Digitalization has impacted agricultural and food production systems, and makes application of technologies and advanced data processing techniques in agricultural field possible. Digital farming ...aims to use available information from agricultural assets to solve several existing challenges for addressing food security, climate protection, and resource management. However, the agricultural sector is complex, dynamic, and requires sophisticated management systems. The digital approaches are expected to provide more optimization and further decision-making supports. Digital twin in agriculture is a virtual representation of a farm with great potential for enhancing productivity and efficiency while declining energy usage and losses. This review describes the state-of-the-art of digital twin concepts along with different digital technologies and techniques in agricultural contexts. It presents a general framework of digital twins in soil, irrigation, robotics, farm machineries, and food post-harvest processing in agricultural field. Data recording, modeling including artificial intelligence, big data, simulation, analysis, prediction, and communication aspects (e.g., Internet of Things, wireless technologies) of digital twin in agriculture are discussed. Digital twin systems can support farmers as a next generation of digitalization paradigm by continuous and real-time monitoring of physical world (farm) and updating the state of virtual world.
•Mathematical models of solar collector, latent heat storage and dryer are presented.•Solar dryer with and without latent heat storage unit are compared.•Heat storage unit allows effective ...temperature control if sized correctly.•Presence of energy storage had modest effect on drying time and moisture uniformity.
Latent heat storage has gained attention as an energy storage method for solar drying due to its high storage density. However, its overall impact in drying performance has not been sufficiently investigated. This study presents detailed, validated mathematical models necessary for the transient simulation of a solar dryer with latent heat storage with the aim of assessing the effect that such storage has on the deep bed drying of wheat. Computer simulations were run with weather data from Germany. A fixed bed dryer with a capacity of one ton was assumed and the size of the solar air heater and latent heat storage unit was varied, as well as the type of phase change material. In drying wheat without storage from 22% to 13% w.b. (0.28 to 0.15 kg kg−1 d.b.), increasing solar collecting area from 6 to 15 m2 reduced drying time by around 50% but resulted in excessive temperatures. At equal collecting area, the use of latent heat storage changed drying time by −5% to +13.9% depending on component sizes, but the drying air temperature was limited effectively if solar collection and storage units are properly sized in relation to each other. Failure to do so can result in higher drying temperatures than recommended or bring little additional benefit. Moisture uniformity at the end of drying was slightly improved by up to 10% in the presence of the storage unit due to a reduction in the average drying temperature. The presented models and corresponding simulation programs are a useful tool to size the components of a solar dryer with and without latent heat storage.
Posture detection targeted towards providing assessments for the monitoring of health and welfare of pigs has been of great interest to researchers from different disciplines. Existing studies ...applying machine vision techniques are mostly based on methods using three-dimensional imaging systems, or two-dimensional systems with the limitation of monitoring under controlled conditions. Thus, the main goal of this study was to determine whether a two-dimensional imaging system, along with deep learning approaches, could be utilized to detect the standing and lying (belly and side) postures of pigs under commercial farm conditions. Three deep learning-based detector methods, including faster regions with convolutional neural network features (Faster R-CNN), single shot multibox detector (SSD) and region-based fully convolutional network (R-FCN), combined with Inception V2, Residual Network (ResNet) and Inception ResNet V2 feature extractions of RGB images were proposed. Data from different commercial farms were used for training and validation of the proposed models. The experimental results demonstrated that the R-FCN ResNet101 method was able to detect lying and standing postures with higher average precision (AP) of 0.93, 0.95 and 0.92 for standing, lying on side and lying on belly postures, respectively and mean average precision (mAP) of more than 0.93.
•A transient solar air heater model using high resolution weather data is developed.•Transient model is compared to stationary model using hourly averaged weather data.•Steady approach results in ...large deviations, especially under variable cloud cover.•Large differences between approaches in useful energy above threshold temperatures.•Potential implications for latent heat storage, solar drying and other processes.
Due to the nature of solar energy, the operation of solar air heaters is fundamentally transient, but most mathematical modelling published to describe their behavior has used stationary models coupled with hourly-averaged weather data. Little attention has been paid to the transient behavior of solar air heaters under real, highly variable weather conditions. In this study, the common modelling approach using a steady-state description of solar air heaters is compared to predictions of using a transient model to which minute resolution weather data is given as input. The steady-state approach was found satisfactory, although not optimal, only under clear sky conditions, with relatively small outlet air temperature errors compared to the results obtained with the transient model. Under less favorable conditions with partial cloud cover, the outlet air temperature with the transient model presented large variations due to the sudden changes in solar radiation not captured in the steady-state approach. With the solar air heater parameters employed, instantaneous deviations of almost 15 °C were found, as well as errors in the predicted useful energy above threshold temperature levels. These results support the use of transient models of solar air heaters and high resolution weather data for accurate, short-term modelling of solar drying, latent heat storage and other highly temperature dependent processes.
