Hot-air drying of sunflower seeds, a common preservation method, often results in high energy consumption and diminished oil quality due to prolonged drying and thermal degradation. This study employs the Taguchi method to systematically investigate and identify optimal conditions for ultrasound-assisted hot-air drying to enhance drying kinetics, energy efficiency, and oil retention. Using a Taguchi L16 orthogonal array, the effects of drying temperature (50 degrees C, 60 degrees C, 70 degrees C, and 80 degrees C), air velocity (0.5, 0.7, 0.9, and 1.1 m/s), and sonication time (0, 4, 8, and 12 min) were investigated. Evaluated responses included total drying time, drying rate, effective moisture diffusivity, specific moisture evaporation rate (SMER), and oil content. Sonication time emerged as the most influential factor in reducing drying time and increasing drying rate by modifying seed microstructure to promote moisture migration. Drying temperature primarily affects energy efficiency and moisture diffusivity but adversely impacted oil content at elevated levels. A trade-off was observed where high temperature increased drying efficiency but reduced oil quality, while lower temperature preserved oil at the expense of drying time. A compromise condition, identified through analysis of individual response optima, balanced these factors, enabling rapid, energy-efficient drying with superior oil retention compared to conventional hot-air methods. This work underscores the potential of combined ultrasonic and thermal treatments to develop sustainable drying protocols for oilseeds.

Date seed grinding remains a significant challenge limiting the utilization of this valuable agricultural by-product." In this study, a compact date seeds grinding unit was designed, tested, and evaluated. The machine has two primary: a pair of toothed cylinders and a hammer mill. The machine’s performance was assessed in terms of throughput, specific energy consumption, and mean particle size of the product. First, the cylindrical section was tested under various conditions, including cylinder rotational speed (150, 250, 350, and 450 rpm), feed gate opening size (30, 37.5, and 45 cm2), and the clearance between cylinders (0, 1, and 2 mm). The feedforward neural network (FNN) framework predicated the optimal operating conditions for this part, which were recorded as 150 rpm cylinder rotational speed, 45 cm2 feed gate opening, and 2 mm cylinder clearance. This optimal operational condition was utilized as the starting conditions for subsequent testing of the hammer mill section. Then, the hammer mill was tested with different hammer rotational speeds (1250, 1500, and 1750 rpm) and screen hole diameters (2, 4, and 6 mm) underneath the hammers. The FNN model was again employed to predicate the most suitable operating parameters for the grinding unit. The key results included the optimal operational parameters at 150 rpm cylinder rotational speed, 2 mm clearance, 45 cm2 feeding area, 1750 rpm hammer speed, and 6 mm screen hole diameter. That operational condition resulted in 30 kg/h for machine’s throughput, 49 kW h/ton specific energy consumption, and 2.14 mm mean product size. With FNN model accuracy R2 of 0.99974, demonstrating high prediction reliability. Meanwhile, the operating cost was 0.027 $/kg, suitable for small to medium-scale operations. The significance of these findings lies in the development of an efficient, versatile milling solution for date seeds and similar agricultural materials. This research pioneers the application of machine learning in optimizing date seed processing, potentially revolutionizing agricultural waste valorization and opening new avenues for sustainable resource utilization.

Closed-loop heat pump drying of wheat constitutes a dynamic and intricately interconnected composite system, wherein the heat pump and the dryer mutually act as heating sources. During operation, it demonstrates various characteristics, such as large inertia, nonlinearity, and multiple disturbances, which pose considerable challenges to the energy optimization of the system. This study introduces a transient analysis model that deeply delves into the dynamic processes of industrial-scale closed-loop heat pump drying. Subsequently, it facilitates in-depth analysis of transient thermodynamic behaviors and energy utilization patterns throughout the drying process. Results indicate that the mean relative deviations for the predicted wheat moisture content and temperature were 2.66 % and 1.12 %, respectively. Reducing the temperature disparity between the condenser and the drying air alongside decreasing the inlet temperature of the expansion valve markedly enhances the energy efficiency of the system. The study proposes an optimization scheme by designing two regenerators to preheat the drying air twice, resulting in a 26.3 % reduction in compressor power and a 32.5 % reduction in system exergy loss. The research findings offer data and methodological support for optimizing the energy efficiency of closed-loop heat pump drying system and provide mathematical as well as analytical methods for system analysis, state tracking, and dynamic parameter tuning.

