Vineyard Fields Research Articles

DNA metabarcoding of gut contents reveals natural predation by spiders on Xylella fastidiosa vectors in the southwestern Spain agroecosystem

Aim of study: To elucidate which species and specific guilds of spiders prey on vectors of Xylella fastidiosa from agroecosystems in southwestern Spain using metabarcoding approach. Area of study: Southwestern Spain. Material and methods: Spiders sampling was carried out on ground cover vegetation of olive, citrus and vineyard fields using a battery powered aspirator. DNA was isolated from each sample using E.Z.N.A.® Tissue DNA kit (Omega Bio-tek). A primer pair was designed to specifically amplify DNA from the following spiders’ potential prey belonging to the order Hemiptera: Philaenus spumarius, Neophilaenus campestris, Neophilaenus lineatus, Lepyronia coleoptrata, Aphrophora sp., Cicadella viridis, and Cercopis sp. Taxonomic assignment was conducted using the MetaCOXI reference database, based on the European Nucleotide Archive (ENA) and the Barcode of Life Data System (BOLD). Main results: Neophilaenus campestris was detected in two spider species: Enoplognatha caricis (Theridiidae) and Thanatus vulgaris (Philodromidae) (10.4% of the captured specimens). In addition, L. coleoptrata was preyed on by Haplodrassus macellinus (Gnaphosidae) (3.5%). In contrast, P. spumarius DNA was not detected in any of the spider samples. However, aphrophorid DNA was detected in the gut of spider collected in vineyards and citrus orchards but not in olive orchards. Concerning the spider guilds, aphrophorids were detected in the gut of “other hunters”, “ground hunters” and “space-web” spiders. Research highlights: Some species of spiders found in vineyards (50% of captured specimens) consumed N. campestris.

Let the dust settle: Impact of enhanced rock weathering on soil biological, physical, and geochemical fertility

Terrestrial enhanced rock weathering (ERW) is a promising carbon dioxide removal technology that consists in applying ground silicate rock such as basalt on agricultural soils. On top of carbon sequestration, ERW has the potential to raise the soil pH and release nutrients, thereby improving soil fertility. Despite these possible co-benefits, concerns such as heavy metal pollution or soil structure damage have also been raised. To our knowledge, these contrasted potential effects of ERW on soil fertility have not yet been simultaneously investigated. This field trial aimed at assessing the impact of ERW on biological, physical, and chemical soil properties in a temperate agricultural context. To do so, three vineyard fields in Switzerland were selected for their distinct geochemical properties and were amended with basaltic rock powder at a dose of 20 tons per hectare (2 kg.m−2). On each field, basaltic rock powder was either applied one year before the sampling campaign, one month before the sampling campaign, or not applied (control) for a total of 27 plots with 9 repetitions of each level. Overall, basaltic rock powder addition had a predominantly positive to neutral effect on soil fertility. Most soil properties showed no significant change either 1 month or 1 year post application. Nevertheless, our study highlighted a significant increase in earthworm abundance (+71 % on average), soil respiration (+50 %) and extractable sodium concentration (+23 %) as early as 1 month post application. The higher soil respiration raises the question of CO2 losses from organic matter mineralization that could limit ERW's efficiency. The increase in sodium raises concerns about a sodification risk potentially damaging soil fertility. These elements now require further investigation before enhanced rock weathering can be considered a viable and secure carbon dioxide removal technology.

