Search Results (315)

Detecting objects in digital images is challenging in computer vision, traditionally requiring manual threshold selection. However, object detection has improved significantly with convolutional neural networks (CNNs), and other advanced algorithms, like region-based convolutional neural networks (R-CNNs) and you only look once (YOLO). Deep learning methods have various applications in agriculture, including detecting pests, diseases, and fruit quality. We propose a lightweight YOLOv4-Tiny-based object detection system with a circular bounding box to accurately determine chrysanthemum flower harvest time. The proposed network in this study uses a circular bounding box to accurately classify the degree of chrysanthemums blooming and detect circular objects effectively, showing better results than the network with the traditional rectangular bounding box. The proposed network has excellent scalability and can be applied to recognize general objects in a circular form. Full article

The gin stand power is measurable using common tools; however, such tools typically do not detect active ginning. Detecting active ginning is important when trying to separate out the energy going to the moving parts of the gin stand (i.e., the baseline energy) versus the active energy doing work to remove the cotton fibers from the seed. Studies have shown that the gin stand is the second largest consumer of electricity in the ginning operation, while electricity accounts for nearly 17% of the average expense per bale. If active energy differences exist between cotton cultivars, there may be room to optimize and lower these expenses. The goal of the current work is to provide a method (and software tool) to analyze typical power logger data, and extract periods of active ginning, along with the energy consumed and ginning times, in a semi-automated way. The new method presented allows multiple periods of active ginning in a single file, and can separate the total energy into the active and baseline components. Other metrics of interest that the software calculates include the ginning time, and average power. Software validation using a simulated test signal showed that a 2%-or-lower error is possible with a noisy signal. Full article

The delineation of management zones is one of the ways to enable the spatially differentiated management of plots using precision agriculture tools. Over the years, the spatial variability of data collected from soil and plant sampling started to be replaced by data collected by proximal and orbital sensors. As a result, the variety and volume of data have increased considerably, making it necessary to use advanced computational tools, such as machine learning, for data analysis and decision-making support. This paper presents a methodology used to establish management zones (MZ) in precision agriculture by analyzing data obtained from soil sampling, proximal sensors and orbital sensors, in experiments carried out in four plots featuring soybean–cotton and soybean–corn crops, in Mato Grosso and Paraná states, Brazil. Four procedures were evaluated, using different input data sets for the MZ delineation: (I) soil attributes, including clay content, apparent electrical conductivity or fertility, along with elevation, yield maps and vegetation indices (VIs) captured during the peak crop biomass period; (II) soil attributes in conjunction with VIs demonstrating strong correlations; (III) solely VIs exhibiting robust correlation with soil attributes and yield; (IV) VIs selected via random forests to identify the importance of the variable for estimating yield. The results showed that the VIs derived from satellite images could effectively replace other types of data. For plots where the natural spatial variability can be easily identified, all procedures favor obtaining MZ maps that allow reductions of 40% to 70% in yield variance, justifying their use. On the other hand, in plots with low natural spatial variability and that do not have reliable yield maps, different data sets used as input do not help in obtaining feasible MZ maps. For areas where anthropogenic activities with spatially differentiated treatment are already present, the exclusive use of VIs for the delineation of MZs must be carried out with reservations. Full article

This study investigated the potential and sustainable use of the biomass derived from various stages of the grape drying process. A total of eleven byproducts, each containing varying organic materials, were produced and subjected to testing. Ultimate analysis, as well as analyses of heating values, chemical composition, lignocellulose composition, total solids concentration and biogas production were performed with the recommended criteria and assessment methods. The results reveal that carbon (C), nitrogen (N), hydrogen (H), and oxygen (O) levels were significantly different among the byproducts. The ash content of byproducts 5–11 ranged from 3.56 to 5.11%, which was lower than the estimated values in the other byproducts. The analysis of higher heating value showed significantly higher calorific values for byproducts 10 and 11 (22.73 ± 0.08 and 22.80 ± 0.07 MJ kg⁻¹, respectively). Byproducts 1–9 had lower sugar content than byproducts 10 and 11 (rejected raisins). Byproducts 5–9 had the lowest lignin content, and there were no significant differences in neutral detergent fiber (NDF) contents between byproducts 1–6. The highest accumulated biogas volume after 40 days was 11.50 NL L⁻¹ of substrate for byproduct group C (byproducts 10 to 11), followed by 11.20 NL L⁻¹ of substrate for byproduct group B (byproducts 5–9) and 9.51 NL L⁻¹ of substrate for byproduct group A (byproducts 1–4). It is concluded that byproducts consisting of biomass derived at different stages of raisin production may be an effective solid fuel and energy source. The amounts of volatile solids in the tested raisin processing byproducts indicated their appropriateness for pyrolysis conversion to a liquid product with high volatile content. Full article