Sugarcane is a vital global crop, serving as a primary source of sugar, biofuel, and renewable energy. Advancements in harvesting are critical to meeting rising demand, enhancing profitability, and supporting eco-friendly agricultural practices in the sugarcane sector. Based on the current challenges of sugarcane harvesting in developed countries, the current study aimed to develop a semiautomatic whole-stalk sugarcane harvester (SWSH) for harvesting two rows of sugarcane stalks at a time and to be front-mounted on a classic four-wheel agricultural tractor. Then performance evaluation and prediction of optimal operational conditions for a double-row sugarcane harvester using Feedforward Neural Network (FNN) and Deep Neural Network (DNN) at different levels of forward speeds (3, 3.5, 4.5, and 5 km/h), row spacing (71, 78.89, and 88.75 cm), cutting heights (0, 2, and 4 cm), and numbers of knives (2 and 4) of the cutting systems. The obtained results showed that the cutting efficiency of the developed SWSH reached 100%. Where the higher cutting efficiency was observed at a cutting height equal to zero (ground level), forward speed of 3 km/hand row spacing of 71 cm using both 2 and 4 knives. The minimum total operating cost of the developed SWSH was about 4.42 USD/ha, and it was detected when using a forward speed of 4.5 km/h, row spacing of 88.75 cm, a cutting height of 4 cm, and two knives only on the cutting disk. Furthermore, at a row spacing of 88.75 cm, the maximum field capacity of the developed SWSH was 0.554 ha/h, observed at a forward speed of 4.5 km/h.

Paddy drying is an energy-intensive process that involves complex interaction such as inertia, nonlinearity, and random disturbances. Real-time energy consumption regulation is challenging due to the interplay of these factors. This study proposes a two-level hierarchical model predictive control (MPC) strategy for industrial-scale circulation counter-flow paddy drying process. The first-level optimizer encompasses an energetic optimizer, engineered to minimize energy consumption. This optimizer integrates drying mathematical and energetic models, as well as drying and ambient data. It operates at a low frequency of once every 180 s to handle computational complexity and slow-changing ambient conditions. To handle high-frequency disturbances, a second-level MPC operates at 2.25 s intervals, relying exclusively on drying mathematical model and tracking ideal trajectory established by first-level optimizer. Experiments show that first-level optimizer reduces total energy consumption by 12.8 % compared to previous proposed static ventilation strategy. Hierarchical MPC strategy consistently achieves lower relative average deviations (0.70 %, 0.79 %, and 0.81 %) from ideal trajectory under varying disturbance fluctuation rates (+60 %, +80 %, and +100 % respectively). These deviations are markedly lower (by 1.58 %, 15.67 %, and 19.52 % respectively) than those observed when applying firstlevel optimizer under noisy conditions. These findings underscore the enhanced energy-saving and