Area and configuration of both semi‐natural habitats and vineyards influence arthropods in South African and central European agricultural landscapes

Abstract Restoring the heterogeneity of farmland mosaics can help mitigate the ongoing global decline of biodiversity. It has been shown that semi‐natural habitats in viticultural landscapes influence biodiversity in vineyards. However, less attention has been paid to the influence of the extent of vineyard fields and their arrangement in the landscape. Using previously published data, we investigated the influence of both semi‐natural habitats and vineyard fields on arthropod diversity in vineyards in 35 viticultural landscapes located in South Africa and Austria. Effects on several arthropod groups were assessed using standardised landscape predictors that integrate compositional (total area) and configurational (shape and spatial arrangement) heterogeneity of semi‐natural habitats and vineyards. In addition, we assessed the influence of within‐vineyard vegetation cover and farming system (organic or non‐organic) to explore local‐scale effects. Within‐vineyard vegetation and flower cover had a consistent positive influence on most arthropod taxa, whereas farming system had little effect. In addition, configurational heterogeneity of semi‐natural vegetation and vineyards influenced several taxa. However, different taxa showed contrasting relationships with configurational heterogeneity, hindering general recommendations for optimal configuration of semi‐natural elements and vineyards in the landscape. The only significant response to compositional heterogeneity was bug abundance in South Africa, which increased with increasing proportion of semi‐natural elements. We found that increasing vegetation cover in vineyards is an effective and easily implementable measure to improve biodiversity in vineyards. In addition, the spatial arrangement of vineyards influences within‐vineyard arthropod diversity as much as the spatial arrangement of semi‐natural vegetation in the landscape, which expands the possibilities for planning viticultural landscapes with high overall biodiversity.

Antifungal activities of vineyard-habitat wild yeast for grape gray-mold disease and its effects on spontaneous winemaking.

Microorganisms, including native yeasts, are abundant in vineyard fields. Herein, we studied the possibility of using vineyard-derived wild yeast as a microbial pesticide against Botrytis cinerea, a pathogen that causes grape gray mold disease, to boost the initial alcohol production of spontaneously fermented wine. We identified the Saccharomyces cerevisiae strain KONDO170908, which showed the most effective antifungal activity in an ex vivo yeast dripping experiment on grape berries. This strain was utilized in an in vivo spray test on grape bunches in vineyard fields and was proven to significantly suppress gray mold disease on the grape berries in test plot #16 when the yeast was sprayed during both the flowering and ripening periods (morbidity 11.2% against 15.3% of the control plot, χ2 test, p < 0.0001). However, in test plot #17, spraying the yeast during only the ripening period had no effect (morbidity 16.3%). The grapes from each test plot were also submitted for spontaneous wine fermentation. Alcoholic fermentation of the grapes from test plot #16 provided the most active bubbling of CO2 gas and the highest ethanol production and colony counts over seven days of fermentation. Unique changes in the different strains of S. cerevisiae among the plots were observed throughout the early fermentation stage. Thus, yeast spraying during the flowering period might trigger modification of the entire microbiota and could ultimately contribute to promoting alcohol production in the spontaneously fermented wine, although it decreased the grape yield by 20%.

MAPPING AGRICULTURAL WASTE FOR BIOGAS PRODUCTION USING A FULLY CONVOLUTIONAL NEURAL NETWORK AND REMOTE SENSING IMAGERY

The increasing generation of waste and depletion of natural resources has led to a growing need for innovative approaches for utilizing different types of waste as potential energy and material resources. Agricultural activities produce large amounts of Agricultural Waste (AW), which, if not adequately managed, can lead to environmental degradation. One potential solution for the effective utilization of AW is converting it into biogas. However, commercializing this process requires a comprehensive understanding of the types and quantities of AW generated. In this paper, the use of a Fully Convolutional Neural Network (FCN), which has rapidly advanced with the progress of Artificial Intelligence and become essential for tasks such as Semantic Segmentation, Object Detection, and Image Classification, is proposed to improve the prediction of AW for biogas production. Furthermore, this paper presents a Deep Learning-based image segmentation method to recognize vineyard fields, which are a significant source of AW, using remote satellite images. The proposed approach can significantly improve the identification of AW sources, and thus contribute to the efficient and sustainable utilization of AW for biogas production.

