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With the increase in the world population and the ensuing surge in organic waste, effective management strategies are crucial to prevent environmental pollution. This study aims to address this challenge by utilising organic waste (OW) as the substrate for the production of lactic acid (LA) and volatile fatty acids (VFAs) through anaerobic bioprocessing. The substrates used, included grass, starch, and fruit wastes inoculated with non-sterile inoculum landfill soil (LS). The anaerobic bioconversion was performed by varying the substrate to the inoculum. The results unveil that a digester loaded with 150 g·L^–1 of fruit waste, exhibits the highest concentration of LA, reaching a significance of 25 mmol·L^–1. A digester fed with 100 g·L^–1 starch, also manifests significant LA production (18.50 mmol·L^–1). A digester, supplied with 150 g·L^–1 starch waste, showcases the highest VFA (92.5 mmol·L^–1). Intriguingly, the anaerobic bioprocessing of the grass substrate did not produce LA at all, yet al. the substrates showcased VFA production, albeit with fluctuating and lower concentrations. This study highlights the potential of incorporating simple sugar for enhanced LA production and starch-based substrates for increased VFA production when utilising LS as the inoculum. The anaerobic bioprocessing shows promising outcomes for the future development in sustainable waste utilisation.

In order to make harvesting table olives profitable, mechanical harvesting has become an absolute necessity. Many small Andalusian producers face structural and financial constraints in implementing the mechanisation of harvesting and, as a consequence, the fruit is still harvested manually. A manual inverted umbrella (MIU), initially designed for harvesting oil olives, was evaluated in order to determine the extent in which this device can optimise the harvesting without jeopardising the fruit quality. Simultaneously, the effects of a diluted lye treatment, applied to prevent the proliferation of brown spots caused by bruising during mechanical harvesting, was also studied. The quality of the harvested fruit was evaluated after complete fermentation. The results indicate that when no diluted lye treatment was applied, using the MIU resulted in a slightly inferior fruit quality. However, when the amount of heavily damaged fruit is taken as a standard, the MIU presented results comparable to those obtained by manual harvesting. The MIU does, therefore, offer small producers an efficient alternative, given that manual harvesting costs are up to three times higher than the costs incurred during MIU harvesting.

This study develops and validates a multilayer diffusion model of wheat grain hydration that incorporates layer-dependent diffusion coefficients for bran, endosperm, and germ. The moisture transport is formulated using Fick’s law with two interface formulations: (i) classical continuity of the concentration and flux and (ii) an interlayer resistance formulation that permits concentration discontinuities. Diffusion coefficients and geometric parameters were determined experimentally; A 3D grain model (structured-light scanning, COMSOL Multiphysics) informed the computational domain. Numerical solutions combined eigenfunction expansions with finite-difference discretisation near the interfaces. Across eight winter wheat varieties, the diffusion coefficients spanned 11.6 – 20.5 × 10–12m2·s–1 (mean 16.27 ± 3.08 × 10–12m2·s–1 ). Relative to the continuity model, the resistance model reduced the early-stage endosperm over-prediction by ~ 0.6–1.0 % (absolute) and lowered the whole-grain RMSE by ~ 20–30% over 0–240 min. These results support the role of thin moisture-retaining films as active barriers and yield smooth, real-time-ready outputs suitable for the automated control of pre-milling hydration; the framework is extensible to full 3D transient simulations.

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.

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.

Indonesia, as a leading coconut producer, generates a substantial amount of coconut pulp from coconut milk extraction, which can be further processed into low-fat desiccated coconut. However, the drying process induces browning, reducing its whiteness and overall quality. Sodium metabisulphite is commonly used to prevent browning, but excessive use raises health concerns. In this study, the optimisation of the drying temperature and sodium metabisulphite concentration was conducted to minimise the browning while maintaining the quality of low-fat desiccated coconut. Using Response Surface Methodology (RSM) with a Central Composite Design (CCD), responses such as the browning index (BI), whiteness index (WI), moisture content, yield, free fatty acids (FFAs), ash, fat, protein, total phenolic content (TPC), and crude fibre were examined. The results showed that both the drying temperature and sodium metabisulphite concentration significantly influenced the physicochemical properties. The optimal conditions were identified at 62.505 °C and 380.059 ppm sodium metabisulphite, resulting in a whiteness index of 87.219, browning index of 5.1025, yield of 43.125%, moisture content of 2.3%, and free fatty acid content of 4.45%. These findings highlight an effective strategy for reducing the additive dependency while maintaining the physicochemical quality of low-fat desiccated coconut.

