Development,Characterization and Application of a Three-Layer Intelligent pH-Sensing Indicator Based on Bromocresol Green(BCG)for Monitoring Fish Freshness

As a novel food quality monitoring technology,intelligent freshness indicator has received wide attention in recent years.However,its poor safety and stability are the main problems hindering its practical application.Hence a new pH-sensing indicator based on bromocresol green(BCG)was developed in this study for nondestructive and real-time monitoring the freshness of marine fishes.The indicator was designed with a three-layer structure,using the polytetrafluoroethylene(PTFE)membrane with high hydrophobicity and air permeability as the inner layer to isolate the moisture in the package,BCG-coated filter paper as the colorchanging layer to indicate the freshness of fish,and a transparent unidirectional permeable(TUP)membrane with moisture resistance as the out layer to isolate the moisture in the environment.This contributed to weaken the influence of humidity and prevent dye migration,so as to improve the accuracy and safety of the indicator.Therefore,a highly sensitive and distinguished color variation response to trimethylamine(TMA)standard solution with different concentrations was observed on the indicator.Additionally,the indicator showed a high color stability at different storage temperatures up to 14 days with total color differences(ΔE)less than 5.0.The indicator presented visible color variations from yellow to green then eventually to blue when applied to monitor the freshness of sea bass and salmon stored at 4℃,implying that fish was spoiled.Meanwhile,indicatorsΔE value was significantly positively correlated with total volatile basic nitrogen(TVB-N)and total viable count(TVC)in sea bass and salmon samples.Thus,the pH-sensing indicator can be applied as a cost-effective and promising intelligent indicator for monitoring fish freshness.

Information Freshness-Oriented Trajectory Planning and Resource Allocation for UAV-Assisted Vehicular Networks

In this paper,multi-UAV trajectory planning and resource allocation are jointly investigated to improve the information freshness for vehicular networks,where the vehicles collect time-critical traffic information by on-board sensors and upload to the UAVs through their allocated spectrum resource.We adopt the expected sum age of information(ESAoI)to measure the network-wide information freshness.ESAoI is jointly affected by both the UAVs trajectory and the resource allocation,which are coupled with each other and make the analysis of ESAoI challenging.To tackle this challenge,we introduce a joint trajectory planning and resource allocation procedure,where the UAVs firstly fly to their destinations and then hover to allocate resource blocks(RBs)during a time-slot.Based on this procedure,we formulate a trajectory planning and resource allocation problem for ESAoI minimization.To solve the mixed integer nonlinear programming(MINLP)problem with hybrid decision variables,we propose a TD3 trajectory planning and Round-robin resource allocation(TTPRRA).Specifically,we exploit the exploration and learning ability of the twin delayed deep deterministic policy gradient algorithm(TD3)for UAVs trajectory planning,and utilize Round Robin rule for the optimal resource allocation.With TTP-RRA,the UAVs obtain their flight velocities by sensing the locations and the age of information(AoI)of the vehicles,then allocate the RBs to the vehicles in a descending order of AoI until the remaining RBs are not sufficient to support another successful uploading.Simulation results demonstrate that TTP-RRA outperforms the baseline approaches in terms of ESAoI and average AoI(AAoI).

Information freshness optimization of multiple status update streams in Internet of things:Generation rate control and service rate reservation

The Internet of things(IoT)has become a key infrastructure providing up-to-date and fresh information for policy analysis and decision-making of upper-layer applications.However,there are limited sensing and communication resources in IoT devices,which significantly affects the timeliness and freshness of the updated status.This work proposes two schemes,namely,the generation rate control and service rate reservation schemes,to improve the overall information freshness of multiple status update streams at the receiver.Specifically,using the recently proposed Age of Information(AoI)as the metric for evaluating information freshness,we characterized the overall information freshness,i.e.,the overall average AoI at the receiver for both schemes,by considering the urgency difference of status update and streams.Both schemes for status updates and streams,respectively,were formulated as two optimization problems.We proved that both problems are convex and the optimal generation and service rates for different streams are found by the standard convex optimization algorithm.Moreover,we proposed both approximate optimal generation and approximate optimal service rate for fast deployment in heavy and light load cases.Numerical results verify the theoretical findings and accuracy of the proposed approximate solutions,guiding the design and deployment of IoT.

