Teerachaichayut, Sontisuk

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Teerachaichayut, Sontisuk
Alternative Name
Teerachaichayut, S.
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Email
sontisuk.te@kmitl.ac.th

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    Item type:Publication,
    Non-destructive prediction of hardening pericarp disorder in intact mangosteen by near infrared transmittance spectroscopy
    (2011-10-01)
    Teerachaichayut, Sontisuk
    ;
    Terdwongworakul, Anupun
    ;
    Thanapase, Warunee
    ;
    Kiji, Kazuaki
    A non-destructive technique to predict a hardening pericarp disorder in intact mangosteen is proposed by using near infrared (NIR) transmittance spectroscopy in the wavelength range of 660-960 nm. The study found that the spectral features of normal pericarp mangosteen and hardening pericarp mangosteen were different. The averaged spectra and individual spectra of hardening pericarp mangosteen from a calibration set (N = 560) were used to develop classification models, using partial least squares discriminant analysis (PLS-DA). A model based on individual spectra obtained better classification. The overall accuracy of classification for a prediction set (N = 358) was 91%. Out of 179 samples of normal pericarp fruits, 167 were identified correctly, while 159 samples out of 179 samples with hard pericarp were predicted correctly. The results showed that NIR transmittance spectroscopy can be used to predict hard pericarp disorder in intact mangosteen fruit accurately. © 2011 Elsevier Ltd. All rights reserved.
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    Item type:Publication,
    Nondestructive prediction of internal browning in pineapple using transmittance short wavelength near infrared spectroscopy
    (2013-01-01)
    Sukwanit, S.
    ;
    Teerachaichayut, S.
    Pineapple [Ananas comosus (L.) Merr.] is one of the most important commercial fruit of Thailand. The taste and consistency of the fruit is of great importance, however "internal browning", a common physiological disorder affecting the fruit, which cannot be identified by visual inspection, makes the product unacceptable for export. In this study, Near Infrared (NIR) spectroscopy in the range of 665-955 nm was investigated as a non-destructive means to identify internal browning. Partial least squares-discriminant analysis (PLS-DA) was used in conjunction with the pre-treated NIR spectra as a first step in the development of an automated method of pineapple fruit sorting. A set of 243 samples was used for this research (131 commercially acceptable pineapples and 112 pineapples suffering from internal browning). A sample of 145 fruits was used for a training set and 98 samples for a test set. The smoothing and the first derivative pretreatment of averaged spectra were performed to obtain the best calibration model. The overall classification accuracy of the PLS-DA/NIR model on the prediction set was 90.8% (47 out of 53 for the sound pineapples and 42 out of 45 for the internally browned pineapples). This study demonstrates that NIR transmittance spectroscopy is potentially a useful nondestructive method that can be used to predict internal browning disorder in intact pineapples. © ISHS 2013.