Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim ...Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.展开更多
Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim ...Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.展开更多
Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim ...Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.展开更多
Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim ...Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.展开更多
Data-driven process monitoring is an effective approach to assure safe operation of modern manufacturing and energy systems,such as thermal power plants being studied in this work.Industrial processes are inherently d...Data-driven process monitoring is an effective approach to assure safe operation of modern manufacturing and energy systems,such as thermal power plants being studied in this work.Industrial processes are inherently dynamic and need to be monitored using dynamic algorithms.Mainstream dynamic algorithms rely on concatenating current measurement with past data.This work proposes a new,alternative dynamic process monitoring algorithm,using dot product feature analysis(DPFA).DPFA computes the dot product of consecutive samples,thus naturally capturing the process dynamics through temporal correlation.At the same time,DPFA's online computational complexity is lower than not just existing dynamic algorithms,but also classical static algorithms(e.g.,principal component analysis and slow feature analysis).The detectability of the new algorithm is analyzed for three types of faults typically seen in process systems:sensor bias,process fault and gain change fault.Through experiments with a numerical example and real data from a thermal power plant,the DPFA algorithm is shown to be superior to the state-of-the-art methods,in terms of better monitoring performance(fault detection rate and false alarm rate)and lower computational complexity.展开更多
The microstructure and mechanical properties of the compact strip production(CSP)processed quenching and partitioning(Q&P)steels were investigated through experimental methods to address the challenge of designing...The microstructure and mechanical properties of the compact strip production(CSP)processed quenching and partitioning(Q&P)steels were investigated through experimental methods to address the challenge of designing high-performance Q&P steels.Compared with the conventional process(CP)produced samples,with slightly reduced strength,the total elongation of the CSP produced samples was increased by nearly 7%.Microstructural analysis revealed that variations in austenite stability were not the primary cause for the differences in mechanical properties between the CSP and the CP.The CSP processed Q&P steel exhibited milder center segregation behavior in contrast to the CP processed Q&P steel.Consequently,in the CSP processed Q&P steel,a higher proportion of austenite and a lower proportion of martensite were observed at the center position,delaying the crack initiation in the central region and contributing to the enhanced ductility.The investigation into the CSP process reveals its effect on alleviation of segregation and enhancement of mechanical properties of the Q&P steel.展开更多
In this study,an automated multimodal system for detecting,classifying,and dating fruit was developed using a two-stage YOLOv11 pipeline.In the first stage,the YOLOv11 detection model locates individual date fruits in...In this study,an automated multimodal system for detecting,classifying,and dating fruit was developed using a two-stage YOLOv11 pipeline.In the first stage,the YOLOv11 detection model locates individual date fruits in real time by drawing bounding boxes around them.These bounding boxes are subsequently passed to a YOLOv11 classification model,which analyzes cropped images and assigns class labels.An additional counting module automatically tallies the detected fruits,offering a near-instantaneous estimation of quantity.The experimental results suggest high precision and recall for detection,high classification accuracy(across 15 classes),and near-perfect counting in real time.This paper presents a multi-stage pipeline for date fruit detection,classification,and automated counting,employing YOLOv11-based models to achieve high accuracy while maintaining real-time throughput.The results demonstrated that the detection precision exceeded 90%,the classification accuracy approached 92%,and the counting module correlated closely with the manual tallies.These findings confirm the potential of reducing manual labour and enhancing operational efficiency in post-harvesting processes.Future studies will include dataset expansion,user-centric interfaces,and integration with harvesting robotics.展开更多
