A Counting Method of Red Jujube Based on Improved YOLOv5s

Due to complex environmental factors such as illumination, shading between leaves and fruits, shading between fruits, and so on, it is a challenging task to quickly identify red jujubes and count red jujubes in orchards. A counting method of red jujube based on improved YOLOv5s was proposed, which realized the fast and accurate detection of red jujubes and reduced the model scale and estimation error. ShuffleNet V2 was used as the backbone of the model to improve model detection ability and light the weight. In addition, the Stem, a novel data loading module, was proposed to prevent the loss of information due to the change in feature map size. PANet was replaced by BiFPN to enhance the model feature fusion capability and improve the model accuracy. Finally, the improved YOLOv5s detection model was used to count red jujubes. The experimental results showed that the overall performance of the improved model was better than that of YOLOv5s. Compared with the YOLOv5s, the improved model was 6.25% and 8.33% of the original network in terms of the number of model parameters and model size, and the Precision, Recall, F1-score, AP, and Fps were improved by 4.3%, 2.0%, 3.1%, 0.6%, and 3.6%, respectively. In addition, RMSE and MAPE decreased by 20.87% and 5.18%, respectively. Therefore, the improved model has advantages in memory occupation and recognition accuracy, and the method provides a basis for the estimation of red jujube yield by vision

Effects of Low Pressure Treatment on the Mortality of Different Life Stages of Indianmeal moth (Plodia interpunctella) and the Quality of Dried Chinese Jujube

Low pressure technology is a potential non-chemical method to control insects in agriculture products. The purpose of this study was to determine the tolerance of different life stages of indianmeal moth (Plodia interpunctella) to low pressure and to validate the mortality of P. interpunctella when infesting Chinese jujube (Zizyphus jujuba Miller) using a low pressure system. Results showed that larvae were the most tolerant life stage of P. interpunctella, with a minimum exposure time of 41.4 h at 1.3 kPa and 25 °C to obtain 100% mortality. Pupae were the most susceptible life stage, with a lethal time of 12 h under the above low pressure conditions. The survival ratio of P. interpunctella in jujube decreased with increasing exposure time and reached 0% when the jujubes with P. interpunctella larvae were exposed to low-pressure treatment for 41.6 h at 1.3 kPa and 25 °C. Although the color, moisture, soluble solid, and vitamin C contents were slightly changed, there was no significant quality difference in these factors between control and treated jujubes. The information provided by this study is useful in developing effective non-chemical low-pressure treatments for disinfesting agricultural products

Deformation Study of Lean Methane-Air Premixed Spherically Expanding Flames under a Negative Direct Current Electric Field

This paper compares numerical simulations with experiments to study the deformation of lean premixed spherically expanding flames under a negative direct current (DC) electric field. The experiments, including the flame deformation and the ionic distribution on the flame surface were investigated in a mesh to mesh electric field. Besides, a numerical model of adding an electric body force to the positive ions on the flame surface was also established to perform a relevant simulation. Results show that the spherical flame will acquire an elliptical shape with a marked flame stretch in the horizontal direction and a slight inhibition in the vertical direction under a negative DC electric field. Meanwhile, a non-uniform ionic distribution on the flame surface was also detected by the Langmuir probe. The simulation results from the numerical model show good agreement with experimental data. According to the velocity field analysis in simulation, it was found the particular motion of positive ions and neutral molecules on the flame surface should be responsible for the special flame deformation. When a negative DC electric field was applied, the majority of positive ions and colliding neutral molecules will form an ionic flow along the flame surface by a superposition of the electric field force and the aerodynamic drag. The ionic flow was not uniform and mainly formed on the upper and lower sides, so it will lead to a non-uniform ionic distribution along the flame surface. What’s more, this ionic flow will also induce two vortexes both inside and outside of the flame surface due to viscosity effects. The external vortexes could produce an entraining effect on the premixed gas and take away the heat from the flame surface by forced convection, and then suppress the flame propagation in the vertical direction, while, the inner vortexes would scroll the burned zones and induce an inward flow at the horizontal center, which could be the reason for the pitted structure at the horizontal center when a high voltage was applied

Microstructural Characteristics and Mechanical Properties of Friction Stir Spot Welded 2A12-T4 Aluminum Alloy

2A12-T4 aluminum alloy was friction stir spot welded, and the microstructural characteristics and mechanical properties of the joints were investigated. A softened microstructural region existed in the joint, and it consisted of stir zone (SZ), thermal mechanically affected zone (TMAZ), and heat affected zone (HAZ). The minimum hardness was located in TMAZ, and the average hardness value in SZ can be improved by appropriately increasing welding heat input. The area of complete bonding region at the interface increased with increasing welding heat input because more interface metals were mixed. In a certain range of FSSW parameters, the tensile shear failure load of the joint increased with increasing rotation speed, but it decreased with increasing plunge rate or decreasing shoulder plunging depth. Two kinds of failure modes, that is, shear fracture mode and tensile-shear mixed fracture mode, can be observed in the tensile shear tests, and the joint that failed in the tensile-shear mixed fracture mode possessed a high carrying capability

