A Survey on Deep Learning Based Crop Yield Prediction
Agriculture is the most important sector and the backbone of a developing country’s economy. Accurate crop yield prediction models can provide decision-making tools for farmers to make better decisions. Crop yield prediction has challenged researchers due to dynamic, noisy, non-stationary, non-linea...
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| Format: | Article |
| Language: | English |
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Technoscience Publications
2023-06-01
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| Series: | Nature Environment and Pollution Technology |
| Subjects: | |
| Online Access: | https://neptjournal.com/upload-images/(4)B-3977.pdf |
| _version_ | 1797808259620405248 |
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| author | S. Archana and P. Senthil Kumar |
| author_facet | S. Archana and P. Senthil Kumar |
| author_sort | S. Archana and P. Senthil Kumar |
| collection | DOAJ |
| description | Agriculture is the most important sector and the backbone of a developing country’s economy. Accurate crop yield prediction models can provide decision-making tools for farmers to make better decisions. Crop yield prediction has challenged researchers due to dynamic, noisy, non-stationary, non-linear features and complex data. The factors that influence crop yield are changes in temperature and rainfall, plant disease, pests, fertilizer, and soil quality. The paper discusses the factors affecting crop yield, explores the features utilized, and analysis deep learning methodologies and performance metrics utilized in crop yield prediction. |
| first_indexed | 2024-03-13T06:35:07Z |
| format | Article |
| id | doaj.art-5308d273b86a4fa3b865da8c81b0307b |
| institution | Directory Open Access Journal |
| issn | 0972-6268 2395-3454 |
| language | English |
| last_indexed | 2024-03-13T06:35:07Z |
| publishDate | 2023-06-01 |
| publisher | Technoscience Publications |
| record_format | Article |
| series | Nature Environment and Pollution Technology |
| spelling | doaj.art-5308d273b86a4fa3b865da8c81b0307b2023-06-09T05:45:18ZengTechnoscience PublicationsNature Environment and Pollution Technology0972-62682395-34542023-06-0122257959210.46488/NEPT.2023.v22i02.004A Survey on Deep Learning Based Crop Yield PredictionS. Archana and P. Senthil KumarAgriculture is the most important sector and the backbone of a developing country’s economy. Accurate crop yield prediction models can provide decision-making tools for farmers to make better decisions. Crop yield prediction has challenged researchers due to dynamic, noisy, non-stationary, non-linear features and complex data. The factors that influence crop yield are changes in temperature and rainfall, plant disease, pests, fertilizer, and soil quality. The paper discusses the factors affecting crop yield, explores the features utilized, and analysis deep learning methodologies and performance metrics utilized in crop yield prediction.https://neptjournal.com/upload-images/(4)B-3977.pdfyield estimation, convolutional neural networks, recurrent neural networks, long short term memory network, multilayer perceptron |
| spellingShingle | S. Archana and P. Senthil Kumar A Survey on Deep Learning Based Crop Yield Prediction Nature Environment and Pollution Technology yield estimation, convolutional neural networks, recurrent neural networks, long short term memory network, multilayer perceptron |
| title | A Survey on Deep Learning Based Crop Yield Prediction |
| title_full | A Survey on Deep Learning Based Crop Yield Prediction |
| title_fullStr | A Survey on Deep Learning Based Crop Yield Prediction |
| title_full_unstemmed | A Survey on Deep Learning Based Crop Yield Prediction |
| title_short | A Survey on Deep Learning Based Crop Yield Prediction |
| title_sort | survey on deep learning based crop yield prediction |
| topic | yield estimation, convolutional neural networks, recurrent neural networks, long short term memory network, multilayer perceptron |
| url | https://neptjournal.com/upload-images/(4)B-3977.pdf |
| work_keys_str_mv | AT sarchanaandpsenthilkumar asurveyondeeplearningbasedcropyieldprediction AT sarchanaandpsenthilkumar surveyondeeplearningbasedcropyieldprediction |