Pub Date : 2021-10-25DOI: 10.1080/09064710.2021.1976266
Thanjai Vadivel, R. Suguna
ABSTRACT The changes in weather have beneficial and harmful effects on crop yields. There will be a loss of yield because of the diseases in crops. With the growing population, the fundamental want of food is growing. That is why agriculture gains a prominent position all around the world. It eventually ends up by a massive defeat for the farmers and the financial boom of India. The article’s primary goalis to bring together farmers and cutting-edge technologies to minimise diseases in plant leaves. To enforce the idea, ‘Tomato’ is selected in which leaf sicknesses are expected and identified by the Artificial Intelligence algorithms, CNN (Convolution Neural Network) with pc technological know-how. Tomato is a mere consumable vegetable in India. In this investigation, seven types of tomato leaf disorders were sensed, including one wholesome elegance. The farmers are able to check the symptoms with the shapes of images of the tomato leaves with those expecting diseases. Its comparison of various classification and filters/methods with different techniques, such as K-Means classifier, SVM (Support Vector), RBF(Radial Basis Function) Kernel, Optimised MLP(Multilayer perceptron), NN classifier, BPNN (back-propagation neural network) and CNN Classifier. The classification accuracy of the existing method after experiment is RBF − 89%, k-means – 85.3%, SVM – 88.8%, Optimised MLP – 91.4%, NN – 97, BPNN – 85.5%, CNN – 94.4%. The proposed architecture can achieve the desired accuracy of 99.4%.
{"title":"Automatic recognition of tomato leaf disease using fast enhanced learning with image processing","authors":"Thanjai Vadivel, R. Suguna","doi":"10.1080/09064710.2021.1976266","DOIUrl":"https://doi.org/10.1080/09064710.2021.1976266","url":null,"abstract":"ABSTRACT The changes in weather have beneficial and harmful effects on crop yields. There will be a loss of yield because of the diseases in crops. With the growing population, the fundamental want of food is growing. That is why agriculture gains a prominent position all around the world. It eventually ends up by a massive defeat for the farmers and the financial boom of India. The article’s primary goalis to bring together farmers and cutting-edge technologies to minimise diseases in plant leaves. To enforce the idea, ‘Tomato’ is selected in which leaf sicknesses are expected and identified by the Artificial Intelligence algorithms, CNN (Convolution Neural Network) with pc technological know-how. Tomato is a mere consumable vegetable in India. In this investigation, seven types of tomato leaf disorders were sensed, including one wholesome elegance. The farmers are able to check the symptoms with the shapes of images of the tomato leaves with those expecting diseases. Its comparison of various classification and filters/methods with different techniques, such as K-Means classifier, SVM (Support Vector), RBF(Radial Basis Function) Kernel, Optimised MLP(Multilayer perceptron), NN classifier, BPNN (back-propagation neural network) and CNN Classifier. The classification accuracy of the existing method after experiment is RBF − 89%, k-means – 85.3%, SVM – 88.8%, Optimised MLP – 91.4%, NN – 97, BPNN – 85.5%, CNN – 94.4%. The proposed architecture can achieve the desired accuracy of 99.4%.","PeriodicalId":7094,"journal":{"name":"Acta Agriculturae Scandinavica, Section B — Soil & Plant Science","volume":"5 1","pages":"312 - 324"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86843067","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 : 2021-10-04DOI: 10.1080/09064710.2021.1984564
M. Christian, H. Shimelis, M. Laing, T. Tsilo, I. Mathew
ABSTRACT The production and quality of wheat are affected by abiotic constraints including water stress and soil nutrient deficiencies. It is imperative to develop drought-tolerant wheat varieties with high yield potential and enhanced grain protein content for food security. Silicon (Si) is important for plant growth and development but its role in abiotic stress tolerance has been overlooked in breeding programs. Identifying the underlying functional genes controlling drought tolerance, protein content and grain yield is essential for wheat improvement, especially under drought stress. Silicon uptake is conditioned by several Si transporter genes such as Lsi1, Lsi2 and Lsi6 and aquaporins, which facilitate transport of silicon and water between cells. The objectives of this review are to examine the role of Si in improving plant nutrition and drought tolerance, and to appraise the genetic control of Si uptake and breeding methods for improving Si uptake for drought adaptation and improved grain yield and quality. The review highlights the limited progress made in breeding for drought tolerance in wheat, especially in sub-Sahara Africa where the challenge is prevalent. Limited understanding of the genetic basis for Si uptake and physiology contribute to the limited progress in its exploitation in wheat improvement programs.
