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The productivity and quality of the entire flock are negatively impacted by heat stress in chickens, which can have major repercussions, particularly in crowded farming settings where diseases are easy to spread and hard to control. This study uses deep networks and optical flow to identify heat stress in chickens. The technique focuses on identifying obvious signs of heat stress, such as panting and open-mouth breathing in chickens. There are two phases to the suggested approach: (1) using a deep network to detect open-mouth breathing in chickens; (2) using the Gunnar Farnebäck algorithm to compute the optical flow vectors of the wattle, the breathing frequency is estimated in the Fourier domain for the detection of panting chickens. The proposed method was tested on the obtained dataset and demonstrated its ability to recognise heat-stressed chickens in crowded conditions, achieving an overall performance metric of 0.90 by integrating the results of both phases. The two-phase approach, which incorporates the open-mouth breathing behaviour and panting frequency, improves the efficiency and assures robust, reliable heat stress detection.

Circular bioeconomy is rapidly gaining ground in the agricultural sector with priority given to the utilisation of more environmentally friendly materials for production and processing. Thus, in this study, biodegradable seedling pots were developed using sawdust (SD) and spent mushroom compost (SMC) as a sustainable alternative to plastic containers. Four pots composed of SMC : SD ratios of 100 : 0, 70 : 30, 60 : 40, and 50 : 50 were developed and evaluated. The mechanical properties, structural characteristics, and water absorption capacity of the pots were assessed and seedlings were made to grow in them to monitor the growth support potential. A universal tensile test machine was used to assess the indirect tensile strength (mechanical properties), while a scanning electron microscope was used to examine the morphology of the samples. Also, images of the seedling roots were segmented and analysed in ImageJ and WinRHIZO software to determine the root system architecture. The results demonstrated that the 60 : 40 ratio exhibited superior performance including having optimal water absorption capacity, indirect tensile strength, and structural properties. The 70 : 30 ratio also showed comparable tensile strength values. However, increasing the SMC content in the pot improved the root developments. This research presents a viable solution for converting agricultural waste into environmentally friendly seedling containers and suggests a potential option for reducing the dependency on plastic pots in agriculture.

This research optimised the application of a hexane-methanol mixture as a binary solvent for the concurrent oil-resin extraction and separation from Calophyllum seeds on a pilot scale, in a direct stage. The optimum oil and resin yields were determined by optimising the extraction conditions using response surface methodology and a second order polynomial model. The extraction conditions affected the oil and resin yields, with the extraction time as the biggest influencing factor. Optimum oil (65%) and resin (16%) yields were predicted to be obtained at 5.2 h and 433 rpm. The model validation with these extraction conditions showed that the predicted results and actual oil (62%) and resin (15%) yields were in passable agreement. The oil was composed of 75.4% triglycerides with a density of 0.874 g.cm^-3, a viscosity of 26.4 mPa.s^-1, an acid value of 46.4 mg KOH.g^-1, an iodine value of 98.0 g iodine.100 g^-1, trace water and sediment contents, and zero ash content. The resin had a viscosity of 4 694.8 mPa.s^-1, a total phenolic content of a 4.51% gallic acid equivalent, an antioxidant activity of an 8.82 mg ascorbic acid equivalent.g^-1, and an acid value of 126.2 mg KOH.g^-1.

Tillage-induced erosion has negative impacts on the soil environment and production of the soil under intensive farming. Tillage erosion was evaluated during soil tillage performed by two technologies, i.e. conventional tillage and reduced tillage, commonly used in the Czech Republic. A field experiment was aimed at evaluating the soil particle translocation and magnitude of the vector angle. Aluminium cubes with an edge length of 16 mm were used as tracers. After each soil tillage operation, a metal detector searched these tracers in the topsoil. During the experiment, agricultural practices were always carried out on their respective dates for the whole season. The experiment results show that conventional tillage had a more adverse effect on tillage erosion than reduced tillage. This was confirmed on three experimental parcels with different slope gradients of 2, 6 and 11°. The largest translocation of soil tracers was observed on a parcel with the highest slope of 11°. There, the length of the translocation of tracers reached up  to almost 10 m. The average length of soil tracer translocation in reduced tillage and conventional tillage ranged between 0.86 and 3.69 m. The largest average vector angle of tracer locations was recorded on a parcel with a slope of 6° for reduced tillage. In the treatment with the slope of 2° and conventional tillage used, the direction vector indicated upslope translocation of soil tracers. It was caused by soil tillage with a mouldboard plough turning over the topsoil layer upslope. In a treatment with a slope of 2° and reduced tillage used, no influence of the crosswise slope gradient of the plot on the direction vector was observed. The acquired knowledge will be used in further study of soil erosion processes.

