Peanut Drying Research Articles

Performance Evaluation of a Hot-Air Groundnut Cabinet Dryer

Groundnut, also known as peanut, is an important source of food and oil, with the seeds being high in protein, fibre, and healthy unsaturated fats which are consumed in large quantities in most parts of the sub-Saharan Africa and the world at large. The post-harvest processing of peanut, most-especially drying that involves dehydrating the crop to safe moisture content for home and commercial purposes still need more attention as local drying prevailed in the country. An existing hot-air cabinet dryer was improved and evaluated for the drying of peanuts under the humid rainforest climate of Akure, Nigeria. The dryer was tested using three varieties of groundnut (red, white and kampala varieties), three drying air temperatures of 400C, 500C and 600C, two drying air velocities of 1.67 m/s and 2.78 m/s and two product loadings of 3 kg and 4.5 kg per batch. The thermal efficiency, drying rate, drying time and moisture loss were determined as the evaluation parameters of the dryer. The evaluation conducted revealed thermal efficiency range of 46% – 96% with average thermal efficiency of 71.31%. The drying rate of the dryer ranges from 0.36 kg/h – 0.21 kg/h, with an average drying rate of 0.28 kg/h at maximum and minimum drying time of 10 h and 6 h respectively. The moisture loss by the groundnut in the dryer ranges from higher value to lower value of 1.05 kg to 0.55 kg for the red variety; 5.4 kg to 1.01 kg for the white variety; and 1.02 kg to 0.55 kg for the kampala variety respectively. Results further revealed that the drying air temperature has the greatest effect on the thermal efficiency, drying rate, drying time and moisture loss as compared with the drying air velocity. It was further discovered that the drying rates of the three varieties were relatively equal. However, the drying rates were in the order: white > kampala > red variety. It can be concluded that the hot-air dryer handled the drying of the three varieties of groundnut optimally with higher performances and in conformity to standard practices.

Peanut Dryer Noise Levels with and without Muffler

Harvested peanuts must be dried before being stored to prevent spoilage. Peanuts are dried using forced heated air dryers that produce a great deal of noise while operating. In an effort to abate dryer noise, a cylindrical muffler was designed, fabricated from sheet metal, and tested. The muffler was 1.17 m in diameter, 0.61 m in length and was lined with 0.55 m of R 30 fiberglass batting. Five configurations of the muffler were tested and the most effective was the two inline mufflers attached to the air intake of the dryer. The two inline mufflers were found to reduce noise 4.5m in front of the dryer air intake to the OSHA permissible level of 90 dBA for an eight-hour time period. The inline lined mufflers reduced noise levels at 4.5 m from the side of the dryer to just less than 85 dBA the level above which OSHA recommends employers initiate hearing conservation programs. Sound levels at 23 m in front of the dryer air intake were reduced to 69 dBA which is equivalent to classroom chatter. Though the muffler designed in the study reduced dyer noise to acceptable levels, study results and new technologies suggest that further noise reduction is possible by redesigning the muffler using natural harmonics of the dryer/muffler structure, new tuned noise damping materials, and designing for sound resonance effects.

Comparison of barrel-shaped fixed bed drying for different ventilation methods by mathematic simulation

Unsteady one-dimensional partial differential equations for heat and mass transfer in peanut drying are used in mathematical simulations to compare the drying performance of a barrel-shaped bed in three ventilation modes: bottom up, inside out and outside in. Results obtained using the finite difference scheme show that the mathematical simulation reliably predicts the drying process of peanuts, and that the drying delay of bottom-up ventilation is the most significant at the beginning of drying. This is because the drying enhancement afforded by the high average velocity of air along the ventilation direction is insufficient to offset the drying delay caused by the large ventilation thickness compared with that afforded by the inside-out and outside-in ventilation. Furthermore, as the air volume flow increases, the time consumption and moisture content difference decrease, whereas the productivity, energy consumption, and uniformity increase for all three ventilation modes, consistent with the classical ventilation drying law. Under the same air volume flow, the time and energy consumptions for the bottom-up ventilation are the lowest, followed by those for the outside-in and inside-out ventilation. The productivity afforded by the bottom-up ventilation is the highest, followed by that by the outside-in and inside-out ventilation. The outside-in ventilation indicates the least moisture content difference and the best drying uniformity. Meanwhile, the inside-out ventilation indicates the most significant moisture content difference and the worst drying uniformity.

