terclim by ICS banner
IVES 9 IVES Conference Series 9 GiESCO 9 Deep learning based models for grapevine phenology

Deep learning based models for grapevine phenology


Context and purpose of the study – the phenological evolution is a crucial aspect of grapevine growth and development. Accurate detection of phenological stages can improve vineyard management, leading to better crop yield and quality traits. However, traditional methods of phenological tracking such as on-site observations are time-consuming and labour-intensive. This work proposes a scalable data-driven method to automatically detect key phenological stages of grapevines using satellite data. Our approach applies to vast areas because it solely relies on open and satellite data having global coverage without requiring any in-field data from weather stations or other sensors making the approach extensible to other areas.

Material and methods we leveraged historical phenological observations and developed a supervised deep-learning model that uses the land surface temperature estimated by the Copernicus Sentinel-3 satellite to estimate the current phenological stage at the parcel level. We compared the performances of our model with traditional approach based on Growing Degrees Days (GDD).

Results – we train our algorithm on manually collected phenological observations of four winegrape cultivars in three Europeanvineyards (Italy, Spain, and Portugal) from 2017 to 2022. Preliminary results indicated that our deep learning phenology model outperforms the traditional methods based on GDD, decreasing the Mean Absolute Error from 33.8 to 7.8 days (-76.5%).


Publication date: July 5, 2023

Issue: GiESCO 2023

Type: Poster


Federico OLDANI1*, Dario SALZA1, Giacomo BLANCO1, Claudio ROSSI1, Boris BASILE2*, Fabrizio CARTENI2, Núria PÉREZ-ZANÓN3, Antonio DENTE4, Fernando ALVES5, Joana VALENTE5, Montse TORRES6, Carlos EZQUERRA6, Rosa ARAUJO7

1LINKS Foundation, Turin, Italy
2Department of Agricultural Sciences, University of Naples Federico II, Portici (Napoli), Italy
3Barcelona Supercomputing Center, Barcelona, Spain
4Mastroberardino, Atripalda (Avellino), Italy
5Symington Family Estates, V. N. Gaia, Portugal
6Familia Torres, Vilafranca del Penedès, Spain
7Eurecat, Centre Tecnològic de Catalunya, Barcelona, Spain

Contact the author*


satellite imagery, earth observation, machine learning, Sentinel-3, Copernicus, climate change


GiESCO | GIESCO 2023 | IVES Conference Series


Related articles…

Effect of foliar application of Ca, Si and their combination on grape volatile composition

Calcium (Ca) is an important nutrient for plants which plays key signaling and structural roles. It has been observed that exogenous Ca application favors the pectin accumulation and inhibition of polygalacturonase enzymes, minimizing fruit spoilage. Silicon (Si) is a non-essential element which has been found to be beneficial for improving crop yield and quality, as well as plant tolerance to diverse abiotic and biotic stress factors. The effect of Si supply to grapevine has been assessed in few investigations, which reported positive changes in grape quality and must composition.

Late winter pruning induces a maturity delay under temperature-increased conditions in cv. Merlot from Chile

Chile is considered vulnerable to climate change; and these phenomena affect several mechanisms in the grape physiology and quality. The global temperature increase affects sugar contents, organic acids, and phenolic compounds in grapes, producing an imbalance maturity. In this sense, an alternative to reduce the impact is to perform pruning after vine budburst, known as “Late Pruning” (LP).

Effect of two water deficit regimes on the agronomic response of 12 grapevine varieties cultivated in a semi-arid climate

The Mediterranean basin is one of the most vulnerable regions to Climate Change effects. According to unanimous forecasts, the vineyards of Castilla-La Mancha will be among the most adversely affected by rising temperatures and water scarcity during the vine’s vegetative period. One potential strategy to mitigate the negative impacts of these changes involves the identification of grapevine varieties with superior water use efficiency, while ensuring satisfactory yields and grape quality.

Influence of irrigation frequency on berry phenolic composition of red grape varieties cultivated in four spanish wine-growing regions

The global warming phenomenon involves the frequency of extreme meteorological events accompanied by a change in rainfall distribution. Irrigation frequency (IF) affects the spatial and temporal soil water distribution but its effects on the phenolic composition of the grape have been scarcely studied. The aim of this work was to evaluate the effects of four deficit irrigation frequencies of 30 % ETo: one irrigation per day (T01), two irrigations per week (T03), one irrigation per week (T07) and one irrigation every two weeks (T15) on berry phenolic composition at harvest.

Response of red grape varieties irrigated during the summer to water availability at the end of winter in four Spanish wine-growing regions: berry phenolic composition

Water availability is the most limiting factor for vineyard productivity under Mediterranean conditions. Due to the effects caused by the current climate change, wine-growing regions may face serious soil moisture conservation problems, due to the lower water retention capacity of the soil and higher soil irradiation. The aim of this work was to evaluate the effects of soil recharge irrigation in pre-sprouting and summer irrigation every week (30 % ETo) from the pea size state until the end of ripening (RP) compared to exclusively summer irrigation every week (R) in the same way that RP, on berry phenolic composition at harvest.