Electronic Nose with an Air Sensor Matrix for Detecting Beef Freshness

China is one of the largest meat producing countries in the wodd. With the growing concern for food safety more attention has been paid to meat quality. The application of conventional test methods for meat quality is limited by many factors, and subjectiveness, such as longer time to prepare samples and to test. A sensor matrix was constructed with several separate air sensors, and tests were conducted to detect the freshness of the beef. The results show that the air sensors TGS2610, TGS2600, TGS2611, TGS2620 and TGS2602 made by Tianjin Figaro Electronic Co, Ltd could be used to determine the degree of freshness but TGS2442 is not suitable. This study provides a foundation for designing and making an economical and practical detector for beef freshness.

Fruits and Vegetables Freshness Categorization Using Deep Learning

The nutritional value of perishable food items,such as fruits and vegetables,depends on their freshness levels.The existing approaches solve a binary class problem by classifying a known fruit\vegetable class into fresh or rotten only.We propose an automated fruits and vegetables categorization approach that first recognizes the class of object in an image and then categorizes that fruit or vegetable into one of the three categories:purefresh,medium-fresh,and rotten.We gathered a dataset comprising of 60K images of 11 fruits and vegetables,each is further divided into three categories of freshness,using hand-held cameras.The recognition and categorization of fruits and vegetables are performed through two deep learning models:Visual Geometry Group(VGG-16)and You Only Look Once(YOLO),and their results are compared.VGG-16 classifies fruits and vegetables and categorizes their freshness,while YOLO also localizes them within the image.Furthermore,we have developed an android based application that takes the image of the fruit or vegetable as input and returns its class label and its freshness degree.A comprehensive experimental evaluation of proposed approach demonstrates that the proposed approach can achieve a high accuracy and F1score on gathered FruitVeg Freshness dataset.The dataset is publicly available for further evaluation by the research community.

A Cooperative Schema between Web Sever and Search Engine for Improving Freshness of Web Repository

Because the web is huge and web pages are updated frequently, the index maintained by a search engine has to refresh web pages periodically. This is extremely resource consuming because the search engine needs to crawl the web and download web pages to refresh its index, Based on present technologies of web refreshing, we present a cooperative schema between web server and search engine for maintaining freshness of web repository. The web server provides metadata defined through XML standard to describe web sites. Before updating the web page the crawler visits the meta-data files. If the meta-data indicates that the page is not modified, then the crawler will not update it. So this schema can save bandwidth resource. A primitive model based on the schema is implemented. The cost and efficiency of the schema are analyzed.

Developing a Machine Vision System Equipped with UV Light to Predict Fish Freshness Based on Fish-Surface Color

This study assessed the feasibility of developing a machine vision system equipped with ultraviolet (UV) light, using changes in fish-surface color to predict aerobic plate count (APC, a standard freshness indicator) during storage. The APC values were tested and images of the fish surface were taken when fish were stored at room temperature. Then, images’ color-space conversion among RGB, HSV, and L*a*b* color spaces was carried out and analyzed. The results revealed that a* and b* values from the UV-light image decreased linearly during storage. A further regression analysis of these two parameters with APC value demonstrated a good exponential relationship between the a* value and the APC value (R2 = 0.97), followed by the b* (R2 = 0.85). Therefore, our results suggest that the change in color of the fish surface under UV light can be used to assess fish freshness during storage.

Colorimetric indicator based on zwitterionic anti-freezing hydrogel and alizarin for visual monitoring of salmon fillets freshness

Indicating hydrogels have shown the advantages of being fast, sensitive, and real-time in demonstrating the freshness of aquatic products due to their noticeable color change. In this work, an anti-freezing hydrogel embedded with pH-sensitive alizarin was developed as an original colorimetric indicator for monitoring the corruption of aquatic products at low temperatures. The anti-freezing hydrogel was prepared from 2-carboxyethyl acrylate, [2-(methacryloyloxy)ethyl]-trimethylammonium chloride, and 2-hydroxyethyl methacrylate monomers with triethylene glycol dimethacrylate as cross-linking agent. The hydrogel showed excellent anti-freezing capability, which was further incorporated with the pH-sensitive dye alizarin to gain the indicating capability. When applied in the indication of the freshness of salmon under low-temperature storage, it was found that the color changes of the indicator corresponded with the total volatile basic nitrogen contents of salmon, the correlation coefficient of which was 0.959 6. These results indicated the application potential of the hydrogels as freshness indicators during low-temperature storage or cold-chain transportation.

