Sensor‐based outdoor monitoring of insects in arable crops for their precise control

Abstract

The implementation of precision farming technologies into agricultural practice requires, among other things, precise determination of the extent and intensity of insect infestation in the farmer' fields. Manual insect identification is time‐consuming and has low efficiency, especially for large fields. Therefore, scientists and practitioners devote much effort to the automatization of this process. There are two complementary approaches to insect identification: (i) direct, in which the insect (ultimately the species) is determined, and (ii) indirect, in which the damage caused by the insects is monitored and forms the basis on which to formulate the information about insect infestation. A mini‐review of both approaches is presented in this work. Additionally, the advantages and disadvantages of each are briefly described. Methods of insect identification are still characterized by relatively small selectivity and efficiency, therefore it is necessary to keep searching for new methods and improve the development of existing ones. The goal of such systems should be to work in real time and be inexpensive to run, enabling widespread use amongst farmers. A possible solution seems to be integrating various techniques (sensor fusion) into a single measurement system. © 2020 Society of Chemical Industry

Success, despite another plague year

“…Several reviews dealt with other aspects of management of arthropod pests. The use of sensors to better manage insect pests in crops was reviewed, 31 as well as available products for detection, monitoring and control of bedbugs 32 and toxic sugar baits for mosquito control 33 . There were general reviews of biology and management of the cotton mealy bug 34 and the emerging mite pest Aculops lycopersici 35 .…”

A novel 3D insect detection and monitoring system in plants based on deep learning

“…To effectively address infestations, it is important to know the location and size of the affected areas. However, because insects can rapidly spread throughout a field during favorable weather conditions, quick action is necessary (Li and Yang, 2020;Bieganowski et al, 2021). Traditional methods of visually assessing field health along a dense sampling grid are not practical due to the time and labor involved, making it difficult to generate pest maps and precise spraying maps.…”

Autonomous Detection of Spodoptera frugiperda by Feeding Symptoms Directly from UAV RGB Imagery

“…At present, the main standard method to control this pest is pesticides, including (a) detecting the occurrence and status of pests by field sampling investigation, which relies on agronomists or trained surveyors [3], and (b) spraying pesticides evenly in the corresponding area [6,7]. It is simple and easy to indiscriminatingly spray, but the process of obtaining the information is time consuming and laborious, which depends on the subjectivity of surveyors.…”

“…Compared with disease studies, insect pests are more flexible. There are two primary approaches to insect identification [29]: (i) direct, focusing on the ontology of the insects, and (ii) indirect, which focus on the damage caused by the insects [6]. For example, Liu et al used a field insect light trap to obtain images and combined the CNN and attention mechanism to construct a direct classification model for insect identification [30].…”