The aim of this work was to elaborate a new methodology that can allow for the identification of the topsoil homogeneous area (tSHA) distribution along land parcels, supporting farmers in keeping low-cost, sustainable, and light logistic management of precision agriculture (PA) practices. This paper shows the assessment of tSHA variability over two production units (PUs), considering radiometric response (optical camera), physicochemical (texture, pH, electrical conductivity), and statistical and geostatistical data analysis. By using unmanned aircraft systems (UASs) and laboratory analysis, our results revealed that the integration between UAS-RGB and physicochemical data can improve the estimation accuracy of tSHA distribution. Firstly, the UAS-RGB dataset was used to isolate bare soil from the vegetative radiometric contribution. Secondly, starting from statistical approaches (correlation matrices), the highest correlation with UAS-RGB and physicochemical data was stated. Thirdly, by using a geostatistical approach (ordinary cokriging), the map representing the tSHA variability was finally obtained. Full article

Shrimp farming and exporting is the main income source for the southern coastal districts of the Mekong Delta. Monitoring these shrimp ponds is helpful in identifying losses incurred due to natural calamities like floods, sources of water pollution by chemicals used in shrimp farming, and changes in the area of cultivation with an increase in demand for shrimp production. Satellite imagery, which is consistent with good spatial resolution and helpful in providing frequent information with temporal imagery, is a better solution for monitoring these shrimp ponds remotely for a larger spatial extent. The shrimp ponds of Cai Doi Vam township, Ca Mau Province, Viet Nam, were mapped using DMC-3 (TripleSat) and Jilin-1 high-resolution satellite imagery for the years 2019 and 2022. The 3 m spatial resolution shrimp pond extent product showed an overall accuracy of 87.5%, with a producer’s accuracy of 90.91% (errors of omission = 11.09%) and a user’s accuracy of 90.91% (errors of commission = 11.09%) for the shrimp pond class. It was noted that 66 ha of shrimp ponds in 2019 were observed to be dry in 2022, and 39 ha of other ponds had been converted into shrimp ponds in 2022. The continuous monitoring of shrimp ponds helps achieve sustainable aquaculture and acts as crucial input for the decision makers for any interventions. Full article

Timely detection of pests and diseases in crops is essential to mitigate severe damage and economic losses, especially in the context of climate change. This paper describes a method for detecting the presence of coffee leaf rust (CLR) using two databases: RoCoLe and a database obtained from an unmanned aerial vehicle (UAV) equipped with an RGB camera. The developed method follows a two-stage approach. In the first stage, images are processed using ImageJ software, while, in the second phase, Python is used to implement morphological filters and the Hough transform for rust identification. The algorithm’s performance is evaluated using the chi-square test, and its discriminatory capacity is assessed through the generation of a Receiver Operating Characteristic (ROC) curve. Additionally, Cohen’s kappa method is used to assess the agreement among observers, while Kendall’s rank correlation coefficient (KRCC) measures the correlation between the criteria of the observers and the classifications generated by the method. The results demonstrate that the developed method achieved an efficiency of 97% in detecting coffee rust in the RoCoLe dataset and over 93.5% in UAV images. These findings suggest that the developed method has the potential to be implemented in the future on a UAV for rust detection. Full article

To address the challenges of climate change and food security, the establishment of smart farm complexes is necessary. While there have been numerous studies on the productivity and environmental control of individual greenhouses, research on greenhouse complexes is considerably limited. Conducting environmental studies during the design phase of these complexes poses financial constraints and practical limitations in terms of on-site experiments. To identify potential issues that may arise when developing large-scale greenhouse complexes, it is possible to utilize modeling techniques using computational fluid dynamics (CFD) to assess environmental concerns and location issues before constructing the facilities. Consequently, simulating large-scale CFD models that incorporate multiple greenhouses and atmospheric conditions simultaneously presents significant numerical challenges. The objective of this study was to design and verify the 3D CFD model for a large-scale Venlo greenhouse, where acquiring field data before construction is not feasible for designing a greenhouse complex. The verification of the CFD models was conducted using the improved grid independence test (GIT) and wall Y⁺ approaches. The findings revealed that a grid resolution of 0.8 m and a first-layer height of 0.04 m were suitable for developing large-scale greenhouse models, resulting in a low Root Mean Square Error (RMSE) of 3.9% and a high coefficient of determination (R²) of 0.968. This process led to a significant reduction of 38% in the number of grid cells. Subsequently, the aerodynamic characteristics and regional ventilation efficiency were analyzed in a 3D greenhouse model for developing a new large-scale greenhouse complex. Full article