Optimum irrigation scheduling and new technologies are the key to the successful practice of modern agriculture and natural resources, such as water management. Α three-year research project was conducted at Velestino, Magnesia, Greece. The aim was to study whether vegetation indices can be used to estimate the crop coefficients of corn in order to apply an intelligent method of irrigation using drones in the future. The normalised difference vegetation index (NDVI), the soil-adjusted vegetation index (SAVI), the renormalised difference vegetation index (RDVI) and a new index [difference infrared – green vegetation index (DIGVI)] were calculated using multispectral photos from a camera adapted to a drone. Three different methods were applied to calculate the crop coefficients: (i) the water balance and the FAO Penman-Monteith reference evapotranspiration, (ii) the climatic data, (iii) the vegetation indices. The irrigation dose covered 100% of the crop water needs according to the soil moisture measurements and the single crop coefficient values. The statistical analysis and the simple linear regression method showed that the corn crop coefficients can be estimated when these indices are used as independent variables.

One major challenge in the continuous growth of the livestock industry is the increased emission of odorous gases, which is not just a nuisance but also a cause of serious health and environmental concerns. Several strategies which aim to: (i) reduce the formation of odorous gases; (ii) enhance dispersion of odour; (iii) capture odour and gases to prevent escape to the environment; and (iv) reduce odour and gaseous concentrations, are developed. These are achieved with the use or employment of one or more of: (i) diet manipulation techniques; (ii) additives and adsorbents; (iii) covers; (iv) shelterbelts or windbreaks; (v) ventilation systems; (vi) biofilters; and (vii) air scrubber. The advantages and limitations of each of these strategies are discussed in this review in order to guide the choice of which strategy to use in a specific livestock application. Moreover, this review also discusses potential researchable areas in the field of odour control in livestock facilities.

Porang (Amorphophallus muelleri) is  an Indonesian parental plant tuber developed vegetatively from bulbils during dormancy and harvested through petiole detachment for the industrial production of glucomannan. Pathogenic fungi and whiteflies can cause infection during harvesting and storage, destructing plant cells as well as reducing seed quality and crop yields. Therefore, this study aimed to develop a calibration model for detecting infected and non-infected porang bulbils using a computer vision system. Image parameters such as colour (red, green, blue – RGB and hue, saturation, intensity – HSI), texture (contrast, homogeneity, correlation, energy, and entropy), and dimensions (width, area, and height) were evaluated on 90 samples in three positions. The results showed that the majority of image quality properties were significantly associated with non–infected and infected porang bulbils as showed by Pearson correlation values of 0.901 and 0.943, respectively. Discriminant analysis based on image attributes effectively classified non-infected and infected seedlings, achieving a model accuracy of 97.0% for correctly classified cross-validated grouped cases. Therefore, computer vision can be used for the preliminary detection of fungal infection in porang bulbils, as evidenced by its high accuracy and outstanding model performance.

The rice drying process in a rotary dryer gives the benefit of producing uniformly dried rice in a short drying time. This work investigated a rotary dryer's efficiency and heat consumption at various temperatures (40, 50, and 60 °C) and capacities (10, 20, 30, and 40 kg). When loaded with 10 to 30 kg of rough rice and operated at 60 °C, the dryer produced dry rice with 14% w.b. moisture content for less than 3 hours. The energy efficiency and consumption were evaluated based on the experiment and theoretical analysis. According to the observation, a high temperature significantly shortened drying time. Thus, the total energy and fuel consumption decreased even at the higher capacity. The lowest carbon dioxide emission was achieved at the highest temperature and capacity.

