capabilities. This suggests that the model can precisely estimate the moisture content of maize seeds. The results showed that hyperspectral imaging technology provides technical support for rapid and non-destructive prediction of corn seed moisture content and new methods in seed quality evaluation.

Quality changes in Chinese high-quality indica rice under different storage temperatures with varying initial moisture contents.

The planting area of high-quality indica rice varieties has been growing rapidly in China. However, the storage characteristics of these varieties remains unclear. In this research, different moisture contents (13.5, 14.5, and 15.5%) of high-quality rice (variety Xiadao No.1) were stored at different temperatures (15, 20, 25, and 30°C) for 360 d, and then evaluated for lipid metabolism, redox enzyme activities, fatty acid composition, and sensory attributes. With the prolongation of storage, rice displayed an upward trend in fatty acid value, malondialdehyde content, and cooked rice hardness and a downward trend in contents of total fat and non-starch lipid, peroxidase and catalase activities, and sensory score of cooked rice. The change trends of these quality parameters were aggravated by elevating storage temperature and moisture content. Linoleic acid content of rice generally decreased with prolonged storage. After 300 d of storage, rice with initial moisture content of 13.5% at 30°C showed a fatty acid value of higher than 30 mg KOH/100 g, while rice of other two initial moisture contents reached similar level at 25°C. After the whole storage period, only rice with initial moisture contents of 13.5 and 14.5% stored at 15°C had a sensory score of higher than 60. These results suggested that the aging process of high-quality rice can be inhibited by decreasing the storage temperature and initial moisture content. These results can provide reference for grain storage enterprises to select proper storage condition to store high-quality rice.

Effect of initial moisture content, resulting from different ratios of vegetable waste to maize straw, on compost was mediated by composting temperatures and microbial communities at low temperatures.

Owing to the huge amounts and perishable character of vegetable wastes, composting is one of the best options for recycling vegetable wastes post-harvest. The initial moisture content (MC) is critical for optimizing composting process, but the effect of high MC in undehydrated vegetable wastes on composting was rarely reported. For this, the plant-scale windrows were prepared by mixing cauliflower waste and maize straw at different ratios to control initial MC of 70 % (T1-70) and 80 % (T2-80), respectively, and composted in winter. As composting progressed, substantial organic matter degradation, progressive humification, decreases in electrical conductivity and increases of pH and germination index (GI) were observed in both treatments. Nonetheless, T1-70 accelerated heating rate early during composting, prolonged high temperature period (>50 °C) by 30 d, thus increased the harmless level of composting, and significantly improved the humification of end-products compared to T2-80. Results also revealed that T1-70 activated more indigenous microbes and enhanced microbial interactions early during composting, with the fungi enriched in T1-70 playing an important role in accelerating the composting process. Remarkably, the difference in composting temperatures, humification degree, and microbial communities between the two treatments was most significant during the maturation phase. In this phase, MWH_CFBk5, Planktosalinus, Pseudopedobacter, and Luteimonas enriched in T1-70 were positively correlated with humification indices. It is suggested that the effect of initial MC, resulting from different ratios of vegetable waste to maize straw, on their composting was mediated by the composting temperature and microbial communities at low temperatures.

Prediction of moisture content for a single maize kernel based on viscoelastic properties.

BACKGROUND: The rapid and accurate detection of moisture content is important to ensure maize quality. However, existing technologies for rapidly detecting moisture content often suffer from the use of costly equipment, stringent environmental requirements, or limited accuracy. This study proposes a simple and effective method for detecting the moisture content of single maize kernels based on viscoelastic properties. RESULTS: Two types of viscoelastic experiments were conducted involving three different parameters: relaxation tests (initial loads: 60, 80, 100 N) and frequency-sweep tests (frequencies: 0.6, 0.8, 1 Hz). These experiments generated corresponding force-time graphs and viscoelastic parameters were extracted based on the four-element Maxwell model. Then, viscoelastic parameters and data of force-time graphs were employed as input variables to explore the relationships with moisture content separately. The impact of different preprocessing methods and feature time variables on model accuracy was explored based on force-time graphs. The results indicate that models utilizing the force-time data were more accurate than those utilizing viscoelastic parameters. The best model was established by partial least squares regression based on S-G smoothing data from relaxation tests conducted with initial force of 100 N. The correlation coefficient and the root mean square error of the calibration set were 0.954 and 0.021, respectively. The corresponding values of the prediction set were 0.905 and 0.029, respectively. CONCLUSIONS: This study confirms the potential for accurate and fast detection of moisture content in single maize kernels using viscoelastic properties, which provides a novel approach for the detection of various components in cereals. © 2024 Society of Chemical Industry.

The effect of moisture content over the fibre saturation points on the impact strength of wood.