The grain production prediction is one of the most important links in precision agriculture. In the process of grain production prediction, mechanical noise caused by the factors of difference in field topography and ...The grain production prediction is one of the most important links in precision agriculture. In the process of grain production prediction, mechanical noise caused by the factors of difference in field topography and mechanical vibration will be mixed in the original signal, which undoubtedly will affect the prediction accuracy. Therefore, in order to reduce the influence of vibration noise on the prediction accuracy, an adaptive Ensemble Empirical Mode Decomposition(EEMD) threshold filtering algorithm was applied to the original signal in this paper: the output signal was decomposed into a finite number of Intrinsic Mode Functions(IMF) from high frequency to low frequency by using the Empirical Mode Decomposition(EMD) algorithm which could effectively restrain the mode mixing phenomenon; then the demarcation point of high and low frequency IMF components were determined by Continuous Mean Square Error criterion(CMSE), the high frequency IMF components were denoised by wavelet threshold algorithm, and finally the signal was reconstructed. The algorithm was an improved algorithm based on the commonly used wavelet threshold. The two algorithms were used to denoise the original production signal respectively, the adaptive EEMD threshold filtering algorithm had significant advantages in three denoising performance indexes of signal denoising ratio, root mean square error and smoothness. The five field verification tests showed that the average error of field experiment was 1.994% and the maximum relative error was less than 3%. According to the test results, the relative error of the predicted yield per hectare was 2.97%, which was relative to the actual yield. The test results showed that the algorithm could effectively resist noise and improve the accuracy of prediction.展开更多
Lentil is a highly nutritious legume with an ample quantity of carbohydrates and good amount of proteins, minerals, vitamins, phytochemicals and fibres. Although it has been used as staple food since ancient times, it...Lentil is a highly nutritious legume with an ample quantity of carbohydrates and good amount of proteins, minerals, vitamins, phytochemicals and fibres. Although it has been used as staple food since ancient times, its usage has been limited in developed countries, especially due to the lower protein digestibility, presence of anti-nutritional factors, flatulence and poor cooking qualities. Processing of lentils including dehulling and splitting and isolation of major fractions, e.g., proteins and starches are some of the strategies that can be adopted to add value and increase consumption of these legumes. This review paper intends to provide detailed overview of lentil＇s global production, nutritional composition and processing methods of lentil. Methods of isolation/characterization of lentil protein and starch and their subsequent application in foods are also presented.展开更多
With the projected global surge in hydrogen demand, driven by increasing applications and the imperative for low-emission hydrogen, the integration of machine learning(ML) across the hydrogen energy value chain is a c...With the projected global surge in hydrogen demand, driven by increasing applications and the imperative for low-emission hydrogen, the integration of machine learning(ML) across the hydrogen energy value chain is a compelling avenue. This review uniquely focuses on harnessing the synergy between ML and computational modeling(CM) or optimization tools, as well as integrating multiple ML techniques with CM, for the synthesis of diverse hydrogen evolution reaction(HER) catalysts and various hydrogen production processes(HPPs). Furthermore, this review addresses a notable gap in the literature by offering insights, analyzing challenges, and identifying research prospects and opportunities for sustainable hydrogen production. While the literature reflects a promising landscape for ML applications in hydrogen energy domains, transitioning AI-based algorithms from controlled environments to real-world applications poses significant challenges. Hence, this comprehensive review delves into the technical,practical, and ethical considerations associated with the application of ML in HER catalyst development and HPP optimization. Overall, this review provides guidance for unlocking the transformative potential of ML in enhancing prediction efficiency and sustainability in the hydrogen production sector.展开更多
Tomatoes are one of the most important specialty crops in United States and tomato products constitute a significant part of the food industry. The quality of tomato paste and juice is evaluated through their viscosit...Tomatoes are one of the most important specialty crops in United States and tomato products constitute a significant part of the food industry. The quality of tomato paste and juice is evaluated through their viscosity, color, flavor and nutritional value. Four processing methods were selected for this study, in-cluding conventional hot break, waring blender with steam, steam injection, and high temperature with shear (HTS) in a twin-screw continuous processor. The HTS method applies high temperature with shear mixer during hot-break tomato processing that improves the efficiency of the extraction process and the resultant tomato products possessed higher consistency, viscosity, and ly-copene content. Lycopene is an excellent antioxidant with cancer-preventing properties. This work showed that HTS method, utilizing whole tomatoes, produced a superior tomato product with a better color, higher viscosity, and improved bioactive properties.展开更多