This study explores the construction of small reservoirs (SRs) as a strategic solution to address water scarcity in Kashkadarya Province, Uzbekistan, where agricultural productivity is heavily dependent on irrigation. By utilising geographic information system (GIS) and remote sensing (RS) technologies, optimal locations for reservoirs were identified, focusing on improving the water availability for irrigation during critical periods. The research highlights the socio-economic and environmental benefits of SRs, including enhanced agricultural yields, increased employment opportunities, and reduced reliance on energy-intensive pumping stations. The findings indicate that the construction of an 18 Mm³ reservoir in the Ayakchisoy River could supply water to 26.5 thousand hectares, thereby improving the region’s resilience to climate variability. This approach offers a sustainable framework for managing water resources in arid regions, contributing to food security and economic stability.

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.

Harvest facilities limit the possibilities of small producers to produce a high-quality olive fruit. This paper discusses the efficiency of a newly designed manual picking device as a possible solution to these specific challenges as confronted in most regions of the Mediterranean basis. The efficiency and cost of the picking method were compared to traditional olive picking using nets, taking a different number of operators and branch shakers into account.

This study optimised the drying process of kaffir lime leaves (Citrus hystrix DC.) to extend the shelf life and preserve the quality by reducing the moisture content. A Central Composite Design (CCD) under the Response Surface Methodology (RSM) framework was employed, with the temperature (55 °C, 60 °C, 65 °C) and drying time (5, 5.5, 6 h) as the variables. Experiments were conducted with a mechanical food dehydrator, and the parameters evaluated included the water content and drying yields. The optimal condition was identified as 60 °C for 5 h, resulting in a drying yield of 33.3% and a final moisture content of 7.153 (% w.b.), which meets the quality standards for dried products. The novelty of this research lies in the application of RSM to determine effective drying conditions for kaffir lime leaves, which are not widely used, but have good economic potential. The research proved that drying with the right conditions can greatly improve the quality and stability of dried kaffir lime leaves.

Banana quality is influenced by many factors, including variety and level of fruit ripeness. This quality can be evaluated from various points of view, one of which is the rheological consideration. Rheological properties are very important to study because they determine the design of equipment and processes, and minimise product damage. The aim of this research was to analyse and model the effect of variety and ripeness level on the rheological properties of banana fruit by applying a creep test. This research was carried out using a factorial experimental design 3 × 3 with 5 replications. Three varieties of banana, namely Ambon (Musa parasidiaca var. sapientum L. Kunt.), Raja (Musa parasidiaca L.), and Kepok (Musa acuminata balbisiana Colla) and each in three levels of ripeness, namely mature green, half ripe, and ripe. It was found that the parameters of the rheological properties of bananas changed according to the ripeness level (P < 0.05). The values of these rheological parameters decreased as the bananas ripened. Meanwhile, the variety and the interaction between variety and ripeness had no significant influence on the rheological parameters measured (P > 0.05). The constants of the four-element Burger model changed with the ripeness in all banana varieties. The Burger model with four elements could accurately predict the strain value of bananas tested in the creep test.

Reference crop evapotranspiration (ET_o) is a vital hydrological component influenced by various climate variables that impact the water and energy balances. It plays a crucial role in determining crop water requirements and irrigation scheduling. Despite the availability of numerous approaches for estimation, accurate and reliable ET_o estimation is essential for effective irrigation water management. Therefore, this study aimed to identify the most suitable machine learning model for assessing ET_o using observed daily values of limited input parameters in tropical savannah climate regions. Three machine learning models – a long short-term memory (LSTM) neural network, an artificial neural network (ANN), and support vector regression (SVM) – were developed with four different input combinations, and their performances were compared with those of locally calibrated empirical equations. The models were evaluated using statistical indicators such as the root mean square error (RMSE), coefficient of determination (R²), and the Nash-Sutcliffe efficiency (NSE). The results showed that the LSTM model, using the combination of temperature and wind speed, provided more reliable predictions with R² values greater than 0.75 and RMSEs less than 0.63 mm·day^–1 across all the considered weather stations. This study concludes that, especially under limited data conditions, the developed deep learning model improves the ET_o estimation more accurately than empirical models for tropical climatic regions.

