Precision Farming
B. Besharati; A. Jafari; H. Mousazadeh; H. Navid
Abstract
IntroductionVarious methods have been performed to control weeds in the world and the use of herbicides is one of them, but public concerns about human health have changed interest in alternative methods. Thermal methods based on flame-weeder, hot air, steam, and hot water have the potential to control ...
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IntroductionVarious methods have been performed to control weeds in the world and the use of herbicides is one of them, but public concerns about human health have changed interest in alternative methods. Thermal methods based on flame-weeder, hot air, steam, and hot water have the potential to control weeds, but due to the high cost are not economical. Electromagnetic waves transfer energy into weeds and finally destroy them. The effect of radiation on plant mutation, high consumption of energy, and human health are problems for this approach. Unlike other methods, electrical energy is an ideal and non-chemical method for weeds. This method applies high voltage to weeds, their roots, and soil so that electric currents pass through them, and the vaporization of the liquid content of weeds kills the weeds. To increase the severity of damage to weeds, the development of a feedback mechanism is required. The ultrasonic sensor measuring physical parameters like plant height is a simple method. Some complex sensing systems include optical sensors such as infrared, and machine vision that require high-speed processors and expensive equipment. In this project, as a simple method, the monitoring of the electrical current passing through weeds was used for developing the feedback mechanism and increasing electric damage to weeds.Materials and MethodsIn this study, the system consisted of a high-voltage device that generated a 15 kV AC voltage to kill weeds, as well as a feedback mechanism that included a sensor to measure the electric current on the input of the weed killer and identify the presence of weeds and their annihilation. All parts were installed on a robotic platform, and an application on a laptop was connected to it via an access point for navigation and data reception. The system was tested in a greenhouse lab with various weeds. Initially, a test was performed to investigate the effect of high voltage on the weeds and establish relationships between the electric currents passing through weeds and their presence (before and after annihilation). During the test, the system was guided along a path and applied high voltage to kill the weeds. The feedback mechanism was then calibrated based on the extracted data on electric current relations. This allowed the system to detect weeds and their annihilation, enabling it to move to the next target once a weed had been eliminated. After calibration, a comparative test was conducted to evaluate the weed-killing efficiency of the two methods (with and without the feedback mechanism), and the results were analyzed using a t-test with p ≤ 0.01.Results and DiscussionThe observations indicated that the input electric current on the weed killer was dependent on the electric current passing through weeds. When the high-voltage electrode touched a weed, the electric current passed through it increased, and simultaneously, the high electrical energy destroyed the weed. After the removal of the weed, the electric current rapidly decreased. The average energy consumption per weed plant was estimated to be 250 joules, which can be compared with other methods. The final test comparing the use and non-use of the feedback mechanism revealed significant differences (P < 0.01) between the results obtained with and without the mechanism, demonstrating that the feedback mechanism increased the efficiency of weed annihilation. The sensing system used in the developed feedback mechanism is a simple method that is affected by the electrical resistivity of weeds. As such, it did not mistakenly detect other objects as weeds, unlike an ultrasonic mechanism. Based on these results, monitoring the electrical current passing through weeds proved to be a suitable method for developing a feedback mechanism for the weed killer to identify the presence of weeds and their annihilation.ConclusionThe use of high voltage as a non-chemical and alternative method for weed control has shown promising results. The study revealed that measuring the electric current applied to the weed killer was an effective and straightforward approach to developing a feedback mechanism. This mechanism aids in identifying the presence of weeds and ensuring their elimination by intensifying the damage inflicted on them through the application of high electrical energy. To further enhance the efficiency and speed of weed control, future research should consider integrating an automatic guidance mechanism with the weed killer.
A. Bakhshipour Ziaratgahi; A. A. Jafari; Y. Emam; S. M. Nassiri; S. Kamgar; D. Zare
Abstract
Introduction Sugar beet (Beta vulgaris L.) as the second most important world’s sugar source after sugarcane is one of the major industrial crops. The presence of weeds in sugar beet fields, especially at early growth stages, results in a substantial decrease in the crop yield. It is very important ...