Performance assessment of a heat pump assisted rotary desiccant dryer for low temperature peanut drying

This study presents the investigation of a drying system in which both a desiccant wheel and a heat pump could be used together for low temperature agricultural food product drying. In the system, it was aimed to reduce the moisture content of the drying air to very low levels by using two dehumidification processes together, thus drying the product in a shorter time at low temperature. A model was formed to analyze the system according to different parameters. Peanuts, which are not suitable for high-temperature drying, were selected as the drying product. It has been observed that the system proposed in this study (System I) has a higher performance compared to other desiccant/heat pump drying systems with different configurations (System II-IV). The drying performance index (COP D ) increases by 23% in System I compared to System II, while specific energy consumption (SEC) decreases by 19%. In the case of drying air with low humidity (at 5.22 g w kg da −1 ), the drying performance parameters improve as drying time decreases, although the power consumed by the compressor increases. From the analysis, it has been determined that the optimum rotational speed of the solid desiccant wheel, which is one of the basic elements of the system, is 10 RPH under conditions considered in this study. The results show that COP D decreases as the SEC increases during the drying process, which is because the food product tends to dry at a decreasing rate. The proposed system is suitable for use in low-temperature food drying applications. • Investigation of a hybrid drying system for low temperature drying. • Determination of optimum desiccant wheel rotational speed. • The humidity of the drying air has a significant effect on the system performance. • The proposed system is suitable for low temperature drying applications. • ANN models of the desiccant wheel can be used in different system analyzes.

Energetic and exergetic performances during drying of freshly harvested peanut with industrial mixed-flow dryer

Rapid drying of peanut is very important to maintain quality and reduce the risk of mildew, especially for peanut harvested in high moisture content in China. The modified mixed-flow dryer can dry freshly harvested peanut efficiently and evenly which is not available for traditional fixed-bed drying. However, the performances of energy and exergy of peanut drying using modified mixed-flow dryer are not clear, lacking of relevant data for equipment improvement and process formulation. Therefore the relevant investigation was carried out to evaluate the performance of fresh harvested peanut drying using industrial mixed-flow dryer with heat-pump full power heating and waste heat recovery The results show that the energy consumption is mainly consumed by heat-pump and centrifugal fan, accounting for 73.5% and 24.2% of all energy consumed respectively. The overall specific energy consumption and specific heat consumption are 1494.5 kJ/kg and 4706.1 kJ/kg respectively. The thermal efficiency and the energy efficiency are affected by the change of the temperature of airflow entering the drying chamber, both fluctuate over time, increase earlier then decrease later and rise again until the material temperature reach to a relatively steady temperature. And the energy efficiency of dryer (178.9%) is approximately triple of thermal efficiencies of drying chamber (56.1%) and dryer (59.4%) for the overall drying. The heat utilization ratio decreases gradually over drying time, with the overall value of 50.0% for drying chamber and 52.9% for dryer. The exergy efficiency of drying process earlier increases then decreases in the overall trend with the overall value of 51.3%. The exergy efficiencies of the drying chamber and whole dryer are both increased gradually with the overall value of 34.5% and 31.8% respectively. However, the variation tendencies of energy improvement potential rates are opposite to exergy efficiencies.

Experimental study of solar drying of multi‐layer peanuts and development of drying model