A ratiometric fluorescent probe for hypoxanthine detection in aquatic products based on the enzyme mimics and fluorescence of cobalt-doped carbon nitride

A ratiometric fluorescent probe for hypoxanthine(Hx)detection was established based on the mimic enzyme and fluorescence characteristics of cobalt-doped graphite-phase carbon nitride(Co doped g-C_(3)N_(4)).In addition to emitting strong fluorescence,the peroxidase activity of Co doped g-C_(3)N_(4)can catalyze the reaction of O-phenylenediamine and H_(2)O_(2)to produce diallyl phthalate which can emit yellow fluorescence at 570 nm.Through the decomposition of Hx by xanthine oxidase,Hx can be indirectly detected by the generating hydrogen peroxide based on the measurement of fluorescent ratio I(F_(570)/F_(370)).The linear range was 1.7-272.2 mg/kg(R^(2)=0.997),and the detection limit was 1.52 mg/kg(3σ/K,n=9).The established method was applied to Hx detection in bass,grass carp,and shrimp,and the data were verified by HPLC.The result shows that the established probe is sensitive,accurate,and reliable,and can be used for Hx detection in aquatic products.

Development of predictive models for egg freshness and shelf-life under different storage temperatures

The objective of the present study was to develop models for egg freshness and shelf-life predictions for the selected evaluation indicators including egg weight,Flaugh unit(HU),and albumen height.Experiments were carried out at different storage temperatures for a total period of 29-32 d.All data were collected and fitted in to Arrhenius equation for egg freshness,while the HU data were applied to a probability model for shelf-life prediction.The results showed that egg weight,albumen height,and HU decreased significantly,while albumen pH increased with the extension of storage time.The higher the storage temperature,the faster the egg quality decreased.In addition,the bias factor,accuracy factor,and the standard error of prediction were selected to verify the developed quality models.Maximum rescaled R-square statistic,the Hosmer-Lemeshow goodness-of-fit statistic,and the receiver operating characteristic curve were used to evaluate the goodness-of-fit of the developed probability model for the shelf-life of eggs,which indicated that the presented predictive models can be used to assess egg freshness and predict shelf-life during different storage temperatures.

Combining MobileNetV1 and Depthwise Separable convolution bottleneck with Expansion for classifying the freshness of fish eyes

Image classification using Convolutional Neural Network(CNN)achieves optimal perfor-mance with a particular strategy.MobileNet reduces the parameter number for learning features by switching from the standard convolution paradigm to the depthwise separable convolution(DSC)paradigm.However,there are not enough features to learn for identify-ing the freshness of fish eyes.Furthermore,minor variances in features should not require complicated CNN architecture.In this paper,our first contribution proposed DSC Bottle-neck with Expansion for learning features of the freshness of fish eyes with a Bottleneck Multiplier.The second contribution proposed Residual Transition to bridge current feature maps and skip connection feature maps to the next convolution block.The third contribu-tion proposed MobileNetV1 Bottleneck with Expansion(MB-BE)for classifying the freshness of fish eyes.The result obtained from the Freshness of the Fish Eyes dataset shows that MB-BE outperformed other models such as original MobileNet,VGG16,Densenet,Nasnet Mobile with 63.21%accuracy.

A statistical analysis of the freshness of postharvest leafy vegetables with application of water based on chlorophyll fluorescence measurement

Vegetable freshness is very important for both restaurant and home consumers.In market,sellers frequently apply water to leafy vegetables to make them not lose weight and look fresh;however,these vegetables may not be stored for a long time as they appear.After a time limit,they may be quickly rotten.It is thus meaningful to investigate early and simple detection tools to measure leafy vegetable freshness while they are frequently applied water in selling.In this work,three types of newly harvested leafy vegetables were bought from a local farmer market and stored in the air with room temperature and roots submerging in water.Chlorophyll a fluorescence(ChlF)from the vegetables was measured each half a day for three days.The obtained ChlF data were analyzed statistically and the correlation of ChlF parameters and vegetable freshness/storage time was obtained.The k-mean classification was also performed.It is found that Fo,Fj,Fm/Fo,and Fv/Fm can be used as an early detection tool to differentiate the freshness of leafy vegetables on which water is constantly applied in storage without visible difference.

