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On April 29, 2024 at 12:28:59 PM UTC,
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| f | 1 | { | f | 1 | { |
| 2 | "acknowledgement": "The authors gratefully acknowledge the financial | 2 | "acknowledgement": "The authors gratefully acknowledge the financial | ||
| 3 | support for this research by the following organizations and agencies: | 3 | support for this research by the following organizations and agencies: | ||
| 4 | Kenya Education Network Trust (KENET) - Grant Number AGMT1170; | 4 | Kenya Education Network Trust (KENET) - Grant Number AGMT1170; | ||
| 5 | Foreign, Commonwealth & Development Office (FCDO) [IMC-Grant 21108]; | 5 | Foreign, Commonwealth & Development Office (FCDO) [IMC-Grant 21108]; | ||
| 6 | Australian Centre for International Agricultural Research (ACIAR) | 6 | Australian Centre for International Agricultural Research (ACIAR) | ||
| 7 | (ProteinAfrica \u2013 Grant No: LS/2020/154), the Rockefeller | 7 | (ProteinAfrica \u2013 Grant No: LS/2020/154), the Rockefeller | ||
| 8 | Foundation (WAVE-IN\u2014 Grant No: 2021 FOD 030); Bill & Melinda | 8 | Foundation (WAVE-IN\u2014 Grant No: 2021 FOD 030); Bill & Melinda | ||
| 9 | Gates Foundation (INV-032416); IKEA Foundation (G-2204-02144), Horizon | 9 | Gates Foundation (INV-032416); IKEA Foundation (G-2204-02144), Horizon | ||
| 10 | Europe (NESTLER - Project: 101060762 - HORIZON-CL6-2021- | 10 | Europe (NESTLER - Project: 101060762 - HORIZON-CL6-2021- | ||
| 11 | FARM2FORK-01), the Curt Bergfors Foundation Food Planet Prize Award; | 11 | FARM2FORK-01), the Curt Bergfors Foundation Food Planet Prize Award; | ||
| 12 | Norwegian Agency for Development Cooperation, the Section for | 12 | Norwegian Agency for Development Cooperation, the Section for | ||
| 13 | Research, Innovation and Higher Education grant number RAF\u20133058 | 13 | Research, Innovation and Higher Education grant number RAF\u20133058 | ||
| 14 | KEN\u201318/0005 (CAP\u2013Africa); the Swedish International | 14 | KEN\u201318/0005 (CAP\u2013Africa); the Swedish International | ||
| 15 | Development Cooperation Agency (SIDA); the Swiss Agency for | 15 | Development Cooperation Agency (SIDA); the Swiss Agency for | ||
| 16 | Development and Cooperation (SDC); the Australian Centre for | 16 | Development and Cooperation (SDC); the Australian Centre for | ||
| 17 | International Agricultural Research (ACIAR); the Norwegian Agency for | 17 | International Agricultural Research (ACIAR); the Norwegian Agency for | ||
| 18 | Development Cooperation (NORAD); the German Federal Ministry for | 18 | Development Cooperation (NORAD); the German Federal Ministry for | ||
| 19 | Economic Cooperation and Development (BMZ); the Federal Democratic | 19 | Economic Cooperation and Development (BMZ); the Federal Democratic | ||
| 20 | Republic of Ethiopia; and the Government of the Republic of Kenya. The | 20 | Republic of Ethiopia; and the Government of the Republic of Kenya. The | ||
| 21 | funders had no role in study design, data collection and analysis, | 21 | funders had no role in study design, data collection and analysis, | ||
| 22 | decision to publish, or preparation of the manuscript. ", | 22 | decision to publish, or preparation of the manuscript. ", | ||
| 23 | "administrative_areas": "Nairobi", | 23 | "administrative_areas": "Nairobi", | ||
| 24 | "author": null, | 24 | "author": null, | ||
| 25 | "author_email": null, | 25 | "author_email": null, | ||
| 26 | "citation_narrative": | 26 | "citation_narrative": | ||
| 27 | ps://www.frontiersin.org/articles/10.3389/frai.2024.1403593/abstract", | 27 | ps://www.frontiersin.org/articles/10.3389/frai.2024.1403593/abstract", | ||
| 28 | "collaborators": "[{\"collaborator\": \"Henry Kyalo\"}, | 28 | "collaborators": "[{\"collaborator\": \"Henry Kyalo\"}, | ||
| 29 | {\"collaborator\": \"Henri E. Z. Tonnang\"}, {\"collaborator\": | 29 | {\"collaborator\": \"Henri E. Z. Tonnang\"}, {\"collaborator\": | ||
| 30 | \"James Egonyu\"}, {\"collaborator\": \"John Olukuru\"}, | 30 | \"James Egonyu\"}, {\"collaborator\": \"John Olukuru\"}, | ||
| 31 | {\"collaborator\": \"Chrysantus M. Tanga\"}]", | 31 | {\"collaborator\": \"Chrysantus M. Tanga\"}]", | ||
| 32 | "contact_person": "Kennedy Senagi", | 32 | "contact_person": "Kennedy Senagi", | ||
| 33 | "contact_person_email": "ksenagi@icipe.org", | 33 | "contact_person_email": "ksenagi@icipe.org", | ||
