VITIS - Journal of Grapevine Research

Genetic characterization and identification of the table grape accessions preserved in the living collection of Ain Taoujdate (Morocco)

2024-04-02T08:34:12+02:00

We have characterized the 60 table grape accessions preserved at the living collection of the Domaine Expérimental de Ain Taoujdate (Morocco) through DNA analyses. Genetic profiling based on 13 SSRs and 240 SNP markers identified up to 40 different genotypes, denoting a certain level of redundancy. This information was useful to detect many cases of misspelled accessions, some misnamed varieties, and several potential new synonymies. The comparison of these genetic profiles with international databases led to the identification of 58 accessions as 38 table grape varieties, half of them corresponding to obtentions bred in recent programs of table grape improvement. Only two accessions (named “Diamant Noir” and “Sultanine Rosée”) did not match any known genetic profile. We found that “Sultanine Rosée” does not correspond to ‘Kishmish Rozovyi’, the described pink-berried variant of ‘Sultanina’. Indeed, it turned out to be a grape variety not catalogued in international genetic databases that arose from the cross between ‘Sultanina’ and ‘Fokiano’, which we suggest to name ‘Sultanine Rose Faux’. Besides, the duo detected between the accession “Diamant Noir” and the variety ‘Moscato D’Adda’ suggests that it might correspond to the table grape variety named ‘Diamante Nero’ (‘Pirovano 57’ × ‘Moscato D’Adda’). We proved that molecular-assisted parentage analyses could be an efficient approach to suggest an identity for grapevine varieties that lack a matching genotype in international catalogues.

Potassium silicate counteracts salt-induced damage associated with changes in some growth characteristics, physiological, biochemical responses, and nutrient contents in two grapevines (Vitis vinifera L.) cultivars

2023-09-19T10:40:39+02:00

This study investigates the effects of potassium silicate on the growth characteristics, physiological parameters, biochemical parameters, and nutrient content of two grapevine cultivars, 'Bidaneh Ghermez' and 'Sahibi Gird', under NaCl stress conditions. The plants were exposed to NaCl solutions with concentrations of 0, 40, and 80 mM in a hydroponic system. Additionally, the plants were treated with potassium silicate sprays at concentrations of 0, 50, 100, and 200 mg L^-1. As NaCl levels increased, both 'Bidaneh Ghermez' and 'Sahibi Gird' cultivars exhibited reduced fresh and dry root weights. However, with potassium silicate application at 200 mg L^-1, the rate of root dry weight loss was reduced to 28% and 66.4% for 40 mM and 80 mM NaCl treatments, respectively. The maximum total protein content (1.65 mg L^-1 fresh weight) was detected at the 80 mM NaCl level and potassium silicate application at 50 mg L^-1. The maximum ascorbate peroxidase activity was observed at a potassium silicate concentration of 50 mg L^-1. Based on the results, increasing NaCl levels significantly boosted plant Na⁺ percentage. In treatments with 40 and 80 mM NaCl (without potassium silicate), nitrate levels decreased by 32.34% and 46.71%, respectively, compared to the control. The amount of leaf iron in the 40 mM salinity treatment increased and by 10.47% with potassium silicate at a concentration of 200 mg L^-1. The findings confirmed the role of potassium silicate in modulating the negative effects of NaCl, although more investigations in different grapevine cultivars under NaCl stress are required in this field.

A Concept Study for Feature Extraction and Modeling for Grapevine Yield Prediction

2024-02-15T08:53:05+01:00

Yield prediction in viticulture is an especially challenging research direction within the field of yield prediction. The characteristics that determine annual grapevine yields are plentiful, difficult to obtain, and must be captured multiple times throughout the year. The processes currently used in grapevine yield prediction are based mainly on manually captured data and rigid statistical measures derived from historical insights. Experts for data acquisition are scarce, and statistical models cannot meet the requirements of a changing environment, especially in times of climate change. This paper contributes a concept on how to overcome those drawbacks, by (1) proposing a deep learning driven approach for feature recognition and (2) explaining how Extreme Gradient Boosting (XGBoost) can be utilized for yield prediction based on those features, while being explainable and computationally inexpensive. The methods developed will be influential for the future of yield prediction in viticulture.

Spatial and temporal characteristics of dryness/wetness for grapevine in the Northeast of China between 1981-2020

2023-11-03T10:58:49+01:00

The Northeast of China has a marked continental monsoon climate characterized by dry and wet hazards that have destructive impacts on wine grape yields and quality. The purpose of this study was to analyze the spatiotemporal characteristics of dryness/wetness of grapevines in the wine region of northeast China from 1981 to 2020. The Crop Water Surplus and Deficit Index (CWSDI) was used to characterize the dryness/wetness using meteorological data collected at 15 meteorological stations located in or near the wine region of northeast China from 1981–2020. Results showed that the multi-year average precipitation could satisfy the water requirement of grapevine with the average CWSDI of 43% (Bud burst), 35% (Shoot growth), 40% (Flowering), 73% (Berry development), 24% (Maturation) and 56% (Full growing stage) respectively for grapevine. Most growing stages experienced a wetting trend and varied discontinuously with the abrupt change in years. The drought-stricken areas were smaller than wet-stricken areas for each growing stage, especially for berry development and full growing stages. The drought and wet characteristics were stage-specific during the grapevine growth period. The precipitation, CWSDI, wet frequency, and wet risk increased from northwest to southeast for each growing stage, while crop evapotranspiration (ETc), drought frequency and drought risk showed the opposite characteristics. The drought risk was lower than wet risk in the Northeast wine region. These results can be used to develop strategies for mitigating and adapting dryness/wetness events in the wine regions of northeast China.

Grape selector: a Shiny application for grapevine breeding

2024-02-27T11:18:14+01:00

Both variety and clonal selection programs require the study of many traits. Selecting the best accession becomes a challenge when the number of accessions and traits being studied increases. Grape selector is a user-friendly tool that allows finding the best compromises according to a set of criteria (selection index). This tool can be used with phenotypic data at the variety or clone scale. The application was tested with existing phenotypic data from a breeding program and provided consistent selection with the one done manually.