This research aims to develop an eco-friendly technique for treating seeds before sowing and improving their physiological features. The developed technique depends on utilizing synchronized electro-magnetization and microwave radiation. An electromagnetic device was evaluated to provide multiple treatment ranges. The treatments are regulated electronically according to the seeds' physiological properties and storage duration. The device was designed to accommodate small and medium seeds for a variety of strategic crops, including wheat, barley, etc. Three different treated wheat varieties were tested and compared to the control. Also, eight different levels of synchronized electro-magnetization and microwave radiation were tested. The treated wheat seeds' vegetative properties, such as germination percentage, germination rate index, germination speed coefficient, and vigour indexes, were highly significant compared to the control. The treated wheat seeds' physiological properties were highly significant. The device productivity ranged from 0.023 to 0.059 Mg·h^–1 with minimum energy consumption rates of 0.396 to 0.018 kWh·Mg^–1, while the operating costs decreased to 11.53–44.13 USD·Mg^–1.

Agriculture and energy are intricately connected, with agriculture being a significant energy consumer and supplier. In this comprehensive study, SPSS and Jupyter Notebook were used to model and predict the energy requirements of potato plants during cultivation. A system using deep learning methods, specifically the Convolutional Neural Network (CNN), was also developed to accurately predict the classification of potato plant growth phases using image data. The CNN model, developed with 100 epochs and 5 layers, used 1 125 image data of potato plants, categorising them into two classes: the vegetative phase, with an energy requirement of 4 195.80 MJ·ha^–1, and the generative phase, with an energy requirement of 746.45 MJ·ha^–1. The model‘s accuracy in reflecting the actual data, with a mean absolute error of 0.11, mean square error of 0.01, and root mean square of 0.13, indicates no significant issues. The test predicted categorization with 99% precision, underscoring the thoroughness and validity of this study and reassuring the audience about the accuracy of the results. The study findings not only validate the use of deep learning in agriculture but also inspire the development of applications to predict the energy demand for each growth phase using plant image data.

In our study location, Merauke Regency, the easternmost city in Indonesia, the sago palm is associated with different types of ecosystems and other non-sago vegetation. During the harvesting season, the white flowers blossoming between the leaves on the tops of palm trees may be distinguished manually. Four classes were determined to address the visual inspections involving different parameters that were examined through the metric evaluation and then analysed statistically. The computed Kruskal-Wallis test found that the parameters vary in each network with a P-value of 0.00341, with at least one class being higher than the others, i.e., non-sago with a P-value of 0.044 with respect to precision, recall, and F1-score. Thus, the general linear model (GLM) was tested specifically in trained Network-15 and Network-17, which have similar parameters except for the batch size. It indicated the two networks' differences based on their prediction results, classes, and actual images. Accordingly, a combination of learning rate (Lr) and batch size improved the reliability of the training and classification task.

This study assessed the gross calorific values (GCV) of crop and bio-energy residues. In addition, it assessed the calorific values of sweet sorghum to clarify its potential as energy crop in the region. Furthermore, it statistically analysed the ash remaining after burning three bio-energy residues, bagasse, oil cakes and fermented sludge of biogas production, to identify their potential for agricultural use. Finally, the study calculated alkali content based on nutrient content and GCVs. Significant differences were found among the GCVs of the investigated materials. Among the crop residues, the least significant difference (LSD) (P ≤ 0.05) of the calorimetric values was 76.26 kJ/kg, and among the by-products of bio-energy production, it was 20.80 kJ/kg. Significant differences were also found in nutrient content. In the case of the alkali content of bio-energy residues, the LSD was 0.04 kJ.kg^-1. For the bagasse and compost, the study recommends some technical operations to avoid slagging.