Fatigue behind the wheel has been addressed repeatedly for at least 15 years. Various research projects, studies, and systems have been developed to prove the effect of fatigue on the number of accidents and possibly to inform drivers that this situation has occurred. The article examines the influence of stimulants on the fatigue of young agricultural machinery drivers. Commonly available means for reducing driver fatigue were chosen as stimulants (coffee, tea, maté, guarana, energy drink, lemon extract with sugar). A special test station with automatic reaction time evaluation was developed to test drivers’ reaction ability (responsiveness). Furthermore, the effects on the physical condition of the tested persons (systolic blood pressure, diastolic blood pressure, blood pressure amplitude and heart rate) were investigated. The conducted experiments confirmed a statistically significant effect of all tested stimulants, except for tea, for which no statistically significant changes in the monitored parameters were observed.

A free electricity tandem-twin-hybrid-solar-biomass dryer comprised of two drying rooms and operated with solar and biomass energy combustion of 10 kg rubber wood per hour separately to dry Robusta coffee cherries with 3, 6, 9, and 12 cm bed thicknesses were studied with the drying completion time (tc), number of defects (ND), and colour parameters, i.e., lightness (L*), hue angle [H(^o)], and chroma (C), used as the performance indicators. The experimental results indicated that the drying room, bed thickness, and drying room-bed thickness interaction significantly affected the tc and ND and bed thickness only significantly affected C for both the solar energy drying and the biomass energy drying. The solar energy drying generated a drying air temperature of 44.6 ± 3.5 °C with a tc of 70.9–90.2 h for the front drying room and 40.1 ± 2.8 °C with a tc of 77.2–116.5 h for the rear drying room, whereas the biomass energy drying produced a drying air temperature of 57.2 ± 3.6 °C with a tc of 34.1–44.9 h for the front drying room and 45.6 ± 6.0 °C with a tc of 56.3–96.6 h for the rear drying room. Both drying processes produced coffee beans with the NDs less than 11 qualified for Grade 1 with similar colour characteristics.

Conventional irrigation practices result in a substantial amount of water loss with okra cultivation. Although micro-irrigation can address this issue by delivering water directly near the rootzone, it requires manual operation. These issues, however, can be resolved with the introduction of a smart micro-irrigation system. This study aims to develop a smart micro-irrigation system for okra, in conjunction with the sub-components of drip irrigation, a microcontroller, and a soil sensor. The experiment was laid out with a randomised complete block design (RCBD) having three treatments: (i) control irrigation (T₁), (ii) drip irrigation (T₂), and (iii) smart micro-irrigation (T₃). The experimental field was irrigated based on soil moisture regimes in the crop rootzone. The plant growth, yield, and water use efficiency were assessed to evaluate the system. The results showed no significant differences among these treatments (at P < 0.05). The best water usage efficiency (15.98 kg·m^–3) was observed in the T₃ treatment, which also provided about 13.10% water savings compared to the conventional irrigation. This study indicates that a smart micro-irrigation system could be a promising technology for water-efficient okra cultivation.

The drying and colour kinetics of H₂O₂-bleached pineapple fibres were studied to determine an optimum drying condition and appropriate drying and colour kinetic models. The experiments were conducted under drying air temperatures of 40, 50 and 60 ºC, air velocities of 0.27, 0.38 and 0.42 m×s^–1 and hydrogen peroxide (H₂O₂) concentrations of 1, 3 and 5% by volume arranged in a three-factor factorial experimental design. Colour values were quantified by the CIELab system where L* is the lightness value, a* is redness/greenness and b* is yellowness/blueness. Total colour difference (ΔE), chroma, hue angle, browning index (BI) and whiteness index (WI) were calculated. The L* value, a* value, b* value, WI, BI, hue angle, and chroma were significantly affected by the interaction of the three factors. A non-parametric test was conducted for the drying rate data and showed that the drying rate was influenced by different treatments. Tensile strength was not affected by any of the factors. The optimum drying condition was determined to be 57 ºC, at an air velocity of 0.345 m·s^–1, and H₂O₂ concentration of 4.8%. The exponential model adequately described drying data. Zero-order kinetic equation described ΔE while L*, a*, b*, chroma, hue angle, WI and BI were satisfactorily described by the first-order kinetic equation.

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.