Observed rainfall is a very essential parameter for the analysis of rainfall,day to day weather forecast and its validation.The observed rainfall data is only available from five observatories of IMD;while no rainfall...Observed rainfall is a very essential parameter for the analysis of rainfall,day to day weather forecast and its validation.The observed rainfall data is only available from five observatories of IMD;while no rainfall data is available at various important locations in and around Delhi-NCR.However,the 24-hour rainfall data observed by Doppler Weather Radar(DWR)for entire Delhi and surrounding region(up to 150 km)is readily available in a pictorial form.In this paper,efforts have been made to derive/estimate the rainfall at desired locations using DWR hydrological products.Firstly,the rainfall at desired locations has been estimated from the precipitation accumulation product(PAC)of the DWR using image processing in Python language.After this,a linear regression model using the least square method has been developed in R language.Estimated and observed rainfall data of year 2018(July,August and September)was used to train the model.After this,the model was tested on rainfall data of year 2019(July,August and September)and validated.With the use of linear regression model,the error in mean rainfall estimation reduced by 46.58% and the error in max rainfall estimation reduced by 84.53% for the year 2019.The error in mean rainfall estimation reduced by 81.36% and the error in max rainfall estimation reduced by 33.81%for the year 2018.Thus,the rainfall can be estimated with a fair degree of accuracy at desired locations within the range of the Doppler Weather Radar using the radar rainfall products and the developed linear regression model.展开更多
Objective:To establish a gas chromatography-mass spectrometry(GC-MS)method for the determination of volatile components in different prepared products of Alisma purpurea.Methods:The volatile components were determined...Objective:To establish a gas chromatography-mass spectrometry(GC-MS)method for the determination of volatile components in different prepared products of Alisma purpurea.Methods:The volatile components were determined by GC-MS,and the types and relative contents of volatile components were compared in 4 kinds of processed products.Result:The main volatile components of 30 kinds of different products from Zelica were analyzed and identified,which were mainly sesquiterpenes,ketones and alcohols,mainly Pogostol,olive,guaiacene,caryophyllene and so on.Conclusion:There are differences in the types and relative contents of volatile components in different products of Alisma platyphylla,in order to provide a basis for improving the quality standards of different products of Alisma platyphylla.展开更多
Cultural and creative education products play a crucial role in modern education,as they can enhance students’creativity and cultural understanding.In the field of cultural and creative product development,Artificial...Cultural and creative education products play a crucial role in modern education,as they can enhance students’creativity and cultural understanding.In the field of cultural and creative product development,Artificial Intelligence Generated Content(AIGC)has not yet been maturely applied,while data-driven design methods can achieve personalized and efficient design outputs,thus facilitating the creative generation and rapid iteration of AIGC.This study aims to explore the application of AIGC in the development of cultural and creative education products,and to form a future-oriented design process transformation in combination with rapid output of data analysis.By building a database of cultural elements and user preferences related to educational aspects in cultural and creative education products,training the AIGC system using machine learning technology,and submitting the design drafts formed in the near term to designers for further optimization,the product is finally subjected to user feedback and market testing,with products that are highly accepted by users as the final output.The research results show that the use of AIGC can not only promote innovation in cultural and creative education products,improve design efficiency and product diversity,but also inspire more creative inspiration for designers.The advantage of data analysis further enhances the accuracy of product development and market response speed,achieving effective transformation of the design process.Moreover,this research provides valuable references for educational management in terms of resource allocation and curriculum design.展开更多
In order to provide certain references for further deepening the development of processing industry of agricultural products,this paper analyzed and elaborated the basic principles,construction priorities and safeguar...In order to provide certain references for further deepening the development of processing industry of agricultural products,this paper analyzed and elaborated the basic principles,construction priorities and safeguard measures of the development of deep processing industry of agricultural products in Nanchong City of Sichuan Province. Besides,it made a scientific planning for accelerating the deep processing of agricultural products in Nanchong City in 2018-2020,to ensure the full implementation of fine and deep processing of agricultural products.展开更多