This study was conducted to model and optimise the efficiency of a disc plough on loamy-sand soil in South-East Nigeria to aid farmers to examine and choose the right ploughing implement based on the soil type for an effective and bountiful production. The operational speed and cutting depth were taken as factors for the study of the plough efficiency. The results revealed that the highest field efficiency of 80% was noted when the plough worked at the cutting depth of 30 cm and a speed of 5 km·h^–1 while the lowest efficiency of 68.10% was achieved at a speed of 9 km·h^–1 and a depth of 10 cm. The quadratic model was significant for the response (P < 0.05). The results indicated that the coefficient of determination (R²) was 0.98, which specified the high correlation among the factors. The predicted R² (0.76) was consistent with the adjusted R² of 0.96. The adequacy precision of 24.89 showed a suitable indicator and that the model could navigate the design space. The optimum field efficiency and the desirability of 77.50% and 1.00 were, respectively, obtained at an optimum speed of 7 km·h^–1 and a cutting depth of 30 cm. Farmers can, however, assess and select the implements with the aid of the developed model.

In Thailand, vibration problems often occur with rice combine harvester automatic header height adjusting systems. This study aimed to identify parameters for reducing the vibration and managing response time for harvesting speed configuration. An experimental combine harvester header model was designed to automatically adjust three parameters: total movement time, time ratio, and final phase distance within vertical movement ranges of 200, 250, or 300 mm. These parameters were controlled using a proportional flow control valve and a professional learning community (PLC) control unit. The results showed that increased time ratio, final phase distance, and total movement time significantly reduced average vibration amplitude. Higher time ratios corresponded to lower vibration amplitude during changing stages but higher amplitude during stopping stages. Vibration amplitudes during starting, changing, and stopping stages ranged from 0.622 to 1.373 mm, 0.042 to 1.097 mm, and 0.132 to 0.902 mm, respectively, for 200, 250, and 300 mm vertical movement distances. To reduce vibration in the first and second wave phases, precise control of start and final speeds through time ratio and total movement time was necessary. Minimizing the time ratio and final phase distance effectively reduced vibration amplitude in the third wave phase.

In modern conditions, high-precision technologies, such as unmanned aerial vehicles (UAVs), are the basis for increasing the efficiency of agricultural land use and crop productivity. Nowadays, new technology development needs to be improved, so the study and the implementation of various innovations in this field are quite relevant and important. The research aimed to find effective pesticides and a selection of spraying solution norms to increase rapeseed yield. The least significant difference test was used to separate the means of the dependent variables in response to predictor variables at P ≤ 0.05. It was established that herbicides applied using UAV provided effective protection of crops against cereal weeds. The spraying solution (herbicide) Evolution, together with Amigo Star, contributed to destroy of annual cereals by 94–100%, which was at level of effectiveness for ground sprayer application. The higher yield of rapeseed was 4.08 t·ha^–1 for variant with spraying solution by UAV with a consumption rate of 15 L·ha^–1 and corresponding indicator reaches 4.13 t·ha^–1 with a rate of 200 L·ha^–1 for ground-based spraying. The advantage of using UAVs is the quicker application, as well as a lower rate of water consumption for preparing spraying solution, compared to ground spraying.

Low-temperature drying (withering) is the first stage in black tea processing. Determination of appropriate end moisture content of green tea leaf as well as temperature and relative humidity (RH) maintained during withering eventually aid the final quality of the processed tea. Therefore, the tea leaf withering (partial drying) properties were evaluated in an environmental chamber using mathematical models. The temperatures and RH considered were 25, 30, 35 °C and 80, 85, 90%, respectively. A total of nine combinations of temperature and RH were considered by keeping one parameter constant. The conditions were taken adhering to that of the climatic conditions of Assam, India. The withering data from experiments were fitted into five drying models using the curve fitting method. The Page model gave better predictions with an R2 value of 0.9989 at 30 °C temperature and 90% RH. The total phenolic and flavonoid contents of the tea leaf samples were evaluated. The best results were 50.60 ± 0.02 mg GAE·g–1 (GAE – gallic acid equivalent) and 22.47 ± 0.01 mg QCE·g–1 (QCE – quercetin equivalent) at 30 °C withering temperature.