Chickpeas hold significant nutritional and cultural importance, being a rich source of protein, fiber, and essential vitamins and minerals. They are a staple ingredient in various cuisines worldwide. Peeling chickpeas is considered a crucial pre-consumption operation due to the undesirability of peels for some uses. This study aimed to design, test, and evaluate a small chickpea seed peeling machine. The peeling prototype was designed in accordance with the chickpeas’ measured properties; the seeds’ moisture content was determined to be 6.96% (d.b.). The prototype was examined under four different levels of drum revolving speeds (100, 200, 300, and 400 rpm), and three different numbers of brush peeling rows. The prototype was tested with rotors of four, eight, and twelve rows of brushes. The evaluation of the chickpea peeling machine encompassed several parameters, including the machine’s throughput (kg/h), energy consumption (kW), broken seeds percentage (%), unpeeled seeds percentage (%), and peeling efficiency (%). The obtained results revealed that the peeling machine throughput (kg/h) exhibited an upward trend with increases in the rotation speed of the peeling drum. Meanwhile, the throughput decreased as the number of peeling brushes installed on the roller increased. The highest recorded productivity of 71.29 kg/h was achieved under the operational condition of 400 rpm and four peeling brush rows. At the same time, the peeling efficiency increased with the increase in both of peeling drum rotational speed and number of peeling brush rows. The highest peeling efficiency (97.2%) was recorded at the rotational speed of 400 rpm and twelve peeling brush rows. On the other hand, the lowest peeling efficiency (92.85%) was recorded at the lowest drum rotational speed (100 rpm) and number of peeling brush rows (4 rows). In the optimal operational condition, the machines achieved a throughput of 71.29 kg/h, resulting in a peeling cost of 0.001 USD per kilogram. This small-scale chickpea peeling machine is a suitable selection for small and medium producers.

Improving the performance of the threshing process is of utmost importance in enhancing the quality of sunflower seeds and minimizing power consumption in sunflower production. In this study, we developed a modified sunflower threshing machine by incorporating two types of threshing rotors, namely the angled rasp bar rotor and the tine bar rotor, as compared to the round bar rotor. The performance of these rotors was evaluated under various rotational speeds (150, 200, 250, and 300 rpm) and concave clearances (10, 15, and 20 mm). The evaluation parameters included machine throughput, the specific energy of threshing, the percentage of damaged seeds, the percentage of unthreshed seeds, and threshing efficiency. The results indicate that the specific energy decreased with an increase in rotor speed and a decrease in concave clearance, with the tine bar rotor exhibiting the lowest values. Threshing efficiency showed an increasing trend with higher rotor speeds and reduced concave clearance. The modifications made to the rotor design resulted in an enhanced threshing efficiency, with an improvement from 96.30% to 97.93% achieved at a rotor revolving speed of 300 rpm and a concave clearance of 10 mm. Moreover, the specific energy consumption reduced from 9.65 kW·h/ton to 5.09 kW·h/ton under the same operational conditions. These findings highlight the efficacy of the novel rotor design modifications in optimizing the performance of the stationary sunflower threshing machine, leading to improved efficiency and reduced energy consumption in sunflower seed threshing operations. Given its performance characteristics, this machine exhibits potential suitability for sunflower farms of small to medium scale.

Drying involves the evaporation of moisture, accompanied by simultaneous heat transfer, mass transfer, and momentum transfer. While the diffusion law is considered an applicable model for explaining the drying phenomenon, the actual drying process cannot be accurately predicted using an analytical solution with a constant diffusion coefficient. Energy efficiency in the drying process is low due to an insufficient understanding of the mechanisms governing moisture migration from solids to air. The development of drying theory has stalled due to an unsolvable discrepancy between experimental results and analytical results. This study analyzes the effect of the binding energy of moisture in paddy rice on the diffusion coefficient. The theoretical relationship between water activity and drying rate in paddy rice was investigated, and the drying process was successfully explained by analyzing free energy transfer and transition theory. The mechanism of rice grain drying was described using a new theoretical solution for the drying process. These results provide new insights into the development of a scientific evaluation standard for assessing the efficiency of actual drying processes.

Water scarcity poses a significant challenge for people living in arid areas. Despite the effectiveness of many bioinspired surfaces in promoting vapor condensation, their water-harvesting efficiency is insufficient. This is often exacerbated by overheating, which decreases the performance in terms of the micro-droplet concentration and movement on surfaces. In this study, we used a spotted amphiphilic surface to enhance the surfaces’ water-harvesting efficiency while maintaining their heat emissivity. Through hydrophilic particle screening and hydrophobic groove modifying, the coalescence and sliding characteristics of droplets on the amphiphilic surfaces were improved. The incorporation of boron nitride (BN) nanoparticles further enhanced the surfaces’ ability to harvest energy from condensation. To evaluate the water-harvesting performance of these amphiphilic surfaces, we utilized a real-time recording water-harvesting platform to identify microscopic weight changes on the surfaces. Our findings indicated that the inclusion of glass particles in hydrophobic grooves, combined with 1.0 wt.% BN nanoparticles, enhanced the water-harvesting efficiency of the amphiphilic surfaces by more than 20%.

