Combination of PCA with LDA and SVM classifiers: A model for determining the geographical origin of coconut in the coastal plantation, Aceh Province, Indonesia

Hayati, Rima; Munawar, Agus Arip; Lukitaningsih, Endang; Earlia, Nanda; Karma, Taufiq; Idroes, Rinaldi

doi:10.1016/j.cscee.2023.100552

Cited by 7 publications

(2 citation statements)

References 45 publications

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“…A combination of PCA with LDA combined with PCA and support vector machine (SVM) for determining the geographical origin of coconuts in the coastal plantation in Indonesia was derived [21]. The examination of coconut endosperms from 13 districts was conducted using portable sensing device near infrared spectroscopy (PSD-NIRS).…”

Section: Regression: Linear Modeling In Foodsmentioning

confidence: 99%

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Ongoing Multivariate Chemometric Approaches in Bioactive Compounds and Functional Properties of Foods—A Systematic Review

Karadžić Banjac,

Kovačević,

Podunavac-Kuzmanović

2024

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In this review, papers published in the chemometrics field were selected in order to gather information and conduct a systematic review regarding food science and technology; more precisely, regarding the domain of bioactive compounds and the functional properties of foods. More than 50 papers covering different food samples, experimental techniques and chemometric techniques were selected and presented, focusing on the chemometric methods used and their outcomes. This study is one way to approach an overview of the current publications related to this subject matter. The application of the multivariate chemometrics approach to the study of bioactive compounds and the functional properties of foods can open up even more in coming years, since it is fast-growing and highly competitive research area.

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Section: Regression: Linear Modeling In Foodsmentioning

confidence: 99%

“…Then, the authors introduced PCA and PCA-LDA, which showed the maximum accuracy (100%) for the data. The combination of PCA and LDA can accurately forecast the sample group [21].…”

Section: Regression: Linear Modeling In Foodsmentioning

confidence: 99%