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In recent years, the post‐harvest commercialization of fresh jujube sorting technology is backward, the efficiency of manual grading is low, and the application of machine vision technology in fruit grading has been a research hotspot. To improve the grading accuracy and speed of the fresh jujube machine vision grading machine, this study designs a method of fresh jujube machine vision grading using an electromagnetic synchronous actuator. The grading machine consists of an automatic distribution and arrangement system, an image acquisition and processing system, and a synchronous actuator assembly, which uses a sensitive electromagnet to adsorb a silicon steel switching buckling plate to execute the action. The image processing process includes an image color component, Sobel operator filtering, Otsu method binarization, and ellipse fitting to extract the color and size eigenvalues. The experimental results show that the date images can be acquired quickly and processed accurately with a processing speed of 50 ms per frame. In addition, the proposed actuator can be sensitively triggered with a response time of 40 ms. The grader successfully classified jujube into five size classes and one color class. The grading accuracy and non‐destructive rate reached 93.7% and 100%, respectively. The grading efficiency is 20 jujubes per second, with a maximum production rate of 1400 kilograms per hour. This grading machine realizes the requirements of high accuracy, high speed, and non‐destructive grading of fresh jujube and provides an important technical and theoretical basis for the development of machine vision jujube rapid grading technology. Practical applications: In recent years, sorting technology in the post‐harvest commercialization of fruits has been outdated, and manual grading has been inefficient. The application of machine vision technology in fruit grading has been a research hotspot in recent years. This study designs a machine vision grading of fresh dates with an electromagnetic synchronous actuator. The grader was composed of a roller conveyor, synchronous actuator assembly, image main processor, and actuator controlling co‐processor. Experimental results indicated that jujube images could be acquired rapidly and processed accurately, with a processing speed of 50 ms per frame. In addition, the proposed actuator could be sensitively triggered with a response time of 40 ms. Finally, the grader successfully sorted jujubes into five size classes and one color class. The grading accuracy rate and non‐destructive rate reached 93.7% and 100%, respectively. The grading efficiency was 20 jujubes per second, and the maximum productivity was 1400 kg/h. [ABSTRACT FROM AUTHOR]

In this work, to evaluate the role of acidic electrolyzed water (AEW) combined with vacuum precooling (VP) treatment in fresh goji preservation, the physicochemical properties and anti‐oxidation indexes of goji berries were compared between the AEW+VP‐treated and control (VP treatment) groups during storage at 4, 7, and 10°C. The results showed that AEW+VP could effectively inhibit the decrease in L* and a* values, reduce the respiratory rate, delay the loss of vitamin C content, and maintain higher total soluble solid (TSS) content. Compared to the control, AEW+VP‐treated goji maintained higher catalase (CAT), peroxidase (POD), and superoxide dismutase (SOD) activity. Therefore, AEW+VP treatment could effectively improve the storage quality and extend the shelf life of fresh goji berries. Practical applications: Acidic electrolyzed water, a clean and environmentally friendly preservation technology, combined with vacuum precooling extended the shelf life of fresh goji berries while delaying the aging of goji berries at different storage temperatures. In this sense, AEW+VP had certain stability in enhancing the storage quality and extending the shelf life of goji berries, which can be regarded as an effective strategy for promoting the preservation of agricultural products. [ABSTRACT FROM AUTHOR]

Summary: Fruits and vegetables (F&V) provide people with a variety of essential vitamins, antioxidants and dietary fibre, thus constituting integral components of human diet. With the surge of interest in F&V, their consumption ratio has kept increasing in recent years. Unfortunately, microorganisms and pesticide residues on the surfaces of F&V may be hazardous to humans. As an emerging technology, electrolysed water (EW) shows great application potential in reducing these hazards. EW treatment not only effectively removes microorganisms from F&V but also degrades pesticide residues on their surfaces. In addition, EW treatment affects the physiological metabolism of harvested F&V, which is conducive to maintain their sensory quality and nutritional value. This article reviews the principles of EW preparation, advantages and disadvantages, and the application of EW in F&V in the last decade, including disinfection of irrigation water, removal of pesticide residues, disinfection after harvest its effects on physicochemical parameters and enzyme activity of F&V, etc. Moreover, the combination of EW and other technology, including ozone, short‐time heat treatment, ultraviolet irradiation and ultrasound, to further improve the quality control effects of F&V is discussed. [ABSTRACT FROM AUTHOR]

Near infrared hyperspectral imaging (NIR‐HSI) with a spectral range of 900 to 1700 nm was for the first time used to predict the changes of sugar content in Lingwu jujube during storage. Monte Carlo method was adopted to detect outliers, and multiple scattering correction (MSC), standard normal variate transformation (SNV), and Baseline were used to optimize modeling. Competitive adaptive reweighted sampling (CARS), interval variable iterative space shrinkage approach (iVISSA), and interval random frog (IRF) were used to select optimal wavelengths. In addition, partial least square regression (PLSR) and support vector machine (SVM) modeling based on optimal wavelengths were compared. The results showed that 30, 30, and 24 wavelengths were selected by CARS; 106, 87, and 112 feature wavelengths were selected by iVISSA; and 96, 71, and 83 optimal wavelengths were selected by IRF for sucrose, fructose, and glucose, respectively. The CARS–PLSR models provided the best results for fructose and glucose, and iVISSA–SVM model was better for sucrose. The results indicated that NIR–HSI model may be used as a rapid and nondestructive method for the determination of sugar content in jujubes. [ABSTRACT FROM AUTHOR]