An experimental study is performed on a natural convection solar dryer on Indian peanuts for multi-layer drying behavior. The solar air dryer developed and employed in this study has parallel flow, single pass with a flat surface design. It has an orientation system to enhance energy gain of the heated air. The present study was aimed to obtain drying characteristics of multi-layer peanuts and thereby developing an empirical model for moisture ratio prediction. It was observed that the thermal efficiency of the dryer decreases over consecutive days of drying while specific energy consumption increases. The effective moisture diffusivity of 6.3927 m2/s × 10−10 m2/s and 2.9225 m2/s × 10−10 m2/s for the thin layer and four-layer peanuts, respectively, was obtained indicating a decrease with multi-layer. Experimental results showed very good agreement with Midilli and Kucuk model for thin layer drying. A new drying model has been proposed for the prediction of drying characteristics of multi-layer peanuts (shelled peanuts), and the same is validated with the experimental findings. Novelty impact statement Drying peanuts in a natural convection solar dryer is one of the simplest processes available to farmers and domestic users. Peanuts have a high content of oil, protein, and nutrients content and is used all over the world throughout the year. During drying of peanuts, the moisture content is reduced to ensure safe moisture content, resulting in a less postharvest loss. The quality of dried peanuts is of great importance to ensure a long shelf life. The purpose of this article was to reduce the drying time in natural convection solar dryer by using the multi-layer drying concept and providing a proposed model for optimum drying. The finding of this study will be useful in reducing drying time, improving product quality, and avoiding product degradation. The obtained results also provide a practical alternative to the existing conventional drying system that is used in the field for postharvest thermal treatment of peanuts.

Peanut drying: Effects of various drying methods on drying kinetic models, physicochemical properties, germination characteristics, and microstructure

The current work aims to explore the suitable drying technique for peanut pods which can be used for seeds or edible peanuts. Four drying methods, namely naturally-open sun drying as the control check (CK), hot air drying (HAD), pulsed vacuum drying (PVD), and radio frequency combined hot air drying (RF-HAD), were employed to dry peanut pods, and their effects on the nutritional quality attributes in terms of protein, fat, fatty acid contents, etc., germination characteristics, microstructure, color, texture, acid value and peroxide value of peanuts were explored. Mathematical models of peanuts drying with four drying methods were also established. According to the statistical parameters including the determination coefficient (R2)、root mean square error (RMSE) and chi-square value (χ2), the Weibull model was best for predicting the moisture ratio change kinetics of peanuts during its four drying processes. There were significant differences in physicochemical indexes of peanut by different drying methods (p < 0.05). Fat and oleic acid contents under RF-HAD were significantly higher than those by the other three drying methods. Compared with the naturally-open sun drying, RF–HAD reduced drying time by 76.70% and the microstructure of RF-HAD peanuts produced larger and more cavities. The RF-HAD kept better comprehensive nutritional quality, but the germination rate was reduced by 27.80%. PVD could maintain good nutritional quality and germination rate among these mechanical drying technologies. However, PVD had a longer drying time of 9.5 h than RF-HAD and HAD, and the microstructure of pulsed vacuum dried peanuts showed dense structure and less cavity. Hot air-dried peanut kernel held the highest protein (28.75%), fatty acids contents (26.11%) and germination rate (88.00%). However, peanut kernel dried by HAD showed poor qualities, such as high acid value, peroxide value and large color changes. These findings indicated RF-HAD was a promising drying technique for edible peanuts regarding the higher drying rate and better–quality preservation, while HAD was suitable for peanut seeds drying as it could well protect the germination rate.

Hopper Bottom Semi-Trailer Modified for In-Shell Peanut Drying: Design, Fabrication, and Performance Testing