The science and technology development of agricultural products processing enterprises in Hubei Province is analyzed.From the perspective of modern marketing,problems in the research and development work of agricultur...The science and technology development of agricultural products processing enterprises in Hubei Province is analyzed.From the perspective of modern marketing,problems in the research and development work of agricultural products processing enterprises are analyzed from the aspects of market,personal training and technology radiation,which are mainly the lack of close connection with market.Countermeasures for the technological innovation of agricultural products processing enterprises are put forward,such as establishing modern enterprise culture with innovative features,strengthening the market benefits of brand,constructing a comprehensive customer orientation information platform,scientifically predicting and developing the market,doing well in market positioning of enterprise,selecting corresponding technology innovation strategy,taking technological innovation strategy as the basis,realizing the transformation from "4P" marketing combination to "4C",cultivating technical personnel,and realizing the integration of professional skill and marketing ability.展开更多
Cloud Computing as a disruptive technology, provides a dynamic, elastic and promising computing climate to tackle the challenges of big data processing and analytics. Hadoop and MapReduce are the widely used open sour...Cloud Computing as a disruptive technology, provides a dynamic, elastic and promising computing climate to tackle the challenges of big data processing and analytics. Hadoop and MapReduce are the widely used open source frameworks in Cloud Computing for storing and processing big data in the scalable fashion. Spark is the latest parallel computing engine working together with Hadoop that exceeds MapReduce performance via its in-memory computing and high level programming features. In this paper, we present our design and implementation of a productive, domain-specific big data analytics cloud platform on top of Hadoop and Spark. To increase user’s productivity, we created a variety of data processing templates to simplify the programming efforts. We have conducted experiments for its productivity and performance with a few basic but representative data processing algorithms in the petroleum industry. Geophysicists can use the platform to productively design and implement scalable seismic data processing algorithms without handling the details of data management and the complexity of parallelism. The Cloud platform generates a complete data processing application based on user’s kernel program and simple configurations, allocates resources and executes it in parallel on top of Spark and Hadoop.展开更多
Food Science of Animal Products(ISSN:2958-4124,e-ISSN:2958-3780)is a peer-reviewed,open access international journal that publishes the latest research findings in the field of animal-origin foods,involving food mater...Food Science of Animal Products(ISSN:2958-4124,e-ISSN:2958-3780)is a peer-reviewed,open access international journal that publishes the latest research findings in the field of animal-origin foods,involving food materials such as meat,aquatic products,milk,eggs,animal offals and edible insects.The research scope includes the quality and processing characteristics of food raw materials,the relationships of nutritional components and bioactive substances with human health,product flavor and sensory characteristics,the control of harmful substances during processing or cooking,product preservation,storage and packaging;microorganisms and fermentation,illegal drug residues and food safety detection;authenticity identifi cation;cell-cultured meat,regulations and standards.展开更多
Food Science of Animal Products(ISSN:2958-4124,e-ISSN:2958-3780)is a peer-reviewed,open access international journal that publishes the latest research findings in the field of animal-origin foods,involving food mater...Food Science of Animal Products(ISSN:2958-4124,e-ISSN:2958-3780)is a peer-reviewed,open access international journal that publishes the latest research findings in the field of animal-origin foods,involving food materials such as meat,aquatic products,milk,eggs,animal offals and edible insects.The research scope includes the quality and processing characteristics of food raw materials,the relationships of nutritional components and bioactive substances with human health,product flavor and sensory characteristics,the control of harmful substances during processing or cooking,product preservation,storage and packaging;microorganisms and fermentation,illegal drug residues and food safety detection;authenticity identification;cell-cultured meat,regulations and standards.展开更多
Food Science of Animal Products(ISSN:2958-4124,e-ISSN:2958-3780)is a peer-reviewed,open access international journal that publishes the latest research findings in the field of animal-origin foods,involving food mater...Food Science of Animal Products(ISSN:2958-4124,e-ISSN:2958-3780)is a peer-reviewed,open access international journal that publishes the latest research findings in the field of animal-origin foods,involving food materials such as meat,aquatic products,milk,eggs,animal offals and edible insects.The research scope includes the quality and processing characteristics of food raw materials,the relationships of nutritional components and bioactive substances with human health,product flavor and sensory characteristics,the control of harmful substances during processing or cooking,product preservation,storage and packaging;microorganisms and fermentation,illegal drug residues and food safety detection;authenticity identification;cell-cultured meat,regulations and standards.展开更多
文摘Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.
