Pub Date : 2023-01-01DOI: 10.1504/ijsami.2023.127539
Bui Thu Hien, Nguyen Thi Khanh Chi
Green agriculture with the benefits of environmental protection, food safety and high economic value is becoming the destination of modern agriculture. Therefore, green innovation in agriculture leads to sustainable development, thereby improving the efficiency of management and use of natural resources while enhancing adaptability and resilience to the impacts of climate change. This study proposed the relationships among environment awareness, technology spillover (TS), social networks, and green innovation. Additionally, this study also investigates moderating role of social networks on green innovation and sustainable development. The probability sampling method was employed to develop a research sample. The research uses correlation analysis and structural equation modelling (SEM) to analyse the data of valid observations collected in the structured questionnaire survey in Vietnam. The results indicate that environment awareness and TS have direct positive impacts on green innovation. Moreover, social networks play the mediator in enhancing the innovation towards green agricultural production.
{"title":"Green innovation in agriculture development: the impact of environment awareness, technology spillover, and social networks","authors":"Bui Thu Hien, Nguyen Thi Khanh Chi","doi":"10.1504/ijsami.2023.127539","DOIUrl":"https://doi.org/10.1504/ijsami.2023.127539","url":null,"abstract":"Green agriculture with the benefits of environmental protection, food safety and high economic value is becoming the destination of modern agriculture. Therefore, green innovation in agriculture leads to sustainable development, thereby improving the efficiency of management and use of natural resources while enhancing adaptability and resilience to the impacts of climate change. This study proposed the relationships among environment awareness, technology spillover (TS), social networks, and green innovation. Additionally, this study also investigates moderating role of social networks on green innovation and sustainable development. The probability sampling method was employed to develop a research sample. The research uses correlation analysis and structural equation modelling (SEM) to analyse the data of valid observations collected in the structured questionnaire survey in Vietnam. The results indicate that environment awareness and TS have direct positive impacts on green innovation. Moreover, social networks play the mediator in enhancing the innovation towards green agricultural production.","PeriodicalId":37272,"journal":{"name":"International Journal of Sustainable Agricultural Management and Informatics","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134954756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An implementation of load cell for smart egg classification on rack","authors":"Kritsana Sureeya, Chalakorn Karupongsiri, Kanadit Chetpattananondh","doi":"10.1504/ijsami.2023.10055373","DOIUrl":"https://doi.org/10.1504/ijsami.2023.10055373","url":null,"abstract":"","PeriodicalId":37272,"journal":{"name":"International Journal of Sustainable Agricultural Management and Informatics","volume":"1 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66712720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijsami.2023.134077
Swami Nisha Bhagirath, Vaibhav Bhatnagar, Linesh Raja
A major crop for agricultural productivity is rice. This study aims to create a convolutional neural network model that is precisely predicting nitrogen deficiency in rice plants. Convolutional neural networks (CNNs) must be tested with a variety of configurations for various numbers of convolutional layers, filter size in each layer, number of convolution filters in each layer, and pool size sampling the images in order to get optimal performance. In this paper, rice leaf dataset was used to predict nitrogen deficiency in rice crop. Secondary data is used to perform convolutional neural network. From which 30% of the total data were used for testing and 70% of the images were used for training the model. After comparing the Adam optimiser accuracy and RMSprop optimiser accuracy, it is clearly seen that Adam optimiser gives higher accuracy. The model achieved 99% of classification accuracy using genetic algorithm (GA).
{"title":"Design of optimised model for nitrogen deficiency in rice leaves","authors":"Swami Nisha Bhagirath, Vaibhav Bhatnagar, Linesh Raja","doi":"10.1504/ijsami.2023.134077","DOIUrl":"https://doi.org/10.1504/ijsami.2023.134077","url":null,"abstract":"A major crop for agricultural productivity is rice. This study aims to create a convolutional neural network model that is precisely predicting nitrogen deficiency in rice plants. Convolutional neural networks (CNNs) must be tested with a variety of configurations for various numbers of convolutional layers, filter size in each layer, number of convolution filters in each layer, and pool size sampling the images in order to get optimal performance. In this paper, rice leaf dataset was used to predict nitrogen deficiency in rice crop. Secondary data is used to perform convolutional neural network. From which 30% of the total data were used for testing and 70% of the images were used for training the model. After comparing the Adam optimiser accuracy and RMSprop optimiser accuracy, it is clearly seen that Adam optimiser gives higher accuracy. The model achieved 99% of classification accuracy using genetic algorithm (GA).","PeriodicalId":37272,"journal":{"name":"International Journal of Sustainable Agricultural Management and Informatics","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136209179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijsami.2023.134071
Amr A. Ghanem, Abd El Azeem M. Mostafa, Enas S. Sadek