HighlightsComputational fluid dynamics modeling of airflow through the peanut load improved the design process.Peanuts dried using the modified hopper bottom semi-trailer passed inspection at 9.1% moisture content in preliminary tests.Final moisture gradient in the modified hopper bottom semi-trailer consisted of even layers from front-to-back with moisture increasing with depth.Current inspection probe sampling pattern biases inspection moisture measurements lower by not sampling the hopper bottom.Abstract. Hopper bottom semi-trailers (HBST) modified to dry loads of in-shell peanuts would provide several advantages to peanut producers and peanut processing facility operators. Producers who have HBST for transporting grain would have an additional use for their HBST and would reduce harvest delays during peak harvest times when trailer availability is limited from peanut processors. Additionally, smaller processing facilities would gain the economic advantages of semi-trailers without the investment in hydraulic lifts to unload peanut drying van semi-trailers. Before this study, no HBST had been modified to add peanut drying functionality. The objectives of this study were to design, fabricate, and test the performance of drying modifications to a HBST. After review of the functional components needed to dry peanuts and existing structural constrains of the HBST, the components fabricated were an air inlet connection, an enclosed transition space, an air plenum vent, and air exhaust vents on the undersides of the hopper tubs. The number, size, and location of the air exhaust vents were determined using a computational fluid dynamic model. Three test loads of peanuts were dried in the modified HBST during the 2020 peanut harvest season. Measurements were taken at intervals throughout the peanut drying process to assess drying and to monitor air temperature and relative humidity. Results of a test load indicated that the moisture content decreased from 12.9% wet basis (w.b.) to 12.0% w.b. after 8.5 h of drying. Average moisture content was reduced to 11.1% w.b. following an additional 8.6 h without the dryer operating. The sample load official grade moisture content was 9.1% w.b after the rest period. The most important finding was that a moisture gradient persisted in the loads of peanuts after active drying and rest period. The peanuts located at the top of the load had a moisture content of 9% w.b. while those with the highest moisture content of 14% w.b. were at the bottom of the load. The official inspection sampling procedure did not detect the moisture content differences in the test loads. The finding of a persistent moisture gradient will require more investigation and modification of the HBST. Keywords: Computational Fluid Dynamics, CFD, Design, Drying, Hopper-bottom semi-trailer, Moisture distribution, Moisture gradient, Peanuts, Retrofit.

COMPUTATIONAL FLUID DYNAMICS MODELED AIR SPEED THROUGH IN-SHELL PEANUTS IN DRYING WAGONS COMPARED TO MEASURED AIR SPEED

Abstract.HighlightsPeanut drying wagon internal airflow simulation and visualization.Comparison of computer fluid dynamic (CFD) solutions to measured air speed.Modeling of airflow through masses of in-shell peanuts. Information is lacking about airflow through masses of drying in-shell peanuts in drying wagons because of the difficulties encountered in making direct measurements. Information about airflow is needed to improve efficiency of drying peanuts to make peanut crops more profitable. Computational Fluid Dynamics (CFD) modeled airflow through in-shell peanuts loaded in drying wagons was validated using actual airflow measurements. CFD models allow for the investigation of airflow within peanut loads and the air plenum of drying wagons. Airflow through a wagon load of in-shell peanuts treated as a solid mass with distributed resistance was modeled using airflow behavior following Darcy’s law. CFD model simulations were undertaken using measured air speed, wagon air plenum static air pressure, and fan performance curve data. CFD modeling was based on actual air speed measurements made at 40 locations on the top surface of wagon loads of in-shell peanuts. The 40 measurement locations represented the top center of 40 blocks which the peanut load was divided into to investigate air speed. To match actual measurements to CFD model results, CFD models were configured with the same 40 blocks as those of the actual measurements. In CFD models, the permeability of the peanuts in each of the 40 blocks could be varied in a trial-and-error fashion to increase or decrease the air speed at the top surface of the peanut load to match that of the actual air speed measured for each of the blocks. Model results reproduced the measured air speed to within the accuracy limits of the air speed measurements. The air speed and static air pressure distribution in the wagon air plenum was found not to be uniform even when all blocks had the same permeability. Model results revealed wagon air plenum air speed patterns and static air pressure distribution could explain the general air speed distribution of slower air speeds at the top surface of the peanut load near the wagon air inlet wall and the increasing air speed along the length of the wagon. Permeability variations within the peanut load were found to explain localized variations in air speed at the top surface of the peanut load. Keywords: Air speed, Airflow, Modeled results compared to measured, Computational fluid dynamics modeling, Drying wagon, In-shell Peanuts, Peanut bulk permeability, Peanut curing, Peanut drying .

