Terroir 2020 banner
IVES 9 IVES Conference Series 9 International Terroir Conferences 9 Terroir 2020 9 History and innovation of terroir 9 Detection of spider mite using artificial intelligence in digital viticulture

Detection of spider mite using artificial intelligence in digital viticulture

Abstract

Aim: Pests have a high impact on yield and grape quality in viticulture. An objective and rapid detection of pests under field conditions is needed. New sensing technologies and artificial intelligence could be used for pests detection in digital viticulture. The aim of this work was to apply computer vision and deep learning techniques for automatic detection of spider mite symptoms in grapevine under field conditions. 

Methods and Results: RGB images of grapevine canopy attacked by the spider mite (Eotetranychus carpini Oud) were manually taken in commercial vineyard (Etxano, Basque Country, Spain) under natural day light conditions. Leaf segmentation in images was performed based on computer vision techniques, isolating target leaves with spider mite visual symptoms from the vineyard canopy. HSV colour space was used to consider colour variations representing symptoms on the leaves, separating these values from those of saturation and brightness of the image. Spider mite detection was done using Convolutional Neural Networks (CNN) models with an artificially augmented dataset for the classification of leaves with this pest symptoms. An accuracy surpassing 75% was obtained using a hold-out validation.

Conclusions: 

High accuracy proves the effectiveness of the trained model in the classification of grapevine leaves. Computer vision techniques were useful to image classification on the relevant pixels. Additionally, deep learning techniques provided a robust model to find complex features of spider mite visual symptoms.

Significance and Impact of the Study: Non-invasive technology and artificial intelligence shown promising results in the automatic detection of pests in commercial vineyards.

DOI:

Publication date: March 23, 2021

Issue: Terroir 2020

Type: Video

Authors

Inés Hernández1, Salvador Gutiérrez2, Sara Ceballos1, Ignacio Barrio1, Fernando Palacios1, Ana M. Diez-Navajas3, Javier Tardáguila1*

1Televitis Research Group. University of La Rioja, 26007 Logroño, Spain 
2Department of Computer Science and Engineering, University of Cádiz, 11519 Puerto Real, Spain 
3Department of Plant Production and Protection, NEIKER-Basque Institute for Agricultural Research and Development, Basque Research and Technology Alliance (BRTA), 01192 Arkaute, Spain

Contact the author

Keywords

Deep learning, computer vision, pests, grapevine, crop protection

Tags

IVES Conference Series | Terroir 2020

Citation

Related articles…

EXPLORING THE INFLUENCE OF S. CEREVISIAE MANNOPROTEINS ON WINE ASTRINGENCY AND THE IMPACT OF THEIR POLYSACCHARIDE STRUCTURE

Mannoproteins (MPs) are proteoglycans from the outmost layer of yeast cell walls released into wine during alcoholic fermentation and ageing on lees processes. The use of commercial preparations of mannoproteins as additives to improve wine stability with regards to the crystallization of tartaric salts and to prevent protein haze in the case of white and rosé wines is authorized by the OIV.
Regarding red wines and polyphenols, mannoproteins are described as able to improve their colloidal stability and modulate the astringent effect of condensed tannins. The latter interact with salivary proteins forming insoluble aggregates that cause a loss of lubrication in the mouth and promote a drying and puckering sensation. However, neither the interaction mechanisms involved in mannoproteins capacity to impact astringency nor the structure-function relationships related to this property are fully understood.

ACIDIC AND DEMALIC SACCHAROMYCES CEREVISIAE STRAINS FOR MANAGING PROBLEMS OF ACIDITY DURING THE ALCOHOLIC FERMENTATION

In a recent study several genes controlling the acidification properties of the wine yeast Saccharomyces cerevisiae have been identified by a QTL approach [1]. Many of these genes showed allelic variations that affect the metabolism of malic acid and the pH homeostasis during the alcoholic fermentation. Such alleles have been used for driving genetic selection of new S. cerevisiae starters that may conversely acidify or deacidify the wine by producing or consuming large amount of malic acid [2]. This particular feature drastically modulates the final pH of wine with difference of 0.5 units between the two groups.

Red wine astringency and the influence of wine–saliva aggregates on oral lubrication

Oral tribology receives growing attention in the field of food sciences as it offers great opportunities to establish correlations between physical parameters, such as the coefficient of friction, and sensory perceptions in the human mouth.

Sensory and consumer perceptions, and consumption barriers of low and no-alcohol wines in Trentino/Alto Adige

The growing demand for non-alcoholic beverages, driven by health-conscious consumers and shifting social norms, has positioned dealcoholized wines as a promising alternative in the global beverage industry (Akhtar et al., 2025, in press; Kakroo, 2024).

WINE SWIRLING: A FIRST STEP TOWARDS THE UNLOCKING OF THE WINE’STASTER GESTURE

Right after the pouring of wine in a glass, a myriad of volatile organic compounds, including ethanol, overwhelm the glass headspace, thus causing the so-called wine’s bouquet [1]. Otherwise, it is worth noting that during wine tasting, most people automatically swirl their glass to enhance the release of aromas in the glass headspace [1]. About a decade ago, Swiss researchers revealed the complex fluid mechanics underlying wine swirling [2]. However, despite mechanically repeated throughout wine tasting, the consequences of glass swirling on the chemical space found in the headspace of wine glasses are still barely known.