Potential of Sentinel-2 satellite images to monitor vine fields grown at a territorial scale

Aim: The aim of this short note is to provide first insights into the ability of Sentinel-2 images to monitor vine growth across a whole season. It focuses on verifying the practical temporal resolution that can be reached with Sentinel-2 images, the main stages of Mediterranean vineyard development as well as potential relevant agronomic information that can be seen on the temporal vegetation curves arising from Sentinel-2 images. Methods and results: The study was carried out in 2017 in a production vineyard located in southern France, 2 km from the Mediterranean seashore. Sentinel-2 images acquired during the whole vine growing cycle were considered, i.e. between the 3rd of March 2017 and the 10th of October 2017. The images were used to compute the classical normalized difference vegetation index (NDVI). Time series of NDVI values were analyzed on four blocks chosen for exhibiting different features, e.g. age, missing plants, weeding practices. The practical time lag between two usable images was closer to 16 days than to the 10 theoretical days (with only one satellite available at the date of the experiment), i.e. near 60% of the theoretical one. Results show that it might be possible to identify i) the main steps of vine development (e.g. budburst, growth, trimming, growth stop and senescence), ii) weed management and inter-row management practices, and iii) possible reasons for significant inter-block differences in vegetative expression (e.g. young vines that have recently been planted, low-productive blocks affected by many missing vines). Conclusions: Although this experiment was conducted at a time when Sentinel-2b was not fully operational, results showed that a sufficient number of usable images was available to monitor vine development. The availability of two Sentinel satellites (2a and 2b) in upcoming seasons should increase the number of usable images and the temporal resolution of the time series. This study also showed the limitations of the Sentinel-2 images’ resolution to provide within-block information in the case of small blocks or blocks with complex borders or both. Significance and impact of the study: This technical note demonstrated the potential of Sentinel-2 images to characterize vineyard blocks’ vigor and to monitor winegrowers’ practices at a territorial (regional) scale. The impact of management operations such as weeding and trimming, along with their incidence on canopy size, were observed on the NDVI time series. Some relevant parameters (slope, maximum values) may be derived from the NDVI time series, providing new insights into the monitoring of vineyards at a large scale. These results provided areas for further investigation, especially regarding the development of new indicators to characterize block-climate relationships

Le Mas numérique, 6 ans d’expérience d’un domaine viticole connecté exemplaire. Partie I : un projet pour la formation et l’acculturation

Le concept d’outil numérique professionnel est souvent perçu comme flou et difficile à concrétiser. L’hypothèse du Mas numérique (Crestey et Tisseyre, 2019, 2020) est que la profession viticole, les instituts de formation et les instituts techniques ont besoin d’exemples concrets pour identifier, évaluer et accompagner la transition numérique des professionnels de la viticulture. Le Mas numérique constitue un exemple de domaine viticole en production qui est équipé avec 15 services numériques professionnels de dernière génération. 6 ans après le lancement du projet, l’objectif de cette note technique est de proposer un retour d’expérience en deux parties. Cette première partie se focalise sur la valeur d’exemple et pédagogique du Mas numérique

Le Mas Numérique: A new model to promote on-farm innovation among digital service providers and to support adoption

International audienceThe objective of the article is to present the results of a project that led to the design and development of a long-term digital Mediterranean farm (commercial wine estate) in the south of France. This farm is intended to demonstrate both the technical and functional interest of digital agricultural tools being adopted by winegrowers and technical services. It presents the original collaboration, the organisation and the financing model that was chosen in order to design a real digital farm with continually up-to-date and updating agri-technologies. This model is new and brings industry, academic and consultancy into the process and allows the digital farm to be continually supported. In 2019, there were 15 digital services embedded on the farm to answer practical issues related to production management and crop protection as well as practical issues related to the interoperability of these services. This model has promoted on-farm interoperability experimentation by digital agriculture service providers and led to new services to fill information gaps

Potential of Sentinel-2 satellite images to monitor vine fields grown at a territorial scale

Aim: The aim of this short note is to provide first insights into the ability of Sentinel-2 images to monitor vine growth across a whole season. It focuses on verifying the practical temporal resolution that can be reached with Sentinel-2 images, the main stages of Mediterranean vineyard development as well as potential relevant agronomic information that can be seen on the temporal vegetation curves arising from Sentinel-2 images. Methods and results: The study was carried out in 2017 in a production vineyard located in southern France, 2 km from the Mediterranean seashore. Sentinel-2 images acquired during the whole vine growing cycle were considered, i.e. between the 3(rd) of March 2017 and the 10(th) of October 2017. The images were used to compute the classical normalized difference vegetation index (NDVI). Time series of NDVI values were analyzed on four blocks chosen for exhibiting different features, e.g. age, missing plants, weeding practices. The practical time lag between two usable images was closer to 16 days than to the 10 theoretical days (with only one satellite available at the date of the experiment), i.e. near 60% of the theoretical one. Results show that it might be possible to identify i) the main steps of vine development (e.g. budburst, growth, trimming, growth stop and senescence), ii) weed management and inter-row management practices, and iii) possible reasons for significant inter-block differences in vegetative expression (e.g. young vines that have recently been planted, low-productive blocks affected by many missing vines). Conclusions: Although this experiment was conducted at a time when Sentinel-2b was not fully operational, results showed that a sufficient number of usable images was available to monitor vine development. The availability of two Sentinel satellites (2a and 2b) in upcoming seasons should increase the number of usable images and the temporal resolution of the time series. This study also showed the limitations of the Sentinel-2 images' resolution to provide within-block information in the case of small blocks or blocks with complex borders or both. Significance and impact of the study: This technical note demonstrated the potential of Sentinel-2 images to characterize vineyard blocks' vigor and to monitor winegrowers' practices at a territorial (regional) scale. The impact of management operations such as weeding and trimming, along with their incidence on canopy size, were observed on the NDVI time series. Some relevant parameters (slope, maximum values) may be derived from the NDVI time series, providing new insights into the monitoring of vineyards at a large scale. These results provided areas for further investigation, especially regarding the development of new indicators to characterize block-climate relationships