{"title":"Breeding for silicon-use efficiency, protein content and drought tolerance in bread wheat (Triticum aestivum L.): a review","authors":"M. Christian, H. Shimelis, M. Laing, T. Tsilo, I. Mathew","doi":"10.1080/09064710.2021.1984564","DOIUrl":"https://doi.org/10.1080/09064710.2021.1984564","url":null,"abstract":"ABSTRACT\u0000 The production and quality of wheat are affected by abiotic constraints including water stress and soil nutrient deficiencies. It is imperative to develop drought-tolerant wheat varieties with high yield potential and enhanced grain protein content for food security. Silicon (Si) is important for plant growth and development but its role in abiotic stress tolerance has been overlooked in breeding programs. Identifying the underlying functional genes controlling drought tolerance, protein content and grain yield is essential for wheat improvement, especially under drought stress. Silicon uptake is conditioned by several Si transporter genes such as Lsi1, Lsi2 and Lsi6 and aquaporins, which facilitate transport of silicon and water between cells. The objectives of this review are to examine the role of Si in improving plant nutrition and drought tolerance, and to appraise the genetic control of Si uptake and breeding methods for improving Si uptake for drought adaptation and improved grain yield and quality. The review highlights the limited progress made in breeding for drought tolerance in wheat, especially in sub-Sahara Africa where the challenge is prevalent. Limited understanding of the genetic basis for Si uptake and physiology contribute to the limited progress in its exploitation in wheat improvement programs.","PeriodicalId":7094,"journal":{"name":"Acta Agriculturae Scandinavica, Section B — Soil & Plant Science","volume":"1 1","pages":"17 - 29"},"PeriodicalIF":0.0,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86488811","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 : 2021-09-22DOI: 10.1080/09064710.2021.1977841
J. Gailis, Nameda Astašova, E. Jākobsone, L. Ozoliņa-Pole
ABSTRACT The broadbean seed beetle (Bruchus rufimanus Boheman, 1833) is a major pest of faba bean (Vicia faba L.) almost everywhere this crop is grown. The main tasks of this research were to study the seed beetle's phenology, and rates of egg laying, larval survival and the emergence of young adults before the harvest. Studies were done in field conditions in farms located in various places in Latvia. The highest density of imagines was observed at a time when the plants were flowering intensively. Egg laying began as soon as the pods had formed in the lower third of the stem and lasted 4–5 weeks. In severe infestation happened, more than 34 eggs were laid per pod. The percentage of damaged yield increased in proportion to the average number of eggs laid on pods until this number reached 11–12 eggs per pod and remained at approximately the same level also when egg-laying rate was higher. In several fields, no seeds with imago exit holes were found in the samples few days before harvest, while in other sowings, the proportion of such seeds exceeded 90% of the total amount of damaged yield.