Abomasal infusion of branched-chain amino acids or branched-chain keto-acids alter lactation performance and liver triglycerides in fresh cows

Background Dairy cows are at high risk of fatty liver disease in early lactation,but current preventative measures are not always effective.Cows with fatty liver have lower circulating branched-chain amino acid(BCAA)concentra-tions whereas cows with high circulating BCAA levels have low liver triglyceride(TG).Our objective was to determine the impact of BCAA and their corresponding ketoacids(branched-chain ketoacids,BCKA)on production performance and liver TG accumulation in Holstein cows in the first 3 weeks postpartum.Methods Thirty-six multiparous Holstein cows were used in a randomized block design experiment.Cows were abomasally infused for the first 21 d postpartum with solutions of 1)saline(CON,n=12);2)BCA(67 g valine,50 g leu-cine,and 34 g isoleucine,n=12);and 3)BCK(77 g 2-ketovaline calcium salt,57 g 2-ketoleucine calcium salt,and 39 g 2-ketoisoleucine calcium salt,n=12).All cows received the same diet.Treatment effects were determined using PROC GLIMMIX in SAS.Results No differences were detected for body weight,body condition score,or dry matter intake averaged over the first 21 d postpartum.Cows receiving BCK had significantly lower liver TG concentrations compared to CON(6.60%vs.4.77%,standard error of the mean(SEM)0.49)during the first 3 weeks of lactation.Infusion of BCA increased milk yield(39.5 vs.35.3 kg/d,SEM 1.8),milk fat yield(2.10 vs.1.69 kg/d,SEM 0.08),and lactose yield(2.11 vs.1.67 kg/d,SEM 0.07)compared with CON.Compared to CON,cows receiving BCA had lower plasma glucose(55.0 vs.59.2 mg/dL,SEM 0.86)but higherβ-hydroxybutyrate(9.17 vs.6.00 mg/dL,SEM 0.80).Conclusions Overall,BCAA supplementation in this study improved milk production,whereas BCKA supplementa-tion reduced TG accumulation in the liver of fresh cows.

Mixed Integer Robust Programming Model for Multimodal Fresh Agricultural Products Terminal Distribution Network Design

The low efficiency and high cost of fresh agricultural product terminal distribution directly restrict the operation of the entire supply network.To reduce costs and optimize the distribution network,we construct a mixed integer programmingmodel that comprehensively considers tominimize fixed,transportation,fresh-keeping,time,carbon emissions,and performance incentive costs.We analyzed the performance of traditional rider distribution and robot distribution modes in detail.In addition,the uncertainty of the actual market demand poses a huge threat to the stability of the terminal distribution network.In order to resist uncertain interference,we further extend the model to a robust counterpart form.The results of the simulation show that the instability of random parameters will lead to an increase in the cost.Compared with the traditional rider distribution mode,the robot distribution mode can save 12.7%on logistics costs,and the distribution efficiency is higher.Our research can provide support for the design of planning schemes for transportation enterprise managers.

Fresh Processing Technology in Polygonatum odoratum Production Area and Its Comparison with Traditional Processing

[Objectives]To compare the effects of traditional processing and fresh processing on the quality of Polygonatum odoratum decoction piece.[Methods]The effects of fresh processing and traditional processing on the quality of P.odoratum decoction piece were compared and analyzed with appearance characteristics,total ash content,extract content,total polysaccharides content,and total flavonoids content as the evaluation indexes.[Results]Fresh processing method in different production areas has different effects on P.odoratum decoction piece.P.odoratum was dried in oven of 50℃.When moisture content was 41.44%-59.67%,it was cut.After complete drying at 50℃,the moisture content of dried P.odoratum was 8.94%-9.60%,and ethanol-soluble extract content was 77.29%-78.20%,and water-soluble extract was 77.7%-78.14%.At this time,the appearance characteristics of section of P.odoratum decoction piece were better than that of traditional processing,which was yellowish white.The total polysaccharide content was higher than that of traditional processing,and the content of total flavonoids was statistically significant different from that of traditional processing.[Conclusions]The quality of P.odoratum decoction piece by fresh processing is better than that of the traditional processing,and it is feasible to use fresh processing.

