Technological advances and the use of IoT in monitoring Diaphorina citri in citrus cultivation
Abstract The Asian citrus psyllid, Diaphorina citri, is a pest of great relevance to the citrus industry, acting as a vector for the bacterium Candidatus Liberibacter asiaticus (CLas), responsible for the disease known as Huanglongbing (HLB) or citrus greening. The distribution of D. citri covers tr...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Instituto Internacional de Ecologia
2025-04-01
|
| Series: | Brazilian Journal of Biology |
| Subjects: | |
| Online Access: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1519-69842025000100163&lng=en&tlng=en |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Abstract The Asian citrus psyllid, Diaphorina citri, is a pest of great relevance to the citrus industry, acting as a vector for the bacterium Candidatus Liberibacter asiaticus (CLas), responsible for the disease known as Huanglongbing (HLB) or citrus greening. The distribution of D. citri covers tropical and subtropical regions, representing a significant threat to global citrus production and causing economic losses. Transmission of CLas occurs when the psyllid feeds on the phloem of citrus plants, spreading the disease severely. Therefore, the management of D. citri is essential for the health of citrus groves, and understanding its habitat and dispersal patterns is crucial for adequate control. Internet of Things (IoT) technology is a promising tool in agriculture, enabling real-time monitoring and control systems that increase the efficiency and sustainability of agricultural practices. The integration of IoT facilitates the early detection of D. citri and the continuous monitoring of their populations, improving the response to pest outbreaks and optimizing the use of insecticides. Systems based on AIoT (Artificial Intelligence of Things) and computer vision have demonstrated high accuracy in identifying and occurring pests, allowing for fast and efficient management. These technological advances, combined with biological strategies and traditional methods such as insecticides and physical traps, create a multifaceted approach to D. citri management. Integrating data from satellite images, field sensors, and machine learning algorithms makes developing more comprehensive and predictive monitoring of agricultural conditions possible. This helps mitigate the impacts of HLB and promotes more innovative, resilient farming practices. Smart agriculture, supported by IoT and technologies, offers a promising path to meet the challenges of modern agricultural production, combining real-time monitoring, innovative biological strategies, and predictive analytics to create a more sustainable and efficient agricultural system, essential to meet future challenges. |
|---|---|
| ISSN: | 1678-4375 |