Development and evaluation of a combined cultivator and band sprayer with a row-centering RTK-GPS guidance system

Strip spraying technology for precise herbicide application in carrot fields

The aim of this empirical field research was to show potential differences due to the precise application of herbicides in the quality and size of the carrot root yield and the amount of working liquid used compared to those for control samples. Empirical verification of the effectiveness of the developed technology, confirmed by statistical analyses of the obtained results, allows for a comparative assessment of this method with the conventional method of herbicide application used in this study. Due to the methodology used, it can be assumed that for carrots, the years were a random factor, and the experiments carried out were a series. It can be assumed that in the analysis of a series of experiments, for each of the examined features there are no differences between the groups and there is no interaction of the groups with the years. The yields of the groups weeded manually, sprayed in a conventional way, and weeded with precise spraying did not differ in a statistically significant way. In the precise application, a 20–30% lower herbicide consumption was observed, which has an impact on the protection of the environment and improves the economic effect of carrot production.

Integration of remote-weed mapping and an autonomous spraying unmanned aerial vehicle for site-specific weed management

BACKGROUND

Unmanned aerial vehicles (UAVs) have been used in agriculture to collect imagery for crop and pest monitoring, and for decision-making purposes. Spraying-capable UAVs are now commercially available worldwide for agricultural applications. Combining UAV weed mapping and UAV sprayers into an UAV integrated system (UAV-IS) can offer a new alternative to implement site-specific pest management.

RESULTS

The UAV-IS was 0.3- to 3-fold more efficient at identifying and treating target weedy areas, while minimizing treatment on non-weedy areas, than ground-based broadcast applications. The UAV-IS treated 20-60% less area than ground-based broadcast applications, but also missed up to 26% of the target weedy area, while broadcast applications covered almost the entire experimental area and only missed 2-3% of the target weeds. The efficiency of UAV-IS management practices increased as weed spatial aggregation increased (patchiness).

CONCLUSION

Integrating UAV imagery for pest mapping and UAV sprayers can provide a new strategy for integrated pest management programs to improve efficiency and efficacy while reducing the amount of pesticide being applied. The UAV-IS has the potential to improve the detection and control of weed escapes to reduce/delay herbicide resistance evolution. © 2019 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Integrated electrochemical Chip-on-Plant functional sensor for monitoring gene expression under stress

The ability to interact with plants, both to sense and to actuate, would open new opportunities for precision agriculture. These interactions can be achieved by using the plant as part of the sensing system. The present work demonstrates real-time monitoring of β-glucuronidase (GUS) expression in transgenic tobacco plants using its activity as a biomarker for functional sensing. As "proof of concept", we demonstrated GUS enzyme biosensing under constitutive expression in Msk8 tomato cells and transgenic tobacco plants and in heat shock inducible BY2 tobacco cells and tobacco plants. The sensing was done using a three-electrode microchip in Msk8 or BY2 cell culture or in tobacco plant leaves. The electrode microchip was used to transduce the expression of the GUS enzyme by chronoamperometry to a measurable electrical current signal. For the constitutive expression of GUS in Msk8 cells, the system sensitivity was 0.076 mA/mM-cm2 and the limit of detection was 0.1 mM. For the heat shock inducible BY2 cells the GUS enzyme activity was detected 12-26 h after the heat shock was applied (40 °C for 2 h) using two different substrates: p-nitrophenyl-β-glucuronide (with sensitivity of 0.051 mA/mM-cm2) and phenolphthalein-β-glucuronide (with sensitivity of 0.029 mA/mM-cm2).

Distributed multi-level supervision to effectively monitor the operations of a fleet of autonomous vehicles in agricultural tasks

This paper describes a supervisor system for monitoring the operation of automated agricultural vehicles. The system analyses all of the information provided by the sensors and subsystems on the vehicles in real time and notifies the user when a failure or potentially dangerous situation is detected. In some situations, it is even able to execute a neutralising protocol to remedy the failure. The system is based on a distributed and multi-level architecture that divides the supervision into different subsystems, allowing for better management of the detection and repair of failures. The proposed supervision system was developed to perform well in several scenarios, such as spraying canopy treatments against insects and diseases and selective weed treatments, by either spraying herbicide or burning pests with a mechanical-thermal actuator. Results are presented for selective weed treatment by the spraying of herbicide. The system successfully supervised the task; it detected failures such as service disruptions, incorrect working speeds, incorrect implement states, and potential collisions. Moreover, the system was able to prevent collisions between vehicles by taking action to avoid intersecting trajectories. The results show that the proposed system is a highly useful tool for managing fleets of autonomous vehicles. In particular, it can be used to manage agricultural vehicles during treatment operations.

A proposal for automatic fruit harvesting by combining a low cost stereovision camera and a robotic arm

This paper proposes the development of an automatic fruit harvesting system by combining a low cost stereovision camera and a robotic arm placed in the gripper tool. The stereovision camera is used to estimate the size, distance and position of the fruits whereas the robotic arm is used to mechanically pickup the fruits. The low cost stereovision system has been tested in laboratory conditions with a reference small object, an apple and a pear at 10 different intermediate distances from the camera. The average distance error was from 4% to 5%, and the average diameter error was up to 30% in the case of a small object and in a range from 2% to 6% in the case of a pear and an apple. The stereovision system has been attached to the gripper tool in order to obtain relative distance, orientation and size of the fruit. The harvesting stage requires the initial fruit location, the computation of the inverse kinematics of the robotic arm in order to place the gripper tool in front of the fruit, and a final pickup approach by iteratively adjusting the vertical and horizontal position of the gripper tool in a closed visual loop. The complete system has been tested in controlled laboratory conditions with uniform illumination applied to the fruits. As a future work, this system will be tested and improved in conventional outdoor farming conditions.

Integrating sensory/actuation systems in agricultural vehicles

In recent years, there have been major advances in the development of new and more powerful perception systems for agriculture, such as computer-vision and global positioning systems. Due to these advances, the automation of agricultural tasks has received an important stimulus, especially in the area of selective weed control where high precision is essential for the proper use of resources and the implementation of more efficient treatments. Such autonomous agricultural systems incorporate and integrate perception systems for acquiring information from the environment, decision-making systems for interpreting and analyzing such information, and actuation systems that are responsible for performing the agricultural operations. These systems consist of different sensors, actuators, and computers that work synchronously in a specific architecture for the intended purpose. The main contribution of this paper is the selection, arrangement, integration, and synchronization of these systems to form a whole autonomous vehicle for agricultural applications. This type of vehicle has attracted growing interest, not only for researchers but also for manufacturers and farmers. The experimental results demonstrate the success and performance of the integrated system in guidance and weed control tasks in a maize field, indicating its utility and efficiency. The whole system is sufficiently flexible for use in other agricultural tasks with little effort and is another important contribution in the field of autonomous agricultural vehicles.