精确的工业化粮食干燥过程数学模型是实现其过程动态跟踪、闭环控制的前提.为此,基于5HNH-15连续式粮食干燥机,构建了8-11-1的BP神经网络预测模型,模型的输入为5 HNH-15连续式干燥机的8个干燥影响因素,输出为出口粮食含水率.利用MmatLab软件进行BP神经网络模型的建立及验证,结果表明:模型在67次迭代后,均方误差MSE达到2.8361e-6,绝对误差小于±0.1,平均绝对误差MAE=0.0288,相对误差小于1.2％,回归系数R=0.99996,决定系数R2=0.9998.新增1组验证试验,结果显示:模型预测值与实际值的绝对误差小于±0.1,平均绝对误差MAE=0.0121,相对误差小于1.1％,证明了所构建模型的精确性与普适性,可为实现工业化粮食干燥的智能控制提供理论依据和技术支撑.

The heat exchanger is the key component of an industrial drying system. The present work introduced a novel tube heat exchanger into a corn drying system. To fully understand the heat exchange process and optimize the heat exchange performance of the heat exchanger, numerical simulation, exergy analysis and economic analysis methodologies were adopted to analyze the comprehensive performance of the heat exchanger. The fluid dynamics as well as the exergy performance of the heat exchanger under different flue gas velocities (3, 5 and 7m/s) and different ambient air relative humidities (80%, 85% and 90%) were investigated. The results showed that there are two strong turbulences causing the huge pressure drop at the last two stages of the flue gas duct, while there are two insufficient heat exchange areas on both sides of the heat exchanger; thus, the corresponding improvement recommendations were proposed in the present work. The values of the Re and Nu were found to vary in the range of 1256.275–2210.554 and 21.337–32.415, respectively. The average heat transfer coefficients were ascertained to be above 8.274 kW·m−2·K−1, while the pressure drop of the ambient air was ascertained to be under 16.138 Pa. Moreover, the exergy analysis revealed that the heat exchanger experiences sustainable development (SI < 2), and the exergy efficiency is above 11.461%. The main results may provide some references for further optimizing the heat transfer performance of the heat exchanger.

In practical industrial-scale paddy drying production, manual empirical operation is still widely used for process control. This often leads to poor uniformity in the moisture content distribution of discharged grains, affecting product quality. Model Predictive Control (MPC) is considered the most effective control method for paddy drying, but its implementation in industrial-scale drying is hindered by its high computational cost. This study aims to address this challenge by proposing a deep-learning-based model predictive control (DL-MPC) strategy for paddy drying. By establishing a mapping relation between the inlet and outlet paddy moisture content and paddy flow velocity, a DL-MPC strategy suitable for multistage counter-flow paddy drying systems is proposed. DL-MPC systems are developed using long short-term memory (LSTM) neural networks and trained using datasets from single-drying-stage and multistage drying systems. Simulation and analysis are conducted, followed by verification experiments on a 5HNH-15 multistage counter-flow paddy dryer. The results show that the DL-MPC system significantly improves computational speed while achieving satisfactory control performance. The predicted paddy flow velocity exhibits a smooth variation and matches field data obtained from multiple transition points, confirming the effectiveness of the designed DL-MPC system. The mean absolute error between the predicted and actual paddy moisture content under the DL-MPC system is 0.190% d.b., further supporting the effectiveness of the control system.