Attenuation and soil biodegradation of fungicides by using vegetated buffer strips in vineyards during a simulated rainfall–runoff event

Rainfall–runoff events occurring in vineyard fields can result in pesticide ground losses and the subsequent pollution of surface water bodies, derivate from the crop protection spray applications. In this study, the capacity of vegetated buffer strips (BS) to prevent surface water pollution due to the application of five fungicide products typically used in vineyards (copper, dimethomorph, oxathiapiprolin, zoxamide, acibenzolar-s-methyl, and laminarin) following a simulated run-off event has been assessed, and compared to that from a bare ground soil (BG). Two strips (5 m in length, each), one with vegetation and the other without were built up, and two different experiments were performed, a runoff event and a soil fungicide degradation kinetic evaluation. The runoff results show that fungicide mass retention in the strips ranged from 73 to 98% and that the presence of vegetation in BS increased the fungicide mass retention in the strips by almost 10% (on average) in comparison to the unvegetated strip. Moreover, soil degradation studies highlighted that the presence of vegetation reduces significantly the half-time life of almost all the studied fungicides by 55%, on average. Eight fungicide transformation products (TPs) were identified following a runoff event in the soil strips, but the abundance of these TPs was up to 78% lower in vegetated strips. These results highlight the effectiveness of using vegetated buffer zones in vineyards to protect aquatic ecosystem pollution.

Conyza Species in Citrus Orchards and Vineyards of Turkey and Their Management with Glyphosate

Conyza species are considered one of the most aggressive weeds in the Aegean and Mediterranean regions of Turkey in terms of their invasive character and their ability to spread to agricultural and nonagricultural areas, including citrus orchards and vineyards. This study was conducted to determine the distribution of Conyza species in citrus orchards and vineyards in these regions and the efficacy of glyphosate when used at different growth stages. The majority of citrus fields and nearly half of the vineyard fields of Turkey were visited in 2015. Due to their similar appearance, the identification of Conyza species at the early stages of growth cannot straightforward; therefore, the species C. canadensis, C. bonariensis, and C. sumatrensis were identified by using PCR and DNA sequence analysis. A total of 252 citrus orchards (131) and vineyards (121) were included in the field survey conducted in the Aegean and Mediterranean regions, and 203 Conyza species were collected. The molecular data revealed that C. bonariensis was the most common Conyza species in nearly half of the citrus orchards, followed by C. canadensis at 33%. C. canadensis was the most dominant Conyza species in more than half of the vineyards, while C. bonariensis and C. sumatrensis were found in 36 and 13 vineyards, respectively. Sequence information of Conyza species was submitted to NCBI with GenBank accession numbers (Conyza (Erigeron) canadensis accession number: OM302550.1, C. bonarensis accession number: OM302551.1, C. sumatrensis accession number: OM302548.1). Glyphosate was more effective when it was applied at the earlier rosette stages for both susceptible and resistant biotypes. Therefore, late treatments could be the main reason for glyphosate having low efficacy against non-resistant populations of Conyza spp.&#x0D; &#x0D; Keywords: Citrus orchard, DNA sequence analysis, Glyphosate, Horseweed, Vineyard

The deterrent ability of Xenorhabdus nematophila and Photorhabdus laumondii compounds as a potential novel tool for Lobesia botrana (Lepidoptera: Tortricidae) management