{"title":"Biology of broadbean seed beetle (Bruchus rufimanus; Coleoptera: Chrysomelidae) in Latvia","authors":"J. Gailis, Nameda Astašova, E. Jākobsone, L. Ozoliņa-Pole","doi":"10.1080/09064710.2021.1977841","DOIUrl":"https://doi.org/10.1080/09064710.2021.1977841","url":null,"abstract":"ABSTRACT The broadbean seed beetle (Bruchus rufimanus Boheman, 1833) is a major pest of faba bean (Vicia faba L.) almost everywhere this crop is grown. The main tasks of this research were to study the seed beetle's phenology, and rates of egg laying, larval survival and the emergence of young adults before the harvest. Studies were done in field conditions in farms located in various places in Latvia. The highest density of imagines was observed at a time when the plants were flowering intensively. Egg laying began as soon as the pods had formed in the lower third of the stem and lasted 4–5 weeks. In severe infestation happened, more than 34 eggs were laid per pod. The percentage of damaged yield increased in proportion to the average number of eggs laid on pods until this number reached 11–12 eggs per pod and remained at approximately the same level also when egg-laying rate was higher. In several fields, no seeds with imago exit holes were found in the samples few days before harvest, while in other sowings, the proportion of such seeds exceeded 90% of the total amount of damaged yield.","PeriodicalId":7094,"journal":{"name":"Acta Agriculturae Scandinavica, Section B — Soil & Plant Science","volume":"11 1","pages":"4 - 16"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88220077","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 : 2021-09-15DOI: 10.1080/09064710.2021.1977380
Silva Sulg, R. Kaasik, Jonathan Willow, E. Veromann
Oilseed rape (Brassica napus) has numerous insect pests, some of which are stem-miners. Currently, blue stem weevil (Ceutorhynchus sulcicollis) is not considered a pest of oilseed rape. In the present study, a total of 60 (30 untreated, 30 insecticide-treated) oilseed rape plants were dissected; and stem-mining larvae were collected, and subsequently allowed to pupate in soil. After pupation, all emerged adult weevils were identified as either blue stem weevil (C. sulcicollis) or cabbage stem weevil (Ceutorhynchus pallidactylus). We report that under favourable conditions C. sulcicollis was capable of reaching pest status, and was significantly more abundant than C. pallidactylus, indicating a critical need for future studies regarding C. sulcicollis.
{"title":"Blue stem weevil (Ceutorhynchus sulcicollis) – a potential threat to oilseed rape production","authors":"Silva Sulg, R. Kaasik, Jonathan Willow, E. Veromann","doi":"10.1080/09064710.2021.1977380","DOIUrl":"https://doi.org/10.1080/09064710.2021.1977380","url":null,"abstract":"Oilseed rape (Brassica napus) has numerous insect pests, some of which are stem-miners. Currently, blue stem weevil (Ceutorhynchus sulcicollis) is not considered a pest of oilseed rape. In the present study, a total of 60 (30 untreated, 30 insecticide-treated) oilseed rape plants were dissected; and stem-mining larvae were collected, and subsequently allowed to pupate in soil. After pupation, all emerged adult weevils were identified as either blue stem weevil (C. sulcicollis) or cabbage stem weevil (Ceutorhynchus pallidactylus). We report that under favourable conditions C. sulcicollis was capable of reaching pest status, and was significantly more abundant than C. pallidactylus, indicating a critical need for future studies regarding C. sulcicollis.","PeriodicalId":7094,"journal":{"name":"Acta Agriculturae Scandinavica, Section B — Soil & Plant Science","volume":"42 1","pages":"1 - 3"},"PeriodicalIF":0.0,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85604674","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 : 2021-09-14DOI: 10.1080/09064710.2021.1966496
Honghong Liu
ABSTRACT To improve the effect of agricultural water management, this paper builds an agricultural water management system based on the Internet of Things and data analysis, and designs an intelligent analysis model of the system using the method of time series forecasting. Moreover, this paper designs the software and hardware of the ZigBee wireless sensor network monitoring node, including the hardware circuit design of the ZigBee network monitoring node and the software acquisition program design to realise the data acquisition and short-distance transmission of the farmland environment. In addition, this paper designs a farmland irrigation system based on the Internet of Things, which can also realise real-time monitoring of agricultural water quality. Finally, this paper designs an experiment to analyse the performance of the system constructed in this paper. Judging from the performance of the agricultural water management system, it can be seen that its performance can meet the actual needs of agricultural water management.