Optimizing the drying parameters of a fixed bed with reversing ventilation for peanut using computer simulation

To obtain the optimal operation parameters of fixed-bed reversing ventilation drying of peanuts, a set of partial differential equations indicating the heat and mass transfer relationships between the peanut pods and air during drying was proposed. Then, a series of discretized models were established for simulation, and the time consumed, unevenness, and energy consumption for batch drying were calculated. The results showed that reversing ventilation and segmented drying was helpful to these issues for high drying ability. The optimal operation parameters were determined by uniform design experimentation of mathematical simulation. The result showed that when the moisture content (wet basis) was above 22%, a ventilation velocity of 0.46 m/s was optimal; when the moisture content was between 8% and 22%, a ventilation velocity of 0.20 m/s was optimal. Using the optimal parameters, the computer simulating result was compared with the experimental results. The correlation coefficients between the simulating and the experimental values for the temperature and moisture content were all above 0.98 and the quality of dried peanuts was close to that of natural sun-dried ones, which indicates that the optimization results of the drying parameters are highly reliable. Keywords: peanut, fix bed drying, reversing ventilation, simulation, optimization DOI: 10.25165/j.ijabe.20211405.6354 Citation: Yan J C, Xie H X, Wei H, Wu H C, You Z Y. Optimizing the drying parameters of a fixed bed with reversing ventilation for peanut using computer simulation. Int J Agric & Biol Eng, 2021; 14(5): 255–266.

Experimental and Modeling Study of Peanut Drying in a Solar Dryer with a Novel Type of a Drying Chamber

ABSTRACT The aim of the present study is to investigate the experimental performance of a solar dryer by using a novel type of a drying chamber for increasing the drying performance and ensuring homogeneous drying. The drying system (SDS) consisted of a new type of a drying chamber and a solar air collector, which were designed, made, and tested in Osmaniye, Turkey. The analyses of Computational Fluid Dynamics were carried out to demonstrate the advantage of the designed drying chamber over the tunnel type drying chamber, which is commonly used in peanut drying. The drying experiments were conducted using in-shell peanut to observe the performance of the system. The drying procedure was performed in the form of open sun drying (OSD), and the results of drying kinetics such as moisture ratio (MR), drying rate (DR), and heat transfer coefficient (hc) obtained from both drying methods were compared. The MR and DR values obtained during the drying experiments were estimated using different models such as mathematical, multiple linear regression (MLR), decision tree (DT), and the support vector machine (SVM). It was observed from the numerical results that the products can dry more homogenously and effectively with the newly designed drying chamber compared to the conventional tunnel type drying chamber. The results of the drying experiments showed that the products dried earlier and more regularly through the SDS compared to the OSD. The DR and hc values were found 0.0051E-01 (gw/gdm)/min and 1.5727 W/m2°C for SDS and 0.0039E-01 (gw/gdm)/min and 1.4664 W/m2°C for OSD, respectively. The models that best estimated the experimentally obtained MR and DR values for peanuts dried with the SDS proved to be the Random Tree Model (R2 = 0.9972) and Quintic Model (R2 = 0.8551), respectively.

Optimizing the drying parameters of a fixed bed with reversing ventilation for peanut using computer simulation

To obtain the optimal operation parameters of fixed-bed reversing ventilation drying of peanuts, a set of partial differential equations indicating the heat and mass transfer relationships between the peanut pods and air during drying was proposed. Then, a series of discretized models were established for simulation, and the time consumed, unevenness, and energy consumption for batch drying were calculated. The results showed that reversing ventilation and segmented drying was helpful to these issues for high drying ability. The optimal operation parameters were determined by uniform design experimentation of mathematical simulation. The result showed that when the moisture content (wet basis) was above 22%, a ventilation velocity of 0.46 m/s was optimal; when the moisture content was between 8% and 22%, a ventilation velocity of 0.20 m/s was optimal. Using the optimal parameters, the computer simulating result was compared with the experimental results. The correlation coefficients between the simulating and the experimental values for the temperature and moisture content were all above 0.98 and the quality of dried peanuts was close to that of natural sun-dried ones, which indicates that the optimization results of the drying parameters are highly reliable. Keywords: peanut, fix bed drying, reversing ventilation, simulation, optimization DOI: 10.25165/j.ijabe.20211405.6354 Citation: Yan J C, Xie H X, Wei H, Wu H C, You Z Y. Optimizing the drying parameters of a fixed bed with reversing ventilation for peanut using computer simulation. Int J Agric & Biol Eng, 2021; 14(5): 255–266.