孔隙率直接关系到稻谷干燥介质迂曲度、能质传递、通风阻力的变化,是解析稻谷干燥过程和能耗的重要参数之一.为准确获取流动状态下稻谷层的孔隙率,设计稻谷流动层孔隙率检测装置;结合正交试验方法和参数的物理意义,分析检测装置的测量性能,并研究不同工况下稻谷流动层孔隙率的演变规律.结果显示,流动层孔隙率检测装置具有较好的可靠性,且多组试验结果的方差范围为0.0101-0.0229;在含水率为12.73%-32.01%区间,流动层孔隙率随稻谷含水率增大而逐渐减小;流动层孔隙率在稻谷流动层厚度为400-850mm范围内呈现先减小后增大的规律变化,且其最小值为63.1%;在开度为0-80mm区间内,流动层孔隙率随开度增大而升高.

Recently, heat pump drying has been widely used in tobacco processing. Considering the importance of this issue, it is of significant importance to further investigate temperature distribution and energy analysis in the drying process. To develop an energy-saving, environmental-friendly, and high-quality tobacco drying method, temperature distribution, dehumidification performance, the economic issues, and thermal efficiency of a heat pump curing barn (HPCB) and a traditional coal-fired bulk curing barn (TCCB) were compared. The regional temperature eigenvalue model was applied to describe the temperature uniformity with HPCB and TCCB. Moreover, thermal efficiency was obtained through energy tests. The obtained results showed that HPCB is beneficial to improve the drying quality of tobacco. The performed analyses showed that the thermal efficiency of the TCCB and HPCB was 42.02% and 66.53%, respectively. Accordingly, heat pump technology is recommended for industrial drying of tobacco leaves and obtaining high-quality products.

Drying isa process of removing water from products down to a specific moisture content. It is an energy-intensive process widely-used for grain and biomass processing. Because of the complicated thermo-dynamics and transport phenomena involved in drying, it is challenging to analyse and optimise drying operations. In this study, computer simulations using a transient model are performed to simulate the real-time paddy drying, and analyse the exergy components, exergy efficiency, exergy loss and destruction of industrial-scale drying process under changing drying air temperature (60-80 ?) and flow velocity (0.56-0.83 m/s) and initial moisture content (0.22-0.3 g water/g wet matter) on a circu-lation counter-flow paddy dryer. Results show our model can predict paddy moisture content and temperature with mean relative deviations of 5.5% and 1.42%, respectively. Exergy efficiency of drying process is specified to be in the range of 28.75-35.68%. Main factor affecting drying rate and energy consumption in high moisture content regions of drying process is drying air flow velocity while that in low moisture content regions is drying air temperature. We also propose control strategy based on two-stage variable ventilation parameters that achieves high exergy utilization level, high drying rate, and high product quality for grain drying.(C)& nbsp;2022 Elsevier Ltd. All rights reserved.

Objective: In order to solve the problem of poor integrity with mechanical coring and get the lantern pulp, and explore the factors affecting the performance of longan coring. Methods: Taking Guangdong 'Chuliang' longan fresh fruit as the research object, the key parts of core removal were designed and the core removal test platform was built. The core removal method with the ejector pin and flexible washer positioning was adopted. The ejector diameter, the rubber washer bore diameter and the ejector speed were chosen as the three main factors,and the stoning success rate, the stoning loss rate and the pulp integrity coefficient were chosen as the evaluation indicators. The single factor and orthogonal experiments were designed. Results: The experiments showed that the ranking of influence was rubber washer aperture ＞ ejector diameter ＞ ejector speed. When the ejector diameter was 7 mm, the rubber washer bore diameter was 14 mm and the ejector speed was 400 mm/min, the best stoning effect was got. Conclusion: It is feasible to obtain longan lantern pulp by the ejector rod mechanical enucleation method positioned with flexible washer and appropriate enucleation operation parameters.

