The weight of shelled shrimp is an important parameter for grading process. The weight prediction of shelled shrimp by contour area is not accurate enough because of the ignorance of the shrimp thickness. In this paper, a multivariate prediction model containing area, perimeter, length, and width was established. A new calibration algorithm for extracting length of shelled shrimp was proposed, which contains binary image thinning, branch recognition and elimination, and length reconstruction, while its width was calculated during the process of length extracting. The model was further validated with another set of images from 30 shelled shrimps. For a comparison purpose, artificial neural network (ANN) was used for the shrimp weight predication. The ANN model resulted in a better prediction accuracy (with the average relative error at 2.67%), but took a tenfold increase in calculation time compared with the weight-area-perimeter (WAP) model (with the average relative error at 3.02%). We thus conclude that the WAP model is a better method for the prediction of the weight of shelled red shrimp.

The near infrared (NIR) spectroscopy technique has been applied in many fields because of its advantages of simple preparation, fast response, and non-destructiveness. We investigated the potential of NIR spectroscopy in diffuse reflectance mode for determining the soluble solid content (SSC) and acidity (pH) of intact loquats. Two cultivars of loquats (Dahongpao and Jiajiaozhong) harvested from two orchards (Tangxi and Chun’an, Zhejiang, China) were used for the measurement of NIR spectra between 800 and 2500 nm. A total of 400 loquats (100 samples of each cultivar from each orchard) were used in this study. Relationships between NIR spectra and SSC and acidity of loquats were evaluated using partial least square (PLS) method. Spectra preprocessing options included the first and second derivatives, multiple scatter correction (MSC), and the standard normal variate (SNV). Three separate spectral windows identified as full NIR (800∼2500 nm), short NIR (800∼1100 nm), and long NIR (1100∼2500 nm) were studied in factorial combination with the preprocessing options. The models gave relatively good predictions of the SSC of loquats, with root mean square error of prediction (RMSEP) values of 1.21, 1.00, 0.965, and 1.16 °Brix for Tangxi-Dahongpao, Tangxi-Jiajiaozhong, Chun’an-Dahongpao, and Chun’an-Jiajiaozhong, respectively. The acidity prediction was not satisfactory, with the RMSEP of 0.382, 0.194, 0.388, and 0.361 for the above four loquats, respectively. The results indicate that NIR diffuse reflectance spectroscopy can be used to predict the SSC and acidity of loquat fruit.

A grafting machine is a kind of machine that can quickly graft scion to rootstock instead of manual grafting. Currently, an inclined inserted grafting machine uses the mechanical clamping method, which can easily damage the rootstock seedlings due to its high stiffness, thus, reducing the success rate of grafting. This study proposed an effective, flexible clamping device for grafting. The suction hole diameter (HD), the negative pressure (NP), and the surface inclination angle (IA) of the clamping device were studied via a single factor experiment to obtain optimal parameter ranges. Optimal HD, NP, and IA were 2–3 mm, 4–8 kPa, and 10–20°, respectively. The orthogonal experiment results showed that the optimal parameter combination for maximum holding success rate was HD, 2.5 mm; NP, 6 kPa; and IA, 10°. The experimental verification was carried out using the optimal parameter combination, with a holding success rate of 98.3% and no damage. This study provides a reference for the optimal design of an inclined inserted grafting machine.

Nitrogen removal under low C/N ratio in cold season is an arduous task. In this study, riboflavin was used as an eco-friendly electron mediator to improve the denitrification process in an SBR reactor under conditions of low temperature (10 °C to 15 °C) and limited carbon source (C/N ratio = 4.0). The results indicated that riboflavin created a suitable pH in the system for denitrification. Under water temperature of 10 °C to 15 °C, riboflavin (10 mg/L) stimulated the NO3–N and TN removal rate by 16.5%, and 51%, respectively. Riboflavin promoted the utilization efficiency of limited carbon source, driving the denitrification process with low residual acetate as electron donor. The rising cost of riboflavin supplement (10 mg/L) was 0.025 USD per m3 of wastewater. To satisfy the efficient nitrogen removal from municipal wastewater, the optimum C/N ratio and the selection of solid/immobilized redox mediators should be developed in future work.

: Thermal conductivity data for foods under high-pressure processing (HPP) conditions is necessary for modeling the associated heat transfer processes, such as HP sterilization, pressure shift freezing, etc. Available data in the literature arescarcebecause of the difficulties associated with property measurements. In this study, a thermal conductivity probe based on line heat source theory was used under HPP conditions. The probe was calibrated using 1.5% agar gel in the HP range of 0.1 to 400 MPa and temperature range of 25°C to 55°C. No clear pressure, temperature, or power supply dependency trend of the calibration factor was observed. A general calibration factor (1.01) was obtained by linear regression analysis between all measured values and reference values of water at different HPP conditions. Thermal conductivities of selected food materials (tofu, wheat flour dough, and pork) were then measured under similar HPP conditions and corrected using the calibration factor. The evaluated thermal conductivity of food materials ranged from 0.40 to 0.79 W m^-1 °C^-1 and increased with increasing pressure and temperature. A prediction model was developed to give a good fit (R² = 0.91) for the thermal conductivity of each food material with pressure and temperature. Keywords: Adiabatic compression heating, Food, Heat transfer, High-pressure processing, Line heat source, Thermal conductivity.