{"title":"The role of management in sustainable African protected agriculture: case study Egypt","authors":"Amr A. Ghanem, Abd El Azeem M. Mostafa, Enas S. Sadek","doi":"10.1504/ijsami.2023.134071","DOIUrl":"https://doi.org/10.1504/ijsami.2023.134071","url":null,"abstract":"","PeriodicalId":37272,"journal":{"name":"International Journal of Sustainable Agricultural Management and Informatics","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136209180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijsami.2023.10057686
Sanjeev Kumar, K. Narwal, Shubham Garg
{"title":"Economic sustainability of organic farming: an empirical study on farmers prospective","authors":"Sanjeev Kumar, K. Narwal, Shubham Garg","doi":"10.1504/ijsami.2023.10057686","DOIUrl":"https://doi.org/10.1504/ijsami.2023.10057686","url":null,"abstract":"","PeriodicalId":37272,"journal":{"name":"International Journal of Sustainable Agricultural Management and Informatics","volume":"1 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66712874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijsami.2023.134087
Caio Senna d, o Amaral, Fernando Tobal Berssaneti
{"title":"Exploring the project manager and project management in agricultural operations: a review","authors":"Caio Senna d, o Amaral, Fernando Tobal Berssaneti","doi":"10.1504/ijsami.2023.134087","DOIUrl":"https://doi.org/10.1504/ijsami.2023.134087","url":null,"abstract":"","PeriodicalId":37272,"journal":{"name":"International Journal of Sustainable Agricultural Management and Informatics","volume":"139 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136209177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijsami.2023.127538
Milan Marković, Jelena J. Stanković, Ivana Marjanović, Georgios Tsaples
The paper aims to calculate and evaluate the degree of achieved agricultural sustainability in the countries of the European Union. Agriculture is a specific activity that, on the one hand, must provide sufficient amounts of food for the population, while on the other hand, it can have a significant negative impact on the environment. The assessment of agricultural sustainability was made by selecting ten relevant indicators from the Eurostat and OECD databases, and by creating a composite index using the Mazziotta-Pareto method. The research results show that the Northern Europe countries (Sweden, Finland and Denmark) achieve the highest level of agricultural sustainability, mainly due to the high participation of organic agricultural production, as well as the low level of soil erosion, considering all European countries. On the contrary, countries with high agricultural economic performance show significantly worse results in terms of sustainability (such as Italy, Spain and France).
{"title":"A non-compensatory approach to the creation of composite indices of agricultural sustainability of the European Union countries","authors":"Milan Marković, Jelena J. Stanković, Ivana Marjanović, Georgios Tsaples","doi":"10.1504/ijsami.2023.127538","DOIUrl":"https://doi.org/10.1504/ijsami.2023.127538","url":null,"abstract":"The paper aims to calculate and evaluate the degree of achieved agricultural sustainability in the countries of the European Union. Agriculture is a specific activity that, on the one hand, must provide sufficient amounts of food for the population, while on the other hand, it can have a significant negative impact on the environment. The assessment of agricultural sustainability was made by selecting ten relevant indicators from the Eurostat and OECD databases, and by creating a composite index using the Mazziotta-Pareto method. The research results show that the Northern Europe countries (Sweden, Finland and Denmark) achieve the highest level of agricultural sustainability, mainly due to the high participation of organic agricultural production, as well as the low level of soil erosion, considering all European countries. On the contrary, countries with high agricultural economic performance show significantly worse results in terms of sustainability (such as Italy, Spain and France).","PeriodicalId":37272,"journal":{"name":"International Journal of Sustainable Agricultural Management and Informatics","volume":"212 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135007846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijsami.2023.10055374
Apostolos Kantartzis
{"title":"Implementation of multi-criteria evaluation for mapping the spatial variability of optimal forest road network","authors":"Apostolos Kantartzis","doi":"10.1504/ijsami.2023.10055374","DOIUrl":"https://doi.org/10.1504/ijsami.2023.10055374","url":null,"abstract":"","PeriodicalId":37272,"journal":{"name":"International Journal of Sustainable Agricultural Management and Informatics","volume":"1 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66712736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijsami.2023.10056114
Stavros Kalogiannidis, F. Chatzitheodoridis
{"title":"Strategic communication and sustainable agricultural competitiveness: a Greek case study","authors":"Stavros Kalogiannidis, F. Chatzitheodoridis","doi":"10.1504/ijsami.2023.10056114","DOIUrl":"https://doi.org/10.1504/ijsami.2023.10056114","url":null,"abstract":"","PeriodicalId":37272,"journal":{"name":"International Journal of Sustainable Agricultural Management and Informatics","volume":"1 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66712787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Design of optimised model for nitrogen deficiency in rice leaves","authors":"Linesh Raja, Swami Nisha Bhagirath, Vaibhav Bhatnagar","doi":"10.1504/ijsami.2023.10056814","DOIUrl":"https://doi.org/10.1504/ijsami.2023.10056814","url":null,"abstract":"","PeriodicalId":37272,"journal":{"name":"International Journal of Sustainable Agricultural Management and Informatics","volume":"1 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66712806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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