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


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.


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.


Publication date: March 23, 2021

Issue: Terroir 2020

Type: Video


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


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


IVES Conference Series | Terroir 2020


Related articles…

Physiological and growth reaction of Shiraz/101-14 Mgt to row orientation and soil water status

Advanced knowledge on grapevine row orientation is required to improve establishment, management and outcomes of vineyards on terroirs with different environmental conditions (climate, soil, topography) and in view of a future change to more extreme climatic conditions. The purpose of this study was to determine the combined effect of row orientation, plant water status and ripeness level on the physiological and viticultural reaction of Shiraz/101-14 Mgt.

Effects of mechanical leafing and deficit irrigation on Cabernet Sauvignon grown in warm climate of California

San Joaquin Valley accounts for 40% of wine grape acreage and produces 70% of wine grape in California. Fruit quality is one of most important factors which impact the economical sustainability of farming wine grapes in this region. Due to the recent drought and expected labor cost increase, the wine industry is thrilled to understand how to improve fruit quality while maintaining the yield with less water and labor input. The present study aims to study the interactive effects of mechanical leafing and deficit irrigation on yield and berry compositions of Cabernet Sauvignon grown in warm climate of California.

The effects of cane girdling on berry texture properties and the concentration of some aroma compounds in three table grape cultivars

The marketability of the table grapes is highly influenced by the consumer demand; therefore the market value of the table grapes is mainly characterized by its berry size, colour, taste and texture. Girdling could cause accumulation of several components in plants above the ringing of the phloem including clusters and resulting improved maturity. The aim of the experiments was to examine the effect of girdling on berry texture characteristics and aroma concentration.

Application of a fluorescence-based method to evaluate the ripening process and quality of Pinot Blanc grape

The chemical composition of grape berries at harvest is one of the most important factors that should be considered to produce high quality wines. Among the different chemical classes which characterize the grape juice, the polyphenolic compound, such as flavonoids, contribute to the final taste and color of wines. Recently, an innovative non-destructive method, based on chlorophyll fluorescence, was developed to estimate the phenolic maturity of red grape varieties through the evaluation of anthocyanins accumulated in the berry skin. To date, only few data are available about the application of this method on white grape varieties.

Different yield regulation strategies in semi-minimal-pruned hedge (SMPH) and impact on bunch architecture

Yields in the novel viticulture training system Semi-Minimal-Pruned Hedge (SMPH) are generally higher compared to the traditional Vertical Shoot Positioning (VSP). Excessive yields have a negative impact on the vine and wine quality, which can result in substantial losses in yield in subsequent vintages (alternate bearing) or penalties in fruit quality. Therefore yield regulation is essential. The bunch architecture in SMPH differs from VSP. Generally there is a higher amount but smaller bunches with lower single berry weights in SMPH compared to VSP.