Disease progression patterns and risk factors associated with mortality in deceased patients with COVID‐19 in Hubei Province, China

Background: Detailed descriptions of the patterns of disease progression of deceased coronavirus disease 2019 (COVID-19) patients have not been well explored. Objectives: This study sought to explore disease progression patterns and risk factors associated with mortality of deceased patients with COVID-19. Materials and Methods: Epidemiological, clinical, laboratory, and imaging data (from 15 January to 26 March 2020) of laboratory-confirmed COVID-19 patients were collected retrospectively from two hospitals, Hubei province, China. Disease progression patterns of patients were analyzed based on laboratory data, radiological findings, and Sequential Organ Failure Assessment (SOFA) score. Risk factors associated with death were analyzed. Results: A total of 792 patients were enrolled in this study, of whom 68 died and 724 survived. Complications during hospitalization, such as sepsis, severe acute respiratory distress syndrome, acute cardiac injury, and acute kidney injury, were markedly more frequent in deceased patients than in surviving patients. Deceased patients presented progressive deterioration pattern in laboratory variables, chest computed tomography evaluation, and SOFA score, while surviving patients presented initial deterioration to peak level involvement followed by improvement pattern over time. Days 10 to 14 after illness onset was a critical stage of disease course. Older age, number of preexisting comorbidities ≥2, and SOFA score were independently associated with death for COVID-19. Conclusions: Multiorgan dysfunction was common in deceased COVID-19 patients. Deceased patients presented progressive deterioration pattern, while surviving patients presented a relatively stable pattern during disease progression. Older age, number of preexisting comorbidities ≥2, and SOFA score were independent risk factors for death for COVID-19

Effects of polymerized whey protein on survivability of Lactobacillus acidophilus LA‐5 during freeze‐drying

Probiotic cultures are commonly freeze‐dried for storage and distribution. However, freeze‐drying and subsequent storage are accompanied by a decline in cell viability. Whey protein (WP) or polymerized whey protein (PWP) was used to protect Lactobacillus acidophilus LA‐5 against damage during freeze‐drying process and the subsequent storage. The protection capacity and effects of polymerized whey protein protected freeze‐dried L. acidophilus LA‐5 on physiochemical properties of cow and goat milk yoghurts were evaluated in comparison with maltodextrin (MD). The survival rate of L. acidophilus LA‐5 after freeze‐drying decreased in the order of MD (80.91%) > PWP (69.86%) > WP (64.89%). The particles of WP‐ and PWP‐based freeze‐dried samples showed an average diameter of about 10 μm, which was significantly higher than that of MD‐based particles (1.5 μm). Both whey protein preparations showed higher protecting effect than MD at high humidity condition during the 180‐day storage. Addition of freeze‐dried L. acidophilus LA‐5 with the presence of WP or PWP improved the protein content and decreased spontaneous whey separation and syneresis significantly for both yoghurts. PWP‐protected L. acidophilus LA‐5 addition significantly improved the firmness and adhesiveness of the yoghurt. Freeze‐dried L. acidophilus LA‐5 mixed with PWP had higher survivability in yoghurts compared with the culture alone at the end of storage. Data indicated that whey protein can be used to protect probiotics during freeze‐drying and may also improve the physiochemical properties of the yoghurt

Effects of polymerized whey protein on survivability of Lactobacillus acidophilus

Probiotic cultures are commonly freeze‐dried for storage and distribution. However, freeze‐drying and subsequent storage are accompanied by a decline in cell viability. Whey protein (WP) or polymerized whey protein (PWP) was used to protect Lactobacillus acidophilus LA‐5 against damage during freeze‐drying process and the subsequent storage. The protection capacity and effects of polymerized whey protein protected freeze‐dried L. acidophilus LA‐5 on physiochemical properties of cow and goat milk yoghurts were evaluated in comparison with maltodextrin (MD). The survival rate of L. acidophilus LA‐5 after freeze‐drying decreased in the order of MD (80.91%) > PWP (69.86%) > WP (64.89%). The particles of WP‐ and PWP‐based freeze‐dried samples showed an average diameter of about 10 μm, which was significantly higher than that of MD‐based particles (1.5 μm). Both whey protein preparations showed higher protecting effect than MD at high humidity condition during the 180‐day storage. Addition of freeze‐dried L. acidophilus LA‐5 with the presence of WP or PWP improved the protein content and decreased spontaneous whey separation and syneresis significantly for both yoghurts. PWP‐protected L. acidophilus LA‐5 addition significantly improved the firmness and adhesiveness of the yoghurt. Freeze‐dried L. acidophilus LA‐5 mixed with PWP had higher survivability in yoghurts compared with the culture alone at the end of storage. Data indicated that whey protein can be used to protect probiotics during freeze‐drying and may also improve the physiochemical properties of the yoghurt