Detailed performance testing of agricultural machinery is very important in determining its value in use. These measurements cannot be limited to laboratory tests, such as braking the power take-off (PTO) shaft of  a tractor or performing dynamic tests of implements in a soil bin. Field tests are the ultimate way to test the capabilities of agricultural machinery. However, during such field tests, there are many parameters that can interfere with and affect the test results, such as inhomogeneity of the soil and tyre characteristics. In order to minimise these effects as much as possible, Hungarian University of Agriculture and Life Sciences (MATE) Institute of Technology, Agriculture Engineering Labs. has developed a dynamometer vehicle with an electronic brake control system that is suitable for measuring the traction characteristics of agricultural tractors and other terrain vehicles. It  is also capable of testing different track systems and tyre-soil interactions. This paper introduces this special test vehicle by presenting measurement results and also describes other interesting applications for the agricultural community.

In recent years, the concept of digitalization has gained increasing attention in the field of agriculture. The adoption of digital technologies such as sensors, drones, and precision farming tools has the potential to revolutionize how agricultural production is carried out, leading to increased efficiency, productivity, and sustainability. This study examines the current state of digitisation and the use of digital tools in agriculture among Hungarian farmers. The uptake of digitalisation has been slow, and more comprehensive policies and strategies are needed to improve progress. The study shows that while there are positive developments, such as the increasing use of precision technologies, there is still a lack of digital infrastructure and skills, as well as limited access to finance and information. The study concludes by making recommendations for policy makers, stakeholders and farmers to enhance the digitalisation of agriculture in Hungary.

The commodity rice in Indonesia and the administration of rice fields are given particular focus by the government. Spraying activities are known to increase the risk of exposure to chemicals for farmers, resulting in a loss of working days for 3–7 days. It is necessary to carry out ergonomic interventions for spraying activities to make the activity safer for farmers. This research aims to identify the ergonomics and safety problems of spraying activities in rice field farming, to analyse and develop intervention parameters to solve issues in spraying activities, and to generate innovative design concepts to overcome spraying problems. Prospective users assign importance weights to the twelve functional requirements. The light sprayer has the highest weight, meaning users need a lightweight sprayer. The relationship between the customer and the functional requirements can be strong, moderate, weak, and zero (no ties). This relationship determines the technical importance of the rating. From the assessment of the relationship between the customer and the functional requirements, it can be seen which technical specifications should be prioritised for developing the product. An automated system is the technical specification that should be prioritised because it has the most significant weight on meeting the consumer needs.

Recently, non-thermal technologies have emerged as a means to ensure the safety of agricultural products while also promoting plant growth and reducing pathogenic and chemical contamination of seeds. An experiment was conducted to investigate the effect of various treatments on the germination characteristics of alfalfa seeds. The experiment utilised a completely randomised design with five treatments and three replications, including cold plasma exposure, direct current (DC) electromagnetic field, magnetic field, and a combination of plasma exposure with magnetic and electromagnetic fields. The treated seeds were compared to the control seeds (without exposure) in terms of seedling length, germination rate index (GRI), vigor index, and seed germination. The results indicated that cold plasma treatment and a combination of plasma and magnetic field treatment significantly increased the germination rate compared to the control and other treatments. Furthermore, the combined treatment of plasma and electromagnetic fields, as well as the individual treatment with magnetic fields, resulted in a significant increase in root length and, consequently, the allometric coefficient. Non-thermal technologies are a promising approach to enhancing seed performance, particularly in terms of the rate of germination and seedling length.

Diversity in the characteristics of agricultural locations has the potential to develop. Unfortunately, the weak transfer of technology based on the characteristics of the location indicates that this potential cannot grow properly. This research aims to synthesise a technology transfer model for an agricultural technology park (ATP) by considering site-specific conditions. This cross-case study was conducted at selected ATP locations. Model synthesis uses the system development life cycle stages of initiation, analysis, and design. The resource-based view approach was broken down into several variables during the analysis stage. Three location-specific technology transfer models were successfully developed: a technology transfer model based on highland specificity, a unique technology transfer model for urban farming, and a tourism village-based model.