文摘Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.
文摘Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.
文摘Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.
基金supported in part by the National Science Fund for Distinguished Young Scholars of China(62225303)the National Natural Science Fundation of China(62303039,62433004)+2 种基金the China Postdoctoral Science Foundation(BX20230034,2023M730190)the Fundamental Research Funds for the Central Universities(buctrc202201,QNTD2023-01)the High Performance Computing Platform,College of Information Science and Technology,Beijing University of Chemical Technology
文摘Data-driven process monitoring is an effective approach to assure safe operation of modern manufacturing and energy systems,such as thermal power plants being studied in this work.Industrial processes are inherently dynamic and need to be monitored using dynamic algorithms.Mainstream dynamic algorithms rely on concatenating current measurement with past data.This work proposes a new,alternative dynamic process monitoring algorithm,using dot product feature analysis(DPFA).DPFA computes the dot product of consecutive samples,thus naturally capturing the process dynamics through temporal correlation.At the same time,DPFA's online computational complexity is lower than not just existing dynamic algorithms,but also classical static algorithms(e.g.,principal component analysis and slow feature analysis).The detectability of the new algorithm is analyzed for three types of faults typically seen in process systems:sensor bias,process fault and gain change fault.Through experiments with a numerical example and real data from a thermal power plant,the DPFA algorithm is shown to be superior to the state-of-the-art methods,in terms of better monitoring performance(fault detection rate and false alarm rate)and lower computational complexity.
基金support from the National Key R&D Program of China(No.2021YFB3702403).
文摘The microstructure and mechanical properties of the compact strip production(CSP)processed quenching and partitioning(Q&P)steels were investigated through experimental methods to address the challenge of designing high-performance Q&P steels.Compared with the conventional process(CP)produced samples,with slightly reduced strength,the total elongation of the CSP produced samples was increased by nearly 7%.Microstructural analysis revealed that variations in austenite stability were not the primary cause for the differences in mechanical properties between the CSP and the CP.The CSP processed Q&P steel exhibited milder center segregation behavior in contrast to the CP processed Q&P steel.Consequently,in the CSP processed Q&P steel,a higher proportion of austenite and a lower proportion of martensite were observed at the center position,delaying the crack initiation in the central region and contributing to the enhanced ductility.The investigation into the CSP process reveals its effect on alleviation of segregation and enhancement of mechanical properties of the Q&P steel.
基金supported by the Deanship of Scientific Research,Vice Presidency for Graduate Studies and Scientific Research,King Faisal University,Saudi Arabia,Grant No.KFU250098.
文摘In this study,an automated multimodal system for detecting,classifying,and dating fruit was developed using a two-stage YOLOv11 pipeline.In the first stage,the YOLOv11 detection model locates individual date fruits in real time by drawing bounding boxes around them.These bounding boxes are subsequently passed to a YOLOv11 classification model,which analyzes cropped images and assigns class labels.An additional counting module automatically tallies the detected fruits,offering a near-instantaneous estimation of quantity.The experimental results suggest high precision and recall for detection,high classification accuracy(across 15 classes),and near-perfect counting in real time.This paper presents a multi-stage pipeline for date fruit detection,classification,and automated counting,employing YOLOv11-based models to achieve high accuracy while maintaining real-time throughput.The results demonstrated that the detection precision exceeded 90%,the classification accuracy approached 92%,and the counting module correlated closely with the manual tallies.These findings confirm the potential of reducing manual labour and enhancing operational efficiency in post-harvesting processes.Future studies will include dataset expansion,user-centric interfaces,and integration with harvesting robotics.
