Changes
On May 23, 2022 at 8:23:57 AM UTC, kennedysenagi:
-
Renamed resource Raw data, meta-data and data dictionary to Raw data, metadata and data dictionary in African fruit fly program
f | 1 | { | f | 1 | { |
2 | "acknowledgement": "", | 2 | "acknowledgement": "", | ||
3 | "administrative_areas": "", | 3 | "administrative_areas": "", | ||
4 | "author": null, | 4 | "author": null, | ||
5 | "author_email": null, | 5 | "author_email": null, | ||
6 | "citation_narrative": "", | 6 | "citation_narrative": "", | ||
7 | "collaborators": "[{\"collaborator\": \"Fatiah Khamisi\"}]", | 7 | "collaborators": "[{\"collaborator\": \"Fatiah Khamisi\"}]", | ||
8 | "contact_person": "Daisy Salifu", | 8 | "contact_person": "Daisy Salifu", | ||
9 | "contact_person_email": "dsalifu@icipe.org", | 9 | "contact_person_email": "dsalifu@icipe.org", | ||
10 | "country": "[{\"country\": \"KE\"}]", | 10 | "country": "[{\"country\": \"KE\"}]", | ||
11 | "creator_user_id": "f09ec764-fe3c-4069-850b-f968ff0c20bb", | 11 | "creator_user_id": "f09ec764-fe3c-4069-850b-f968ff0c20bb", | ||
12 | "date_uploaded": "2021-10-17", | 12 | "date_uploaded": "2021-10-17", | ||
13 | "donor": "", | 13 | "donor": "", | ||
14 | "groups": [], | 14 | "groups": [], | ||
15 | "id": "4bd2ffd3-fc6c-4189-bce1-f54ca34ea011", | 15 | "id": "4bd2ffd3-fc6c-4189-bce1-f54ca34ea011", | ||
16 | "isopen": true, | 16 | "isopen": true, | ||
17 | "license_id": "cc-by", | 17 | "license_id": "cc-by", | ||
18 | "license_title": "Creative Commons Attribution", | 18 | "license_title": "Creative Commons Attribution", | ||
19 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | 19 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | ||
20 | "maintainer": "Kennedy Senagi", | 20 | "maintainer": "Kennedy Senagi", | ||
21 | "maintainer_email": "ksenagi@icipe.org", | 21 | "maintainer_email": "ksenagi@icipe.org", | ||
22 | "metadata_created": "2022-05-18T05:49:38.498118", | 22 | "metadata_created": "2022-05-18T05:49:38.498118", | ||
n | 23 | "metadata_modified": "2022-05-18T06:00:10.113818", | n | 23 | "metadata_modified": "2022-05-23T08:23:57.283939", |
24 | "name": "african-fruit-fly-program", | 24 | "name": "african-fruit-fly-program", | ||
25 | "notes": "Taxonomic identity of fruitfly pest using morphometrics", | 25 | "notes": "Taxonomic identity of fruitfly pest using morphometrics", | ||
26 | "num_resources": 4, | 26 | "num_resources": 4, | ||
27 | "num_tags": 0, | 27 | "num_tags": 0, | ||
28 | "organization": { | 28 | "organization": { | ||
29 | "approval_status": "approved", | 29 | "approval_status": "approved", | ||
30 | "created": "2022-05-17T13:51:43.824504", | 30 | "created": "2022-05-17T13:51:43.824504", | ||
31 | "description": "", | 31 | "description": "", | ||
32 | "id": "b3f6f7ff-df08-49a0-8959-dc1444685c2f", | 32 | "id": "b3f6f7ff-df08-49a0-8959-dc1444685c2f", | ||
33 | "image_url": "2022-05-17-135143.809085plant.jpeg", | 33 | "image_url": "2022-05-17-135143.809085plant.jpeg", | ||
34 | "is_organization": true, | 34 | "is_organization": true, | ||
35 | "name": "plant-health", | 35 | "name": "plant-health", | ||
36 | "state": "active", | 36 | "state": "active", | ||
37 | "title": "Plant Health", | 37 | "title": "Plant Health", | ||
