Modeling °Brix and pH in Wine Grapes from Satellite Images in Colchagua Valley, Chile

Sandra N Fredes,Jorge A Recio,Luis Á Ruiz

doi:10.3390/agriculture11080697

Sandra N Fredes, Jorge A Recio + Show 1 more

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https://doi.org/10.3390/agriculture11080697

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Abstract

To monitor the ripeness and composition of wine grape berries and establish an optimal harvest date, the determination of °Brix and pH is vital. This research studies two harvest seasons of Cabernet Sauvignon wine grapes: 2017 and 2018. Field data were periodically collected to follow the phenological state of the fruits. In parallel, eight bands and four spectral indices from Sentinel-2 image time series were used, which are directly related to the foliage properties and activity, and indirectly to the fruit evolution. They were related to the variables measured from field samples: °Brix and pH. The °Brix models obtained with the spectral indices presented an R2 of 69% and 73% in the 2017 and 2018 seasons, respectively. In pH modeling, the 2017 season had low R2 results, reaching 43%, improving considerably in the 2018 season, reaching 63.8%. Estimated Brix and pH maps were obtained, expressing the spatial variability in the evolution of the fruit, which is useful for zoning the plots and to improve the sampling task prior to harvest. They are therefore a valuable tool to monitor the maturation, to improve the efficiency of harvest and subsequently, the quality of the wine.

Highlights

According to the latest data presented by the International Grape and Wine Organization (OIV) in April 2020, the world viticultural area would be over 7.5 million hectares considering the area of grapes destined for winemaking, table grapes and raisins [1]
This study aims to contribute to the selective management of vine crops, through the use of satellite images of medium spatial resolution (Sentinel-2) from a two-fold perspective: (i) the analysis of spectral bands and indices to generate models that allow one to estimate ◦ Brix and pH; and (ii) to explore the use of Sentinel-2 imagery to differentiate and map the vine growing variability, in order to identify potential areas of early or late ripeness
We found that the Normalized Difference Vegetation Index (NDVI) had different behavior when comparing both seasons

Summary

Introduction

According to the latest data presented by the International Grape and Wine Organization (OIV) in April 2020, the world viticultural area would be over 7.5 million hectares considering the area of grapes destined for winemaking, table grapes and raisins [1]. Chile is currently the second-largest wine producer in America and the fourth world exporter of wines, being surpassed only by European countries with vast experience in winemaking matters, such as France, Spain and Italy [3]. A plot corresponds thewine polygon enclosing group of rows the same vine In this case, Most of tothe production in athe world takesofplace in Mediterranean-type they are grouped in two batches: plots formed by parcels that add to aintensity total of climates, characterized by high temperatures in the summer season, highup light.

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