Development and performance evaluation of a livestock feed chopper/pulverizer

Crop residues are bulky and low in nutrients. Their size reduction is imperative in order to compound them with other feed ingredients to achieve balanced feedstock for livestock. A chopping and pulverizing machine was designed and constructed to chop and pulverized feed materials. It comprises of chopping hopper, pulverizing hopper, metering device, chopping/ pulverizing chamber, screen and the processed feed outlet. The performance of the machine was evaluated on the basis of throughput capacity, pulverizing efficiency, scatter losses as dependent variables while moisture content was the independent variable. There were two level of speeds (1500 rpm and 2100 rpm) and five levels of moisture content (13 %, 16 %, 19 %, 21 %, 24 %, and 27 % dry basis). The throughput capacity, pulverizing efficiency had highest values of 222 kg/h and of 92.5 % respectively at moisture content level of 13 % (db) and 2100 rpm speed. However, the least scatter losses obtained was 2.5 % at moisture content level of 27 % (db) and 1500 rpm speed. As the moisture content increased, throughput capacity, pulverizing efficiency and scatter losses decreases at both speeds. The developed machine could enhance the use of crop residues in feeding livestock which could ultimately reduce the cost of livestock feed production.

ALTERNATIVES OF DOMESTIC WASTEWATER SLUDGE DRYING PROCESSES FOR ENERGY RECOVERY : A REVIEW

As communities grow, cities need to increase their capacity to collect and treat domestic wastewater. The need of larger domestic wastewater treatment plants and proper disposal of its solid waste has attracted the scientific community to research about new technologies that will use those systems and waste as a way to generate energy. The moisture content of a fuel effects the combustion products and the energy released by the reaction. Therefore, in order to make biomass to be a viable fuel option, the technological and scientific challenges of the drying process of wastewater sludge must be faced and overcome so the lowest moisture content level is achieved. Conventional drying processes as for example, direct and indirect thermal drying, are commonly used. However, other processes using renewable energy as for example solar drying are also being studied by the scientist around the world. Moisture content, physical-chemical properties as for example, heating values, composition, ash fusibility are all relevant properties taken into consideration when choosing a fuel for a specific application. The herein review is intended to present some existing domestic wastewater drying processes, alternative ways of improving the efficiency of those processes.

Fuelwood Characteristics of Five Species Grown in Merauke Forest

Papua has a large area of production forests, such as in Merauke. These forests provide great benefits for the pulp and wooden industries, which generate a large amount of biomass waste. Therefore, this study aimed to investigate the proximate analysis, specific gravity, calorific value, and Fuelwood Value Index (FVI) of wood and bark of five species, namely Acacia mangium Willd, Acacia crassicarpa A. Cunn, Eucalyptus pellita F. Muell, Melaleuca viridiflora Sol. Ex Gaertn, and Lophostemon suaveolens Sol. Ex Gaertn. The calorific value ranged from 4,066 to 5,435 cal/g, while the FVI values ranged from 4.04 to 76.41. The highest calorific value was observed in the bark of Melaleuca viridiflora, while the highest fuelwood value index was observed in Eucalyptus pellita wood. Furthermore, the calorific value of wood was higher compared to the bark in all species. There was no significant correlation between specific gravity, calorific or FVI value. It is noticed that a strong correlation (r = -0.92*) was observed between the calorific value and volatile matter in the bark. Based on the proximate analysis results, only the moisture content level was significantly correlated with the calorific value of wood or bark.

Intelligent Control in the Application of a Rotary Dryer for Reduction in the Over-Drying of Cut Tobacco

The drying process is fundamental for cut tobacco processing. However, there are some problems related to the drying process such as overheating, or inconsistent control of moisture content. This paper shows how an intelligent controller is designed for an industrial rotary drying system. This controller is applied to a tobacco production unit to reduce overdried cut tobacco and improve the overall unit performance. The proposed control system aims to keep the content of moisture at the dryer outlet as close as possible to the optimal value and improve the homogeneity of the product without any operator intervention. The study shows that, if a reduction of humidity in the cut tobacco drying process is achieved using AI, the quality of the final product improves. In particular, if compared to regulatory control, the proposed method constantly monitors and adjusts the moisture content level in order to reduce the amount of overdried product. The findings of this paper indicate that the suggested process can save at least 222.2 kg of cut tobacco for each batch in the first stage of the drying process.

