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Author: search.filters.author.Teerachaichayut, S.Subject: search.filters.subject.Nondestructive

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    Quantitative analysis of quality for marian plum (Bouea burmanica Griff.) by transmittance near infrared spectroscopy
    (2018-10-05)
    Phonmakham, S.
    ;
    Suttivijitpukdee, N.
    ;
    Teerachaichayut, S.
    Marian plum (Bouea burmanica Griff.) is one of the most popular tropical fruits in Thailand. The good quality of marian plum is required by consumers. Total soluble solid (TSS) and titratable acidity (TA) are important indices for consideration of quality for marian plum. Transmittance mode of near infrared (NIR) spectroscopy in the short wavelength (665-955 nm) was considered for nondestructive evaluation of quality in marian plum. A set of 153 marian plums (105 samples for a calibration group and 48 samples for a prediction group) was carried out in this research. The partial least squares regression (PLSR) was used to develop the calibration models. Spectral pretreatments were investigated in order to obtain the best performance of the models. A calibration model for TSS using original spectra obtained best results for calibration and prediction (R=0.90, RMSEC=0.57 °Bx and R=0.88, RMSEP=0.65 °Bx, respectively). As well as the calibration model for TA using original spectra obtained best results for calibration and prediction (R=0.98, RMSEC=0.01% and R=0.88, RMSEP=0.03%, respectively). All results indicated that it is possible to use transmittance SW-NIRS for nondestructive prediction of TSS and TA in marian plums.
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    Interactance and reflectance near infrared spectroscopy for freshness evaluation of hen eggs
    (2018-10-05)
    Suktanarak, S.
    ;
    Teerachaichayut, S.
    ;
    Jannok, P.
    ;
    Supprung, P.
    Haugh units is an important index for evaluate freshness of hen eggs. High score of Haugh units (≥60) from eggs means those are new fresh eggs. This research is aimed to use near infrared spectroscopy for nondestructive prediction of egg's freshness by quantitative evaluation based on Haugh units. Interactance mode (588-1091 nm) and reflectance mode (1000-2500 nm) of near infrared spectroscopy were investigated in this research. Hen eggs from farm in Thailand were studied by storage at 25°C for 21 days. Samples were taken for measurements at different days of storage (0, 4, 7, 10, 14, 18 and 21 days). A set of 247 samples (165 for calibration and 82 for prediction) was used for interactance mode and a set of 150 samples (102 for calibration and 48 for a prediction) was used for reflectance mode. Calibration models were established and cross-validated using partial least squares regression (PLSR). The accuracies were considered by test in prediction groups. The results showed that the interactance obtained better accuracy for prediction (correlation coefficient, R=0.91 and root mean square error prediction, RMSEP=5.64) when compared with reflectance mode (R=0.83 and RMSEP=7.11). In this study, the interactance near infrared spectroscopy is more suitable to use in application for freshness sorting of hen eggs.
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    Detection of hardening pericarp disorder and determination of firmness at hardening area in mangosteen by visible-near infrared reflectance spectroscopy
    (2015-01-01)
    Workhwa, S.
    ;
    Teerachaichayut, S.
    Mangosteen (Garcinia mangostona L.) is an economically important fruit grown commercially in Thailand for domestic consumption and export. The fruit has a thick and hard pericarp. However, hardening pericarp disorder can easily occur as a result of compression or impact during harvest and transport. Classification and prediction of hardening pericarp disorder in mangosteen was investigated using visible-near infrared spectroscopy (Vis/NIRS). Reflectance spectra were acquired on each of 1100 mangosteen samples. The number of samples for training and test set was 733 and 367 samples, respectively. Partial least squares-discriminant analysis (PLS-DA) was used for quantitative analysis. The results of discriminant analysis of normal and hardening pericarp samples using leave-one-out cross-validation achieved an average total accuracy of 92.92%. A further goal was quantitative analysis of firmness of mangosteens with hardening pericarp using Vis/NIR measurements. The optimum calibration model was pretreated using standard normal variate transformation (SNV) pretreatment and was developed using partial least squares regression (PLSR). The model was proven useful for prediction of the degree of pericarp hardening of mangosteen. The coefficients of correlation (R) and root mean square error of cross validation (RMSECV) were 0.89 and 2.67N respectively. This technique has potential use for nondestructive and rapid classification of quality for mangosteen.
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    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.