terclim by ICS banner
IVES 9 IVES Conference Series 9 GiESCO 9 Mapping grape composition in the field using VIS/SWIR hyperspectral cameras mounted on a UTV

Mapping grape composition in the field using VIS/SWIR hyperspectral cameras mounted on a UTV

Abstract

Context and purpose of the study – Assessing grape composition is critical in vineyard management. It is required to decide the harvest date and to optimize cultural practices toward the achievement of production goals. The grape composition is variable in time and space, as it is affected by the ripening process and depends on soil and climate conditions. This variability makes an appropriate assessment of the overall grape composition of a vineyard block complicated and time-consuming. Our work focused on developing a system to assess and map grape composition directly in the field through the application of machine-vision models to hyperspectral images acquired on the go in a vineyard with sprawling canopies, where the fruit tends to be hidden by the foliage. 

Material and methods – For this study, a UTV was specially adapted to lift the canopy and expose the fruits, two hyperspectral cameras (a Senop HSC VIS/NIR and a Specim NIR/SWIR) were mounted with GPS systems and halogen lights for night imaging. We imaged a Merlot vineyard located in Madera, California, four times during the 2022 growing season. At the same time, we sampled grapes from 160 vine locations which were analyzed in the laboratory to assess anthocyanin, soluble solids, pH, and titratable acidity. A total of ~1,000 samples were collected. For the analysis, the images needed to be segmented to extract the grape’s signal from sampled vines. Then, the reflectance of the grapes was used to look for correlations with grape composition using machine learning models. Evaluation and interpretation of models were performed using RMSE, R2. Interpretation of the model was conducted through feature importance and partial dependence plots to understand the relationship between wavelength predictors and the outcome. This project is the first to use a SWIR camera mounted on a UTV to assess grape composition.

Results – Our results demonstrate that SWIR images can be used to perform a classification to extract grape signal with a mean error of 2.2% using the spectral signature of each class represented in the image (grape, leaves and background). The prediction of grape compounds from the refined spectral signal shows promising results. This project aims to help growers to monitor grape composition in the field rapidly and spatially to inform variable rate management.

DOI:

Publication date: July 5, 2023

Issue: GiESCO 2023

Type: Poster

Authors

Luca BRILLANTE1,2*, Eve LAROCHE-PINEL1,2, Brent SAMS3, Benjamin CORALES1,2, Kaylah VASQUEZ1,2, Vincenzo CIANCIOLA1,2

1Department of Viticulture & Enology, California State University Fresno, Fresno, CA, USA
2Viticulture and Enology Research Center, California State University, Fresno CA, USA
3Winegrowing Research Department, E&J Gallo Winery, Modesto, CA, USA

Contact the author*

Keywords

precision viticulture, grape composition, hyperspectral imaging, mapping, machine-learning

Tags

GiESCO | GIESCO 2023 | IVES Conference Series

Citation

Related articles…

Tomatoes and Grapes: berry fruits with a (bright) biotech future?

Tomatoes and Grapes are berries that are genetically related and therefore at least partially their developmental pathways leading to a fleshy fruit should share some of the components. In a sense knowledge obtained from the model plant tomato could be useful for grape and conversely the more amenable tomato can be used to test some hypothesis that would be difficult to obtain in grape. Research in my lab and other labs have led to a better understanding of the molecular genetics mechanisms underlying fruit development and ripening in tomato and more specifically those related to metabolite accumulation that may lead to changes in fruit nutritional and flavor composition. This research has involved the use of genetic variability in natural population, but also biparental population and genetically engineered lines that are easy to develop in tomato tomato but not in grape. NGTs also can be easily implemented in tomato to not only speed up the gene-to-trait but also develop new tomato varieties.

Methodological advances in relating deep root activity to whole vine physiology

Full understanding of grapevine responses to variable soil resources requires
assessing the grapevine root system. Grapevine root systems are expansive and examining deep roots (i.e., >40 cm)
is particularly important in conditions where grapevines increase reliance on deep soil resources, such as drought
or plant competition. Traditional methods of assessing roots rely on morphological traits associated specific
functions (e.g., root color, diameter, length), while recent methodological advances allow for estimating root
function more directly (e.g., omics). Yet, the potential of applying refined methods remains underexplored for roots
at deep depths.

NACs intra-family hierarchical transcriptional regulatory network orchestrating grape berry ripening

Considering that global warming is changing berry ripening timing and progression, uncovering the molecular mechanisms and identifying key regulators governing berry ripening could provide important tools in maintaining high quality grapes and wine. NAC (NAM/ATAF/CUC) transcription factors represent an interesting family due to their key role in the developmental processes control, such as fruit-ripening-associated genes expression, and in the regulation of multiple stress responses. Between the 74 NAC family members, we selected 12 of them as putative regulators of berry ripening: NAC01, NAC03, NAC05, NAC11, NAC13, NAC17, NAC18, NAC26, NAC33, NAC37, NAC60 and NAC61.

Molecular characterization of a variegated grapevine mutant cv Bruce’s Sport

Variegation, a frequently observed trait in plants, is characterized by the occurrence of white or discoloured plant tissue. This phenomenon is attributed to genetic mosaicism or chimerism, potentially impacting the epidermal (L1) and subepidermal (L2) cell layers. In grapevine, variegation manifests as white or paler leaf, flower, or berry tissues, often leading to stunted growth and impeded development. Despite its prevalence, variegation in grapevines remains understudied.

Phenotypical impact of a floral somatic mutation in the cultivar Listán Prieto

The accession Criolla Chica Nº2 (CCN2) is catalogued as a floral mutation of cultivar Criolla Chica (synonym for cv. Listán Prieto). Contrary to what is observed in hermaphrodite-cultivated varieties like Criolla Chica, CCN2 exhibits a prevalence of masculinized flowers. Aiming to study the incidence and phenotypical implications of this mutation, CCN2 plants were deeply studied using Criolla Chica ‘Ballista’ (CCBA) as control plants. For each CCN2 plant, two inflorescences per shoot were sampled and segmented into proximal, mid and distal positions, relative to the pedicel. Flowers were observed through magnifying lens and classified according to OIV151 descriptor.