Broad-Spectrum Antimicrobial Activity and Low Cytotoxicity against Human Cells of a Peptide Derived from Bovine αS1-Casein

The primary objective of this study was to improve our understanding of the antimicrobial mechanism of protein-derived peptides and to provide evidence for protein-derived peptides as food bio-preservatives by examining the antimicrobial activities, low cytotoxicity, stabilities, and mechanism of Cp1 (LRLKKYKVPQL). In this study, the protein-derived peptide Cp1 was synthesized from bovine αS1-casein, and its potential use as a food biopreservative was indicated by the higher cell selectivity shown by 11-residue peptide towards bacterial cells than human RBCs. It also showed broad-spectrum antimicrobial activity, with minimum inhibitory concentrations (MICs) of 64–640 μM against both gram-positive and gram-negative bacteria. The peptide had low hemolytic activity (23.54%, 512 μM) as well as cytotoxicity. The results of fluorescence spectroscopy, flow cytometry, and electron microscopy experiments indicated that Cp1 exerted its activity by permeabilizing the microbial membrane and destroying cell membrane integrity. We found that Cp1 had broad-spectrum antimicrobial activity, low hemolytic activity, and cytotoxicity. The results also revealed that Cp1 could cause cell death by permeabilizing the cell membrane and disrupting membrane integrity. Overall, the findings presented in this study improve our understanding of the antimicrobial potency of Cp1 and provided evidence of the antimicrobial mechanisms of Cp1. The peptide Cp1 could have potential applications as a food biopreservative

A Diameter Measurement Method of Red Jujubes Trunk Based on Improved PSPNet

A trunk segmentation and a diameter measurement of red jujubes are important steps in harvesting red jujubes using vibration harvesting robots as the results directly affect the effectiveness of the harvesting. A trunk segmentation algorithm of red jujubes, based on improved Pyramid Scene Parsing Network (PSPNet), and a diameter measurement algorithm to realize the segmentation and diameter measurement of the trunk are proposed in this research. To this end, MobilenetV2 was selected as the backbone of PSPNet so that it could be adapted to embedded mobile applications. Meanwhile, the Convolutional Block Attention Module (CBAM) was embedded in the MobilenetV2 to enhance the feature extraction capability of the model. Furthermore, the Refinement Residual Blocks (RRBs) were introduced into the main branch and side branch of PSPNet to enhance the segmentation result. An algorithm to measure trunk diameter was proposed, which used the segmentation results to determine the trunk outline and the normal of the centerline. The Euclidean distance of the intersection point of the normal with the trunk profile was obtained and its average value was regarded as the final trunk diameter. Compared with the original PSPNet, the Intersection-over-Union (IoU) value, PA value and Fps of the improved model increased by 0.67%, 1.95% and 1.13, respectively, and the number of parameters was 5.00% of that of the original model. Compared with other segmentation networks, the improved model had fewer parameters and better segmentation results. Compared with the original network, the trunk diameter measurement algorithm proposed in this research reduced the average absolute error and the average relative error by 3.75 mm and 9.92%, respectively, and improved the average measurement accuracy by 9.92%. To sum up, the improved PSPNet jujube trunk segmentation algorithm and trunk diameter measurement algorithm can accurately segment and measure the diameter in the natural environment, which provides a theoretical basis and technical support for the clamping of jujube harvesting robots

A Counting Method of Red Jujube Based on Improved YOLOv5s

Due to complex environmental factors such as illumination, shading between leaves and fruits, shading between fruits, and so on, it is a challenging task to quickly identify red jujubes and count red jujubes in orchards. A counting method of red jujube based on improved YOLOv5s was proposed, which realized the fast and accurate detection of red jujubes and reduced the model scale and estimation error. ShuffleNet V2 was used as the backbone of the model to improve model detection ability and light the weight. In addition, the Stem, a novel data loading module, was proposed to prevent the loss of information due to the change in feature map size. PANet was replaced by BiFPN to enhance the model feature fusion capability and improve the model accuracy. Finally, the improved YOLOv5s detection model was used to count red jujubes. The experimental results showed that the overall performance of the improved model was better than that of YOLOv5s. Compared with the YOLOv5s, the improved model was 6.25% and 8.33% of the original network in terms of the number of model parameters and model size, and the Precision, Recall, F1-score, AP, and Fps were improved by 4.3%, 2.0%, 3.1%, 0.6%, and 3.6%, respectively. In addition, RMSE and MAPE decreased by 20.87% and 5.18%, respectively. Therefore, the improved model has advantages in memory occupation and recognition accuracy, and the method provides a basis for the estimation of red jujube yield by vision