Many farms utilize closed-type livestock systems to enhance productivity and facilitate effective environmental management. However, the confined nature of these closed spaces poses an increased risk of exposure to harmful gases and organic dust for both workers and livestock. Additionally, the introduction of outside air through ventilation systems can lead to temperature fluctuations within the breeding environment, resulting in potential productivity issues. This research paper employs computational fluid dynamics (CFD) to develop ventilation operation management plans that address both the working environment and the breeding environment simultaneously. The proposed plans are designed to be easily implemented in practical farm settings. The findings of this study, based on the simulation analysis, indicate that while ventilation is effective in reducing harmful gases and improving the working environment, its efficiency decreases after the initial 3 min of operation. Furthermore, uncontrolled ventilation can cause sudden temperature changes, which may adversely affect the well-being of the livestock. However, when upgraded ventilation structures are implemented, significant improvements in the working environment (an average of 27.3% improvement) can be achieved while maintaining temperature stability for the livestock. These results highlight the importance of referring to the provided ventilation operation management table before commencing work, as it enables workers to improve the working environment while minimizing the potential impact of ventilation on the breeding environment. Full article

This review aims to provide a comprehensive overview of nano- and microscopic materials that can provide thermal radiation insulation without reducing visible light transmittance, thereby reducing heat loss and conserving energy in greenhouses. We also reviewed the radial and thermal properties of greenhouse covering materials. Fillers, colorants, reinforcers, and additives, as well as glass, plastic film, and plastic sheet materials, were discussed. Additionally, by searching for keywords like insulation film, insulation agent, and infrared insulation, compounds based on graphene and fullerene as well as phase transition materials (PCMs) that may be used for radiation insulation, we proposed their potential use in greenhouse covers. They can be divided into semi-transparent photovoltaic (PV) materials, zinc oxide-based film fillers, and silica filter films. We discussed the radiation heat insulation and light transmission characteristics of these materials. Nano-synthesis techniques were also investigated. Based on latest advances in the literature, future developments in the micro- and macroscale synthesis of nanomaterials will enable additional innovations in covering materials for greenhouse structures. A limiting factor, though, was the high sensitivity of PVs to external climatic and meteorological variables. The ability of materials used to make greenhouse covers to control the microclimate, reduce CO₂ emissions, use less energy, and increase agricultural productivity, however, cannot be disputed. Similar to this, a thorough examination of the uses of various greenhouse technologies reveals that the advancements also have financial advantages, particularly in terms of reducing greenhouse heating and cooling expenses. The PCMs, which decreased greenhouse-operating costs by maintaining constant ambient temperatures, provide ample evidence of this. Full article

Like most crops, sugarcane needs to be kept upright until it is harvested. The lodging of sugarcane has significant negative effects on the cane yield and sugar content of sugarcane. To keep sugarcane upright, earthing up is an essential in the cultural part of the operation. In Bangladesh, most of the sugarcane cultivation operations, including earthing-up, are generally performed in a traditional manual method which increases the production costs as well as reduces the income of sugarcane growers. Therefore, a cost-effective two-wheeled tractor (2WT)-mounted earthing-up machine was developed at the Bangladesh Sugarcrop Research Institute (BSRI), Pabna, to reduce drudgery and the cost of sugarcane production. Field tests were conducted in an experimental sugarcane field at BSRI and technical and economic performances of the developed earthing-up machine were also carried out based on the field test. The average effective field capacity and field efficiency of the earthing-up machine were found to be 0.16 ha/h and 77.41%, respectively. The 2WT-driven earthing-up machine was not found to be economically viable when it was used only for earthing-up operations. However, when the 2WT was used as the main driver for other activities, including earthing-up operation, the earthing-up machine became economically beneficial with net cash flow (NCF), net present value (NPV), internal rate of return (IRR), benefit–cost ratio (BCR), and payback period (PP) of BDT 148,497/ha, BDT 23,184, 3%, 3.81:1, and approximately 1 year, respectively. On the contrary, considering the cost of only earthing-up tool without 2WT, it was found to be economically beneficial with NCF, NPV, IRR, BCR, and PP of BDT 16,428/ha, BDT 3053, 4.7%, 2.71:1, and approximately 2 years, respectively. In Bangladesh, 2WT is commonly used for versatile farming purposes. Therefore, the versatile use of 2WT as a prime mover for other machines, including the earthing-up machine, can make earthing-up machine economically viable and beneficial for sugarcane growers in Bangladesh. Full article

