terclim by ICS banner
IVES 9 IVES Conference Series 9 Hyperspectral imaging and machine learning for monitoring grapevine physiology

Hyperspectral imaging and machine learning for monitoring grapevine physiology

Abstract

Rootstocks are gaining importance in viticulture as a strategy to combat abiotic challenges, as well as enhancing scion physiology and attributes. Therefore, understanding how the rootstock affects photosynthesis is insightful for genetic improvement of either genotype in the grafted grapevines. Photosynthetic parameters such as maximum rate of carboxylation of RuBP (Vcmax) and the maximum rate of electron transport driving RuBP regeneration (Jmax) have been identified as ideal targets for breeding and genetic studies. However, techniques used to directly measure these photosynthetic parameters are limited to the single leaf level and are time-consuming measurements. Hyperspectral remote sensing uses the optical properties of the entire vine to predict photosynthetic capacity at the canopy level. In this study, estimates of Vcmax and Jmax were assessed, in six different rootstocks with a common scion, using direct measurements and canopy reflectance obtained with hyperspectral wavelengths (400 to 1000 nm). Using artificial intelligence-based modeling, prediction models were developed for Marquette on the six different rootstock genotypes. Results for direct and indirect measures indicate that each rootstock promotes differences in scion Vcmax and Jmaxprofiles across the season. Application of machine learning and neural networks of spectral data provided good predictions of both photosynthetic parameters. 

Download the abstract

DOI:

Publication date: June 14, 2024

Issue: Open GPB 2024

Type: Poster

Authors

Prakriti Sharma1, Anne Fennell1*

1 South Dakota State University, Brookings SD, USA

Contact the author*

Keywords

Hyperspectral, photosynthesis, neural networks, rootstock

Tags

IVES Conference Series | Open GPB | Open GPB 2024

Citation

Related articles…

CONSUMER PERCEPTION OF INTERSPECIFIC HYBRID RED WINE COLOR IN RELATION TO ANTHOCYANIN PROFILE AND CHEMICAL COLOR PARAMETERS

Interspecific hybrid winegrapes are of growing interest in the context of climate change based on their disease resistance and cold hardiness. In addition to a need for increased understanding of their chemical composition, there is little empirical evidence on the consumer perception of non-vinifera wine. Phenolic compounds, and particularly color, play an important organoleptic and quality determination role in wine, but can vary significantly in interspecific hybrid wines compared to wines produced from Vitis vinifera cultivars [1, 2, 3]. Anecdotally, the variation in anthocyanin species, interactions, and concentrations in interspecific hybrids could result in a variance from“vinifera-like” wine color.

Read More

Geologic and geomorphologic features applied for identification of wine terroir units by digital image processing, spectroradiometric and GIS techniques in Encruzilhada do Sul, RS, Brazil

Results in the characterization of a new wine terroir unit in south Brazil are reported. Presently, several areas in Brazil are being studied, in an effort to define new wine terroirs and improve the quality of Brazilian wines.

Read More

METAPIWI: unveiling the role of microbial communities in PIWI grapes for sustainable winemaking

The METAPIWI project advances viticulture research by examining microbial communities in PIWI (fungus-resistant) grapevines compared to traditional Vitis vinifera. It investigates how these microbes influence spontaneous fermentation and the production of distinct metabolites and aromas.

Read More

Phenolic composition of Xinomavro (vitis vinifera L.cv.) grapes from different regions of Greece

[lwp_divi_breadcrumbs home_text="IVES" use_before_icon="on" before_icon="||divi||400" module_id="publication-ariane" _builder_version="4.20.4" _module_preset="default" module_text_align="center" module_font_size="16px" text_orientation="center"...
Read More

Fingerprinting the origin of rosé wines with a new high throughput polyphenomics method

Wine is a widely consumed alcoholic beverage with a high commercial value. More specifically, the worldwide consumption of rosé wine has increased by 20% since 2002[1]. But because of its high commercial value, it can become a subject of fraud, and authenticity control is necessarily required. More than one hundred polyphenols have been recently quantified in various rosé wines [2]. They are key components defining color, taste and quality of wines. Their amount and composition depend on many different factors such as grape variety, winemaking and age of the wine. In this study, the influence of geographic origin of some rosé French wines was investigated. An original and very fast UPLC-QTOF-MS method was developed and used to predict the geographic origin authenticity of rosé wines.

Read More