This paper presents the experimental research of factors influencing the UDS 214 excavator efficiency. The hydraulic oil flow rate is measured in hydraulic circuits for controlling the moving of the bucket of the UDS 214 ex­cavator. From the measured values, the total power losses of the individual hydraulic circuits and their efficiencies are evaluated by calculations and measurements. Furthermore, the times of the excavator cycles during a soil excavation and loading of the transport vehicle were measured. From the measured operating cycle times of the excavator, the average value of the operating cycle time was evaluated and, from this average time, the theoretical performance and the operating performance of the given excavator in the given operational states were calculated. Then, at the end of the paper, the individual calculated power losses as well as the efficiencies of the hydraulic circuits for controlling the moves of the excavator are evaluated. According to the findings, the swing hydraulic circuit of the excavator, which has the second highest power loss of 5.926 kW and its percentage in the average tested cycle time of the excavator is 48%, seems to be a suitable hydraulic circuit for the innovation.

Drip irrigation is a highly efficient method for watering crops, as  it delivers water directly to the roots and minimises wastage due to evaporation or runoff. This paper presents the development and implementation of  a low-cost drip irrigation control system that uses both time- and soil sensor-based approaches. The system’s efficiency was compared through a field experiment of melon growing, divided into three categories and four replications using a completely randomised design. The treatments include: T1 [time-based irrigation (TBI)], T2 [soil moisture-based irrigation (SMI)], and T3 [hand watering irrigation system (HWI)]. Results indicated that the TBI technique resulted in faster plant growth compared to the other treatments, as evidenced by increased leaf widths, lengths, numbers, and stem diameter. All irrigation techniques showed significant differences in yield characteristics, with TBI and SMI producing no differences in the first flowering day of female fruit widths, lengths, and weight of melon. However, the HWI treatment resulted in lower fruit length and weight yields. Cost analysis showed that the system is beneficial as  a very low-cost device that is affordable, precise, and useful for measuring and controlling irrigation-related parameters for melon cultivation.

The delightful pungency, aromatic compounds and phytochemicals in some spices make them indispensable in local food systems and native medicine, hence, driving a robust market in many parts of the world. The understanding of their drying characteristics is very important for processing and adding value, and a thin layer drying study is a proven method for achieving this. In this study, changes in the moisture content, moisture ratio, drying rate and effective diffusivity of alligator peppers, ginger and turmeric were investigated at three drying temperatures 50, 60, and 70 °C following standard procedures. Five models were proposed to simulate the drying process. Non-linear regression was used to establish the coefficient of determination (R²), sum of square error (SSE) and root mean square error (RMSE) for each model to determine the model of the best fit. The Page model gave the best fit for ginger while the logarithmic model was best fitted for alligator peppers and turmeric. The effective diffusivity ranged from 1.79–3.08 × 10^–9, 8.44–9.74 × 10^–9, and 4.06–6.49 × 10^–9 m²·s^–1 for alligator peppers, ginger and turmeric, respectively. The activation energy ranged from 16.5–22 kJ·mol^–1·K^–1 for the three spices. These findings promise improvement in the drying, processing and handling of spices, thereby boosting the obtainable income from the value chain.

Pyrolysing agricultural crop residues and other biomass constitutes a newer method of transforming often difficult, waste materials into a novel type of soil amendment/additive. Simultaneously, this process also makes it possible to exploit part of the energy released in the agricultural production. Biochar, viewed as the solid product of biomass pyrolysis, is a remarkable, porous material, rich in carbon. Two agricultural crop residues, such as wheat and barley straw, were selected for the experimental studies. The results indicate that the practical temperature for the production of biochar from the two explored materials occurs in the vicinity of 600 °C. Starting at this temperature, the biochar produced complies safely with the principal European Biochar Certificate standards (EBC 2012). Thus, for the wheat straw and barley straw - originated char, the content of the carbon amounts to 67.2 and 67.0 mass %, the atomic ratio H : C is as large as 0.032 and 0.026, and the specific surface area amounts to 217 and 201 m².g^-1, respectively.