The article's main aim is to assess the mechanical behaviour of linden under high-rate loadings (impact) and its change due to changes in moisture content (MC) over fibre saturation point. For assessing the mechanical properties of green wood, mainly the data of the dried wood is not applicable since the moisture content can drastically affect the mechanical properties of the wood. By testing both dried and high-moisture-content wood, we can understand a general viewpoint toward the effect of the moisture content on the impact behaviour of the wood. Several test samples were made of linden wood with different moisture content levels of 11%, 60% and 160%. A drop-weight impact machine tested the specimens to measure the reaction force of the hammer during a very short impact period. The results of the tests were parameters such as force-time chart, the maximum force required for crack initiation, the impact bending strength (IBS) and the work needed for crack initiation. The results indicated an increase in MC decreases the maximum force, work required for crack initiation and IBS drastically. However, when MC exceeded the fibre saturation point (FSP), there was no further influence on the force pattern and maximum required force.

Quality of eucalyptus wood chips for bioenergy as a function of drying time and horizontal chipper settings.

The increase in the use of energy from forest biomass has increased the demand for knowledge about tree-chipping operations. Therefore, this study aimed to evaluate the effect of different drying times of wood logs and various combinations of knife and anvil configurations in the horizontal chipper on the quality of Eucalyptus dunnii chips produced for energy purposes. The study was conducted in a seven-year-old stand of E. dunnii. A horizontal chipper was used to chip whole trees and obtain nine types of chips, resulting from the interaction between the three drying times of the trees and three configurations of the horizontal chipper. The chips were characterized, followed by an evaluation of energy quality for comparison between the treatments. Among the outcomes discerned, it became evident that the employed wood exhibited a Basic Density (0.506 g.cm-³). The chip dimensions and bulk density presented notable disparities owing to the distinct chipper configurations and tree drying time. The extended drying period (150 days) conferred a lower average moisture content (34.20%) to the study materials. Moreover, the ash content was lower in the treatment with 150 drying days (0.52%). Both the useful calorific value and the Fuel Value Index were also greater in the treatment (150 drying days), measuring 2600.00 kcal kg-1 and 128.06 cal cm-3, respectively. In the analysis of the Fuel Value Index concerning chipper configurations, it was observed that for chips featuring a granulometry of 25 mm, the treatment involving 150 days of drying, four knives, and one shim proved the most efficient (Q = 0.979). Conversely, for chips with a granulometry of 16 mm, the treatment involving 150 days of drying, eight knives, and one shim emerged as the most efficient (Q = 0.970). Consequently, the proposed index is efficacious and underscores the necessity of adapting knife settings in response to moisture content changes to maintain the desired granulometry and apparent density standards.

Numerical Study on Effect of Aggregate Moisture on Mixing Process.

During the concrete mixing process, the transition of aggregates from a dry to a moist state introduces a crucial dynamic that significantly influences particle interaction, consequently impacting mixing homogeneity. In this paper, based on the discrete element method, the effect of aggregate moisture on the mixing process of sand and stone was investigated. The interaction between dry particles was described by the Hertz-Mindlin model, while the interaction between wet particles was calculated by the linear cohesion model considering the liquid bridge force. Additionally, a functional relationship between the moisture content and the parameters of the linear cohesive contact model was established. The results show that the numerical method can be employed to simulate the mixing process. Notably, when the moisture content of pebbles ranges from 0% to 0.75% and that of sand ranges from 0% to 10.9%, the linear cohesion model is deemed suitable. The standard deviation of the mixing homogeneity of wet particles is lower than that of dry particles for short mixing time, indicating that a small amount of liquid enhances mixing homogeneity. However, moisture has no obvious effect on mixing homogeneity for a long mixing time. This nuanced understanding of the interplay between moisture, particle interactions, and mixing duration contributes valuable insights to optimize concrete mixing processes.

The maturity, humus content, and microbial metabolic function of sheep manure compost on the Qinghai-Tibet Plateau can be significantly improved by reducing the moisture content.

The Qinghai-Tibet Plateau (QTP) is characterized by an extreme hypoxia, which may lead to lack of sufficient oxygen for compost production, and thus seriously affecting the compost quality. The moisture content (MC) has a direct effect on the oxygen content of composting pile. At present, the research on the optimum moisture content of compost production on the QTP is still lacking. This study aimed to investigate the influences of MC on fermentation quality of sheep manure composting on the QTP and to further analyze the changes of microbial metabolic function and enzyme activity under different MC. Composting experiment with low MC (45%) and conventional MC (60%) was conducted in both summer and autumn. The results showed that the composting efficiency of 45% MC was better than 60% in both seasons, which was mainly manifested as longer high-temperature period (summer:16 d vs 14 d, autumn: 7 d vs 2 d), higher germination index (summer:136.1% vs 128.6%, autumn:103.5% vs 81.2%), and more humus synthesis (summer:159.8 g/kg vs 151.2 g/kg, autumn:136.1 k/kg vs 115.5 k/kg). The 45% MC can improve microbial metabolism, including increasing the abundance of functional genes involved in carbohydrate metabolism, amino acid metabolism, and nucleotide metabolism and improving the activities of cellulase, ß-glucosidase, protease, polyphenol oxidase, and peroxidase. In conclusion, 45% MC can improve the fermentation efficiency and products quality of sheep manure compost on QTP.