基金Supported by National Science and Technology Support Program(2014BAD06B04-1-09)China Postdoctoral Fund(2016M601406)Heilongjiang Postdoctoral Fund(LBHZ15024)
文摘The grain production prediction is one of the most important links in precision agriculture. In the process of grain production prediction, mechanical noise caused by the factors of difference in field topography and mechanical vibration will be mixed in the original signal, which undoubtedly will affect the prediction accuracy. Therefore, in order to reduce the influence of vibration noise on the prediction accuracy, an adaptive Ensemble Empirical Mode Decomposition(EEMD) threshold filtering algorithm was applied to the original signal in this paper: the output signal was decomposed into a finite number of Intrinsic Mode Functions(IMF) from high frequency to low frequency by using the Empirical Mode Decomposition(EMD) algorithm which could effectively restrain the mode mixing phenomenon; then the demarcation point of high and low frequency IMF components were determined by Continuous Mean Square Error criterion(CMSE), the high frequency IMF components were denoised by wavelet threshold algorithm, and finally the signal was reconstructed. The algorithm was an improved algorithm based on the commonly used wavelet threshold. The two algorithms were used to denoise the original production signal respectively, the adaptive EEMD threshold filtering algorithm had significant advantages in three denoising performance indexes of signal denoising ratio, root mean square error and smoothness. The five field verification tests showed that the average error of field experiment was 1.994% and the maximum relative error was less than 3%. According to the test results, the relative error of the predicted yield per hectare was 2.97%, which was relative to the actual yield. The test results showed that the algorithm could effectively resist noise and improve the accuracy of prediction.
文摘Lentil is a highly nutritious legume with an ample quantity of carbohydrates and good amount of proteins, minerals, vitamins, phytochemicals and fibres. Although it has been used as staple food since ancient times, its usage has been limited in developed countries, especially due to the lower protein digestibility, presence of anti-nutritional factors, flatulence and poor cooking qualities. Processing of lentils including dehulling and splitting and isolation of major fractions, e.g., proteins and starches are some of the strategies that can be adopted to add value and increase consumption of these legumes. This review paper intends to provide detailed overview of lentil＇s global production, nutritional composition and processing methods of lentil. Methods of isolation/characterization of lentil protein and starch and their subsequent application in foods are also presented.
基金express their gratitude to the Higher Institution Centre of Excellence (HICoE) fund under the project code (JPT.S(BPKI)2000/016/018/015JId.4(21)/2022002HICOE)Universiti Tenaga Nasional (UNITEN) for funding the research through the (J510050002–IC–6 BOLDREFRESH2025)Akaun Amanah Industri Bekalan Elektrik (AAIBE) Chair of Renewable Energy grant,and NEC Energy Transition Grant (202203003ETG)。
文摘With the projected global surge in hydrogen demand, driven by increasing applications and the imperative for low-emission hydrogen, the integration of machine learning(ML) across the hydrogen energy value chain is a compelling avenue. This review uniquely focuses on harnessing the synergy between ML and computational modeling(CM) or optimization tools, as well as integrating multiple ML techniques with CM, for the synthesis of diverse hydrogen evolution reaction(HER) catalysts and various hydrogen production processes(HPPs). Furthermore, this review addresses a notable gap in the literature by offering insights, analyzing challenges, and identifying research prospects and opportunities for sustainable hydrogen production. While the literature reflects a promising landscape for ML applications in hydrogen energy domains, transitioning AI-based algorithms from controlled environments to real-world applications poses significant challenges. Hence, this comprehensive review delves into the technical,practical, and ethical considerations associated with the application of ML in HER catalyst development and HPP optimization. Overall, this review provides guidance for unlocking the transformative potential of ML in enhancing prediction efficiency and sustainability in the hydrogen production sector.
文摘Tomatoes are one of the most important specialty crops in United States and tomato products constitute a significant part of the food industry. The quality of tomato paste and juice is evaluated through their viscosity, color, flavor and nutritional value. Four processing methods were selected for this study, in-cluding conventional hot break, waring blender with steam, steam injection, and high temperature with shear (HTS) in a twin-screw continuous processor. The HTS method applies high temperature with shear mixer during hot-break tomato processing that improves the efficiency of the extraction process and the resultant tomato products possessed higher consistency, viscosity, and ly-copene content. Lycopene is an excellent antioxidant with cancer-preventing properties. This work showed that HTS method, utilizing whole tomatoes, produced a superior tomato product with a better color, higher viscosity, and improved bioactive properties.