{"title":"Agricultural water management based on the Internet of Things and data analysis","authors":"Honghong Liu","doi":"10.1080/09064710.2021.1966496","DOIUrl":"https://doi.org/10.1080/09064710.2021.1966496","url":null,"abstract":"ABSTRACT\u0000 To improve the effect of agricultural water management, this paper builds an agricultural water management system based on the Internet of Things and data analysis, and designs an intelligent analysis model of the system using the method of time series forecasting. Moreover, this paper designs the software and hardware of the ZigBee wireless sensor network monitoring node, including the hardware circuit design of the ZigBee network monitoring node and the software acquisition program design to realise the data acquisition and short-distance transmission of the farmland environment. In addition, this paper designs a farmland irrigation system based on the Internet of Things, which can also realise real-time monitoring of agricultural water quality. Finally, this paper designs an experiment to analyse the performance of the system constructed in this paper. Judging from the performance of the agricultural water management system, it can be seen that its performance can meet the actual needs of agricultural water management.","PeriodicalId":7094,"journal":{"name":"Acta Agriculturae Scandinavica, Section B — Soil & Plant Science","volume":"103 1","pages":"300 - 311"},"PeriodicalIF":0.0,"publicationDate":"2021-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79465909","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 : 2021-08-31DOI: 10.1080/09064710.2021.1938200
Huo Yuanyuan, Zhang-hui Yan
ABSTRACT This paper empirically analyses the promotional effect of preferential fiscal and tax policies on the performance of agricultural enterprises in the straw power generation industry chain through the small- and medium-sized enterprises in the straw gasification cogeneration project industry chain. It has a positive effect. This paper discusses the implementation of agricultural enterprises straw power generation project industry chain, the situation of pollution reduction and efficiency improvement of agricultural enterprises, and the positive effects of fiscal and tax preferential policies on promoting agricultural enterprises straw power generation project industry chain. It points out that it is highly important to promote agricultural enterprises straw power generation project industry chain in China and implement fiscal and tax preferential policies for corresponding projects.
{"title":"Research on the impact of China’s fiscal and tax policies on the performance of agricultural enterprises in straw power generation industry chain","authors":"Huo Yuanyuan, Zhang-hui Yan","doi":"10.1080/09064710.2021.1938200","DOIUrl":"https://doi.org/10.1080/09064710.2021.1938200","url":null,"abstract":"ABSTRACT This paper empirically analyses the promotional effect of preferential fiscal and tax policies on the performance of agricultural enterprises in the straw power generation industry chain through the small- and medium-sized enterprises in the straw gasification cogeneration project industry chain. It has a positive effect. This paper discusses the implementation of agricultural enterprises straw power generation project industry chain, the situation of pollution reduction and efficiency improvement of agricultural enterprises, and the positive effects of fiscal and tax preferential policies on promoting agricultural enterprises straw power generation project industry chain. It points out that it is highly important to promote agricultural enterprises straw power generation project industry chain in China and implement fiscal and tax preferential policies for corresponding projects.","PeriodicalId":7094,"journal":{"name":"Acta Agriculturae Scandinavica, Section B — Soil & Plant Science","volume":"97 1","pages":"1050 - 1062"},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79116492","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 : 2021-08-31DOI: 10.1080/09064710.2021.1967439
Chao Huang, Yaling Chen
ABSTRACT To expand agricultural business and upgrade the effects of product marketing, supported by the concept of smart agricultural, this paper introduces us the methods to undertake agricultural business promotion and build up product marketing system in combination with big data technology and machine learning technology, put forward the application of fuzzy c-means algorithm in the agricultural marketing data. The algorithm is a clustering algorithm that uses degree of membership function to determine which cluster each data point belongs to; thus to build up a basic model of smart agriculture based on actual situation, and integrate the agricultural business promotion and agricultural products marketing, as important function modules, into the agricultural products marketing system; and then the process of this system is analysed before the frame of the overall system is shaped; based on which, system performance verification is conducted by designed test. From the research, the agricultural business promotion and products marketing system based on smart agriculture have some positive effect.