Discrete Element Modelling of Soil Compaction of a Press-Wheel

Press-wheels are wheels designed to compact the soil above seeds in the “seed cover” region. Soil compaction, produced by the press-wheels of seeders, affects seedling emergence and early plant growth. The Discrete Element Method (DEM) was used to model the amount of soil compaction from a press-wheel with varying down forces. The model was used to predict sinkage and rolling resistance of the press-wheel. The model results were validated with data from soil bin tests of the press-wheel in a sandy loam soil under varying soil moisture content levels (low, medium, and high). The sinkage results from the soil bin tests were 27.7, 26.7, and 25.2 mm for the low, medium, and high soil moisture content levels, respectively. The corresponding rolling resistances obtained from the tests were 104.4, 89.9, and 113.6 N. The press-wheel model adequately predicted the sinkage and rolling resistance for each soil moisture content level with overall Relative Mean Errors (RME) ranging from 13 to 23%. Additional simulation results show that average peak soil stresses across the three soil moisture contents at a depth of 0.12 m were 22,466.7, 8700.0, and 6900.0 Pa for vertical, horizontal, and lateral directions, respectively. The results enhance the understanding of the dynamics of the soil–press-wheel interaction and provided useful information for seeder press-wheel design.

RF-Based Moisture Content Determination in Rice Using Machine Learning Techniques

Seasonal crops require reliable storage conditions to protect the yield once harvested. For long term storage, controlling the moisture content level in grains is challenging because existing moisture measuring techniques are time-consuming and laborious as measurements are carried out manually. The measurements are carried out using a sample and moisture may be unevenly distributed inside the silo/bin. Numerous studies have been conducted to measure the moisture content in grains utilising dielectric properties. To the best of authors’ knowledge, the utilisation of low-cost wireless technology operating in the 2.4 GHz and 915 MHz ISM bands such as Wireless Sensor Network (WSN) and Radio Frequency Identification (RFID) have not been widely investigated. This study focuses on the characterisation of 2.4 GHz Radio Frequency (RF) transceivers using ZigBee Standard and 868 to 915 MHz UHF RFID transceiver for moisture content classification and prediction using Artificial Neural Network (ANN) models. The Received Signal Strength Indicator (RSSI) from the wireless transceivers is used for moisture content prediction in rice. Four samples (2 kg of rice each) were conditioned to 10%, 15%, 20%, and 25% moisture contents. The RSSI from both systems were obtained and processed. The processed data is used as input to different ANNs models such as Support Vector Machine (SVM), K-Nearest Neighbour (KNN), Random Forest, and Multi-layer Perceptron (MLP). The results show that the Random Forest method with one input feature (RSSI_WSN) provides the highest accuracy of 87% compared to the other four models. All models show more than 98% accuracy when two input features (RSSI_WSN and RSSI_TAG2) are used. Hence, Random Forest is a reliable model that can be used to predict the moisture content level in rice as it gives a high accuracy even when only one input feature is used.

Understanding wet tear strength at varying moisture content in handsheets

A laboratory study was conducted looking at the effects of moisture content on wet tear strength in handsheets. Three different wetting techniques were used to generate the wet tear (Elmendorf-type) data at varying moisture levels, from TAPPI standard conditions (dry) to over 60% moisture content (saturated). Unbleached hard-wood and softwood fiber from full-scale kraft pulp production were used. The softwood fiber was refined using a Valley beater to reduce freeness. Handsheets were made with a blend of hardwood and softwood and with refined softwood, without the addition of wet-end chemistry. The resulting grams-force tear data obtained from the test was indexed with basis weight and plotted versus both moisture content and dryness. As moisture content levels in the handsheets increased, the wet tear strength also increased, reaching a critical maximum point. This marked a transition point on the graph where, beyond a critical moisture content level, the tear strength began to decline linearly as moisture increased. This pattern was repeated in handsheets made from a blend of hardwood and softwood and from 100% refined softwood.