The high contents of bioactive compounds make the pumpkin fruit an important crop for the development of novel functional foods for improving food security, nutrition and health. This study ...investigated the effect of drying air temperatures (50, 60 and 70 °C) and slice thicknesses (3 and 5 mm) on the drying behaviour, colour change kinetics and bioactive compounds content of the dried pumpkin slices. The effective moisture diffusivity of pumpkin increased from 2.860 × 10−10 to 9.815 × 10−10 m2/s as drying temperature increased while activation energy values ranged between 47.14 and 51.60 kJ/mol. After the drying process, Lightness (L*) and yellowness (b*) values of pumpkin decreased from 74.61 ± 1.18 to 56.50–70.15 and 61.95 ± 2.03 to 51.90–56.10, respectively whereas redness (a*) and total colour difference (ΔE) increased from 8.47 ± 0.09 to 9.98–11.07 and 0 to 10.01–17.12, respectively. Changes in L* and b* values during drying were adequately predicted by the first-order reaction kinetics while a* and ΔE followed zero-order reaction kinetics (R2 = 0.9765 to 0.9978). The reaction rate constants for colour change greatly depended on the drying air temperature. Contents of β-carotene, ascorbic acid, total phenols, flavonoids and antioxidant activity of the dried pumpkins varied between 43.80 and 58.15 μg g−1, 37.62–50.13 mg/100g, 109.60–155.92 mg GAE/100g, 49.68–67.74 mg kaempferol/100g and 61.45–80.72%, respectively. Predominantly, an increase in pumpkin slice thickness prolonged drying time and caused a greater loss of bioactive compounds and antioxidant activity. Moreover, β-carotene and ascorbic acid contents were higher in 60 °C dried pumpkin than those dried at 50 °C and 70 °C. Nonetheless, increasing the drying air temperature increased the total phenolic compounds and flavonoid contents in dried pumpkin products. The study results could be useful for the food industry and further research work.
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•Colour change kinetics of pumpkin during convective drying at 50–70°C was studied.•Drying air temperature and slice thickness affected colour change rate constants.•Degradation of yellow pigments (b*) of pumpkin followed first-order reaction model.•Reducing pumpkin slice thickness increased drying rate and β-carotene retention.•Increasing drying air temperature improved total phenols content of dried pumpkin.
Abstract
A downward roughing filter unit consisting of silica sand as the filter medium was optimized for performance towards removal of turbidity and suspended solids from handwashing wastewater. ...Design-Expert software was employed to optimize media particle size, filter depth, and flowrate. Linear and quadratic models were found to best fit the responses of turbidity and suspended solids removal, respectively. Particle size and flow rate were the only parameters with significant effects on removal of turbidity and suspended solids. Optimal conditions were found to be media particle size 0.6 mm, filter depth 12 cm, and flow rate 0.3 Lmin−1, corresponding to removal efficiencies of 62 and 67% for turbidity and total suspended solids (TSS), respectively, as predicted by the model. Validation of model at optimal conditions resulted in turbidity and TSS removal of 55 and 53%, respectively. Additionally, removal efficiencies of the roughing filter towards apparent colour, true colour, biochemical oxygen demand (BOD5), and chemical oxygen demand (COD) from handwashing wastewater were 56, 20, 32, and 5%, respectively. Overall, although turbidity of filtered water was >50 NTU, the reduction achieved by roughing filtration is a significant step in enhancing the performance of water treatment processes downstream, including filtration and adsorption by slow sand filters and activated carbon, respectively.
Technosols are characterized by a substantial quantity of artifacts or industrial wastes in the upper 100 cm. They can be used as cover caps in mining rehabilitation, in which vegetation cover is ...subsequently established. However, prolific vegetation growth can be limited by the chemical and physical properties of technogenic substrates. As further studies need to be conducted to evaluate the suitability of municipal solid waste incineration bottom ash and coal combustion residues as cover caps, the pH, electrical conductivity, total porosity, and bulk density of these substrates were measured. Furthermore, the seepage pH and electrical conductivity of the covered and uncovered technosols after saturation were determined. The municipal solid waste incineration bottom ash, 4–10 mm in diameter, showed the highest bulk density (1.16 g cm
-3
) and lowest total porosity by saturation (24.7%). In contrast, the coal combustion residues registered the highest total porosity (57.2%). The coal combustion residues also revealed a higher pH of 12.5 and electrical conductivity values of 7.8 mS cm
-1
. Furthermore, no differences were observed between the treatments for pH seepage (8.2–8.3) and its electrical conductivity (14.3–16.0 mS cm
-1
) in the covered and uncovered columns, when using a technosol. This study provides information on the use of municipal solid waste incineration bottom ash and coal combustion residues as evapotranspiration covers during mining rehabilitation. The management of municipal solid waste residues is a global challenge and the use of this resource is valuable not only for the mining industry but potentially also in other fields, such as construction. The heavy metal content of the bottom ash from municipal solid waste incineration and coal combustion residues should be studied before implementing these waste residues on a large scale.