The grapevine moth, Lobesia botrana (Lepidoptera: Tortricidae), is a critical pest for vineyards and causes significant economic losses in wine-growing areas worldwide. Identifying and developing novel semiochemical cues (e.g. volatile bacterial compounds) which modify the ovipositional and trophic behaviour of L. botrana in vineyard fields could be a novel control alternative in viticulture. Xenorhabdus spp. and Photorhabdus spp. are becoming one of the best-studied bacterial species due to their potential interest in producing toxins and deterrent factors. In this study, we investigated the effect of the deterrent compounds produced by Xenorhabdus nematophila and Photorhabdus laumondii on the ovipositional moth behaviour and the larval feeding preference of L. botrana. Along with the in-vitro bioassays performed, we screened the potential use of 3 d cell-free bacterial supernatants and 3 and 5 d unfiltered bacterial ferments. In addition, we tested two application systems: (i) contact application of the bacterial compounds and (ii) volatile bacterial compounds application. Our findings indicate that the deterrent effectiveness varied with bacterial species, the use of bacterial cell-free supernatants or unfiltered fermentation product, and the culture times. Grapes soaked in the 3 d X. nematophila and P. laumondii ferments had ∼ 55% and ∼ 95% fewer eggs laid than the control, respectively. Likewise, the volatile compounds emitted by the 5 d P. laumondii fermentations resulted in ∼ 100% avoidance of L. botrana ovipositional activity for three days. Furthermore, both bacterial fermentation products have larval feeding deterrent effects (∼65% of the larva chose the control grapes), and they significantly reduced the severity of damage caused by third instar larva in treated grapes. This study provides insightful information about a novel bacteria-based tool which can be used as an eco-friendly and economical alternative in both organic and integrated control of L. botrana in vineyard.

New insights from short and long reads sequencing to explore cytochrome b variants in Plasmopara viticola populations collected from vineyards and related to resistance to complex III inhibitors.

Downy mildew is caused by Plasmopara viticola, an obligate oomycete plant pathogen, a devasting disease of grapevine. To protect plants from the disease, complex III inhibitors are among the fungicides widely used. They specifically target the mitochondrial cytochrome b (cytb) of the pathogen to block cellular respiration mechanisms. In the French vineyard, P. viticola has developed resistance against a first group of these fungicides, the Quinone outside Inhibitors (QoI), with a single amino acid substitution G143A in its cytb mitochondrial sequence. The use of QoI was limited and another type of fungicide, the Quinone inside Inhibitors, targeting the same gene and highly effective against oomycetes, was used instead. Recently however, less sensitive P. viticola populations were detected after treatments with some inhibitors, in particular ametoctradin and cyazofamid. By isolating single-sporangia P. viticola strains resistant to these fungicides, we characterized new variants in the cytb sequences associated with cyazofamid resistance: a point mutation (L201S) and more strikingly, two insertions (E203-DE-V204, E203-VE-V204). In parallel with the classical tools, pyrosequencing and qPCR, we then benchmarked short and long-reads NGS technologies (Ion Torrent, Illumina, Oxford Nanopore Technologies) to sequence the complete cytb with a view to detecting and assessing the proportion of resistant variants of P. viticola at the scale of a field population. Eighteen populations collected from French vineyard fields in 2020 were analysed: 12 showed a variable proportion of G143A, 11 of E203-DE-V204 and 7 populations of the S34L variant that confers resistance to ametoctradin. Interestingly, the long reads were able to identify variants, including SNPs, with confidence and to detect a small proportion of P. viticola with multiple variants along the same cytb sequence. Overall, NGS appears to be a promising method for assessing fungicide resistance of pathogens linked to cytb modifications at the field population level. This approach could rapidly become a robust decision support tool for resistance management in the future.

Autonomous Vineyard Tracking Using a Four-Wheel-Steering Mobile Robot and a 2D LiDAR

The intensive advances in robotics have deeply facilitated the accomplishment of tedious and repetitive tasks in our daily lives. If robots are now well established in the manufacturing industry, thanks to the knowledge of the environment, this is still not fully the case for outdoor applications such as in agriculture, as many parameters are varying (kind of vegetation, perception conditions, wheel–soil interaction, etc.) The use of robots in such a context is nevertheless important since the reduction of environmental impacts requires the use of alternative practices (such as agroecological production or organic production), which require highly accurate work and frequent operations. As a result, the design of robots for agroecology implies notably the availability of highly accurate autonomous navigation processes related to crop and adapting to their variability. This paper proposes several contributions to the problem of crop row tracking using a four-wheel-steering mobile robot, which straddles the crops. It uses a 2D LiDAR allowing the detection of crop rows in 3D thanks to the robot motion. This permits the definition of a reference trajectory that is followed using two different control approaches. The main targeted application is navigation in vineyard fields, to achieve several kinds of operation, such as monitoring, cropping, or accurate spraying. In the first part, a row detection strategy based on a 2D LiDAR inclined in front of the robot to match a predefined shape of the vineyard row in the robot framework is described. The successive detected regions of interest are aggregated along the local robot motion, through the system odometry. This permits the computation of a local trajectory to be followed by a robot. In a second part, a control architecture that allows the control of a four-wheel-steering mobile robot is proposed. Two different strategies are investigated, one is based on a backstepping approach, while the second considers independently the regulation of front and rear steering axle position. The results of these control laws are then compared in an extended simulation framework, using a 3D reconstruction of actual vineyards in different seasons.

