Terroir 2010 banner
IVES 9 IVES Conference Series 9 Valutazione dell’equilibrio vegeto-produttivo con metodiche di proximal sensing

Valutazione dell’equilibrio vegeto-produttivo con metodiche di proximal sensing

Abstract

Nel biennio 2008-2009, nell’ambito di un progetto multidisciplinare coordinato e finanziato dal Consorzio Tuscania, 4 vigneti in differenti zone della Toscana sono stati monitorati con strumenti di proximal sensing al fine di valutare la variabilità riscontrabile e ottenere delle indicazioni sulle risposte vegetative delle piante e quanti-qualitative delle produzioni. La creazione di mappe di NDVI (uno degli indici di vegetazione più comunemente utilizzati) e di spessore delle chiome (CT, derivato dalla lettura dei sensori ad ultrasuoni), ha permesso di evidenziare nette differenze tra i vigneti studiati e all’interno dei singoli appezzamenti, oltre ad una forte influenza temporale sulle caratteristiche delle chiome; tali evidenze sono state confermate da un’analisi della varianza multivariata. I dati rilevati sono stati correlati con alcuni indici comunemente utilizzati per la valutazione vegeto-produttiva delle piante ottenendo delle correlazioni significative, a conferma della validità dei rilievi effettuati e del loro possibile utilizzo come metodo di monitoraggio della situazione esistente in vigneto e di supporto nei processi decisionali

English version: In 2008, collaborating with Tuscania Consortium, Ibimet of Florence and IASMA, a research was started with the aim of understanding and monitoring existing variability in vineyards and, basing on it, evaluating agronomical practices useful for qualitative and quantitative responses optimization. With this purpose, some experimental parcels were chosen in 4 different Sangiovese and Cabernet S. vineyards placed in 3 areas of Tuscany. Parcels were made by the use of different canopy management techniques in various vigour zones. In established periods (fruit setting, veraison and before technological maturity) some instrumental records were made, using ATV mounted optical and ultrasonic sensors; at the same time, indirect measurements of leaf surface and a Point Quadrat were performed. Statistical analysis allowed to validate instrumental relives and to underline the capability of the system of surveying both spatial and temporal variability both an artificial one, made by agronomical practices.

DOI:

Publication date: October 8, 2020

Issue: Terroir 2010

Type: Article

Authors

P. Carnevali (1), L. Brancadoro (1), S. Di Blasi (2), M. Pieri (2)

(1) Dipartimento di Produzione Vegetale, Università degli Studi di Milano. Via Celoria 2, Milano, Italia
(2) Società Consortile Tuscania s.r.l. Piazza Strozzi 1, Firenze, Italia

Contact the author

Keywords

Proximal Sensing – GreenSeeker – Ultrasounds – Vegetative expression

Tags

IVES Conference Series | Terroir 2010

Citation

Related articles…

Effect of multi-level and multi-scale spectral data source on vineyard state assessment

Currently, the main goal of agriculture is to promote the resilience of agricultural systems in a sustainable way through the improvement of use efficiency of farm resources, increasing crop yield and quality under climate change conditions. This last is expected to drastically modify plant growth, with possible negative effects, especially in arid and semi-arid regions of Europe on the viticultural sector. In this context, the monitoring of spatial behavior of grapevine during the growing season represents an opportunity to improve the plant management, winegrowers’ incomes, and to preserve the environmental health, but it has additional costs for the farmer. Nowadays, UAS equipped with a VIS-NIR multispectral camera (blue, green, red, red-edge, and NIR) represents a good and relatively cheap solution to assess plant status spatial information (by means of a limited set of spectral vegetation indices), representing important support in precision agriculture management during the growing season. While differences between UAS-based multispectral imagery and point-based spectroscopy are well discussed in the literature, their impact on plant status estimation by vegetation indices is not completely investigated in depth. The aim of this study was to assess the performance level of UAS-based multispectral (5 bands across 450-800nm spectral region with a spatial resolution of 5cm) imagery, reconstructed high-resolution satellite (Sentinel-2A) multispectral imagery (13 bands across 400-2500 nm with spatial resolution of <2 m) through Convolutional Neural Network (CNN) approach, and point-based field spectroscopy (collecting 600 wavelengths across 400-1000 nm spectral region with a surface footprint of 1-2 cm) in a plant status estimation application, and then, using Bayesian regularization artificial neural network for leaf chlorophyll content (LCC) and plant water status (LWP) prediction. The test site is a Greco vineyard of southern Italy, where detailed and precise records on soil and atmosphere systems, in-vivo plant monitoring of eco-physiological parameters have been conducted.