稻谷间歇微波干燥可消除籽粒过热焦变,实现干燥效能提升,但干燥后稻谷品质存在易玻璃化转变而裂变率增加的问题.为综合提升稻谷干燥效能与品质,分别测定了缓苏比不同和缓苏比相同下的4种加热缓苏周期(TR 1,TR 2,TR 3,TR 4)微波干燥稻谷的失水性能和玻璃化转变温度、裂变率.基于2种增长模型(Weibull模型、Logistic模型),比较了不同加热缓苏周期下间歇微波干燥稻谷裂变率的增长性能,考察了其玻璃化转变与裂变率间的关联.结果显示:随着缓苏比增加,在加热缓苏周期中具有相同加热时间已干燥稻谷的含水率依次增大,但其玻璃化转变温度、裂变率依次减小;加热缓苏时间比相同而周期缩短,稻谷的玻璃化转变温度、裂变率均低;经TR 4微波干燥的稻谷的总裂变率仅为7.67％,显著低于其他3种工艺(p<0.05);以Weibull模型预测间歇微波干燥稻谷的裂变率增长的准确度高于Logistic模型(R2≥0.9783).研究结果可为深入研究稻谷间隙微波干燥机理提供参考.

Paddy drying is a spontaneous dehydration process following the principles of high product quality, high drying efficiency, low energy consumption, and environmental protection. However, its complex properties hinder the development of optimal control during drying. In this study, the real-time paddy drying state of a paddy multistage counter-flow dryer is simulated utilising numerical simulation technology. Results indicate the simulation results agreed well with the experimental data with mean relative deviation of less than 15%. Moreover, the steady and transient characteristics of present dryer are analysed under multiple disturbances. In addition, the effects of ambient and ventilation parameters on productivity, specific energy consumption, heat loss, and exergy loss characteristics are investigated in detail. Based on the simulation and analysis, a uniform design experiment is performed to determine the optimal ventilation parameters of paddy with initial moisture content of 0.238 g water g(-1) wet matter when ambient temperature and relative humidity are 20 degrees C and 50%, respectively. Drying air temperatures of 60 degrees C and 40 degrees C, and flow velocity of 1600 m h(-1) and 1150 m h(-1), respectively, in the high- and low-temperature drying stages are found to be the optimal ventilation parameters. (c) 2022 IAgrE. Published by Elsevier Ltd. All rights reserved.

为了实现对葵花籽含水率的快速、准确检测,采用非接触式平行板电容法对不同含水率水平的葵花籽在不同的温度和频率范围内的介电特性进行研究,建立了描述含水率、温度和介电常数的数学模型,验证了基于介电常数检测葵花籽含水率的可行性和模型的可靠性,并设计了一种能够按预定频率快速可靠地检测葵花籽含水率的装置.试验结果表明:葵花籽含水率检测装置在10°～40℃、6％～20％的含水率范围内绝对误差小于0.95％.由此验证了含水率检测装置的准确性和可靠性,为葵花籽的干燥、安全储藏和品质把控提供了技术支撑.

为了提高干燥系统的能量利用效率,增强干燥机的通用性、可靠性、作业效率和年利用率,该研究围绕增大干燥动力系数和工艺能力指数,基于粮食的物性特征,从干燥工艺方式、机械结构参数和运动参数间的内在关系入手,把几何因子和运动参数有机结合,揭示了粮食在干燥机内流动特性;按照引风降压,连续闪蒸降温,强化传热传质,自适应排粮的设计思想,研制了一款粮食通用的干燥机,实现了粮食在干燥机内连续流动过程中,自发地改变流态、连续回转换位,强化了传热传质,改善了干燥的均匀性.设计的升角为6°的变截面角状盒,与传统的横流方法相比,可使干燥动力系数增大2～4倍,干燥稻谷时的爆腰增率可控制在1％以内,发芽势提高76％以上,发芽率达到95％;设计往复式差速排粮机构,实现了自适应无损排粮,有效解决了粮食架桥、堵塞问题,避免了粮种的机械损伤.设计的5HP-25型粮食干燥机,实际应用效果显示,在粮食平均干燥强度为1.37～2.70％/h的条件下,干燥水分单位热耗为2900～4300kJ/kg,与国标7400 kJ/kg相比,降低了单位热耗量.研究结果为实现优质、高效、节能干燥工艺及装备设计提供了参考.