The aim of the present study is the development of an electronic nose system prototype for the classification of Gyrinops versteegii agarwood. The prototype consists of three gas sensors, i.e., TGS822, TGS2620, and TGS2610. The data acquisition and quality classification of the nose system are controlled by the Artificial Neural Network backpropagation algorithm in the Arduino Mega2650 microcontroller module. The testing result shows that an electronic nose can distinguish the quality of Gyrinops versteegii agarwood. The good-quality agarwood has an output of [1 -1], while the poor-quality agarwood has an output of [-1 1].

A mathematical model for predicting the peeling efficiency of a cassava peeler was developed using a dimensional analysis based on Buckingham' s pi theorem. The model was validated using data from experimental studies which revealed a maximum coefficient of determination of R2 = 0.8366 between the measured and predicted values. The developed model proved appropriate in estimating the peel removal efficiency for a cassava peeler by up to 83.66%. There was no significance difference between the experimental and predicted values at a 0.05 significance level.

A forced convection automatic cabinet dryer integrated with a data logger was designed and fabricated. The okra samples were dried in the dryer at drying temperatures of 50, 60, and 70 °C and at three different load densities of 200, 300, and 400 g at a continuous air velocity of 0.7 m.s^-1. Energy and exergy analyses of the drying process were performed. The obtained results showed that the energy efficiency, energy utilisation, and utilisation ratio increased from 26.59 to 68.24%, 5.47 to 114.36 W, and 0.36 to 0.71 as the temperature increased to 70 °C, respectively. The inflow, outflow, and exergy losses were in the range of 7.02 to 26.14 W, 4.43 to 14.16 W, and 2.59 to 11.98 W, respectively, while exergy efficiency varied from 49.15 to 63.47%. The findings show that exergy efficiencies decrease with an increase in the drying temperature, but increase with a lower load rate. The index of sustainability varies from 2.14 to 2.77, the value increases as the load density decreases while it decreases with a temperature increment.

This study focused on drying moringa leaves using a cabinet dryer. The impact of the 40, 50, and 60 °C drying air temperatures on the moisture content of the leaves at a constant air velocity with variation in weight (40, 80, and 120 g) was considered. Ten drying models were fitted to the drying data to describe the drying parameters of moringa leaves. The best model was chosen based on the highest coefficient of determination (R²), and the lowest sum of square error (SSE) and root mean square error (RMSE) values. The Henderson and Pabis model best described the drying characteristics of the moringa leaves having the highest R² (0.9888) and lowest SSE (0.0401) and RMSE (0.0604). The effective moisture diffusivity increased with the temperatures ranging from 8.72 × 10^–9 to 1.40 × 10^–8 m²·s^–1. The activation energy ranged from 90.4636, 40.4884, and 22.7466 KJ·mol^–1 for 40, 80, and 120 g, respectively.

Tillage intensity can affect soil quality through soil aggregates, which are strongly associated with organic carbon. In this study, we evaluated the effect of different intensity tillage (conventional ploughing (CP), shallow ploughing (SP), deep cultivation (DC), shallow cultivation (SC), no-tillage (NT)) on soil organic carbon (SOC) and soil aggregates at the 0-5, 5-10, 10-20 and 20-30 cm layers and root biomass at the 0-10, 10-20 and 20-30 cm layers. The field experiment on spring barley (Hordeum vulgare L.) consisted of a split-plot arrangement with four replications. Dry soil aggregates were evaluated using the mean weight diameter (MWD) index. Wet aggregates were assessed using a water-stable aggregate (WSA) index. We identified that tillage intensity significantly influenced the MWD index at four soil levels. Shallow tillage showed greater results at 0-5 and 5-10 cm depths. However, deep tillage increased the MWD at 10-20 and 20-30 cm depth. NT was dominated by evaluating the WSA at every level of the soil. SOC was correlated with WSA. The highest SOC was found under NT. The different tillage intensities did not significantly affect root biomass.