Performance Comparison of Three Density-Independent Calibration Functions for Microwave Moisture Sensing in Unshelled Peanuts during Drying

HighlightsReal-time, free-space transmission measurements of relative complex permittivity in unshelled peanuts during dryingDynamic application: temperature, density and moisture content changing during dryingThree density-independent calibration functions evaluated for accuracy in real-time moisture content determinationReal-time moisture content determination with standard error of performance (SEP) = 0.55% moisture content for all calibration functionsCalibration function most commonly used with microwave moisture sensor was determined to be most accurate; SEP = 0.448% moisture contentAbstract. A microwave moisture sensor, developed within USDA ARS, has been used to determine moisture content in unshelled peanuts during drying. Relative complex permittivities of the peanuts obtained from free-space transmission measurements at 5.8 GHz are used for the moisture determination. Due to variations in density caused by drying, it is advantageous to estimate moisture content independent of bulk density. Therefore, moisture content was estimated with three density-independent calibration functions to assess which one provided optimal accuracy. One of the functions is based on the measured attenuation and phase shift, and the other two are permittivity based (one of which is commonly used with the microwave moisture sensor). The sensor was calibrated for peanut pod moisture content determination over a temperature range of 10°C to 40°C and a moisture content range of 6.5% to 19% wet basis (w.b.). Statistical analysis showed high coefficients of determination (r2), = 0.97 for the calibration with each function. Peanut pod moisture content was determined with the sensor in real-time as peanuts dried, and estimated moisture content was compared to the reference oven drying method. While the standard error of performance (SEP) for the three functions was = 0.55% moisture content, the calibration function most commonly used with the microwave sensor was observed to be the most accurate (SEP = 0.448% moisture content). Microwave sensing is a viable solution for nondestructive, real-time determination of moisture content in peanuts in dynamic situations such as drying. Keywords: Complex permittivity, Dielectric properties, Free-space measurements, Microwave sensing, Moisture content, Peanut drying.

Effect of Drying Temperatures on the Peanut Quality during Hot Air Drying.

Peanuts are usually with high moisture after harvest and must be dried to prevent mildew. Hot air drying is the most commonly used method for peanut drying. The purpose of this study was to evaluate the drying temperatures on the peanut qualities. In this paper, fresh peanuts were dried with solar radiation (control group) and hot air at 35-60°C until the moisture content of peanut reduced below 10%. The physical (texture, damaged percentage of red testa and breakage percentage of peanut kernel), physiological (germination) and biochemical (the contents of vitamin E and aflatoxin B1; acidity values, iodine values, peroxide values and fatty acid composition of peanut oil; solubility, emulsifying, foaming, water-holding capacity and oil-binding capacity of peanut protein) properties of peanut kernel were determined under different drying conditions (solar radiation, 35°C, 40°C, 45°C, 50°C, 55°C, 60°C). The results showed that hot air temperatures had obvious influences on peanut qualities. The damaged percentage of red testa and breakage percentage of peanut kernel increased remarkably when the drying temperatures were above 45°C. Meanwhile, when drying temperatures were more than 45°C, the acid value and peroxide value of the extracted oil increased significantly. Furthermore, some properties exhibited prominent changes when the temperatures were higher than 50°C, such as hardness, brittleness, germination percentage, and the Vitamin E content of peanut kernel. In addition, the research results revealed that hot air can increase hydrophobicity of peanut protein and affect the functional properties of peanut protein. Therefore, it could be concluded that peanut should be dried by hot air below 45°C for quality maintenance. It also provided reference to choose suitable drying temperatures based on the final use of peanut.

Effects of peanut drying and blanching on Salmonella spp.