Precision agriculture is increasingly relying on tractor auto-steer systems to boost productivity and optimize crop inputs. Identifying field variations and performance, on the other hand, is necessary for giving site-specific recommendations. This study reports the field operating performance indicators of manual (MG), semi-automatic (SG), and automatic (AG) tractor guidance for weed control in wheat production in Southern Italy. Performance indicators include effective worked area, overall working time, effective field capacity, field efficiency, fuel consumption, and product usage. The SG tractor guidance working times were similar to the MG, but with significant savings in the herbicide spray solution and work quality. In terms of all parameters examined, the AG outperformed the SG and MG. The AG was 54% faster than the MG, resulting in an increased area worked and effective field capacity of 5 and 46%, respectively. The total time (effective time plus non-productive time) was reduced by 28%, while overlapped areas by 88.9%. Herbicide and fuel input was reduced by 30 and 11.5%, respectively. A streamlined environmental analysis indicated that AG could reduce the energy and carbon intensity of the one-time weed control process by 25 and 27% for each hectare. Our results confirm that auto guidance provides numerous benefits (e.g., machining uniformity, increased work quality, reduced resource use, and reduced environmental burdens), supporting the larger goal of agricultural production sustainability.

One of the main causes of having low crop efficiency in Peru is the poor management of water resources; which is why the main objective of this article is to estimate the amount of irrigation water required in quinoa crops through a comparison between the machine learning and AquaCrop models. For the development of this study, meteorological data from the province of Jauja and descriptive data of quinoa crops were processed and a simulation period was established from June to December 2020. From the simulation carried out, it was determined that the best model to predict the required irrigation water is the Adaptive Boosting (AdaBoost) model in which it was observed that the mean and standard deviation of the AdaBoost models (mean = 19.681 and SD = 4.665) behave similarly to AquaCrop (mean = 19.838 and SD = 5.04). In addition, the result of ANOVA was that the AdaBoost model has the best P-value indicator with a value of 0.962 and a smaller margin of error in relation to the mean absolute error (MAE) indicator with a value of 0.629. Likewise, it was identified that, for the simulation period of 190 days, 472.35 mm of water was required to carry out the irrigation process in red quinoa crops.

Tillage operations in dry soil conditions have increasingly been used in Iran in recent years. However, due to the recent droughts, the choice of suitable implements to reduce the clod and draught force is still under investigation. This study was aimed at determining the effect of the geometry of a bent leg tillage implement on the soil pulverisation and draught force in dry soil conditions. The treatments included three bent leg tillage depths (10, 15, and 20 cm) and three forward speeds (6, 9, and 12 km·h^–1). The effect of the bent leg tillage implement on the clod mean weight diameter (MWD) and draught force was studied using a split plot experiment with three replications. The results showed that the tillage depth and forward speed affected the MWD and the draught force. Increasing the tillage depth from 10 to 20 cm increased the MWD and draught force by 24.9 and 35.1%, respectively. Increasing the forward speed from 6 to 12 km·h^–1 decreased the MWD by 7.4% and increased the draught force by 40.0%. These findings show that the bent leg tillage technology has the potential to reduce the MWD and draught force at higher forward speeds. Therefore, a bent leg tillage implement can be suggested as a proper implement for tilling in dry land conditions.

The purpose of this research is  to design a rounding cylinder tube on a coffee roaster using an electric heating element that will be used to roast coffee. The roasting process also uses an electric motor to rotate the cylindrical drum so that the stirring process becomes even. The research was conducted using engineering methods including identification of problems, roasting machine design formulation, prototyping, functional testing, and performance testing. The data analysed are roasting capacity, roasting temperature and the need for electrical energy used. The results showed that the roasting capacity was 2.3 kg·h^–1. The serving of coffee for dark roast maturity levels can be ended when the temperature has reached a temperature of 201 °C. The need for electrical energy in the heater for roasting arabica coffee beans with a maturity level of  a dark roast for 1 hour 54 minutes obtained an average value of 3.4 kWh, with the need for electrical energy for roasting arabica coffee beans which is 1.35 kWh.

Eggshell is a solid waste, with production of several tons per day. Eggshell is mostly sent to the landfill with a high management cost. It is economical to transform the eggshell waste to create new values from these waste materials. The present article is an attempt to summarize the possible applications of eggshell. The eggshell waste can be used (a) at biodiesel production as a solid base catalyst used for biodiesel pollutants minimization, reducing the production costs of biodiesel and making the process of biodiesel production fully ecological and environment-friendly; (b) as an absorbent of heavy metals from wastewater as it is a serious environmental problem in the ecosystem; (c) as biomaterial in order to replace bone tissues due to the rise in the number of patients; (d) as a fertilizer and calcium supplement in nutrition for human, animals, plants, etc. Number of research articles have been included in this review to describe a methodical growth in this subject matter.