38 | "type": "organization" | 38 | "type": "organization" | ||
39 | }, | 39 | }, | ||
40 | "owner_org": "b3f6f7ff-df08-49a0-8959-dc1444685c2f", | 40 | "owner_org": "b3f6f7ff-df08-49a0-8959-dc1444685c2f", | ||
41 | "principal_investigator": "Daniel Masiga", | 41 | "principal_investigator": "Daniel Masiga", | ||
42 | "principal_investigator_email": "dmasiga@icipe.org", | 42 | "principal_investigator_email": "dmasiga@icipe.org", | ||
43 | "private": false, | 43 | "private": false, | ||
44 | "region": "East Africa", | 44 | "region": "East Africa", | ||
45 | "relationships_as_object": [], | 45 | "relationships_as_object": [], | ||
46 | "relationships_as_subject": [], | 46 | "relationships_as_subject": [], | ||
47 | "resources": [ | 47 | "resources": [ | ||
48 | { | 48 | { | ||
49 | "cache_last_updated": null, | 49 | "cache_last_updated": null, | ||
50 | "cache_url": null, | 50 | "cache_url": null, | ||
51 | "created": "2022-05-18T05:51:33.159984", | 51 | "created": "2022-05-18T05:51:33.159984", | ||
52 | "date_last_updated": "2022-05-18", | 52 | "date_last_updated": "2022-05-18", | ||
53 | "date_uploaded_resource": "2021-10-17", | 53 | "date_uploaded_resource": "2021-10-17", | ||
54 | "description": "", | 54 | "description": "", | ||
55 | "format": "XLSX", | 55 | "format": "XLSX", | ||
56 | "hash": "", | 56 | "hash": "", | ||
57 | "id": "0613d1d8-d0a2-4d34-9b4d-29f698855766", | 57 | "id": "0613d1d8-d0a2-4d34-9b4d-29f698855766", | ||
58 | "last_modified": "2022-05-18T05:51:33.141075", | 58 | "last_modified": "2022-05-18T05:51:33.141075", | ||
n | 59 | "metadata_modified": "2022-05-18T06:00:10.124519", | n | 59 | "metadata_modified": "2022-05-23T08:23:57.289435", |
60 | "mimetype": | 60 | "mimetype": | ||
61 | "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet", | 61 | "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet", | ||
62 | "mimetype_inner": null, | 62 | "mimetype_inner": null, | ||
t | 63 | "name": "Raw data, meta-data and data dictionary ", | t | 63 | "name": "Raw data, metadata and data dictionary ", |
64 | "package_id": "4bd2ffd3-fc6c-4189-bce1-f54ca34ea011", | 64 | "package_id": "4bd2ffd3-fc6c-4189-bce1-f54ca34ea011", | ||
65 | "position": 0, | 65 | "position": 0, | ||
66 | "resource_type": null, | 66 | "resource_type": null, | ||
67 | "restricted": "{\"allowed_users\": \"\", \"level\": | 67 | "restricted": "{\"allowed_users\": \"\", \"level\": | ||
68 | \"public\"}", | 68 | \"public\"}", | ||
69 | "size": 734510, | 69 | "size": 734510, | ||
70 | "state": "active", | 70 | "state": "active", | ||
71 | "url": | 71 | "url": | ||
72 | -29f698855766/download/fruitfly-morphometrics_data-repository-1.xlsx", | 72 | -29f698855766/download/fruitfly-morphometrics_data-repository-1.xlsx", | ||
73 | "url_type": "upload" | 73 | "url_type": "upload" | ||
74 | }, | 74 | }, | ||
75 | { | 75 | { | ||
76 | "cache_last_updated": null, | 76 | "cache_last_updated": null, | ||
77 | "cache_url": null, | 77 | "cache_url": null, | ||
78 | "created": "2022-05-18T05:59:22.824877", | 78 | "created": "2022-05-18T05:59:22.824877", | ||
79 | "date_last_updated": "2022-05-18", | 79 | "date_last_updated": "2022-05-18", | ||
80 | "date_uploaded_resource": "2021-10-17", | 80 | "date_uploaded_resource": "2021-10-17", | ||