文摘Observed rainfall is a very essential parameter for the analysis of rainfall,day to day weather forecast and its validation.The observed rainfall data is only available from five observatories of IMD;while no rainfall data is available at various important locations in and around Delhi-NCR.However,the 24-hour rainfall data observed by Doppler Weather Radar(DWR)for entire Delhi and surrounding region(up to 150 km)is readily available in a pictorial form.In this paper,efforts have been made to derive/estimate the rainfall at desired locations using DWR hydrological products.Firstly,the rainfall at desired locations has been estimated from the precipitation accumulation product(PAC)of the DWR using image processing in Python language.After this,a linear regression model using the least square method has been developed in R language.Estimated and observed rainfall data of year 2018(July,August and September)was used to train the model.After this,the model was tested on rainfall data of year 2019(July,August and September)and validated.With the use of linear regression model,the error in mean rainfall estimation reduced by 46.58% and the error in max rainfall estimation reduced by 84.53% for the year 2019.The error in mean rainfall estimation reduced by 81.36% and the error in max rainfall estimation reduced by 33.81%for the year 2018.Thus,the rainfall can be estimated with a fair degree of accuracy at desired locations within the range of the Doppler Weather Radar using the radar rainfall products and the developed linear regression model.
文摘Objective:To establish a gas chromatography-mass spectrometry(GC-MS)method for the determination of volatile components in different prepared products of Alisma purpurea.Methods:The volatile components were determined by GC-MS,and the types and relative contents of volatile components were compared in 4 kinds of processed products.Result:The main volatile components of 30 kinds of different products from Zelica were analyzed and identified,which were mainly sesquiterpenes,ketones and alcohols,mainly Pogostol,olive,guaiacene,caryophyllene and so on.Conclusion:There are differences in the types and relative contents of volatile components in different products of Alisma platyphylla,in order to provide a basis for improving the quality standards of different products of Alisma platyphylla.
基金2024 University Teachers Innovation Fund Project:Research on Decoding and Differentiated Innovation Strategies of Dunhuang Cultural and Creative Symbols under IP Cross-border Collaboration Background2023 Northwest Normal University“Course Ideological and Political Education”Demonstration Construction Project:DemonstrationDemonstration Course of Folk Art and Crafts.
文摘Cultural and creative education products play a crucial role in modern education,as they can enhance students’creativity and cultural understanding.In the field of cultural and creative product development,Artificial Intelligence Generated Content(AIGC)has not yet been maturely applied,while data-driven design methods can achieve personalized and efficient design outputs,thus facilitating the creative generation and rapid iteration of AIGC.This study aims to explore the application of AIGC in the development of cultural and creative education products,and to form a future-oriented design process transformation in combination with rapid output of data analysis.By building a database of cultural elements and user preferences related to educational aspects in cultural and creative education products,training the AIGC system using machine learning technology,and submitting the design drafts formed in the near term to designers for further optimization,the product is finally subjected to user feedback and market testing,with products that are highly accepted by users as the final output.The research results show that the use of AIGC can not only promote innovation in cultural and creative education products,improve design efficiency and product diversity,but also inspire more creative inspiration for designers.The advantage of data analysis further enhances the accuracy of product development and market response speed,achieving effective transformation of the design process.Moreover,this research provides valuable references for educational management in terms of resource allocation and curriculum design.
基金Supported by the Project of National Modern Agriculture Demonstration Area of the Ministry of Agriculture "Nanchong City National Modern Agriculture Demonstration Area"[Nong Ji Fa(2010)22]Project of Nanchong City National Modern Agriculture Demonstration Area Agricultural Reform and Construction Pilot Demonstration Area of the Ministry of Agriculture and Ministry of Finance[Nong Cai Fa(2013)13]Project of Nanchong City Nanchong National Agricultural Science and Technology Park of Ministry of Science and Technology(Guo Ke Ban Nong(2015)9]
文摘In order to provide certain references for further deepening the development of processing industry of agricultural products,this paper analyzed and elaborated the basic principles,construction priorities and safeguard measures of the development of deep processing industry of agricultural products in Nanchong City of Sichuan Province. Besides,it made a scientific planning for accelerating the deep processing of agricultural products in Nanchong City in 2018-2020,to ensure the full implementation of fine and deep processing of agricultural products.