The design of animal housing and manure management systems are key factors in livestock farming. Frequent removal methods, in fact, allow for the reduction of gasses produced from fermentations of the organic matter contained in manure, that affect animal welfare and farmer health and are emitted from animal housings into the atmosphere as a consequence of ventilation. The present study aims to evaluate the performance of a Robotic Scraper (RS) operating on the floors in a full-scale, operative free-stall dairy barn. The research is focused on the evaluation of gaseous emissions from the two types of floors (concrete and rubber mat coated), and with and without RS operation. The floors with rubber coating demonstrated higher emission rates of ammonia (NH₃), carbon dioxide (CO₂), nitrous oxide (N₂O), and methane (CH₄) compared to the uncovered concrete floors, both before and after RS operations. The operation of RS, furthermore, determined significant reduction of greenhouse gasses (GHG) but did not have relevant effect in terms of NH₃ emission, which reduced only of 1.4% from concrete floors, but increase of 12.7% from rubber coated floors.

In this study, the effect of tine type, adding wing, operating depth and forward speed on the draft requirement of subsoil tillage tines was investigated in clay loam soil. Three subsoil tillage tines (subsoiler, bentleg and paraplow), four levels of forward speed (1.8, 2.3, 2.9 and 3.5 km/h), three levels of depth (30, 40 and 50 cm) and winged and no-wing tines were examined with the exception of bentleg as it would not be winged. It was revealed that draft of the tines is less affected by forward speed but is much affected by tine type, depth and wing. It was observed that an increase of speed and depth plus adding wing results in an increase of draft in all tines. Additionally, it was found that in all depths and speeds, subsoiler required more draft than paraplow and paraplow required more draft than bentleg. Multiple regression models including the studied parameters were developed to predict the draft requirements for each tine with high accuracy.

A traceability system is an effective tool to guarantee safety in horticultural products and to improve supply chain transparency. A direct data matrix (DM) code created with carbon dioxide laser (wavelength 10.6 µm) can be used as a trust mark on bananas. In this study, green bananas were marked with the above-mentioned CO₂ laser. Subsequently, the samples were held under storage conditions. Images of the codes on bananas were captured by using two different cameras; i.e. hyperspectral imaging camera and charge-couple device (CCD) camera. Image processing was used for evaluating print quality of 2D codes based on the ISO/IEC 15415 standard. The quality of the codes on bananas mainly depends on some parameters: laser power, laser energy, marking time per module and storage time. The best readability results were achieved by using laser power of 1.8 W and marking time of 0.09 s per data matrix module, whereby an 80-100% readability of DM codes after the storage was obtained.

Translocation of tracers incorporated into the upper layer of topsoil was evaluated in the course of seedbed preparation for winter wheat. Aluminium cubes with the edge length of 16 mm were used as tracers that were placed into the soil before its tillage into furrows perpendicular to the direction of passes. After the passes of the OPALL-AGRI combined cultivator, the tracers were searched and marked using a metal detector. The translocation of tracers was evaluated during multiple passes on flatland and on the slope. During the seedbed preparation on the slope, downslope and upslope passes in a fall line direction were chosen. Results of the tracers movement measuring that simulate the soil particle translocation indicate a pronounced movement of the upper layer of topsoil during multiple downslope passes of the combined cultivator. A significant translocation was also observed after passes on flatland. A significantly smaller lengthwise translocation of tracers was found out at upslope passes. The type of translocation on flatland and upslope was quite similar, on the other hand, downslope movement was much larger. The upslope passes were found to have a very limited function with regard to the correction of the undesirable downslope movement of soil particles that occurs in the course of tillage.

The using possibilities of secondary raw materials produced during the liquid biofuels production such as bioethanol and biodiesel, and also those produced during solid fuel production was determined. The study presents combustion of distiller's dried grain with solubles (DDGS) and pressing refuse of rapeseed methyl ester (RME). The combustion was done in gravimetric oven, according to the standards, under the laboratory conditions. Combustion heat of samples was measured with calorimeter IKA C5000. The results show the average combustion heat of 20.91 MJ/kg for DDGS and 18.996 MJ/kg for RME. Results are chronologically presented in tables and figures.

This article describes the results of the analysis of correlation between the soil electrical conductivity and BPEJ (valued soil-ecological units). The measurements were made in 2006 at the School Agribusiness Land Farm in Lány established by the Czech University of Life Sciences in Prague. The soil electrical conductivity (EC) was measured by the contact method using a sensor with six electrodes. The soil EC data measured were compared with the data obtained from BPEJ maps. The aim was to verify if any relationship exists between the soil EC and BPEJ. The results achieved show that the same dependency exists between the values of the main soil unit of the BPEJ code and the soil EC. The results achieved can be used in the precise agriculture system to improve the decision process.