Habitat amount mediates the effect of fragmentation on a pollinator's reproductive performance, but not on its foraging behaviour.

Agricultural intensification, with its associated habitat loss and fragmentation, is among the most important drivers of the ongoing pollination crisis. In this quasi-experimental study, conducted in intensively managed vineyards in southwestern Switzerland, we tested the separate and interdependent effects of habitat amount and fragmentation on the foraging activity and reproductive performance of bumblebee Bombus t. terrestris colonies. Based on a factorial design, we selected a series of spatially replicated study sites across a dual gradient of habitat amount (area of ground-vegetated vineyards) and fragmentation (density of ground-vegetated vineyard fields) in a landscape predominantly consisting of vineyards with bare grounds. The foraging activity of individual bumblebees was measured using the radio frequency identification (RFID) technology, and we assessed final colony size to measure reproductive performance. We found an interactive effect of habitat amount and fragmentation on colony size. More specifically, the degree of fragmentation had a negative effect on bumblebee colony size when the amount of habitat was low, while it had a weak positive effect on colony size in landscapes with high amounts of habitat. At the level of individual vineyard fields, ground vegetation cover exerted a positive effect on bumblebee colony size. Fragmentation, but not habitat amount, significantly influenced foraging activity, with more foraging trips in sites with lower degrees of fragmentation. Our results emphasise the importance of studying the separate and interdependent effects of habitat amount and fragmentation to understand their influence on pollinators, providing guidance for optimising the spatial configuration of agricultural landscapes from a biodiversity viewpoint.

Ground greening in vineyards promotes the Woodlark Lullula arborea and their invertebrate prey

Vineyards are intensively managed monocultures, constituting homogeneously cultivated landscapes. They often have a mineral appearance, not only because they occur mostly in xeric biomes but also as a result of the herbicide treatments used to combat ground vegetation. However, new vineyard management practices are being developed that tolerate more vegetation cover on the ground, potentially having positive impacts on biodiversity. We have investigated the effects of ground greening on habitat preferences of the Woodlark (Lullula arborea), an emblematic, insectivorous passerine typical of vineyards in central and southern Europe. We first investigated the role of ground vegetation cover and plant species richness on habitat use by Woodlarks, while accounting for various additional habitat characteristics. Second, we assessed whether the dependence of Woodlarks on ground vegetation cover could be mediated by an increased occurrence of invertebrate prey. Ground-dwelling invertebrates were sampled with pitfall traps placed in vineyard fields visited by Woodlarks (presence fields) and in adjacent vineyards where Woodlarks had not been observed (pseudo-absence fields). We show that increased ground vegetation cover, plant species richness and wider inter-rows were the main drivers of Woodlark occurrence. Overall invertebrate prey abundance increased with ground vegetation cover. Similarly, the abundance and number of beetle and spider families were primarily driven by increased ground vegetation cover, plant species richness or wider inter-rows. We conclude that less intensive management, which involves the restricted use of herbicides and concomitantly favors a diverse plant community, promotes Woodlarks and their invertebrate prey, thus having a positive impact on vineyard biodiversity at multiple trophic levels.

