terclim by ICS banner
IVES 9 IVES Conference Series 9 A novel dataset and deep learning object detection benchmark for grapevine pest surveillance

A novel dataset and deep learning object detection benchmark for grapevine pest surveillance

Abstract

Flavescence dorée (FD) stands out as a significant grapevine disease with severe implications for vineyards. The American grapevine leafhopper (Scaphoideus titanus) serves as the primary vector, transmitting the pathogen that causes yield losses and elevated costs linked to uprooting and replanting. Another potential vector of FD is the mosaic leafhopper, Orientus ishidae, commonly found in agroecosystems. The current monitoring approach involves periodic human identification of chromotropic traps, a labor-intensive and time-consuming process.

Therefore, there is a compelling need to develop an automatic pest detection system, leveraging the recent progress in computer vision and deep learning techniques. However, the current progress in developing such a system is hindered by the lack of effective datasets to serve as ground-truth data for the training process.

To fill this gap, our study contributes a fully annotated dataset of S. titanus and Or. ishidae from yellow sticky traps. The dataset comprises more than 400 images, with 1000 identification per class. Guided by entomologists, the annotation task involved defining bounding boxes around relevant insects with corresponding class labels.

We trained and compared the performance of state-of-the-art object detection algorithms (YOLOv8 and Faster R-CNN). Pre-processing included automatic cropping to eliminate irrelevant background information and image enhancements to improve overall quality. Additionally, we tested the impact of altering image resolution, data augmentation, and single-class detection. Preliminary results achieved a high detection accuracy, with mAP@50 and F1-score above 90%, and mAP@50-95 around 70%, allowing a first deployment as an automatic annotation support tool.

DOI:

Publication date: June 14, 2024

Issue: Open GPB 2024

Type: Poster

Authors

Giorgio Checola1*, Paolo Sonego1, Valerio Mazzoni2, Franca Ghidoni3, Alberto Gelmetti3, Pietro Franceschi1

1 Research and Innovation Centre, Digital Agriculture Unit, Fondazione Edmund Mach, S. Michele all’Adige, TN, Italy
2 Research and Innovation Centre, Plant Protection Unit, Fondazione Edmund Mach, S. Michele all’Adige, TN, Italy
3 Technology Transfer Centre, Viticulture Unit, Fondazione Edmund Mach, S. Michele all’Adige, TN, Italy

Contact the author*

Keywords

insect detection, deep learning, smart pest monitoring, flavescence dorée, insect traps

Tags

IVES Conference Series | Open GPB | Open GPB 2024

Citation

Related articles…

Correlation between skin cell wall composition and phenolic extractability in Cabernet sauvignon wines

The phenolic component of red wine is responsible for important elements of flavor and mouthfeel, and thus quality of the finished wine. Additionally, many of these phenolics have been associated with health benefits such as reduction of the risk of developing cardiovascular disease, cancer, osteoporosis and preventing Alzheimer’s disease. While the origins, concentrations, and chemistries of the phenolics in a finished red wine are well known, the fundamental mechanisms and kinetics of extraction of these phenolics from grape skins and seeds during red wine fermentation are poorly understood. This lack of knowledge regarding the extraction mechanisms of phenolics during red wine fermentation makes informed manipulations of the finished wine’s phenolic composition difficult.

Interaction between the enzymes of central carbon metabolism and anthocyanin biosynthesis during grape berry development

Primary and secondary metabolites are major components of grape quality and wine typicity. Their accumulation is interconnected through a complex metabolic network, which is still not well understood. This study aims to investigate how the enzymes of central carbon metabolism interact with anthocyanin biosynthesis during grape berry development: does the accumulation of anthocyanins, which represents a non-negligible diversion of carbon metabolic fluxes, require reprogramming of central enzymes or is it controlled downstream of central metabolism? To this end, 23 enzymes involved in central carbon metabolism pathways have been analyzed in the berries of 3 grape cultivars, which have close genetic background but distinct temporal dynamics of anthocyanin accumulation.

Acetaldehyde-induced condensation products in red wines affect the precipitation of salivary proteins. Will this impact astringency?

Acetaldehyde is a common component of wine. It is already formed during the fermentation being an intermediate in the production of ethanol. Moreover, it can derive from the oxidation of ethanol during the wine production and aging. In wine, concentrations of acetaldehyde range from 30 to 130 mg/L. Acetaldehyde in wine can react with many compounds such as SO2, amino acids and

PRECISE AND SUSTAINABLE OENOLOGY THROUGH THE OPTIMIZED USE OF AD- JUVANTS: A BENTONITE-APPLIED MODEL OF STUDY TO EXPLOIT

As wine resilience is the result of different variables, including the wine pH and the concentration of wine components, a detailed knowledge of the relationships between the adjuvant to attain stability and the oenological medium is fundamental for process optimization and to increase wine durability till the time of consumption.

The French grapevine breeding program resdur: state of the art and perspectives

The French grapevine breeding program for durable resistance to downy and powdery mildew (INRAE-ResDur) was initiated more than 20 years ago to help reduce the heavy use of plant protection products and provide a durable mean to cope with a strong pathogen pressure. This program has now proved to be effective, with about ten new varieties already officially registered. However, there is still a lot to be done (1) to reduce the duration of each breeding cycle, (2) to diversify disease factors’ pyramiding and anticipate emerging diseases, (3) to work towards larger adoption of the new resistant varieties. New breeding schemes incorporating for example genomic prediction of breeding values are being evaluated to accelerate genetic gains, saving cost and time while handling complex traits.