Anupun Terdwongworakul

Rapid assessment of wood chemical properties and pulp yield of Eucalyptus camaldulensis in Thailand tree plantations by near infrared spectroscopy for improving wood selection for high quality pulp

Near-infrared (NIR) spectroscopy has been demonstrated as a means for rapid nondestructive determination of the chemical composition and final pulp yield of Eucalyptus camaldulensis in Thailand tree plantations. Multiple linear regression (MLR) analysis and partial least squares (PLS) analysis were introduced to develop statistical models in terms of calibration equations for total pulp yield, screened pulp yield, and contents of α-cellulose, pentosans, and lignin in wood. In MLR analysis, a reasonably good calibration equation was found only for pentosans (standard error of prediction (SEP): 0.98%). The PLS analysis improved the accuracy of prediction for every criterion variable, especially for pentosans (SEP: 0.91%) and lignin (SEP: 0.52%). Also, in the case of screened pulp yield, we were able to use such a statistical result as an indicator of the characteristics of the pulp and paper. Thus, NIR spectroscopy could be satisfactorily used as an effective assessment technique for Eucalyptus camaldulensis plantation trees.

Evaluation of Astringency and Tannin Content in ‘Xichu’ Persimmons Using Near Infrared Spectroscopy

Carbon dioxide treatment to reduce soluble tannins and astringency in persimmons is sometimes ineffective. Near-infrared spectroscopy was used to develop a predictive model for soluble tannin content and persimmon classification. A model using averaged spectra collected in the interactance mode showed better performance (correlation coefficient of prediction, rp = 0.95 and root mean square error of prediction, RMSEP = 0.17% w/w) than that from the transmittance mode (rp = 0.94 and RMSEP = 0.19% w/w). Models generated using spectra from the stem-end or middle plane flesh and whole fruit were comparable. Classification accuracy of 97.1% was achieved using stem-end flesh spectra. Therefore, near-infrared spectroscopy is a rapid and non-destructive technique with potential applications in the estimation of persimmon tannin content.

Application of Near Infrared Spectroscopy for Indirect Evaluation of “Monthong” Durian Maturity

Durian contains thick rind which restricts light penetration into the pulp region. Indirect prediction of pulp dry matter as a reference of maturity was investigated using spectral information from the rind and stem. Partial least squares regression was performed to model variation in the pulp dry matter using the rind and stem absorbance. The rind model showed better performance in predicting the dry matter content than the stem model. However, the accuracy was relatively poor (correlation coefficient of prediction, rp = 0.76 and root mean square error of prediction, RMSEP = 1.82%) compared with that of the reference pulp model (rp = 0.83 and RMSEP = 1.61%). The rind model was superior to the stem model in the classification of durian samples into immature, early-mature, and mature classes based on the number of days after anthesis and the dry matter content. Effective wavelengths were chosen from the regression coefficients of the corresponding models and used to create a simplified classification model. A combination of both rind and stem spectral data at selected wavelengths provided the highest accuracy of classification (94.4%).

Nondestructive classification of mung bean seeds by single kernel near-infrared spectroscopy

Near-infrared spectroscopy (NIRS) in the range 900–1700 nm was performed to develop a classifying model for dead seeds of mung bean using single kernel measurements. The use of the combination of transmission-absorption spectra and reflection-absorption spectra was determined to yield a better classification performance (87.88%) than the use of only transmission-absorption spectra (81.31%). The effect of the orientation of the mung bean with respect to the light source on its absorbance was investigated. The results showed that hilum-down orientation exhibited the highest absorbance compared to the hilum-up and hilum-parallel-to-ground orientations. We subsequently examined the spectral information related to the seed orientation by developing a classifying model for seed orientation. The wavelengths associated with classification based on seed orientation were obtained. Finally, we determined that the re-developed classifying model excluding the wavelengths related to the seed orientation afforded better accuracy (89.39%) than that using the entire wavelength range (87.88%).

Near-infrared hyperspectral imaging for classification of mung bean seeds

ABSTRACT Hard mung bean seeds pose a problem in the sprouting process as they develop mold and infect neighboring seeds. Near-infrared hyperspectral imaging combined with partial least squares discriminant analysis was applied to develop a classifying model to separate hard mung beans from normal ones. The orientation of the measured beans was found to affect the classification result. The optimal partial least squares discriminant analysis model based on all orientations resulted in a correlation coefficient (R) of 0.919 with a root mean squared error of prediction of 0.197. The non-germinative parts were mapped and were concentrated at one end of the bean. Finally, a germinability index was proposed according to the proportion of colored areas between the germinative and non-germinative parts from the hyperspectral imaging results.

Determination of Physical, Acoustical, Mechanical, and Chemical Properties of Fresh Young Coconut Fruit for Maturity Separation

Young coconut is a popular tropical fruit featuring soft white aromatic flesh and sweet white or transparent juice. As most coconut pickers are relatively unskilled, the harvested crop tends to be distinguished by the collection of fruit of varying levels of maturity. This research has sought to improve the accuracy of grading-packaging systems by developing correlations between maturity levels and the physical, acoustical, mechanical, and chemical properties of the fruit. Results show that maturity significantly affects the specific gravity, shell rupture force, shell secant modulus, flesh penetrating force, flesh firmness, total soluble solids, titratable acidity, flesh thickness (FT), and natural frequency of young coconut at p