Niuton Rubio-Padilla’s research while affiliated with Public University of Navarre and other places

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Publications (1)


Fig. 1 Total of documents (n = 451) found in the search strategy
Fig. 2 Flowchart of the steps carried out for the inclusion of the studies
Fig. 3 Proportion of machine and deep learning methods used in the potato field: a regression and b classification methods
Fig. 4 Principal characteristics analysed in potatoes utilising HSI technique. a Major components; b minor components; c diseases; d defects
A Systematized Review on the Applications of Hyperspectral Imaging for Quality Control of Potatoes
  • Article
  • Full-text available

February 2024

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108 Reads

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10 Citations

European Potato Journal

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The application of hyperspectral imaging (HSI) has gained significant importance in the past decade, particulary in the context of food analysis, including potatoes. However, the current literature lacks a comprehensive systematic review of the application of this technique in potato cultivation. Therefore, the aim of this work was to conduct a systematized review by analysing the most relevant compounds, diseases and stress factors in potatoes using hyperspectral imaging. For this purpose, scientific studies were retrieved through a systematic keyword search in Web of Science and Scopus databases. Studies were only included in the review if they provided at least one set of quantitative data. As a result, a total of 52 unique studies were included in the review. Eligible studies were assigned an in-house developed quality scale identifying them as high, medium or low risk. In most cases the studies were rated as low risk. Finally, a comprehensive overview of the HSI applications in potatoes was performed. It has been observed that most of the selected studies obtained better results using linear methods. In addition, a meta-analysis of studies based on regression and classification was attempted but was not possible as not enough studies were found for a specific variable.

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Citations (1)


... Hyperspectral imaging has been used to analyze the most relevant compounds, diseases, and stress factors in potatoes [18]. This study used hyperspectral imaging technology combined with machine learning models to detect five different external defects of potatoes: scab, black skin, broken skin, green skin, and mechanical damage. ...

Reference:

Non-Destructive Detection of External Defects in Potatoes Using Hyperspectral Imaging and Machine Learning
A Systematized Review on the Applications of Hyperspectral Imaging for Quality Control of Potatoes

European Potato Journal