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Introduction Sugar beet (Beta vulgaris L.) as the second most important world’s sugar source after sugarcane is one of the major industrial crops. The presence of weeds in sugar beet fields, especially at early growth stages, results in a substantial decrease in the crop yield. It is very important to efficiently eliminate weeds at early growing stages. The first step of precision weed control is accurate detection of weeds location in the field. This operation can be performed by machine vision techniques. Hough transform is one of the shape feature extraction methods for object tracking in image processing which is basically used to identify lines or other geometrical shapes in an image. Generalized Hough transform (GHT) is a modified version of the Hough transform used not only for geometrical forms, but also for detecting any arbitrary shape. This method is based on a pattern matching principle that uses a set of vectors of feature points (usually object edge points) to a reference point to construct a pattern. By comparing this pattern with a set pattern, the desired shape is detected. The aim of this study was to identify the sugar beet plant from some common weeds in a field using the GHT. Materials and Methods Images required for this study were taken at the four-leaf stage of sugar beet as the beginning of the critical period of weed control. A shelter was used to avoid direct sunlight and prevent leaf shadows on each other. The obtained images were then introduced to the Image Processing Toolbox of MATLAB programming software for further processing. Green and Red color components were extracted from primary RGB images. In the first step, binary images were obtained by applying the optimal threshold on the G-R images. A comprehensive study of several sugar beet images revealed that there is a unique feature in sugar beet leaves which makes them differentiable from the weeds. The feature observed in all sugar beet plants at the four-leaf stage was a stretched S-shaped curve at the junction of the leaf and petiole. This unique shape characteristic was used as the pattern for sugar beet detection using GHT. To implement the Hough transform in the images, a 50-member group of samples was prepared from S-shaped curve to build appropriate patterns. Desired features for the Hough transformation were extracted from the patterns. In the next step, the attempts were made to find the images for the shapes similar to each of the patterns. Results and Discussion Plants were thoroughly separated from soil and residues. The accuracy of segmentation algorithm was achieved by almost 100%. The accuracy of the generalized Hough algorithm was evaluated in two stages. In the first stage, the algorithm accuracy was assessed in detecting patterns in the images. Results showed that the accuracy of the algorithm was 96.21%. In the second stage, the algorithm was evaluated for some other test images, whereas the algorithm achieved an overall accuracy of 91.65%. In some cases, the presence of a large overlap between objects in the image reduced the detection accuracy. This was because of two main reasons; 1) high interference and ambiguity in the object edges, so that Hough transform was not able to detect the predefined patterns in the objects and, 2) weeds highly overlapped with sugar beet plants and thereby they were wrongly detected as sugar beet. However, since there is no or little interference between plants at the four-leaf stage, this interference can be eliminated by morphological operations. Due to this fact, it can be said that the results of GHT algorithm are acceptable for the detection of sugar beet in the plants close to four-leaf stage. Conclusion A special feature in the shape of sugar beet leaves was used as a criterion to distinguish between sugar beet and weeds. The results showed that by quantifying this special feature, which is an S-shaped curve near the petioles connection of beet leaves, sugar beet can be discriminated from weeds with an accuracy of 91.65 %. Recalled that this feature is a shape characteristic, therefore, the generalized Hough algorithm must be applied prior to plant canopy development, which is consistent with the critical period of weed control in sugar beet fields.
Design and Construction
R. Loni; M. Loghavi
Abstract
Farmers are now more interested in application of weed control methods and tools with less environmental side effects. Flame weeding using propane gas is an approach with almost no any chemical residue on the soil and plant surfaces or underground water. In this research, a flame weeding machine with ...
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Farmers are now more interested in application of weed control methods and tools with less environmental side effects. Flame weeding using propane gas is an approach with almost no any chemical residue on the soil and plant surfaces or underground water. In this research, a flame weeding machine with the ability of uniform and also discrete flaming was developed and evaluated in laboratory and field scales. In this apparatus, machine vision technology successfully discriminates between soil and weeds (plants grown in between the corn rows are considered as weeds) under natural illumination. In the laboratory tests, the effect of three forward speeds (0.5, 0.7 and 0.9 m s-1) on flam leading or lagging was investigated. The feasibility of using this technology for site-specific weed control of a corn field in comparison with conventional continuous flaming was investigated. The field trials were conducted with both continuous and discrete flaming approaches. The system performance and weed response to flaming treatments were evaluated by measuring the fuel consumption, counting the number of and weighting the survived and dead weeds one and three days after each flaming treatment. The results of laboratory tests showed that the effect of forward speed on system accuracy was significant and the system performance was more accurate at forward speeds of 0.5 and 0.7 m s-1 than 0.9 m s-1. According to the field experiments, continuous and discrete flaming methods exhibited similar results in eradication of weeds (both number and weight-based), while the fuel consumption of the discrete flaming was lower than the continuous one. The results also showed that discrete flaming by employing machine vision technology could be an efficient substitute for continuous flaming due to its lower fuel consumption and potential reduction of air pollution as well as other benefits of flame weeding.
K. Gerami; M. Safari
Abstract
This experiment was conducted to study the effect of nozzle types and the time of herbicide incorporation in soil on weed control, using split plot design by randomized block design. The main plots were soil and herbicide mixing time and the subplots were nozzle types with three replications. This study ...
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This experiment was conducted to study the effect of nozzle types and the time of herbicide incorporation in soil on weed control, using split plot design by randomized block design. The main plots were soil and herbicide mixing time and the subplots were nozzle types with three replications. This study was performed in Karaj station of Seed and Plant Improvement Institute, located 25 km west of Tehran, in 2008. Treatments were including: T-Jet standard nozzle, Flood-Jet nozzle and Air induction nozzle as well as mixing with the soil immediately, three, six and nine hours after spraying. The parameters were measured includes: the number of weeds before spraying, 15 days and 30 days after spraying; dry weed at two stages of 15 and 30 days after the spraying; and yield of corn. The results revealed that the spraying quality coefficient was greater for T-jet nozzle compared to the other types. However Flood-jet nozzle had a wide range of corn weeds control in comparison to other treatments. Regardless of the nozzle type, the immediate incorporation of herbicide in soil after spraying significantly increased the yield. The time of herbicide incorporation in soil and poison intermixture with soil, from zero to 4.5 hours after spraying was superior to the other times. This was mainly due to different weeds reactions to the times of herbicide incorporation in soil after spraying, and also treatments effect on yield and weed dry weight. Combined data analysis showed that treatment combination of T-Jet nozzle (with time of herbicide incorporation in soil immediately and three hours after spraying), Flood-jet nozzle (with time of herbicide incorporation in soil immediately after spraying) and air induction nozzle (with time of herbicide incorporation in soil immediately, three and six hours after spraying) produced the highest yield than the other treatment combinations.
