Chemometric strategies for near infrared hyperspectral imaging analysis: classification of cotton seed genotypes. Issue 42 (15th October 2021)

• Record Type: Journal Article
• Authors: Rocha, Priscilla Dantas; Medeiros, Everaldo Paulo; Silva, Carolina Santos; da Silva Simões, Simone
• Is Part Of: Analytical methods. Volume 13:Issue 42(2021)
• Page Start: 5065
• Page End: 5074
• Publication Date: 2021-10-15
• Subjects: Chemistry, Analytic -- Periodicals; Analytical biochemistry -- Periodicals; Chemical laboratories -- Standards -- Periodicals; 543.1905
• DOI: 10.1039/d1ay01076j
• Languages: English
• ISSNs: 1759-9660

Abstract

Abstract : Hyperspectral images have been increasingly employed in the agricultural sector for seed classification for different purposes. Abstract : Hyperspectral images have been increasingly employed in the agricultural sector for seed classification for different purposes. In the present paper we propose a new methodology based on HSI in the near infrared range (HSI-NIR) to distinguish conventional from transgenic cotton seeds. Three different chemometric approaches, one pixel-based and two object-based, using partial least squares discriminant analysis (PLS-DA) were built and their performances were compared considering the pros and cons of each approach. Specificity and sensitivity values ranged from 0.78–0.92 and 0.62–0.93, respectively, for the different approaches.