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In-field hyperspectral imaging dataset of Manzanilla and Gordal olive varieties throughout the season.

Data in brief · 7 Dec 2022 · 10.1016/j.dib.2022.108812

Abstract

Because spectral technology has exhibited benefits in food-related applications, an increasing amount of effort is being dedicated to develop new food-related spectral technologies. In recent years, the use of remote sensing or unmanned aerial vehicles for precision agriculture has increased. As spectral technology continues to improve, portable spectral devices become available in the market, offering the possibility of realising in-field monitoring. This study demonstrates hyperspectral imaging and spectral olive signatures of the Manzanilla and Gordal cultivars analysed throughout the table-olive season from May to September. The data were acquired using an in-field technique and sampled via a non-destructive approach. The olives were monitored periodically during the season using a hyperspectral camera. A white reference was used to normalise the illumination variability in the spectra. The acquired data were saved in files named raw, normalised, and processed data. The normalised data were calculated by the sensor by correcting the white and black levels using the acquired reflectance values. The olive spectral signature of the images is saved in the processed data files. The images were labelled and processed using an algorithm to retrieve the olive spectral signatures. The results were stored as a chart with 204 columns and 'n' rows. Each row represents the pixel of an olive in the image, and the columns contain the reflectance information at that specific band. These data provide information about two olive cultivars during the season, which can be used for various research purposes. Statistical and artificial intelligence approaches correlate spectral signatures with olive characteristics such as growth level, organoleptic properties, or even cultivar classification.

Plant phenotyping relevance

オリーブ果実を対象とした圃場ハイパースペクトル画像データセットであり、画像取得、正規化、アルゴリズムによるスペクトル特徴抽出、データ保存が中心的に記述されているため、植物フェノタイピング手法・データセットとして収録する。

abstractThis study demonstrates hyperspectral imaging and spectral olive signatures of the Manzanilla and Gordal cultivars analysed throughout the table-olive season from May to September.
abstractThe images were labelled and processed using an algorithm to retrieve the olive spectral signatures.
abstractThese data provide information about two olive cultivars during the season, which can be used for various research purposes.

Code and data availability

The paper is a data descriptor whose hyperspectral olive dataset (raw/normalised HSIs and processed spectral signatures) is publicly deposited in Mendeley Data with DOI and direct URL given in the article.

Datasetpublic

olive field in a city on the north-west side of Seville in the south of Spain. • City/Town/Region: Espartinas, Seville province • Country: Spain • Latitude and longitude: 37.394327, -6.121881 Data accessibility Repository name: Mendeley Data Data identification number: http://dx.doi.org/10.17632/8xvhcsdvst.1 Direct URL to data: https://data.mendeley.com/datasets/8xvhcsdvst/1 Value of the Data • In smart agro applications, there are technological approaches that use artificial intelligence or traditional statistical methods such as ANOVA or PLS [1] , [2] , [3] , which require the use of data. In this regard, data are essential for both artificial intelligence and stochastic approaches. There

Open resource ↗Mendeley Data · 10.17632/8xvhcsdvst.1 · lines:1-52

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