Assessment of soil quality for vineyard fields: A case study in Menderes District of Izmir, Turkey

This study was carried out to determine the suitable classification of soil quality for vineyard fields of Akçaköy, Çatalca, Efemçukuru, Görece and Yeniköy villages in Menderes district of Izmir-Turkey. In vineyard fields, soil pH gave a positive relation with Ca and significant negative relations with P, Fe, Mn and Zn contents. Soil organic matter (OM) content had significant positive relations with EC, P, Fe, Mn and Zn and significant negative relations with bulk density and CaCO 3 content. Soil quality index values for the vineyard fields varied between 0.38 and 0.85 with a mean of 0.57. Only one of the 28 soil samples taken from different vineyard fields was found in very suitable (S 1 :1.00-0.75) class, 8 in suitable (S 2 :0.75-060), 12 in marginal suitable (S 3 :0.60-0.50) and 7 in non-suitable (N:<0.50) class according to the soil quality index (SQI). Restricting soil factors for vine growth in the fields classified in S 2 and S 3 classes generally became low pH, low organic matter (OM), P, Fe, Mn, Cu, Mg and K contents than that of suggested levels. In addition to restring factors in S 2 and S 3 classes, physical properties in soils classified in N class were lower than suggested levels. The SQI values showed significant positive relations with grape yield, soil OM, P, K, Fe, Cu, Mn, Zn contents and significant negative relations with soil pH, exch. Ca and CaCO 3 contents. The grape yields had also positive relations with soil OM, Fe, Mn, Zn contents and negative correlations with soil pH and CaCO 3 content. Soil quality in a vineyard field should be assessed to reach successful sustainable and precision agricultural practices for high crop production.

Mapping Crop Calendar Events and Phenology-Related Metrics at the Parcel Level by Object-Based Image Analysis (OBIA) of MODIS-NDVI Time-Series: A Case Study in Central California

Remote sensing technology allows monitoring the progress of vegetation and crop phenology in large regions. Seasonal vegetation trends are commonly estimated from high temporal resolution but coarse spatial resolution satellite imagery, e.g., from MODIS-NDVI (Moderate Resolution Imaging Spectroradiometer—Normalized Difference Vegetation Index) time-series, which has usually limited their application to scenarios with few land uses or crops covering areas larger than actual parcel sizes. As an alternative, this paper proposes a general and robust procedure to map crop phenology at the level of individual crop parcels, and validates its feasibility in a complex and diverse cropland area located in central California. A first calibration phase consisted of evaluating the three curve-fitting models implemented in the TIMESAT software (i.e., asymmetric Gaussian (AG), double logistic (DL), and adaptive Savitzky–Golay (SG) filtering) and reporting the model and its settings that best adjusted to the MODIS-NDVI profile of each crop studied. Next, based on the selected crop-specific models and with a crop map previously obtained from ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) multi-temporal images, the procedure mapped four crop calendar events (i.e., start, end, middle, and length of the season) and five phenology-related metrics (i.e., base, maximum, amplitude, derivatives, and integrals of the NDVI values) of the study region by object-based image analysis (OBIA) of the MODIS-NDVI time-series. To mitigate the impact of mixed pixels, the OBIA procedure was designed to automatically apply a restrictive criterion based on the coverage of MODIS-NDVI pixels in each crop parcel: (1) using only the MODIS-NDVI pixels that were placed 100% within each crop parcel (i.e., “pure” pixels); or (2) if no “pure” pixels exist in any crop parcel, using only pixels with coverage percentages greater than 50%, and in such cases, reporting the mixing percentage in the output file. The calibration phase showed that the performance of the SG filtering was superior in most crops, with the exception of rice, while the AG model was intermediate in all of the cases. Differences between the dates of the start and end of the season that were observed in 120 ground-truth fields and the ones estimated by the crop-specific models were in a range of 11 days (for the corn fields) and 22 days (for the vineyard fields) on average. The OBIA procedure was also validated in 240 independent parcels with “pure” MODIS-NDVI pixels, reporting 89% and 82% of accuracy when mapping the start and end of the season, respectively. Our results revealed different growth patterns of the studied crops, especially of the crop calendar events of herbaceous (i.e., corn, rice, sunflower, and tomato) and woody crops (i.e., almond, walnut, and vineyard), of the NDVI derivatives of rice and the other studied herbaceous crops, and of the NDVI integrals of vineyard and the other studied woody crops. The resulting maps and tables provide valuable geospatial information for every parcel over time with several applications in cropland management, irrigation scheduling, and ecosystem modeling.

