A review of the use of Near-Infrared Hyperspectral Imaging (NIR-HSI) techniques for the non-destructive quality assessment of root and tuber crops
| cg.authorship.types | CGIAR and developing country institute | en |
| cg.contributor.affiliation | International Institute of Tropical Agriculture | en |
| cg.contributor.affiliation | Bowen University | en |
| cg.contributor.donor | French Agricultural Research Center for International Development | en |
| cg.contributor.donor | Bill & Melinda Gates Foundation | en |
| cg.coverage.country | Nigeria | |
| cg.coverage.iso3166-alpha2 | NG | |
| cg.coverage.region | Africa | |
| cg.coverage.region | Western Africa | |
| cg.creator.identifier | Michael Adesokan: 0000-0002-1361-6408 | |
| cg.creator.identifier | ALAMU Emmanuel Oladeji (PhD, FIFST, MNIFST): 0000-0001-6263-1359 | |
| cg.creator.identifier | Busie Maziya-Dixon: 0000-0003-2014-2201 | |
| cg.howPublished | Formally Published | en |
| cg.identifier.doi | https://doi.org/10.3390/app13095226 | en |
| cg.identifier.iitatheme | NUTRITION & HUMAN HEALTH | |
| cg.isijournal | ISI Journal | en |
| cg.issn | 2076-3417 | en |
| cg.issue | 9 | en |
| cg.journal | Applied Sciences | en |
| cg.reviewStatus | Peer Review | en |
| cg.subject.iita | CASSAVA | en |
| cg.subject.iita | FOOD SECURITY | en |
| cg.subject.iita | NUTRITION | en |
| cg.subject.iita | PLANT BREEDING | en |
| cg.subject.iita | PLANT PRODUCTION | en |
| cg.subject.iita | POST-HARVESTING TECHNOLOGY | en |
| cg.subject.iita | VALUE CHAINS | en |
| cg.subject.impactArea | Nutrition, health and food security | |
| cg.subject.sdg | SDG 2 - Zero hunger | en |
| cg.volume | 13 | en |
| dc.contributor.author | Adesokan, Michael | en |
| dc.contributor.author | Alamu, Emmanuel Oladeji | en |
| dc.contributor.author | Otegbayo, B. | en |
| dc.contributor.author | Maziya-Dixon, Busie | en |
| dc.date.accessioned | 2023-05-08T08:44:23Z | en |
| dc.date.available | 2023-05-08T08:44:23Z | en |
| dc.identifier.uri | https://hdl.handle.net/10568/130269 | |
| dc.title | A review of the use of Near-Infrared Hyperspectral Imaging (NIR-HSI) techniques for the non-destructive quality assessment of root and tuber crops | en |
| dcterms.abstract | Hyperspectral imaging (HSI) is one of the most often used techniques for rapid quality evaluation for various applications. It is a non-destructive technique that effectively evaluates the quality attributes of root and tuber crops, including yam and cassava, and their food products. Hyperspectral imaging technology, which combines spectroscopy and imaging principles, has an advantage over conventional spectroscopy due to its ability to simultaneously evaluate the physical characteristics and chemical components of various food products and specify their spatial distributions. HSI has demonstrated significant potential for obtaining quick information regarding the chemical composition of the root and tuber, such as starch, protein, dry matter, amylose, and soluble sugars, as well as physical characteristics such as textural properties and water binding capacity. This review highlights the principles of near-infrared hyperspectral imaging (NIR-HSI) techniques combined with relevant image processing tools. It then provides cases of its application in determining crucial biochemical quality traits and textural attributes of roots and tuber crops, focusing on cassava and yam. The need for more information on using NIR-HSI in the quality evaluation of yam and cassava was underscored. It also presents the challenges and prospects of this technology. | en |
| dcterms.accessRights | Open Access | |
| dcterms.audience | Scientists | en |
| dcterms.available | 2023-04-22 | |
| dcterms.bibliographicCitation | Adesokan, M., Alamu, E. O., Otegbayo, B., & Maizya-Dixon, B. (2023). A review of the use of Near-Infrared Hyperspectral Imaging (NIR-HSI) techniques for the non-destructive quality assessment of root and tuber crops. Applied Sciences, 13(9), 1-17. | en |
| dcterms.description | Open Access Journal | en |
| dcterms.extent | 1-17 | en |
| dcterms.issued | 2023 | |
| dcterms.language | en | |
| dcterms.license | CC-BY-4.0 | |
| dcterms.publisher | MDPI | en |
| dcterms.subject | spectroscopy | en |
| dcterms.subject | evaluation | en |
| dcterms.subject | yams | en |
| dcterms.subject | cassava | en |
| dcterms.subject | breeding | en |
| dcterms.subject | processing | en |
| dcterms.subject | value chain | en |
| dcterms.type | Journal Article |