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.

Download the abstract

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…

Rootstock impact on foliar symptom expression of esca on Vitis vinifera cv. Cabernet-Sauvignon

Trunk diseases and esca in particular, represent a major threat to the sustainability of the vineyards. The percentages of unproductive vines in a plot could vary from 4% to over 20 % depending on local conditions and vintages.

Read More

Hyperspectral imaging for precision viticulture

Precision viticulture aims to optimize vineyard management by monitoring and responding to variability within vine plots. this work presents a comprehensive study on the application of hyperspectral imaging (hsi) technology for monitoring purposes in precision viticulture. authors explore the deployment of hsi sensors on various platforms including laboratory settings, terrestrial vehicles, and unmanned aerial vehicles, facilitating the collection of high-resolution data across extensive vineyard areas.

Read More

Correlation between stable isotopic composition of the fungus aspergillus niger and its growth substrate and the extracted chitin

Wine is one of the most consumed and appreciated beverages in the world. Due to the growing attention paid to consumer health, there is a continuous search for sustainable alternatives to common additives (such as sulfur dioxide) used to preserve wine. An example is represented by chitosan, the main derivative of chitin, approved for the treatment of must and wine since 2009 by the “international organization of vine and wine” (OIV/OENO 338a/2009) and by the european commission (EC Reg. No. 606/2009).

Read More

What is the fate of oxygen consumed by red wine? Main processes and reaction products

Oxygen consumed by wine is used to oxidize sulfur dioxide and ethanol to form acetaldehyde wine oxygen consumption rate (OCR) was negatively correlated with the initial acetaldehyde level.

Read More

Analysis of mousy off-flavour wines

Winemakers are increasingly experimenting with new techniques, such as spontaneous fermentation, prolonged yeast contact, higher pH, minimal sulphur dioxid, filtration and clarification or oxidative ageing. Along with this, the risk of microbial spoilage increases, and so the off-flavour mousiness, long time underestimated, is becoming more frequent. Characteristic of the mousy off-flavour is the delayed perception after swallowing the wine. After a few seconds the flavour appears, reminiscent of a dirty mouse cage. There are three known compounds that cause mousy off-flavor: 2-ethyltetrahydropyridine, 2-acetyltetrahydopyridine, and 2-acetylpyrroline. Yeasts such as Dekkera/Brettanomyces and heterofermentative lactic acid bacteria like Lactobacillus hilgardii can release these compounds.

Read More