Due to the lack of farm-gate milk processing facilities, dairy farmers have to sell raw milk, resulting in economic and quality compromises. The study compared the quality of yogurt processed in ...solar assisted yogurt processing unit with the existing milk value chain and its techno-economic feasibility. For this, an investigation of the experiment was executed where four different milk processing approaches were compared. The quality attributes for processed milk like fat (5.283%), solid-not-fat (9.0833%), salts (0.6833%), protein (3.8%), lactose (4.1%), total solids (14.383%), pH (6.87), density (1.031 kg/L) and freezing point (- 0.532 °C) were found within the standardized ranges. Similarly, for the case of yogurt, these attributes were found as fat (5.5%), solid-not-fat (8.683%), acidity (0.93%), lactose (4.73%), total solids (14.183%), pH (4.3433), density (1.039 kg/L) syneresis (9.87 mL/100 g), S. thermophilus count range (10.18-10.30 log cfu/mL) and L. bulgaricus count range (10.26-10.34 log cfu/mL). Moreover, no detection of coliform count in solar-processed yogurt, endorsed the current idea to perform three processes of heating, fermentation, and cooling in a single unit. Based on the energy sources utilized, the payback period was calculated to be 1.3-9 years with an expected lifespan of 15 years while in terms of product profit, the payback period was predicted to be 1.78 years. The processing cost per liter of milk for yogurt production was calculated to be 0.0189 USD. Considering CO
emission savings, it is anticipated that a solar-powered yogurt processing unit can generate 107.73 MWh of useful energy during its operating life with zero CO
emission.
Optimal nutrition during lactation is essential for the well-being of the mother and the infant. Studies have shown that access to nutrient-rich foods during lactation is critical as minimal stores ...of nutrients can have adverse effects. This study aimed to investigate the diversity, composition, and nutrient adequacy of diets of lactating mothers in Southwest Ethiopia.
A community-based cross-sectional survey was carried out in three districts of Jimma Zone, Southwest Ethiopia, in February 2014. A stratified multistage sampling technique was used to select 558 lactating mothers. Data were collected using a pre-tested and structured interviewer-administered questionnaire. Minimum dietary diversity for women (MDD-W) was computed from a single 24-h recall. A cut off value of 5 was used to classify the dietary diversity into achieving MDD-W or not. The proximate, mineral and anti-nutritional compositions of 12 commonly consumed foods were analysed using standard methods. Nutrient adequacy ratio (NAR) and Mean adequacy ratio (MAR) of these foods were estimated.
The mean (±SD) dietary diversity score (DDS) of the study participants was 3.73±1.03. Meeting MDD-W was positively associated with agricultural production diversity (P = 0.001) and educational level of the women (P = 0.04). Conversely, district of the study (P = 0.003) and place of residence (P = 0.019) were negatively associated with meeting MDD-W. The proximate composition (g/100g) of the sampled foods ranged between 24.8-65.6 for moisture, 7.6-19.8 for protein, 2.1-23.1 for crude fat, 2.0-27 for crude fibre, 1.0-21.2 for total ash, and 0.9-45.8 for total carbohydrate content. The calorific value ranged between 124.5-299.6 Kcal/100g. The mineral contents (mg/100g) ranged between 9.5-52.5 for iron, 2.2-4.2 for zinc, 42.6-318.2 for calcium, and 150.7-379.9 for phosphorus. The content of anti-nutritional factors (mg/100g) ranged between 11.1-178.9 for phytate and 3.7-315.9 for tannin. All the commonly consumed maternal foods were not sufficient to meet the energy, fat and protein requirements, (NAR<1). However, all diets provided adequate iron and most of the cereal-based foods provided adequate carbohydrate and minerals. The overall nutrient adequacy was below the cut-off point for all food types.
The diets of lactating mothers in Southwest Ethiopia lack diversity and nutrient adequacy. A community-based nutrition education program on the importance of diet diversity and nutrient intake during lactation based on a multi-sectoral approach is needed.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Digital farming approach merges new technologies and sensor data to optimize the quality of crop monitoring in agriculture. The successful fusion of technology and data is highly dependent on the ...parameter collection, the modeling adoption, and the technology integration being accurately implemented according to the specified needs of the farm. This fusion technique has not yet been widely adopted due to several challenges; however, our study here reviews current methods and applications for fusing technologies and data. First, the study highlights different sensors that can be merged with other systems to develop fusion methods, such as optical, thermal infrared, multispectral, hyperspectral, light detection and ranging and radar. Second, the data fusion using the internet of things is reviewed. Third, the study shows different platforms that can be used as a source for the fusion of technologies, such as ground-based (tractors and robots), space-borne (satellites) and aerial (unmanned aerial vehicles) monitoring platforms. Finally, the study presents data fusion methods for site-specific crop parameter monitoring, such as nitrogen, chlorophyll, leaf area index, and aboveground biomass, and shows how the fusion of technologies and data can improve the monitoring of these parameters. The study further reveals limitations of the previous technologies and provides recommendations on how to improve their fusion with the best available sensors. The study reveals that among different data fusion methods, sensors and technologies, the airborne and terrestrial LiDAR fusion method for crop, canopy, and ground may be considered as a futuristic easy-to-use and low-cost solution to enhance the site-specific monitoring of crop parameters.
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