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Agriculture 2018, 8(4), 59; https://doi.org/10.3390/agriculture8040059

Characterisation of Castor (Ricinus communis L.) Seed Quality Using Fourier Transform Near-Infrared Spectroscopy in Combination with Multivariate Data Analysis

1
Department of Agroecology, Science and Technology, Aarhus University, 4200 Slagelse, Denmark
2
Department of Agronomy, Shahrekord University, Shahrekord 64165478, Chaharmahal va Bakhtiyari, Iran
3
Novozymes A/S, 2880 Bagsværd, Denmark
*
Author to whom correspondence should be addressed.
Received: 19 February 2018 / Revised: 4 April 2018 / Accepted: 13 April 2018 / Published: 17 April 2018
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Abstract

The potential of single-seed near-infrared (NIR) spectroscopy was investigated to characterise castor seeds based on their seed viability and seed oil content. Distinct differences between viable and non-viable seeds were observed in the principal component analysis (PCA) analysis. Furthermore, the PCA compared heavy and medium seeds with light seeds, which were comparable to the clusters of viable and non-viable seeds, respectively. Prediction accuracies of 98.7% and 99.6% were obtained with the partial least squares discriminant analysis (PLS-DA) model with a classification error rate of 0.8% and 1.1% for the training set and test set, respectively. The NIR spectral regions having chemical information from the oil in castor seeds were found to be vital for determination of seed viability. View Full-Text
Keywords: NIRS; chemometric; oilseed; ricinoleic acid; seed quality NIRS; chemometric; oilseed; ricinoleic acid; seed quality
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Gislum, R.; Nikneshan, P.; Shrestha, S.; Tadayyon, A.; Deleuran, L.C.; Boelt, B. Characterisation of Castor (Ricinus communis L.) Seed Quality Using Fourier Transform Near-Infrared Spectroscopy in Combination with Multivariate Data Analysis. Agriculture 2018, 8, 59.

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