Importance of the spatial extent for using soil properties estimated by laboratory VNIR/SWIR spectroscopy: Examples of the clay and calcium carbonate content

Visible, near-infrared and short-wave infrared (VNIR/SWIR, 400–2500 nm) laboratory soil spectrometry is now considered to provide accurate estimations of primary soil properties (clay, calcium carbonate, iron, soil organic carbon, etc.). The performances of primary soil property prediction models are evaluated in regard to figures of merit calculated over calibration and validation databases but not in regard to the spatial extent of predicted soil samples. The objective of this study was to analyze regional model performances for soil property prediction at regional and within-field extents within contrasted representative geopedological situations. This study used a database of 240 soil samples collected over eight vineyard fields located in the Languedoc Region (southern France) (between 20 and 36 soil samples per field) for which VNIR/SWIR laboratory spectra were acquired and two soil physico-chemical properties (clay and calcium carbonate) were measured. Soil property prediction models were built using the classical partial least square regression (PLSR) method, which links the VNIR/SWIR laboratory spectra and the physico-chemical soil property. Our results showed that both clay and calcium carbonate prediction models are accurate at the regional extent, whereas prediction model performances at the within-field extent depend on the model robustness. Therefore, primary soil properties predicted by VNIR/SWIR laboratory spectra must be used with care at different extents.

3-D Characterization of Vineyards Using a Novel UAV Imagery-Based OBIA Procedure for Precision Viticulture Applications

Precision viticulture has arisen in recent years as a new approach in grape production. It is based on assessing field spatial variability and implementing site-specific management strategies, which can require georeferenced information of the three dimensional (3D) grapevine canopy structure as one of the input data. The 3D structure of vineyard fields can be generated applying photogrammetric techniques to aerial images collected with Unmanned Aerial Vehicles (UAVs), although processing the large amount of crop data embedded in 3D models is currently a bottleneck of this technology. To solve this limitation, a novel and robust object-based image analysis (OBIA) procedure based on Digital Surface Model (DSM) was developed for 3D grapevine characterization. The significance of this work relies on the developed OBIA algorithm which is fully automatic and self-adaptive to different crop-field conditions, classifying grapevines, and row gap (missing vine plants), and computing vine dimensions without any user intervention. The results obtained in three testing fields on two different dates showed high accuracy in the classification of grapevine area and row gaps, as well as minor errors in the estimates of grapevine height. In addition, this algorithm computed the position, projected area, and volume of every grapevine in the field, which increases the potential of this UAV- and OBIA-based technology as a tool for site-specific crop management applications.

Temporal and Spatial Scales Matter: Circannual Habitat Selection by Bird Communities in Vineyards.

Vineyards are likely to be regionally important for wildlife, but we lack biodiversity studies in this agroecosystem which is undergoing a rapid management revolution. As vine cultivation is restricted to arid and warm climatic regions, biodiversity-friendly management would promote species typical of southern biomes. Vineyards are often intensively cultivated, mostly surrounded by few natural features and offering a fairly mineral appearance with little ground vegetation cover. Ground vegetation cover and composition may further strongly vary with respect to season, influencing patterns of habitat selection by ecological communities. We investigated season-specific bird-habitat associations to highlight the importance of semi-natural habitat features and vineyard ground vegetation cover throughout the year. Given that avian habitat selection varies according to taxa, guilds and spatial scale, we modelled bird-habitat associations in all months at two spatial scales using mixed effects regression models. At the landscape scale, birds were recorded along 10 1-km long transects in Southwestern Switzerland (February 2014 –January 2015). At the field scale, we compared the characteristics of visited and unvisited vineyard fields (hereafter called parcels). Bird abundance in vineyards tripled in winter compared to summer. Vineyards surrounded by a greater amount of hedges and small woods harboured higher bird abundance, species richness and diversity, especially during the winter season. Regarding ground vegetation, birds showed a season-specific habitat selection pattern, notably a marked preference for ground-vegetated parcels in winter and for intermediate vegetation cover in spring and summer. These season-specific preferences might be related to species-specific life histories: more insectivorous, ground-foraging species occur during the breeding season whereas granivores predominate in winter. These results highlight the importance of investigating habitat selection at different spatial scales and all along the annual cycle in order to draw practical, season-specific management recommendations for promoting avian biodiversity in farmland.