A sensitive xanthine oxidase electrode with silk net for estimating fish freshness

An enzyme biosensor was constructed using a plate platinum electrode and immobilized xanthine oxidase (XOD). Only a very small quantity of enzyme was chemically immobilized on a special silk net. Hydrogen peroxide released during the enzymatic reaction was detected by the electrode at +0.65 V (vs. Ag/AgCl). The electrode was very sensitive to hypoxanthine and its detection limit was 1X10(-7) mol/L. When it was applied to the determination of fish freshness, the results agreed well with those obtained by traditional methods-determination of total volatile basic nitrogen (TVB-N) and microbial count. A range for estimating the freshness of river fish was suggested.

A Configurationally Tunable Perylene Bisimide Derivative-based Fluorescent Film Sensor for the Reliable Detection of Volatile Basic Nitrogen towards Fish Freshness Evaluation

Rapid and real-time mon itoring of food quality plays critical roles in the food industry and for the gen era I public health.Herei n,we specially synthesized a new perylene bisimide(PBI)derivative(PCB-EpE)composed of two PBI units and a rigid o-carborane linker,which was further employed in constructi ng a con ceptual fluoresce nt film sen sor for evaluati ng fish fresh ness.Photophysical studies indicate that PCB-EpE displays an open"Z-type"molecular configuration in chloroform and a closed"△-type"configuration in methyl cyclohexa ne.Comparatively,"Z-type"molecular configurati on possesses higher fluoresce nee qua ntum yield and is more sen sitive toward volatile basic nitrogen(VBN).

Nondestructive determination of the freshness change in bighead carp heads under variable temperatures by using excitation-emission matrix fl uorescence and back-propagation neural networks

This study established back-propagation neural networks(BPNNs)for evaluating the freshness of bighead carp(Hypophthalmichthys nobilis)heads during chilled storage via fluorescence spectroscopy using an excitation-emission matrix(EEM).The total volatile basic nitrogen(TVB-N)and total aerobic count(TAC)of fish increased obviously during storage at 0,4,8,12,and 16°C,while sensory scores decreased with increasing storage time.The EEM fluorescence intensity was measured,and its change was correlated with the freshness indicators of the samples.Three characteristic components of EEM data were extracted by parallel factor analysis,and two freshness indicators were used to construct the EEM-BPNNs model.The results demonstrated that the relative errors of the EEM-BPNNs model for TVB-N and TAC were less than 14%.This result indicated that the EEM-BPNNs model could determine the freshness of fish in cold chains in a rapid and nondestructive way.

Matching while Learning: Wireless Scheduling for Age of Information Optimization at the Edge

In this paper,we investigate the minimization of age of information(AoI),a metric that measures the information freshness,at the network edge with unreliable wireless communications.Particularly,we consider a set of users transmitting status updates,which are collected by the user randomly over time,to an edge server through unreliable orthogonal channels.It begs a natural question:with random status update arrivals and obscure channel conditions,can we devise an intelligent scheduling policy that matches the users and channels to stabilize the queues of all users while minimizing the average AoI?To give an adequate answer,we define a bipartite graph and formulate a dynamic edge activation problem with stability constraints.Then,we propose an online matching while learning algorithm(MatL)and discuss its implementation for wireless scheduling.Finally,simulation results demonstrate that the MatL is reliable to learn the channel states and manage the users’buffers for fresher information at the edge.

Changes of structure and functional properties of rice protein in the fresh edible rice during the seed development

It has been reported that fresh edible rice has more bioactive compounds and its protein is easier to digest and has lower hypoallergenic than mature rice. In this paper, the changes in structure and functional properties of proteins at five different stages, including early milky stage(EMS), middle milky stage(MMS), late milky stage(LMS), waxy ripe stage(WS)and ripening stage(RS), during the seed development were investigated. It was found that with the seed developing, the molecular weight of fresh rice protein gradually become larger while the secondary structure changed from the highest content of disordered structure at MMS to the highest content of ordered structure at RS, which affect the surface hydrophobicity and then the functional properties of proteins, including foaming properties, emulsifying properties and oil holding capacity. Fresh rice protein at MMS has the strongest surface hydrophobicity while fresh edible rice protein at RS has the strongest oil holding capability. The results of our study can provide a theoretical basis for the application of fresh rice protein in the food industry and help to develop new fresh edible rice food.