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, r p = 0.95 and root mean square error of prediction, RMSEP = 0.17% w/w) than that from the transmittance mode (r p = 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.

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The sawn timber Para rubber (Hevea brasiliensis) wood is an important wood product accounting for the highest export value of Thailand. The objective of this research was to build a prediction model of moisture content and modulus of rupture of sawn timber Hevea wood samples using desktop near infrared spectrometer. The timber samples were collected from the southern region and eastern region of Thailand and scanned using Fourier transform near infrared (FT-NIR) spectrometer in a range of 12489–3594 cm−1 (800-2700 nm) in diffuse reflectance mode. Then they were determined for moisture content and modulus of rupture (MOR) following ASTM. The predictive models were built by the partial least squares regression (PLSR). The result showed high performance in prediction of moisture content with correlation coefficient of prediction, Rp = 0.89 and root mean square error of prediction; RMSEP = 0.70%db. Regarding a predictive model of modulus of rupture, the results showed fair performance giving Rp = 0.78 and RMSEP = 17.11 MPa. Therefore, using near-infrared spectroscopy technique to predict the moisture content and strength based on the modulus of rupture of timber Hevea wood offered a rapid and non-destructive measurement as an alternative to the destructive checking the quality of sawn timber Hevea wood.

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This study investigated the effect of temperature on the thermal denaturation of skimmed coconut milk which is the residue of the virgin coconut oil extraction industry to produce a new product, coconut meat water. Skimmed coconut milk is a waste product that is expensive to dispose. The thermal denaturation of protein was applied to skimmed coconut milk to obtain coconut meat water and protein sludge.The optimum conditions were at 100°C for 10 min which had a significant effect on the amount of protein sediment. The separated coconut meat water was sterilized and stored which were analyzed the properties. The results indicated that the color (L* and a* values) decreased over time. The pH and total soluble solids content were 6.19-6.29 and 5.0-5.1°Brix, respectively. No microorganisms were detected.The nutrients identified included potassium, magnesium, and phosphorus. Consumer sensory testing using a 9-point hedonic scale indicated the product was in the range of 6.45-6.92 which was acceptable. Practical applicationsThe study focused on the utilization of skimmed coconut milk (a residue of the virgin coconut oil extraction industry) to produce a new product. The developed sterilized coconut meat water has high nutritional value, good sensory quality, and low raw material cost. The technology to produce this product is simple and accessible to smallscale manufacturers. The sterilized coconut meat water could be used as a valuable new beverage product with a taste similar to commercial coconut water.