The purpose of milking machines is to harvest milk at optimal quality and speed, while maintaining animal comfort and teat defense mechanisms against invading mastitis pathogens. Therefore, the milking machine is a very important piece of equipment on dairy farms to maintain a long healthy lactation by following the physiological conditions of the udder. The mechanical forces during long-term machine milking processes lead to changes in the teat tissue. This effect is related to the degree of adaptation of the milking machines to the physiological requirements of the individual udder anatomy and the physiological conditions of the lactating animals. If both, milking machine settings and liner design are not suitable for all teats and animals on the farm, some animals will not be fully milked, the teat condition will deteriorate over time and in the end, they may suffer from mastitis. Therefore, maintaining healthy udders and teats during milking is a central key component of an effective milking machine to produce good milk yield with higher quality by preventing mastitis and maintaining animal health and welfare. On large and thick teats, conventional liners often fit too tight, causing a massive mechanical stress load on the tissue. On small teats, however, they often do not adhere sufficiently close to the teat which can cause a considerable air admission and hence liner slips. The new liners, “Stimulor^® StressLess” (Siliconform, Türkheim, Germany), have a wave-like lip construction and adapt well to the different teat sizes in a herd, thus ensuring consistent milking of lactating animals. A proper milking machine accommodates all teat sizes and forms, has a low vacuum to effectively open the teat and to stimulate physiological milk release and letdown. In addition, the right pulsation rate will maintain a stable vacuum on the teat area during milking. In conclusion, an ideal milking machine adapts to the morphological, anatomical, and physiological characteristics of the udder and teats of the lactating animals and it should achieve a physiologically ideal milking process that meets high animal welfare standards and increases milk production with a high quality standard. Full article

The application of precision agriculture in cocoa and papaya cultivation in Brazil is still incipient. This study aimed to evaluate the spatial variability of the physical attributes of soil cultivated with a consortium of papaya and cocoa. The study was conducted in two sampling grids of 50 points, in two areas cultivated with papaya and cocoa with different planting times (three and eleven months). The soil attributes soil resistance to penetration (RP) and soil gravimetric moisture (UG) were determined at soil depths of 0–20, 20–40 and 40–60 cm. The data were submitted to an exploratory and descriptive analysis. Subsequently, a geostatistical analysis was performed to quantify spatial dependence and then interpolation of the data through kriging. The maps showed weak spatial variability for the UG and RP. In the two areas, it was observed that the depth of 0–20 cm had a lower RP (1.7 Mpa) and a higher UG (40 g g⁻¹), and as the depth was higher, had a higher RP (4.4 Mpa) and a lower UG (38 g g⁻¹). Area 1 presented higher RP values in depth, showing greater susceptibility to compaction. The area characterized by the consortium of papaya and cocoa presented more susceptible to compaction. The mechanical resistance of the soil to penetration was more critical in the 40–60 cm layer for the two consortia evaluated, evidencing areas with possible restriction to plant growth. Full article

In a world in continuous evolution and in which human needs grow exponentially according to the increasing world population, the advent of new technologies plays a fundamental role in all fields of industry, especially in agriculture. Optimizing times, automating machines, and guaranteeing product quality are key objectives in the field of Agriculture 4.0, which integrates various innovative technologies to meet the needs of producers and consumers while guaranteeing respect for the environment and the planet’s resources. In this context, our research aims to propose an integrated system using data coming from an innovative experimental atmospheric and forecasting simulator (capable of predicting some characteristic climate variables subsequently validated with local sensors), combined with indices deriving from Remote Sensing and UAV images (treated with the data fusion method), that can give fundamental information related to Agriculture 4.0 with particular reference to the subsequent phases of system automation. These data, in fact, can be collected in an open-source GIS capable of displaying areas that need irrigation and fertilization and, moreover, establishing the path of an automated drone for the monitoring of the crops and the route of a self-driving tractor for the irrigation of the areas of interest. Full article

The global cultivation of blood oranges is experiencing an increase due to their remarkable nutritional properties. Blood orange by-products, especially the peel, have a high concentration of bioactive compounds with exceptional antioxidant potential, making them an ideal choice for incorporation into various food products. This study aimed to determine the morphological parameters and primary and secondary metabolite content of peel of eight blood orange varieties using ¹H NMR and HPLC-ESI-DAD-MSⁿ. “Tarocco Meli” had the highest weight (367.83 g), caliber (94.13 mm and 88.87 mm), peel thickness (6.73 mm), and peel weight (155.0 g). “Tarocco Rosso”, “Sanguinelli”, and “Tarocco Gallo” had the highest levels of total amino acids (25.57 g kg⁻¹ DW), total organic acids (29.99 g kg⁻¹ DW), and total sugars (68.56 g 100 g⁻¹ DW), respectively. The peel of “Moro” had significantly higher concentrations of total anthocyanins, hydroxycinnamic acids, and flavones (650.67, 263.33, and 449.85 mg kg⁻¹, respectively) compared to the other varieties. In conclusion, “Tarocco Meli” had the most interesting values for morphological parameters, “Tarocco Rosso”, “Sanguinelli”, and “Tarocco Gallo” for primary metabolites, and “Moro” for secondary metabolites. With the increasing interest in utilizing co-products, these findings could be useful in developing functional food products that meet consumer demands for healthier and more sustainable food choices. Full article