Possibilities of Decreasing Hygroscopicity of Resonance Wood Used in Piano Soundboards Using Thermal Treatment

This article presents the possibilities of decreasing moisture sorption properties via thermal modification of Norway spruce wood in musical instruments. The 202 resonance wood specimens that were used to produce piano soundboards have been conditioned and divided into three density groups. The first specimen group had natural untreated properties, the second was thermally treated at 180 °C, and the third group was treated at 200 °C. All specimens were isothermally conditioned at 20 °C with relative humidity values of 40, 60, and 80%. The equilibrium moisture content (EMC), swelling, and acoustical properties, such as the longitudinal dynamic modulus (E’L), bending dynamic modulus (Eb), damping coefficient (tan δ), acoustic conversion efficiency (ACEL), and relative acoustic conversion efficiency (RACEL) were evaluated on every moisture content level. Treatment at 180 °C caused the EMC to decrease by 36% and the volume swelling to decrease by 9.9%. Treatment at 200 °C decreased the EMC by 42% and the swelling by 39.6%. The 180 °C treatment decreased the value of the longitudinal sound velocity by 1.6%, whereas the treatment at 200 °C increased the velocity by 2.1%. The acoustical properties EL′, Eb, ACEL, and RACEL were lower due to the higher moisture content of the samples, and only the tanδ increased. Although both treatments significantly affected the swelling and EMC, the treatment at 180 °C did not significantly affect the acoustical properties.

Improving The Physical Properties of Young Teak Wood Through Phenol Formaldehyde Compregnation

Young teak wood exhibits inferior properties due to a high proportion of juvenile wood and sapwood. The modification through compregnation of phenol formaldehyde is required to improve wood qualities. Therefore, this study aimed to observe the possibility of improving the physical properties of young teak wood (15 years) using phenol formaldehyde compregnation at various concentrations (5%, 10%, 15%) and pressing times (15, 30, 60 minutes). The results showed that phenol formaldehyde concentration produced retention with a maximum value of 31.19 kg/m3. Based on wood without treatment (controls), the compregnation significantly increased the redness (a*) level by 45.57% and the specific gravity by 7.93%. The decreasing levels after treatment were observed in the brightness (L*) (by 36.56%), the yellowness (b*) (by 38.40%), and air-dried moisture contents by (by 5.44%). Furthermore, the reduction in hygroscopicity was observed in an equilibrium moisture content level in various relative humidity, as well as in increasing the stability dimension, though in a small magnitude.

EFFECT OF BEAN FLOUR ON THE CHEMICAL COMPOSITION, VITAMIN, MINERAL LEVEL AND ORGANOLEPTIC PROPERTIES OF MEAT ROLL

This study was carried out to evaluate the effect of bean flour on the nutritional value and the yield stress of meat rolls. The main components of meat rolls are minced beef, eggs, bread, milk, and beans, but in the current study, the author mixed bean flour with these active ingredients and evaluated the effect of this on the various nutrient parameters of meat rolls. Four samples of meat rolls were prepared, with 0% to 20% beans flour. Results of the study found that depending on the concentration of beans, the moisture content, level of carbohydrate, and other nutritive parameters of meat roll have changed significantly due to the specific chemical composition of the bean flour. In terms of vitamin composition, significant changes are observed in the content of vitamin C and vitamin B1. The addition of bean flour (up to 15%) to minced rolls gradually increases the yield stress and improving the consistency of the product. According to organoleptic evaluation, the addition of up to 15% of beans has a positive effect on the consistency of the product due to improved water-binding ability. Results of the study suggesting new data related to the impact of bean flour on the nutritional value and consistency of meat rolls. The developed technology and recipe can be used for large scale meat rolls production.