A Systematized Review on the Applications of Hyperspectral Imaging for Quality Control of Potatoes

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. Th...

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Bibliographic Details
Published in:Potato research 2024, Vol.67 (4), p.1539-1561
Main Authors: Peraza-Alemán, Carlos Miguel, López-Maestresalas, Ainara, Jarén, Carmen, Rubio-Padilla, Niuton, Arazuri, Silvia
Format: Article
Language:English
Subjects:
Agriculture
Biomedical and Life Sciences
Cultivation techniques
Food analysis
Food quality
Hyperspectral imaging
Life Sciences
Meta-analysis
Plant Genetics and Genomics
Plant Sciences
Plant Systematics/Taxonomy/Biogeography
Potatoes
Quality control
Vegetables
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Summary: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.
ISSN:0014-3065
1871-4528
DOI:10.1007/s11540-024-09702-7