{"title":"Agricultural business and product marketing effected by using big data analysis in smart agriculture","authors":"Chao Huang, Yaling Chen","doi":"10.1080/09064710.2021.1967439","DOIUrl":"https://doi.org/10.1080/09064710.2021.1967439","url":null,"abstract":"ABSTRACT To expand agricultural business and upgrade the effects of product marketing, supported by the concept of smart agricultural, this paper introduces us the methods to undertake agricultural business promotion and build up product marketing system in combination with big data technology and machine learning technology, put forward the application of fuzzy c-means algorithm in the agricultural marketing data. The algorithm is a clustering algorithm that uses degree of membership function to determine which cluster each data point belongs to; thus to build up a basic model of smart agriculture based on actual situation, and integrate the agricultural business promotion and agricultural products marketing, as important function modules, into the agricultural products marketing system; and then the process of this system is analysed before the frame of the overall system is shaped; based on which, system performance verification is conducted by designed test. From the research, the agricultural business promotion and products marketing system based on smart agriculture have some positive effect.","PeriodicalId":7094,"journal":{"name":"Acta Agriculturae Scandinavica, Section B — Soil & Plant Science","volume":"37 1","pages":"980 - 991"},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86216190","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 : 2021-08-31DOI: 10.1080/09064710.2021.1967438
Hongchang Li, Fang Gao
ABSTRACT In order to overcome the shortcomings of traditional agricultural cultivator opener, this paper combines digital drawing technology and digitisation to analyse the structure of cultivator opener, improves the structure of traditional cultivator opener, establishes a mathematical model of the transmission mechanism, and determines the relationship between various parameters. Furthermore, this paper differentiates the ideal motion trajectory, calculates the length of each rod through the iterative trajectory coordinates, optimises and improves the structure of the entire cultivator opener, and combines the simulation method to draw the structure. In order to verify the improvement effect of the cultivator opener, this paper uses the quadratic orthogonal rotation regression test to improve the structure of the cultivator opener designed and improved in this paper. From the experimental research, it can be seen that the cultivator opener designed in this paper can improve the uniformity of seeding depth, reduce soil disturbance, and enhance the compactness of the seedbed soil, which provides a reference for the design of the cultivator opener.
{"title":"Investigation on optimising agricultural cultivator openers using quadratic orthogonal rotation regression","authors":"Hongchang Li, Fang Gao","doi":"10.1080/09064710.2021.1967438","DOIUrl":"https://doi.org/10.1080/09064710.2021.1967438","url":null,"abstract":"ABSTRACT In order to overcome the shortcomings of traditional agricultural cultivator opener, this paper combines digital drawing technology and digitisation to analyse the structure of cultivator opener, improves the structure of traditional cultivator opener, establishes a mathematical model of the transmission mechanism, and determines the relationship between various parameters. Furthermore, this paper differentiates the ideal motion trajectory, calculates the length of each rod through the iterative trajectory coordinates, optimises and improves the structure of the entire cultivator opener, and combines the simulation method to draw the structure. In order to verify the improvement effect of the cultivator opener, this paper uses the quadratic orthogonal rotation regression test to improve the structure of the cultivator opener designed and improved in this paper. From the experimental research, it can be seen that the cultivator opener designed in this paper can improve the uniformity of seeding depth, reduce soil disturbance, and enhance the compactness of the seedbed soil, which provides a reference for the design of the cultivator opener.","PeriodicalId":7094,"journal":{"name":"Acta Agriculturae Scandinavica, Section B — Soil & Plant Science","volume":"13 1","pages":"970 - 979"},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86920399","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 : 2021-08-31DOI: 10.1080/09064710.2021.1956580
Xiaona Hou
ABSTRACT The number of rural populations is increasing year by year, but the rural economy is developing slowly and lacking certain vitality, and resources are wasted excessively in the process of agricultural production. As a result, the agro-ecological complex system is inefficient, unreasonable in structure, low in output, and slow in regional economic growth. This paper uses the spatial panel model to study and analyse the agricultural innovation ecosystem and economic growth and by analysing the spatial influencing factors of various variables a spatial Dubin model is constructed. Moreover, this paper combines the classic panel and the space model and expands the space model into a space panel model. Finally, this paper combines the regional economic development to conduct an experimental analysis on the correlation of the agricultural innovation ecosystem and economic growth. From the research results, it can be seen that the method proposed in this paper has certain practical significance. Finally, this paper advances agriculture innovation progress over harmless to the ecosystem agrarian innovation development exercises.
