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

René Gislum, Pejman Nikneshan, Santosh Shrestha, Ali Tadayyon, Lise Christina Deleuran and Birte Boelt
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René Gislum: Department of Agroecology, Science and Technology, Aarhus University, 4200 Slagelse, Denmark
Pejman Nikneshan: Department of Agronomy, Shahrekord University, Shahrekord 64165478, Chaharmahal va Bakhtiyari, Iran
Santosh Shrestha: Department of Agroecology, Science and Technology, Aarhus University, 4200 Slagelse, Denmark
Ali Tadayyon: Department of Agronomy, Shahrekord University, Shahrekord 64165478, Chaharmahal va Bakhtiyari, Iran
Lise Christina Deleuran: Novozymes A/S, 2880 Bagsværd, Denmark
Birte Boelt: Department of Agroecology, Science and Technology, Aarhus University, 4200 Slagelse, Denmark

Agriculture, 2018, vol. 8, issue 4, 1-10

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.

Keywords: NIRS; chemometric; oilseed; ricinoleic acid; seed quality (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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