René Gislum

Separation of viable and non-viable tomato (Solanum lycopersicum L.) seeds using single seed near-infrared spectroscopy

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

Single seed near-infrared (NIR) spectroscopy is a non-destructive technology commonly used for predicting lipids, proteins, carbohydrates and water content of agricultural products. The aim of the current study is to investigate the prospects of NIR spectroscopy in classifying viable and non-viable tomato seeds of two cultivars using chemometrics. The data exploration were performed by principal component analysis (PCA). Subsequently, viable and non-viable seeds were classified by partial least squares-discriminant analysis (PLS-DA) and interval PLS-DA (iPLS-DA). The indication of clustering of viable and non-viable seeds were observed in the PCA of each cultivar and the pooled samples. However, the PCA did not exhibit a pattern of separation among the early, normal and late germinated tomato seeds. The NIR spectral regions of 1160–1170, 1383–1397, 1647–1666, 1860–1884 and 1915–1940 nm were identified as important for classification of viable and non-viable tomato seeds by iPLS-DA. The sensitivity i.e. ability to correctly identify the positive samples and specificity i.e. ability to reject the negative samples of the (iPLS-DA) model on identified spectral regions for prediction of viable and non-viable seeds were 0.94 and 0.94 respectively and were higher than from (PLS-DA) model on original spectra. The iPLS-DA model predicted samples with classification error rate of 6.29 percent as compared to the 13.10 percent by the PLS-DA. The study indicated NIR regions related to the protein-bound water, protein and carbohydrates have a positive relationship to viability in tomato seeds. The study shows the potential of NIR spectroscopy for non-destructive discrimination of viable and non-viable tomato seeds using spectral information.
Original languageEnglish
JournalComputers and Electronics in Agriculture
Pages (from-to)348-355
Number of pages8
Publication statusPublished - Nov 2017

    Research areas

  • Chemometrics, IPLS-DA, Interval selection, Seed germination, Variable selection

See relations at Aarhus University Citationformats

ID: 117297803