| 34 | "country": "[{\"country\": \"KE\"}]", | 34 | "country": "[{\"country\": \"KE\"}]", | ||
| 35 | "creator_user_id": "f09ec764-fe3c-4069-850b-f968ff0c20bb", | 35 | "creator_user_id": "f09ec764-fe3c-4069-850b-f968ff0c20bb", | ||
| 36 | "date_uploaded": "2024-04-26", | 36 | "date_uploaded": "2024-04-26", | ||
| 37 | "donor": "Kenya Education Network Trust (KENET)", | 37 | "donor": "Kenya Education Network Trust (KENET)", | ||
| 38 | "end_date": "2024-04-26", | 38 | "end_date": "2024-04-26", | ||
| 39 | "groups": [], | 39 | "groups": [], | ||
| 40 | "id": "59311393-3b0b-4f79-92b3-62a9b30a89ff", | 40 | "id": "59311393-3b0b-4f79-92b3-62a9b30a89ff", | ||
| 41 | "isopen": false, | 41 | "isopen": false, | ||
| 42 | "license_id": "cc-nc", | 42 | "license_id": "cc-nc", | ||
| 43 | "license_title": "Creative Commons Non-Commercial (Any)", | 43 | "license_title": "Creative Commons Non-Commercial (Any)", | ||
| 44 | "license_url": "http://creativecommons.org/licenses/by-nc/2.0/", | 44 | "license_url": "http://creativecommons.org/licenses/by-nc/2.0/", | ||
| 45 | "maintainer": "Kennedy Senagi", | 45 | "maintainer": "Kennedy Senagi", | ||
| 46 | "maintainer_email": "ksenagi@icipe.org", | 46 | "maintainer_email": "ksenagi@icipe.org", | ||
| 47 | "metadata_created": "2024-04-29T09:38:54.556778", | 47 | "metadata_created": "2024-04-29T09:38:54.556778", | ||
| n | 48 | "metadata_modified": "2024-04-29T12:27:56.505290", | n | 48 | "metadata_modified": "2024-04-29T12:28:58.917300", |
| 49 | "name": | 49 | "name": | ||
| 50 | p-learning-algorithms-in-farming-edible-crickets-as-a-source-of-food", | 50 | p-learning-algorithms-in-farming-edible-crickets-as-a-source-of-food", | ||
| 51 | "notes": "Crickets (Gryllus bimaculatus) produce sounds as a natural | 51 | "notes": "Crickets (Gryllus bimaculatus) produce sounds as a natural | ||
| 52 | means to communicate and convey various behaviors and activities, | 52 | means to communicate and convey various behaviors and activities, | ||
| 53 | including mating, feeding, aggression, distress, and more. These | 53 | including mating, feeding, aggression, distress, and more. These | ||
| 54 | vocalizations are intricately linked to prevailing environmental | 54 | vocalizations are intricately linked to prevailing environmental | ||
| 55 | conditions such as temperature and humidity. By accurately monitoring, | 55 | conditions such as temperature and humidity. By accurately monitoring, | ||
| 56 | identifying, and appropriately addressing these behaviors and | 56 | identifying, and appropriately addressing these behaviors and | ||
| 57 | activities, the farming and production of crickets can be enhanced. | 57 | activities, the farming and production of crickets can be enhanced. | ||
| 58 | This research implemented a decision support system that leverages | 58 | This research implemented a decision support system that leverages | ||
| 59 | machine learning (ML) algorithms to decode and classify cricket songs, | 59 | machine learning (ML) algorithms to decode and classify cricket songs, | ||
| 60 | along with their associated key weather variables (temperature and | 60 | along with their associated key weather variables (temperature and | ||
| 61 | humidity). Videos capturing cricket behavior and weather variables | 61 | humidity). Videos capturing cricket behavior and weather variables | ||
| 62 | were recorded. From these videos, sound signals were extracted and | 62 | were recorded. From these videos, sound signals were extracted and | ||
| 63 | classified such as calling, aggression, and courtship. Numerical and | 63 | classified such as calling, aggression, and courtship. Numerical and | ||
| 64 | image features were extracted from the sound signals and combined with | 64 | image features were extracted from the sound signals and combined with | ||
| 65 | the weather variables. The extracted numerical features, i.e., | 65 | the weather variables. The extracted numerical features, i.e., | ||
| 66 | Mel-Frequency Cepstral Coefficients (MFCC), Linear Frequency Cepstral | 66 | Mel-Frequency Cepstral Coefficients (MFCC), Linear Frequency Cepstral | ||
| 67 | Coefficients, and chroma, were used to train shallow (support vector | 67 | Coefficients, and chroma, were used to train shallow (support vector | ||
| 68 | machine, k-nearest neighbors, and random forest (RF)) ML algorithms. | 68 | machine, k-nearest neighbors, and random forest (RF)) ML algorithms. | ||
