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. 

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…

Identification of several glycosidic aroma precursors in six varieties of winemaking grapes and assessment of their aroma potential by acid hydrolysis

In winemaking grapes, it is known that most aroma compounds are present as non-volatile precursors, such as glycosidic precursors. In fact, there is strong evidence supporting the connection between the content of aroma precursors and the aromatic quality of wine [1]. Acid hydrolysis is preferred to reveal the aroma potential of winemaking grapes, as it predicts more accurately the chemical rearrangements occurring during fermentation in acidic environments [2]. In this study, a method involving a fast fermentation followed by acid hydrolysis at 75ºC was used to evaluate the accumulation of aroma compounds over time in fractions obtained from six different varieties of winemaking grapes.

Agronomic behavior of three grape varieties in different planting density and irrigation treatments

In the O Ribeiro Denomination of Origin, there is a winemaking tradition of growing vines under a high-density plantation framework (8,920 vines/ha) and maintaining its vegetative cycle under rainfed conditions.
Currently, viticulture is advancing to plantation frames in which the density is considered medium (5,555 vines/ha), thus allowing mechanized work to be carried out for vineyard management operations. Although, the application of irrigation applied proportionally to the needs of the vegetative cycle of the vine, is a factor that increasingly helps a good development of the vine compared to the summer period, with increasingly uncertain weather forecasts.

Evaluation of intra-vineyard spatial and temporal variability of leaf area index using multispectral images obtained by satellite (Landsat 8, Sentinel-2) and unmanned aerial vehicle platforms

Estimation of vineyard leaf area index (LAI) is an important aspect for the winegrowers. However, tracking and monitoring are difficult tasks due to time constraints. Satellite and unmanned aerial vehicle (UAV) imaging have become a practical monitoring method for LAI. Nevertheless, for a proper LAI determination, the image’s spatial resolution is a key factor, since low-resolution images are incapable of distinguishing between adjacent vines due to the large area covered in each pixel, this leads to misinterpretation or generalisation of vineyard information.

Disease‐induced alterations in the reflectance spectrum of grape leaves

Context and purpose of the study ‐ Phytopathogenic diseases impact the development and yield of grapevines, resulting in economical, social and environmental losses.

Grapevine responses to Botrytis cinerea infection: noble rot versus grey rot

The intricate relationship between the necrotrophic pathogen Botrytis cinerea and grape berries (Vitis vinifera spp.) can lead to the development of either the desirable noble rot (NR) or the unfavourable grey rot (GR), depending on the prevailing weather conditions.