Volume 16, Issue 12

Traditional assessment method for the food crispness was sensory analysis which was time consuming and needed experienced panelists. Aiming to to develop a quick evaluation of the food crispness, a mechanical-acoustic testing method was proposed where two parameters-maximum force (F max ) and maximum acoustic energy in unit time (SE max ) were applied to assess the crispness of dried potato chips. It was found the mechanical-acoustic testing was completed in about 1.2 s and the potato chips had a statistic distributions for F max and SE max . The brand A potato chips had a statistic average F max of 13.48 N and SE max of 93.51 mV·ms. Three kinds of potato chips can be effectively differentiated according to the statistic average SE max and F max . Sensory “crispness” had a good correlation with the statistic average SE max . This work shows that it is feasible for a quick measurement of the food crispness using this mechanical-acoustic method.

Mixtures of water and ethanol were tested for the extraction of betacyanins from Hylocereus polyrhizus peel to obtain natural colorants. In order to obtain betacyanins in a purified form, adsorption was carried out with two types of multi-walled carbon nanotubes (MWCNTs; pristine MWCNTs and carboxylated MWCNTs) and two macroporous resins (X-5 and AB-8). Carboxylated MWCNTs showed the highest adsorption capacity. On the basis of static adsorption test, carboxylated MWCNTs were selected for kinetic and isotherm studies. Langmuir and pseudo-first-order models could describe the process well. According to the Langmuir model, the maximum monolayer adsorption amount of carboxylated MWCNTs was 84.6 mg/g. After purification on a chromatographic column packed with carboxylated MWCNTs, the content of H. polyrhizus peel betacyanins in the pigment product was 4.62%.

Effects of high humidity air-impingement blanching (HHAIB) temperature, relative humidity over a range of application time and drying temperature on air-impingement drying kinetics, colour attributes, browning index, blanching weight loss and total flavonoids content of chrysanthemum heads were studied. HHAIB could shorten the drying time of chrysanthemum heads significantly (p < 0.05) by up to 52% compared to the control group without blanching. Meanwhile blanching humidity has a greater influence on drying kinetic than other blanching parameters. D eff values of samples declined first and rose later with the growth of blanching humidity, while increased continuously with the growth of blanching temperature. The highest growth of total flavonoids content can be up to 21.6% under the HHAIB blanching conditions (110 °C of blanching temperature, 45% of relative humidity, 150 s of blanching time) in comparison with the control group. Lightness of all blanched samples was lower than the control group, and redness and total colour difference under different blanching conditions showed significant differences compared to the control group, while no obvious variation was observed in terms of yellowness values.

As one of the most famous traditional Chinese vinegars, the grains physicochemical content of Zhenjiang aromatic vinegar during solid-state fermentation (SSF) reflects the growth status of microorganisms and the quality of fermentation products. In addition, the time for grain-turning has a significant effect on the quality of fermentation products. In this study, a new evaluation method combined near-infrared (NIR) spectroscopy with partial least squares regression (PLSR) was proposed to predict the physicochemical content of grains and the fermentation stage. The performance of the PLSR models for the total acid and the nonvolatile acid were RMSEP  = 0.0371, R p 2  = 0.9760, and RMSEP  = 0.0216, R p 2  = 0.9646, respectively. The accuracy ratio of SSF stage judgment was 100%. Experimental results indicate that the proposed method can be used to guide on-site grain-turning and improve the quality of fermentation products.

Neutral detergent fiber (NDF) content was the critical indicator of fiber in corn stover. This study aimed to develop a prediction model to precisely measure NDF content in corn stover using near-infrared spectroscopy (NIRS) technique. Here, spectral data ranging from 400 to 2500 nm were obtained by scanning 530 samples, and Monte Carlo Cross Validation and the pretreatment were used to preprocess the original spectra. Moreover, the interval partial least square (iPLS) was employed to extract feature wavebands to reduce data computation. The PLSR model was built using two spectral regions, and it was evaluated with the coefficient of determination ( R 2 ) and root mean square error of cross validation (RMSECV) obtaining 0.97 and 0.65%, respectively. The overall results proved that the developed prediction model coupled with spectral data analysis provides a set of theoretical foundations for NIRS techniques application on measuring fiber content in corn stover.

In this study, we reported a facile and economical strategy for producing a functional protein-based composite film that was based on soybean protein isolate (SPI), eggshell membrane (ESM) and eugenol (Eu). The composite films were also characterized by mechanical, water vapor permeability (WVP), UV barrier, water resistance, hydrophobicity, antioxidant and antimicrobial activity. The results suggested the appropriate content of ESM could significantly enhance the mechanical, barrier, water resistance and hydrophobicity performances of the film. The addition of Eu into the SPI/ESM film could improve not only these properties, but also antimicrobial and antioxidant properties. The intermolecular interaction between SPI, ESM and Eu was mainly hydrogen bond confirmed by the Fourier-transform infrared spectroscopy (FTIR). The scanning electron microscopy (SEM) and X-ray diffraction (XRD) indicated a good compatibility existed between SPI and ESM, and the Eu could be well emulsified and dispersed into the SPI/ESM film matrices network. Such edible films carried potentially developed in active packaging applications.

Coconut water ( Cocos nucifera L.) from fruits of two ripening stages (green and mature) was used to perform microwave heat treatments. Three different heating conditions with maximum temperatures of 70, 80 and 90 °C were tested in three holding times (0, 2 and 4 min). The Total Phenolic Content (TPC) using the Folin-Ciocalteu method and ABTS radical scavenging capacity were evaluated for each combination of coconut fruit age, heating temperature and holding time. It was observed that green coconut water exhibited significant differences (p < 0.05) compared to mature coconuts in terms of TPC (46.03 and 69.16 mg GAE/L, respectively) and ABTS radical scavenging capacity (422.31 and 549.1 μmol TE/L, respectively). An increase in TPC (up to 23%) and antioxidant activity (up to 19%) was also observed with increasing temperature in the range of 70–90 °C. Green coconut water showed the largest increase in both TPC and antioxidant activity.

Proper farming, transportation, and storage processes of Hass avocado are important owing to its recent increase in production, export, and economic activity in Colombia. Since Hass avocado pricing and utility depend on its consumption ripeness, related to changes in skin color, sensory properties, texture, and nutritional value, developing an Android mobile application, namely iHass for smartphones and tablets, which estimates the number of days in which the Hass avocado reaches its optimal ripening level during post-harvest storage, contributes toward improving the fruit quality and decreasing the export costs and losses. This study aims to monitor the ripening processes of Hass avocados in complex backgrounds and indoor environments using various digital image processing techniques. The proposed study uses the red, green, and blue color model based on the physical and chemical changes that are observed during the ripening process. Herein, the color, shape, and texture characteristics of the fruits are obtained, and the fruits are classified using an artificial neural network, which features three layers, four input parameters, six hidden neurons, and four output parameters. Furthermore, ripeness was monitored in two crops, which provided 65 samples each. The results provided a ripeness estimate accuracy of 88% and a regression value of 0.819 during the post-harvest period.