{"title":"Analysis of the correlation between agricultural innovation ecosystem and economic growth","authors":"Xiaona Hou","doi":"10.1080/09064710.2021.1956580","DOIUrl":"https://doi.org/10.1080/09064710.2021.1956580","url":null,"abstract":"ABSTRACT The number of rural populations is increasing year by year, but the rural economy is developing slowly and lacking certain vitality, and resources are wasted excessively in the process of agricultural production. As a result, the agro-ecological complex system is inefficient, unreasonable in structure, low in output, and slow in regional economic growth. This paper uses the spatial panel model to study and analyse the agricultural innovation ecosystem and economic growth and by analysing the spatial influencing factors of various variables a spatial Dubin model is constructed. Moreover, this paper combines the classic panel and the space model and expands the space model into a space panel model. Finally, this paper combines the regional economic development to conduct an experimental analysis on the correlation of the agricultural innovation ecosystem and economic growth. From the research results, it can be seen that the method proposed in this paper has certain practical significance. Finally, this paper advances agriculture innovation progress over harmless to the ecosystem agrarian innovation development exercises.","PeriodicalId":7094,"journal":{"name":"Acta Agriculturae Scandinavica, Section B — Soil & Plant Science","volume":"48 1","pages":"1036 - 1049"},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86069360","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 : 2021-08-31DOI: 10.1080/09064710.2021.1964592
S. Durai, C. Mahesh
ABSTRACT Rice Seed varietal classification and germination evaluation system is developed to identify the variety and evaluate the germination of rice seeds using Digital Image processing system. For economic and ease of usage, we have used mobile phones to take digital images. The objective of our research is, it will be easily used by farmers. Our research is done on four major rice varieties, which commonly cultivated by Tamilnadu farmers, namely (1) Andhra Ponni (2) Atchaya Ponni (3) KO50 and (4) IR 20 was collected from Tamilnadu Agricultural University Tiruchirappalli, Tamilnadu, India. We have extracted 24 features: 3 colour features, 13 morphological features and 8 textural features. Created data set tested with all possible classification algorithms, out of which Ensemble classification algorithm gives 91.6% accuracy for Variety Identification and SVM gives 63% of accuracy for germination prediction. According to the germination percentage, a support vector machine (SVM) was utilised to categorise the seeds specimens into 3 groups: healthy, old, and deceased. The categorisation prediction accuracy has always been significant. We have created the data set for successful identification of varieties and germination prediction for the above-mentioned varieties; it is publicly available for usage.
{"title":"Research on varietal classification and germination evaluation system for rice seed using hand-held devices","authors":"S. Durai, C. Mahesh","doi":"10.1080/09064710.2021.1964592","DOIUrl":"https://doi.org/10.1080/09064710.2021.1964592","url":null,"abstract":"ABSTRACT Rice Seed varietal classification and germination evaluation system is developed to identify the variety and evaluate the germination of rice seeds using Digital Image processing system. For economic and ease of usage, we have used mobile phones to take digital images. The objective of our research is, it will be easily used by farmers. Our research is done on four major rice varieties, which commonly cultivated by Tamilnadu farmers, namely (1) Andhra Ponni (2) Atchaya Ponni (3) KO50 and (4) IR 20 was collected from Tamilnadu Agricultural University Tiruchirappalli, Tamilnadu, India. We have extracted 24 features: 3 colour features, 13 morphological features and 8 textural features. Created data set tested with all possible classification algorithms, out of which Ensemble classification algorithm gives 91.6% accuracy for Variety Identification and SVM gives 63% of accuracy for germination prediction. According to the germination percentage, a support vector machine (SVM) was utilised to categorise the seeds specimens into 3 groups: healthy, old, and deceased. The categorisation prediction accuracy has always been significant. We have created the data set for successful identification of varieties and germination prediction for the above-mentioned varieties; it is publicly available for usage.","PeriodicalId":7094,"journal":{"name":"Acta Agriculturae Scandinavica, Section B — Soil & Plant Science","volume":"32 1","pages":"939 - 955"},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80377086","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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