Mobile device to induce heat-stress on grapevine berries

Studying heat stress response of grapevine berries in the field often relies on weather conditions during the growing season. We constructed a mobile heating device, able to induce controlled heat stress on grapes in vineyards. The heater consisted of six 150 W infrared lamps mounted in a profile frame. Heating power of the lamps could be controlled individually by a control unit consisting of a single board computer and six temperature sensors to reach a pre-set temperature. The heat energy applied to individual berries within a cluster decreases by the squared distance to the heat source, enabling the establishment of temperature profiles within individual clusters. These profiles can be measured by infrared thermography once a steady state has been reached. Radiant flux density received by a berry depending on the distance was calculated based on a view factor and measured lamp surface temperature and resulted to 665 Wm-2 at 7cm. Infrared thermography of the fruit surface was in good agreement with measurements conducted with a thermocouple inserted at epidermis level. In combination with infrared thermography, the presented device offers possibilities for a wide range of applications like phenotyping for heat tolerance in the field to proceed in the understanding of the complex response of plants to heat stress. Sunburn necrosis symptoms were artificially induced with the aid of the device for cv. Bacchus and cv. Sylvaner in the 2020 and 2021 growing season. Threshold temperatures for sunburn induction (LT5030min) were derived from temperature data of single berries and visual sunburn assessment, applying logistic regression. A comparison of threshold temperatures for the occurrence of sunburn necrosis confirmed the higher susceptibility of cv. Bacchus. The lower susceptibility of cv. Sylvaner did not seem to be related to its phenolic composition, rendering a thermoprotective role of berry phenolic compounds unlikely.

Legacy of land-cover changes on soil erosion and microbiology in Burgundian vineyards

Soils in vineyards are recognized as complex agrosystems whose characteristics reflect complex interactions between natural factors (lithology, climate, slope, biodiversity) and human activities. To date, most of the unknown lies in an incomplete understanding of soil ecosystems, and specifically in the microbial biodiversity even though soil microbiota is involved in many key functions, such as nutrient cycling and carbon sequestration. Soil biological properties are indicative of soil quality. Therefore, understanding how soil communities are related to soil ecosystem functioning is becoming an essential issue for soil strategy conservation. Here, we propose to assess the importance of land-cover history on the present-day microbiological and physico-chemical properties. The studied area was selected in the Burgundian vineyards (Pernand-Vergelesses, Burgundy, France) where land occupation has been reconstructed over the last 40 years. Soil samples were collected in five areas reflecting various land cover history (forest, vineyards, shifting from forest to vineyards). For each area, physico-chemical parameters (pH, C, N, P, grain size) were measured and DNA was extracted to characterize the abundance and diversity of microbial communities. The obtained results show significant differences in the five areas suggesting that present-day microbial molecular biomass and bacterial taxonomic is partly inherited from past land occupation. Over longer period of time, such study of land-uses legacies may help to better assess ecosystem recovery and the impact of management practices for a better soil quality and vineyards sustainability.

Grapevine sugar concentration model in the Douro Superior, Portugal

Increasingly warm and dry climate conditions are challenging the viticulture and winemaking sector. Digital technologies and crop modelling bear the promise to provide practical answers to those challenges. As viticultural activities strongly depend on harvest date, its early prediction is particularly important, since the success of winemaking practices largely depends upon this key event, which should be based on an accurate and advanced plan of the annual cycle. Herein, we demonstrate the creation of modelling tools to assess grape ripeness, through sugar concentration monitoring. The study area, the Portuguese Côa valley wine region, represents an important terroir in the “Douro Superior” subregion. Two varieties (cv. Touriga Nacional and Touriga Franca) grown in five locations across the Côa Region were considered. Sugar accumulation in grapes, with concentrations between 170 and 230 g l-1, was used from 2014 to 2020 as an indicator of technological maturity conditioned by meteorological factors. The climatic time series were retrieved from the EU Copernicus Service, while sugar data were collected by a non-profit organization, ADVID, and by Sogrape, a leading wine company. The software for calibrating and validating this model framework was the Phenology Modeling Platform (PMP), version 5.5, using Sigmoid and growing degree-day (GDD) models for predictions. The performance was assessed through two metrics: Roots Mean Square Error (RMSE) and efficiency coefficient (EFF), while validation was undertaken using leave-one-out cross-validation. Our findings demonstrate that sugar content is mainly dependent on temperature and air humidity. The models achieved a performance of 0.65

Grapevine yield-gap: identification of environmental limitations by soil and climate zoning in Languedoc-Roussillon region (south of France)

Grapevine yield has been historically overlooked, assuming a strong trade-off between grape yield and wine quality. At present, menaced by climate change, many vineyards in Southern France are far from the quality label threshold, becoming grapevine yield-gaps a major subject of concern. Although yield-gaps are well studied in arable crops, we know very little about grapevine yield-gaps. In the present study, we analysed the environmental component of grapevine yield-gaps linked to climate and soil resources in the Languedoc Roussillon. We used SAFRAN data and IGP Pays d’Oc wine yields from 2010 to 2018. We selected climate and soil indicators proving to have a significant effect on average wine yield-gaps at the municipality scale. The most significant factors of grapevine yield were the Soil Available Water Capacity; followed by the Huglin Index and the Climatic Dryness Index. The Days of Frost; the Soil pH; and the Very Hot Days were also significant. Then, we clustered geographical zones presenting similar indicators, facilitating the identification of resources yield-gaps. We discussed the number of zones with the experts of IGP Pays d’Oc label, obtaining 7 zones with similar limitations for grapevine yield. Finally, we analysed the main resources causing yield-gaps and the grapevine varieties planted on each zone. Mapping grapevine resource yield-gaps are the first stage for understanding grapevine yield-gaps at the regional scale.