Application of Artificial Neural Network in Agriculture
With the need for farming to become more efficient and environmentally sustainable to meet the demands of a growing global population, the application of artificial neural networks (ANNs) to inform and enhance agricultural practice and production is gathering momentum and interest. This Reprint titl...
में बचाया:
| स्वरूप: | Online |
|---|---|
| भाषा: | अंग्रेज़ी |
| प्रकाशित: |
MDPI - Multidisciplinary Digital Publishing Institute
2025
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| विषय: | |
| ऑनलाइन पहुंच: | ONIX_20250812T095121_9783725831227_43 |
| टैग: |
कोई टैग नहीं, इस रिकॉर्ड को टैग करने वाले पहले व्यक्ति बनें!
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| _version_ | 1869526753656963072 |
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| collection | Directory of Open Access Books |
| description | With the need for farming to become more efficient and environmentally sustainable to meet the demands of a growing global population, the application of artificial neural networks (ANNs) to inform and enhance agricultural practice and production is gathering momentum and interest. This Reprint titled "Application of Artificial Neural Network in Agriculture" showcases fourteen high-quality research articles highlighting the use of ANNs and related technologies for pest detection, plant disease detection, nutritional monitoring and prediction, the classification of the phenology of beans, and the optimisation of egg production. We also present how ANNs may be used for predicting the power requirements of agricultural machinery and for dynamic behaviour forecasting of an indirect solar dryer. The multidisciplinary nature of the articles presented will likely strongly appeal to researchers and scientists working in the areas of agricultural technology, communications engineering, computer science, data analytics, electronic engineering, information technology, image processing, and mathematical modelling. |
| format | Online |
| id | doab-20.500.12854ir-165094 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1650942025-08-12T08:01:04Z Application of Artificial Neural Network in Agriculture Sheriff, Ray E. Kwong, Chiew Foong animal nutrition egg laying feed costs mathematical model multivariate analysis poultry pest detection GoogLeNet Convolutional Neural Network mobile application convolutional neural network Fusarium wilt transfer learning ResNet-50 banana crop solar dryer thermal analysis electronic instrumentation artificial neural networks feedforward propagation algorithm artificial neural network particle-swarm optimization specific draft specific torque equivalent PTO power rice leaf diseases blast leaf leaf folder brown spot YOLOv8 plant disease tomato machine learning deep learning bean phenology food security San Andreas fertilization model greenhouses Rhodena lettuce diseased macronutrient point clouds rice blast Magnaporthe oryzae weather parameters INGARCHX SVRX ANNX soil analysis reflectance spectra YOLO models image analysis precision agriculture pest identification tiny object recognition multi-stage detection approach edge-based processing feature integration thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology With the need for farming to become more efficient and environmentally sustainable to meet the demands of a growing global population, the application of artificial neural networks (ANNs) to inform and enhance agricultural practice and production is gathering momentum and interest. This Reprint titled "Application of Artificial Neural Network in Agriculture" showcases fourteen high-quality research articles highlighting the use of ANNs and related technologies for pest detection, plant disease detection, nutritional monitoring and prediction, the classification of the phenology of beans, and the optimisation of egg production. We also present how ANNs may be used for predicting the power requirements of agricultural machinery and for dynamic behaviour forecasting of an indirect solar dryer. The multidisciplinary nature of the articles presented will likely strongly appeal to researchers and scientists working in the areas of agricultural technology, communications engineering, computer science, data analytics, electronic engineering, information technology, image processing, and mathematical modelling. 2025-08-12T08:01:02Z 2025-08-12T08:01:02Z 2025 book ONIX_20250812T095121_9783725831227_43 9783725831227 9783725831210 https://directory.doabooks.org/handle/20.500.12854/165094 eng image/jpeg Attribution 4.0 International https://mdpi.com/books https://mdpi.com/books/pdfview/book/10537 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-3121-0 10.3390/books978-3-7258-3121-0 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725831227 9783725831210 242 open access |
| spellingShingle | animal nutrition egg laying feed costs mathematical model multivariate analysis poultry pest detection GoogLeNet Convolutional Neural Network mobile application convolutional neural network Fusarium wilt transfer learning ResNet-50 banana crop solar dryer thermal analysis electronic instrumentation artificial neural networks feedforward propagation algorithm artificial neural network particle-swarm optimization specific draft specific torque equivalent PTO power rice leaf diseases blast leaf leaf folder brown spot YOLOv8 plant disease tomato machine learning deep learning bean phenology food security San Andreas fertilization model greenhouses Rhodena lettuce diseased macronutrient point clouds rice blast Magnaporthe oryzae weather parameters INGARCHX SVRX ANNX soil analysis reflectance spectra YOLO models image analysis precision agriculture pest identification tiny object recognition multi-stage detection approach edge-based processing feature integration thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Application of Artificial Neural Network in Agriculture |
| title | Application of Artificial Neural Network in Agriculture |
| title_full | Application of Artificial Neural Network in Agriculture |
| title_fullStr | Application of Artificial Neural Network in Agriculture |
| title_full_unstemmed | Application of Artificial Neural Network in Agriculture |
| title_short | Application of Artificial Neural Network in Agriculture |
| title_sort | application of artificial neural network in agriculture |
| topic | animal nutrition egg laying feed costs mathematical model multivariate analysis poultry pest detection GoogLeNet Convolutional Neural Network mobile application convolutional neural network Fusarium wilt transfer learning ResNet-50 banana crop solar dryer thermal analysis electronic instrumentation artificial neural networks feedforward propagation algorithm artificial neural network particle-swarm optimization specific draft specific torque equivalent PTO power rice leaf diseases blast leaf leaf folder brown spot YOLOv8 plant disease tomato machine learning deep learning bean phenology food security San Andreas fertilization model greenhouses Rhodena lettuce diseased macronutrient point clouds rice blast Magnaporthe oryzae weather parameters INGARCHX SVRX ANNX soil analysis reflectance spectra YOLO models image analysis precision agriculture pest identification tiny object recognition multi-stage detection approach edge-based processing feature integration thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| topic_facet | animal nutrition egg laying feed costs mathematical model multivariate analysis poultry pest detection GoogLeNet Convolutional Neural Network mobile application convolutional neural network Fusarium wilt transfer learning ResNet-50 banana crop solar dryer thermal analysis electronic instrumentation artificial neural networks feedforward propagation algorithm artificial neural network particle-swarm optimization specific draft specific torque equivalent PTO power rice leaf diseases blast leaf leaf folder brown spot YOLOv8 plant disease tomato machine learning deep learning bean phenology food security San Andreas fertilization model greenhouses Rhodena lettuce diseased macronutrient point clouds rice blast Magnaporthe oryzae weather parameters INGARCHX SVRX ANNX soil analysis reflectance spectra YOLO models image analysis precision agriculture pest identification tiny object recognition multi-stage detection approach edge-based processing feature integration thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| url | ONIX_20250812T095121_9783725831227_43 |