In order to evaluate the behavior of Salmonella during peanut drying and blanching, a study was conducted with Runner type peanuts. Samples of raw in-shell or unblanched peanuts were inoculated by spraying with a pool of five Salmonella serotypes isolated from the peanut supply chain (Miami, Muenster, Yoruba, Javiana and Glostrup). The in-shell peanuts were submitted to drying at 35 and 40 °C up to 18 h. After this time, the Salmonella counts went down ca. 2.0 log MPN/g at 35 and 40 °C. According to the Weibull model the time needed to achieve Salmonella 3-log reduction (T3d) and 5-log reduction (T5d) on the in-shell peanuts would be ca. 49 and 117 h at 35 °C and 35 and 79 h at 40 °C, respectively. The results showed that there was no statistical difference (p > .05) between either of the temperatures employed in the process. The blanching process was performed in two steps: pre-roasting (step 1) and skin removal (step 2). Reduction of up to 2.1 log MPN/g was observed after blanching at 100 °C/15 min plus 15 s of air impact. The skin removal process did not result in recontamination of the final sample. The Weibull model predicted 3- and 5-log reductions of Salmonella in 37.0 and 68.9 min for blanching at 95 °C, and in 39.1 and 114.9 min at 100 °C. The results demonstrated that drying and blanching processes did not generate large reductions of Salmonella in the peanut samples. Thus, the product resulting from these steps may be a possible source of cross-contamination for the processing plant and the final product.

Design Build Dryer Machine Frying Results Nuts Eggs

The purpose of this research is to design oil drying machine in nurts eggs to get the result of working drawing and to determine the peanut dryer component. The concept of planning oil drying machine in nurts eggss is by conducting a direct survey of the egg industry, the problems arise still high levels of oil in manually dried peanuts, then carry out the design concept. Based on the concept, then designed a design drawing. The result of this final task is in the form of design or design of oil oven dryers that utilize centrifugal force for drying oil, oil stainless steel rotary tube components, stainless steel container tube with stainless steel , axle components to support tubes of 22mm diameter and 520mm length, pulleys with a 3/6 ratio as a rotary reducer of an electric motor of 0.5 HP 1400 rpm to 500 rpm. Frame profile machine L 40 x 40 x 4 mm 42 st material and engine components made by Fernando Ferry from material st 37.

Estimating Energy Costs of Nonbeneficial Dryer Operation by Using a Peanut Drying Monitoring System

Abstract. Knowledge of kernel moisture content during peanut drying is important to ensure that the bed of peanuts is dried appropriately. However, the lack of a commercially available, industry-accepted solution for real-time kernel moisture content determination during peanut drying makes its detection cumbersome and laborious. Samples of unshelled peanuts are extracted from the semitrailer by an operator periodically, and the samples have to be cleaned and shelled to determine kernel moisture content with the official meter. A peanut drying monitoring system that includes a microwave kernel moisture sensor, developed within the USDA ARS, provides a means for monitoring in-shell kernel moisture content in real-time. The system determines kernel moisture content with a standard error of prediction (SEP) of 0.55% moisture content when compared to the reference oven-drying method. During recent peanut harvest seasons, peanut drying monitoring systems were placed in 13.7-m (45-ft) drying semitrailers, one 3 m (10 ft) from the front of the trailer and the other 3 m (10 ft) from the back of the trailer. As the peanuts dried, pod and kernel moisture content, temperature of the drying peanuts, temperature and relative humidity of the air exhausted from the peanuts, and temperature and relative humidity of the air being blown into the peanuts were measured every 12 seconds. The continuous data, provided by the monitoring systems, were useful in observing the loss of moisture by the peanuts throughout drying. The data also revealed periods of at least 3 hours during which dryer operation did not result in loss of moisture from the peanuts; thus, identifying nonbeneficial dryer operation. Such periods cause a peanut buying point to accumulate unnecessary expenses for propane and/or electric energy which can total up to $3,250 annually for an average-size buying point. Keywords: Dielectric properties, Energy cost, In-shell kernel moisture content, Microwave sensing, Peanut drying, Real-time monitoring, Sensors.

