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

Author

Listed:
  • 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)

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.

Suggested Citation

  • René Gislum & Pejman Nikneshan & Santosh Shrestha & Ali Tadayyon & Lise Christina Deleuran & Birte Boelt, 2018. "Characterisation of Castor ( Ricinus communis L.) Seed Quality Using Fourier Transform Near-Infrared Spectroscopy in Combination with Multivariate Data Analysis," Agriculture, MDPI, vol. 8(4), pages 1-10, April.
    • Handle: RePEc:gam:jagris:v:8:y:2018:i:4:p:59-:d:141428
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    Cited by:

    1. Da-Song Kim & Moon-Hee Choi & Hyun-Jae Shin, 2021. "Estimation of Starch Hydrolysis in Sweet Potato ( Beni Haruka ) Based on Storage Period Using Nondestructive Near-Infrared Spectrometry," Agriculture, MDPI, vol. 11(2), pages 1-14, February.
    2. Diding Suhandy & Meinilwita Yulia, 2021. "Classification of Lampung robusta Specialty Coffee According to Differences in Cherry Processing Methods Using UV Spectroscopy and Chemometrics," Agriculture, MDPI, vol. 11(2), pages 1-11, February.

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