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…

Overall conceptual characterization of aged dry white wines using a mental descriptive questionnaire

The purpose of the present study was to understand the overall concept of an aged dry white wine using a descriptive mental questionnaire. A total of 680 worldwide participants, grouped according to their involvement in the wine business, replied to an online questionnaire to characterize the sensory analytical and synthetic descriptors of an aged dry white wine. The descriptors were selected using a Check-All-That-Apply (CATA) approach concerning wine colour, aroma, taste, mouthfeel, and global appreciation.

Using GIS to assess the terroir potential of an Oregon viticultural region

Deciding to grow grapes in Oregon is complex issue due to our diverse geography, climate, and relatively short history of grape growing. For any potential grape grower, vineyard site selection is the single most important decision they will face.

Developmental and genetic mechanisms underlying seedlessness in grapevine somatic variants

Seedless table grapes are greatly appreciated for fresh and dry consumption. There is also some interest in seedless winegrapes, because the combination of lower fruit set, smaller berries with higher skin/pulp ratio and looser bunches with the absence of seeds in crushed berries, a possible source of astringent tannins, might also have favorable effects on wine quality.
The gene VviAGL11 has been shown to play a central role in stenospermocarpy in Sultanina, but the molecular bases of other sources of stenospermocarpy as well as of parthenocarpy have not been clarified yet.

Impact of press fractioning on Pinot noir and Pinot meunier grape juice and wine compositions and colour

The separation of different grape juice press fractions is an important step in the production of sparkling base wines. A complete press cycle for this style of wine is a series of pressure increases (squeezes) resulting in variations in juice composition during the press cycle. After alcoholic fermentation, wines obtained from grape juices also exhibit strong differences for numerous characteristics. Nevertheless, there is no statistical study of the impact of the press cycle on grape juices and wine colour/composition. So, the aim of this study (vintage 2018) was to investigate the changes in composition and colour parameters of Pinot noir and Pinot meunier grapes juices, as well as their corresponding wines, during the pressing cycle.

Le réseau français des partenaires de la sélection vigne : un dispositif unique au monde au service de la sauvegarde du patrimoine variétal

The French vine selection partners network is currently made up of 40 regional partners, grouped around IFV (French Institute for Vine and Wine) and INRAE (national research institute for agriculture and environment), whose missions are preservation, selection, and innovation of our varietal diversity. The originality of this device is based on a 3-level organisation: – varietal diversity preservation, with the world reference: the INRAE’s vine genetics resources centre of Vassal-Montpellier (Marseillan, France), the world’s largest ampelographic collection, which includes nearly 6 000 accessions of cultivated Vitis vinifera from 54 countries, as well as rootstocks, interspecific hybrids, wild vines (lambrusques) and wild American and Asian species.