Solar Drying: A Means of Improving the Quality of Peanuts in Ghana

ABSTRACT An indirect, passive, wooden dryer, with a galvanized steel panel (4.5 m2) and four wire mesh shelves (2.62 m2 each), was constructed in Kumasi, Ghana. The dryer was evaluated for its capacity in drying of freshly-harvested in-shell peanuts on a single layer (8.5 Kg), and then up-scaled to four layers (4x18 Kg). Equal amounts of peanuts, dried simultaneously on a concrete floor under the open sun, served as comparisons. The moisture content of solar dried peanuts decreased from 35.85-5.25% and 32.00 %-4.25% in the single-layer and four-layer drying, respectively, in 4 days. Faster drying rates were observed when peanuts had relatively higher moisture contents with R2 values ranging from 0.72-0.95. The average daily solar radiation ranged from 360-592.99 W/m2 and daily energies generated were from 42.24-69.16 MJ. The drying efficiency ranged from 1.50-6.47% in the single-layer drying and 23.07-24.93% in the four-layer drying whereas the thermal efficiency was 3.15-21.60% in the single-layer drying and 3.08-24.93% in the four-layer drying. Peanuts from the solar dryer had lower free fatty acid and peroxide values but higher germination percentage compared to open sundried peanuts. The study suggests that solar drying can be used effectively for improving peanut safety and preserving peanut quality in Ghana.

Real-time monitoring of peanut drying parameters in semitrailers

ABSTRACTKnowledge of peanut drying parameters, such as temperature and relative humidity of the ambient air, temperature and relative humidity of the air being blown into the peanuts, and kernel moisture content, is essential in managing the dryer for optimal drying rate. The optimal drying rate is required to preserve quality and desired flavor. In the current peanut-drying process, such parameters are elusive in real time and are either not measured or only measured periodically by an operator. A peanut-drying monitoring system, controlled by an embedded microcontroller and consisting of relative humidity and temperature sensors and a microwave peanut moisture sensor, was developed to monitor drying parameters in real time. It was deployed during the 2014 peanut harvest season at a peanut buying point in central Georgia, USA. It was placed in 45-ft (13.7-m) drying semitrailers to monitor in-shell kernel moisture content, temperature of the drying peanuts, temperature, and relative humidity of the exhaust air from the peanuts and relative humidity of the air being blown into the peanuts in real time. In-shell kernel moisture content was determined with a standard error of performance of 0.55% moisture content when compared to the reference oven-drying method. Data from drying parameters were time-stamped and stored on a CompactFlash card every 12 s and were used to assess the efficiency of dryer control settings. Ambient air conditions were measured by an on-site weather station. Results of the study support the value of such a monitoring system and show that implementation of the system for dryer control has the potential for saving a buying point, in the current economical context, as much as $22,000 annually in costs of electric energy and propane.

Using Microwave Sensing to Investigate Kernel Moisture Content at the Front and Back of Semitrailers during Peanut Drying

Abstract. Several factors influence the effectiveness of peanut drying. Such factors include temperature and relative humidity of the air used for aeration, air velocity through the peanuts, and the presence of foreign material that could obstruct air flow. All of these factors can vary at any location in a semitrailer holding 20 to 25 tons of peanuts being dried. Therefore, it is highly unlikely that a volume of peanuts &amp;gt;71 m3 (2500 ft3) will dry uniformly. During the drying process, an operator removes samples of peanuts for kernel moisture content testing every 3 to 4 h to validate the estimated drying time determined by peanut-drying models used in the peanut industry. However, if samples are only taken from one location, it is likely that other locations differ in kernel moisture content. To investigate kernel moisture content near the front and back of the semitrailer, two peanut drying monitoring systems, each equipped with a microwave moisture sensor, were deployed at a peanut buying point in central Georgia during the 2014 and 2015 peanut harvest seasons. Each system monitored in-shell kernel moisture content and drying parameters in real-time, every 12 s. In-shell kernel moisture content was determined with a standard error of prediction of 0.55% moisture when compared to the reference oven-drying moisture tests. The two monitoring systems were placed in 13.7-m (45-ft) drying semitrailers, one 3 m (10 ft) from the front and the other 3 m (10 ft) from the back. Data from the measurements were time-stamped and reconciled accordingly, and they were analyzed to compare the moisture loss in real-time at both locations in the trailer. The 12-s resolution provided a continuous moisture profile to analyze rather than the discrete profile currently provided by sampling every few hours. Results show that moisture loss, and therefore resulting kernel moisture content, can vary from one end of the trailer to the other during peanut drying. Therefore, systems that monitor peanut drying at various locations throughout the semitrailer would improve peanut drying efficiency. Keywords: Dielectric properties, In-shell kernel moisture content, Microwave sensing, Peanut drying, Real-time monitoring, Sensors.