terclim by ICS banner
IVES 9 IVES Conference Series 9 VINIoT: Precision viticulture service for SMEs based on IoT sensors network

VINIoT: Precision viticulture service for SMEs based on IoT sensors network

Abstract

The main innovation in the VINIoT service is the joint use of two technologies that are currently used separately: vineyard monitoring using multispectral imaging and deployed terrain sensors. One part of the system is based on the development of artificial intelligence algorithms that are feed on the images of the multispectral camera and IoT sensors, high-level information on water stress, grape ripening status and the presence of diseases. In order to obtain algorithms to determine the state of ripening of the grapes and avoid losing information due to the diversity of the grape berries, it was decided to work along the first year 2020 at berry scale in the laboratory, during the second year at the cluster scale and on the last year at plot scale. Different varieties of white and red grapes were used; in the case of Galicia we worked with the white grape variety Treixadura and the red variety Mencía. During the 2020 and 2021 campaigns, multispectral images were taken in the visible and infrared range of: 1) sets of 100 grapes classifying them by means of densimetric baths, 2) individual bunches. The images taken with the laboratory analysis of the ripening stage were correlated. Technological maturity, pH, probable degree, malic acid content, tartaric acid content and parameters for assessing phenolic maturity, IPT, anthocyanin content were determined. It has been calculated for each single image the mean value of each spectral band (only taking into account the pixels of interest) and a correlation study of these values with laboratory data has been carried out. These studies are still provisional and it will be necessary to continue with them, jointly with the training of the machine learning algorithms. Processed data will allow to determine the sensitivity of the multispectral images and select bands of interest in maturation.

DOI:

Publication date: May 31, 2022

Issue: Terclim 2022

Type: Poster

Authors

María del Carmen Saborido Díaz1, María Dolores Loureiro Rodríguez1, Rocío Pena2, Julio Illade2 Tamara Rodríguez3, Javier José Cancela Barrio4, Beatriz Castiñeiras1 and Emilia Díaz Losada1

1Axencia Galega da Calidade Alimentaria (Agacal) – EVEGA, Leiro, Ourense, Spain
2Centro Tenológico AIMEN, Porriño, Pontevedra, Spain
3FEUGA-Fundación Empresa-Universidad Gallega, Santiago de Compostela, A Coruña, Spain
4USC – Universidade de Santiago de Compostela, Lugo, Spain

Contact the author

Keywords

vineyard monitoring, vineyard sensors, multispectral images, environmental impact, IoT design

Tags

IVES Conference Series | Terclim 2022

Citation

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.