基金Supported by the Innovation Fund Project for Graduate Students of Wuhan Polytechnic University(09cx028)
文摘The science and technology development of agricultural products processing enterprises in Hubei Province is analyzed.From the perspective of modern marketing,problems in the research and development work of agricultural products processing enterprises are analyzed from the aspects of market,personal training and technology radiation,which are mainly the lack of close connection with market.Countermeasures for the technological innovation of agricultural products processing enterprises are put forward,such as establishing modern enterprise culture with innovative features,strengthening the market benefits of brand,constructing a comprehensive customer orientation information platform,scientifically predicting and developing the market,doing well in market positioning of enterprise,selecting corresponding technology innovation strategy,taking technological innovation strategy as the basis,realizing the transformation from "4P" marketing combination to "4C",cultivating technical personnel,and realizing the integration of professional skill and marketing ability.
文摘Cloud Computing as a disruptive technology, provides a dynamic, elastic and promising computing climate to tackle the challenges of big data processing and analytics. Hadoop and MapReduce are the widely used open source frameworks in Cloud Computing for storing and processing big data in the scalable fashion. Spark is the latest parallel computing engine working together with Hadoop that exceeds MapReduce performance via its in-memory computing and high level programming features. In this paper, we present our design and implementation of a productive, domain-specific big data analytics cloud platform on top of Hadoop and Spark. To increase user’s productivity, we created a variety of data processing templates to simplify the programming efforts. We have conducted experiments for its productivity and performance with a few basic but representative data processing algorithms in the petroleum industry. Geophysicists can use the platform to productively design and implement scalable seismic data processing algorithms without handling the details of data management and the complexity of parallelism. The Cloud platform generates a complete data processing application based on user’s kernel program and simple configurations, allocates resources and executes it in parallel on top of Spark and Hadoop.
文摘Food Science of Animal Products(ISSN:2958-4124,e-ISSN:2958-3780)is a peer-reviewed,open access international journal that publishes the latest research findings in the field of animal-origin foods,involving food materials such as meat,aquatic products,milk,eggs,animal offals and edible insects.The research scope includes the quality and processing characteristics of food raw materials,the relationships of nutritional components and bioactive substances with human health,product flavor and sensory characteristics,the control of harmful substances during processing or cooking,product preservation,storage and packaging;microorganisms and fermentation,illegal drug residues and food safety detection;authenticity identifi cation;cell-cultured meat,regulations and standards.
文摘Food Science of Animal Products(ISSN:2958-4124,e-ISSN:2958-3780)is a peer-reviewed,open access international journal that publishes the latest research findings in the field of animal-origin foods,involving food materials such as meat,aquatic products,milk,eggs,animal offals and edible insects.The research scope includes the quality and processing characteristics of food raw materials,the relationships of nutritional components and bioactive substances with human health,product flavor and sensory characteristics,the control of harmful substances during processing or cooking,product preservation,storage and packaging;microorganisms and fermentation,illegal drug residues and food safety detection;authenticity identification;cell-cultured meat,regulations and standards.
文摘Food Science of Animal Products(ISSN:2958-4124,e-ISSN:2958-3780)is a peer-reviewed,open access international journal that publishes the latest research findings in the field of animal-origin foods,involving food materials such as meat,aquatic products,milk,eggs,animal offals and edible insects.The research scope includes the quality and processing characteristics of food raw materials,the relationships of nutritional components and bioactive substances with human health,product flavor and sensory characteristics,the control of harmful substances during processing or cooking,product preservation,storage and packaging;microorganisms and fermentation,illegal drug residues and food safety detection;authenticity identification;cell-cultured meat,regulations and standards.