Empirical mapping for evaluating an LPWAN (LoRa) wireless network sensor prior to installation in a vineyard

International audienceThe main aim of this study was to use Empirical mapping to test the efficiency of local low cost wireless network sensors (LPWAN - Low-Power Wide Area Network) before being applied in real wine-growing conditions. The second aim was to obtain information on the communication distances to be expected from a LPWAN, taking into account the specific needs and real conditions of a vineyard. A hand-held autonomous end-device was specifically built to simulate short messages sent by sensors via a locally designed LPWAN. This device was used to test the quality of the network from different locations within an entire vineyard and also inside the cellar. Two parameters were used to test the quality of reception of the messages: i) The Received Signal Strength Indication (RSSI), which is the received signal power measured in decibels (dB or dBm), and ii) the Signal-to-Noise Ratio (SNR), which is the ratio of the received signal power to the ambient noise power. Maps of signal reception and errors between the observed and the theoretical signal highlighted how vineyard environment (e.g., hedges, topography, and buildings) affects the signal. The results show that the maximum communication distance differed considerably from distances published in the literature. In the open field, the signal, although attenuated by the distance, was received up to 600 meters away, or even more in favourable conditions. Meanwhile, in urban areas the signal was attenuated by buildings and the electro-magnetic environment and therefore communication distances were very short (< 50 m). Empirical mapping has great potential for determining how the local environment affects signal quality and as a decision support tool for identifying the optimal location for the sensors and gateway. With a single well-positioned gateway, such low cost wireless sensor networks (LPWAN-LoRa) could be used by small to medium-sized vineyards to collect information from sensors either outside in the fields or indoors in the vineyard cellar. This paper proposes a very cheap method (< 40 €) for testing and spatialising the quality of a low cost wireless sensor network before its implementation, and it also provides information on zones with low quality reception

GeoFIS: An Open Source, Decision-Support Tool for Precision Agriculture Data

The world we live in is an increasingly spatial and temporal data-rich environment, and agriculture is no exception. However, data needs to be processed in order to first get information and then make informed management decisions. The concepts of ‘Precision Agriculture’ and ‘Smart Agriculture’ are and will be fully effective when methods and tools are available to practitioners to support this transformation. An open-source software called GeoFIS has been designed with this objective. It was designed to cover the whole process from spatial data to spatial information and decision support. The purpose of this paper is to evaluate the abilities of GeoFIS along with its embedded algorithms to address the main features required by farmers, advisors, or spatial analysts when dealing with precision agriculture data. Three case studies are investigated in the paper: (i) mapping of the spatial variability in the data; (ii) evaluation and cross-comparison of the opportunity for site-specific management in multiple fields; and (iii) delineation of within-field zones for variable-rate applications when these latter are considered opportune. These case studies were applied to three contrasting crop types, banana, wheat and vineyards. These were chosen to highlight the diversity of applications and data characteristics that might be handled with GeoFIS. For each case-study, up-to-date algorithms arising from research studies and implemented in GeoFIS were used to process these precision agriculture data. Areas for future development and possible relations with existing geographic information systems (GIS) software is also discussed

Design, Synthesis, and Biological Evaluation of Erythrina Alkaloid Analogues as Neuronal Nicotinic Acetylcholine Receptor Antagonists

The synthesis of a new series of Erythrina alkaloid analogues and their pharmacological characterization at various nicotine acetylcholine receptor (nAChR) subtypes are described. The compounds were designed to be simplified analogues of aromatic erythrinanes with the aim of obtaining subtype-selective antagonists for the nAChRs and thereby probe the potential of using these natural products as scaffolds for further ligand optimization. The most selective and potent nAChR ligand to come from the series, 6,7-dimethoxy-2-methyl-1,2,3,4-tetrahydroisoquinoline (<b>3c</b>) (also a natural product by the name of <i>O</i>-methylcorypalline), displayed submicromolar binding affinity toward the α4β2 nAChR with more than 300-fold selectivity over α4β4, α3β4, and α7. Furthermore, this lead structure (which also has inhibitory activity at monoamine oxidases A and B and at the serotonin and norepinephrine transporters) showed antidepressant-like effect in the mouse forced swim test at 30 mg/kg

Tying up Nicotine: New Selective Competitive Antagonist of the Neuronal Nicotinic Acetylcholine Receptors

Conformational restriction of the pyrrolidine nitrogen in nicotine by the introduction of an ethylene bridge provided a potent and selective antagonist of the α4β2-subtype of the nicotinic acetylcholine receptors. Resolution by chiral SFC, pharmacological characterization of the two enantiomers, and determination of absolute configuration via enantioselective synthesis showed that the pharmacological activity resided almost exclusively in the (<i>R</i>)-enantiomer