Terroir 2010 banner
IVES 9 IVES Conference Series 9 Using open source software in viticultural research

Using open source software in viticultural research

Abstract

Many high quality Open Source scientific applications have been available for a long time. Some of them have proved to be particularly useful for carrying out the usual activities involved in viticultural research projects, such as statistical analyses (including spatial analyses), GIS work, database management (possibly integrated with statistical and spatial analysis) and even “low-level” often highly time-consuming activities (e.g. repetitive task on text files).
A few essential applications regularly used by the author in agronomic and viticultural research during more than a decade are summarily presented. They have consistently made the successful accomplishment of the projects possible without having to rely on commercial software. The advantages and disadvantages of Open Source applications versus commercial software (with comparable features and quality) are discussed from a more general point of view.

DOI:

Publication date: October 8, 2020

Issue: Terroir 2010

Type: Article

Authors

O. Zecca

Institut Agricole Régional. Région La Rochère 1/A, Aosta, Italy

Contact the author

Tags

IVES Conference Series | Terroir 2010

Citation

Related articles…

Bunch placement effects on dehydration kinetics and physico-chemical composition of Nebbiolo grapes

Sforzato di Valtellina DOCG is a special reinforced red wine produced using withered Nebbiolo grapes. The withering process takes place in traditional rooms under natural environmental conditions; it starts immediately after the harvest and ends not before the 1st December of the same year. The process can be performed with different bunch placements that can influence the grapes features.The purpose of the study is to compare the effect on grape physico-chemical parameters for four withering bunch placement systems: hanged clusters (HC), plastic crates (CT), breathable mesh fabric on wooden frames panels (MF), and reed mats (RM). For all the systems studied, the withering length was two months at a temperature between 6 and 19 °C and a relative humidity of 41-88%.

Riesling aroma composition in light of changing global temperatures – delving into the effects of warmer nights on the volatile profile of riesling grapes

Climate is a key parameter when the modulation of berry and subsequent wine composition is considered. Recent decades have already seen an increase in global surface temperatures

Malbec wines from Argentina: influence of climate on aromatic components and Organoleptic profile. Is it possible to stablish regional identities?

Malbec grapes have been cultivated for 150 years in Argentina. In the last 20 years Argentinian Malbec wines have emerged as a commercial boom worldwide.

A few observations on double sigmoid fruit growth

Many fleshy fruit, including the grape berry, exhibit a double‐sigmoid growth (DSG) pattern. Identification of the curious DSG habit has long been attributed to Connors’ (1919) work with peaches

Comparison of imputation methods in long and varied phenological series. Application to the Conegliano dataset, including observations from 1964 over 400 grape varieties

A large varietal collection including over 1700 varieties was maintained in Conegliano, ITA, since the 1950s. Phenological data on a subset of 400 grape varieties including wine grapes, table grapes, and raisins were acquired at bud break, flowering, veraison, and ripening since 1964. Despite the efforts in maintaining and acquiring data over such an extensive collection, the data set has varying degrees of missing cases depending on the variety and the year. This is ubiquitous in phenology datasets with significant size and length. In this work, we evaluated four state-of-the-art methods to estimate missing values in this phenological series: k-Nearest Neighbour (kNN), Multivariate Imputation by Chained Equations (mice), MissForest, and Bidirectional Recurrent Imputation for Time Series (BRITS). For each phenological stage, we evaluated the performance of the methods in two ways. 1) On the full dataset, we randomly hold-out 10% of the true values for use as a test set and repeated the process 1000 times (Monte Carlo cross-validation). 2) On a reduced and almost complete subset of varieties, we varied the percentage of missing values from 10% to 70% by random deletion. In all cases, we evaluated the performance on the original values using normalized root mean squared error. For the full dataset we also obtained performance statistics by variety and by year. MissForest provided average errors of 17% (3 days) at budbreak, 14% (4 days) at flowering, 14.5% (7 days) at veraison, and 17% (3 days) at maturity. We completed the imputations of the Conegliano dataset, one of the world’s most extensive and varied phenological time series and a steppingstone for future climate change studies in grapes. The dataset is now ready for further analysis, and a rigorous evaluation of imputation errors is included.