| 69 | While image features, i.e., spectrograms, were used to train different | 69 | While image features, i.e., spectrograms, were used to train different | ||
| 70 | state-of-the-art deep ML models, i,e., convolutional neural network} | 70 | state-of-the-art deep ML models, i,e., convolutional neural network} | ||
| 71 | architectures (ResNet152V2, VGG16, and EfficientNetB4). In the deep ML | 71 | architectures (ResNet152V2, VGG16, and EfficientNetB4). In the deep ML | ||
| 72 | category, ResNet152V2 had the best accuracy of 99.42%. The RF | 72 | category, ResNet152V2 had the best accuracy of 99.42%. The RF | ||
| 73 | algorithm had the best accuracy of 95.63% in the shallow ML category | 73 | algorithm had the best accuracy of 95.63% in the shallow ML category | ||
| 74 | when trained with a combination of MFCC+chroma and after feature | 74 | when trained with a combination of MFCC+chroma and after feature | ||
| 75 | selection. In descending order of importance, the top 6 ranked | 75 | selection. In descending order of importance, the top 6 ranked | ||
| 76 | features in the RF algorithm were, namely humidity, temperature, C#, | 76 | features in the RF algorithm were, namely humidity, temperature, C#, | ||
| 77 | mfcc11, mfcc10, and D. From the selected features. With this | 77 | mfcc11, mfcc10, and D. From the selected features. With this | ||
| 78 | information, it is notable that insects require specific temperatures | 78 | information, it is notable that insects require specific temperatures | ||
| 79 | and humidity for growth and metabolic activities. Moreover, the songs | 79 | and humidity for growth and metabolic activities. Moreover, the songs | ||
| 80 | produced by certain cricket species naturally align to musical tones | 80 | produced by certain cricket species naturally align to musical tones | ||
| 81 | such as C# and D as ranked by the algorithm. Using this knowledge, a | 81 | such as C# and D as ranked by the algorithm. Using this knowledge, a | ||
| 82 | decision support system was built to guide farmers about the optimal | 82 | decision support system was built to guide farmers about the optimal | ||
| 83 | temperature and humidity ranges and interpret the songs (calling, | 83 | temperature and humidity ranges and interpret the songs (calling, | ||
| 84 | aggression, and courtship) in relation to weather variables. With this | 84 | aggression, and courtship) in relation to weather variables. With this | ||
| 85 | information, farmers can put in place suitable measures such as | 85 | information, farmers can put in place suitable measures such as | ||
| 86 | temperature regulation, humidity control, addressing aggressors, and | 86 | temperature regulation, humidity control, addressing aggressors, and | ||
| 87 | other relevant interventions to minimize or eliminate losses and | 87 | other relevant interventions to minimize or eliminate losses and | ||
| 88 | enhance cricket production.", | 88 | enhance cricket production.", | ||
| 89 | "num_resources": 11, | 89 | "num_resources": 11, | ||
| 90 | "num_tags": 6, | 90 | "num_tags": 6, | ||
| 91 | "organization": { | 91 | "organization": { | ||
| 92 | "approval_status": "approved", | 92 | "approval_status": "approved", | ||
| 93 | "created": "2022-05-17T13:53:24.098004", | 93 | "created": "2022-05-17T13:53:24.098004", | ||
| 94 | "description": "", | 94 | "description": "", | ||
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| 96 | "image_url": "2022-05-17-135324.083479bees.jpeg", | 96 | "image_url": "2022-05-17-135324.083479bees.jpeg", | ||
| 97 | "is_organization": true, | 97 | "is_organization": true, | ||
| 98 | "name": "environmental-health", | 98 | "name": "environmental-health", | ||
| 99 | "state": "active", | 99 | "state": "active", | ||
| 100 | "title": "Environmental Health", | 100 | "title": "Environmental Health", | ||
| 101 | "type": "organization" | 101 | "type": "organization" | ||
| 102 | }, | 102 | }, | ||
| 103 | "owner_org": "d16ea320-c49c-4a2e-b419-49c90c384c7d", | 103 | "owner_org": "d16ea320-c49c-4a2e-b419-49c90c384c7d", | ||
| 104 | "principal_investigator": "Kennedy Senagi", | 104 | "principal_investigator": "Kennedy Senagi", | ||
| 105 | "principal_investigator_email": "ksenagi@icipe.org", | 105 | "principal_investigator_email": "ksenagi@icipe.org", | ||
| 106 | "private": false, | 106 | "private": false, | ||
| 107 | "region": "Nairobi", | 107 | "region": "Nairobi", | ||
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