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Moisture content in the process of drying is often unknown when carrying out the drying process, especially the fluidized dryer. A lot of experimental designs are needed when observing the drying phenomenon more deeply.  It is because to stop and repeat drying process from the beginning again when the sample is taken to test its moisture content needed more experiments. Therefore, this paper presents development of a non-intrusive moisture measurement system prepared for fluidization type dryers. The method used in to conduct this research consists of (i) structural design analysis and (ii) functional (mechanical and electrical systems) and (iii) simple testing of the water content measurement system of constructed material. Test parameters observed include errors in measuring and fluctuating sensor signals against vibration applied to the weighing system. The results showed that non-intrusive moisture content measurement system for fluidized dryers based on the ESP8266 microcontroller had been successfully developed and worked normally. The measurement system has been calibrated with a coefficient of determination (R2) close to one. Measurement error resulting from the effect of vibration on this system shows a very satisfactory value of 6.89%.

This study aimed to evaluate the effects of mixed microbial culture from civet fecal suspension used as the inoculum for the fermentation of Arabica coffee. The type of Arabica coffee used for the research was the unpeeled coffee or the Arabica coffee cherries. Different proportion of inoculum introduced was thoroughly evaluated to assess the appropriate concentration of inoculum (0-40% inoculums represented in treatment 0-4 or T0 to T4) that would be applied to the fermentation of Arabica coffee cherries. Results revealed that treatment 4 (T4) containing 40% of the inoculum could degrade the sugar of the coffee beans faster than that of the other treatments in which within 24 hours of the incubation approximately 84% of the sugar was converted. T4 also reached the lowest caffeine content (1.8%) of the fermented coffee beans among other that of other treatments while the control had higher caffeine content (2.2%).This was substantially significant as the Arabica coffee cherries fermented with mixed microbial civet fecal suspensions can remarkably reduce the sugar and caffeine content of the Arabica coffee beans.

This paper presents the spectroscopic dataset, pre-processing, calibration, and predicted model database of Fourier transform infrared (FTIR) spectroscopy used to detect adulterated coconut milk with water. Absorbance spectral data were acquired and recorded in wavelength range from 2500 to 4000 nm for a total of 43 coconut milk samples. Coconut milk ware prepared in three forms of adulteration. Coconut milk comes from traditional markets and instant coconut milk in Indonesia. Spectra data may also be pre-processed to increase prediction accuracy, robustness performance using normalize, multiplicative scatter correction (MSC), standard normal variate (SNV), 1st derivative, 2nd derivative, and combination of 1st derivative and MSC. Calibration models and cross-validation to forecast those adulteration parameters use two regression algorithms, i.e., principal component regression (PCR) and partial least square regression (PLSR). By looking at its statistical metrics, prediction efficiency can be measured and justified (correlation coefficient (r), correlation of determination (R 2 ), and root mean square error (RMSE)). Obtained FTIR datasets and models can be used as a non-invasive method to predict and determine adulteration on coconut milk.

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