Assessing opportunities for selective winery vintage with a market-driven composite index

AbstractAn opportunity index (OISV) is proposed for selective vine harvest management to ensure vineyard sustainability making use of precision farming technologies. Vigour maps derived from remote sensors are the basis of the method. In terms of validation, the index was applied in 36 vineyard fields of different varieties in Raimat (Lleida, northeast Spain). The OISV is based on three components: (i) the spatial variability in vine vigour (to ensure variability in the quality of grapes), (ii) the spatial structure or pattern of vigour (to facilitate harvesting operations), and (iii) the availability of a minimum productive quality area within the plot (to ensure that benefits derived from the differentiation of the final product will compensate for the expenses of differential management). The results suggest that only few plots were suitable for selective vintage, although an acceptable agreement was obtained when comparing the plots harvested selectively by the winery and those classified as favourabl...

A new host [Centaurea stapfiana (Hand.-Mazz.) Wagenitz (Asteraceae)] record for the moth Metzneria subflavella Englert (Lepidoptera: Gelechiidae) from Turkey

The present study was carried out in vineyard fields of Diyarbakır province, Turkey, in 2014 on Centaurea stapfiana (Hand.-Mazz.) Wagenitz (Asteraceae) infested with the larvae of moth Metzneria subflavella Englert (Lepidoptera: Gelechiidae). Metzneria subflavella were obtained from C. stapfiana flower buds collected in vineyard fields. C. stapfiana is a new host record for M. subflavella. In addition, this is the first record of M. subflavella from insect fauna of Turkey.

Use of multi-spectral airborne imagery to improve yield sampling in viticulture

The wine industry needs to know the yield of each vine field precisely to optimize quality management and limit the costs of harvest operations. Yield estimation is usually based on random vine sampling. The resulting estimations are often not precise enough because of the high variability within vineyard fields. The aim of the work was to study the relevance of using NDVI-based sampling strategies to improve estimation of mean field yield. The study was conducted in nine non-irrigated vine fields located in southern France. For each field, NDVI was derived from multi-spectral airborne images. The variables which define the yield: [berry weight at harvest (BWh), bunch number per vine (BuN) and berry number per bunch (BN)] were measured on a regular grid. This data-base allowed for five different sampling schemes to be tested. These sampling methods were mainly based on a stratification of NDVI values, they differed in the way as to whether NDVI was used as ancillary information to design a sampling strategy for BuN, BN, BW or for all yield variables together. Results showed a significant linear relationship between NDVI and BW, indicating the interest of using NDVI information to optimize sampling for this parameter. However this result is mitigated by the low incidence of BW in the yield variance (4 %) within the field. Other yield components, BuN and BN explain a higher percentage of yield variance (60 and 11 % respectively) but did not show any clear relationship with NDVI. A large difference was observed between fields, which justifies testing the optimized sampling methods on all of them and for all yield variables. On average, sampling methods based on NDVI systematically improved vine field yield estimates by at least 5–7 % compared to the random method. Depending on the fields, error improvement ranged from −2 to 15 %. Based on these results, the practical recommendation is to consider a two-step sampling method where BuN is randomly sampled and BW is sampled according to the NDVI values.