81 | "description": "", | 81 | "description": "", | ||
82 | "format": "PDF", | 82 | "format": "PDF", | ||
83 | "hash": "", | 83 | "hash": "", | ||
84 | "id": "7524a0ed-79fc-47cf-a478-fb0b45988fe1", | 84 | "id": "7524a0ed-79fc-47cf-a478-fb0b45988fe1", | ||
85 | "last_modified": "2022-05-18T05:59:22.800928", | 85 | "last_modified": "2022-05-18T05:59:22.800928", | ||
86 | "metadata_modified": "2022-05-18T05:59:22.819494", | 86 | "metadata_modified": "2022-05-18T05:59:22.819494", | ||
87 | "mimetype": "application/pdf", | 87 | "mimetype": "application/pdf", | ||
88 | "mimetype_inner": null, | 88 | "mimetype_inner": null, | ||
89 | "name": "Protocol", | 89 | "name": "Protocol", | ||
90 | "package_id": "4bd2ffd3-fc6c-4189-bce1-f54ca34ea011", | 90 | "package_id": "4bd2ffd3-fc6c-4189-bce1-f54ca34ea011", | ||
91 | "position": 1, | 91 | "position": 1, | ||
92 | "resource_type": null, | 92 | "resource_type": null, | ||
93 | "restricted": "{\"allowed_users\": \"\", \"level\": | 93 | "restricted": "{\"allowed_users\": \"\", \"level\": | ||
94 | \"public\"}", | 94 | \"public\"}", | ||
95 | "size": 456159, | 95 | "size": 456159, | ||
96 | "state": "active", | 96 | "state": "active", | ||
97 | "url": | 97 | "url": | ||
98 | /resource/7524a0ed-79fc-47cf-a478-fb0b45988fe1/download/protocol.pdf", | 98 | /resource/7524a0ed-79fc-47cf-a478-fb0b45988fe1/download/protocol.pdf", | ||
99 | "url_type": "upload" | 99 | "url_type": "upload" | ||
100 | }, | 100 | }, | ||
101 | { | 101 | { | ||
102 | "cache_last_updated": null, | 102 | "cache_last_updated": null, | ||
103 | "cache_url": null, | 103 | "cache_url": null, | ||
104 | "created": "2022-05-18T05:54:07.020692", | 104 | "created": "2022-05-18T05:54:07.020692", | ||
105 | "date_last_updated": "2022-05-18", | 105 | "date_last_updated": "2022-05-18", | ||
106 | "date_uploaded_resource": "2021-10-17", | 106 | "date_uploaded_resource": "2021-10-17", | ||
107 | "description": "", | 107 | "description": "", | ||
108 | "format": "HTML", | 108 | "format": "HTML", | ||
109 | "hash": "", | 109 | "hash": "", | ||
110 | "id": "e8e406c3-6816-4330-99b4-8ef68999eb76", | 110 | "id": "e8e406c3-6816-4330-99b4-8ef68999eb76", | ||
111 | "last_modified": null, | 111 | "last_modified": null, | ||
112 | "metadata_modified": "2022-05-18T05:54:07.015551", | 112 | "metadata_modified": "2022-05-18T05:54:07.015551", | ||
113 | "mimetype": null, | 113 | "mimetype": null, | ||
114 | "mimetype_inner": null, | 114 | "mimetype_inner": null, | ||
115 | "name": "[R codes] - Machine learning algorithms on insect | 115 | "name": "[R codes] - Machine learning algorithms on insect | ||
116 | morphometrics data", | 116 | morphometrics data", | ||
117 | "package_id": "4bd2ffd3-fc6c-4189-bce1-f54ca34ea011", | 117 | "package_id": "4bd2ffd3-fc6c-4189-bce1-f54ca34ea011", | ||
118 | "position": 2, | 118 | "position": 2, | ||
119 | "resource_type": null, | 119 | "resource_type": null, | ||
120 | "restricted": "{\"allowed_users\": \"\", \"level\": | 120 | "restricted": "{\"allowed_users\": \"\", \"level\": | ||
121 | \"public\"}", | 121 | \"public\"}", | ||
122 | "size": null, | 122 | "size": null, | ||
123 | "state": "active", | 123 | "state": "active", | ||
124 | "url": | 124 | "url": | ||
125 | pe-official/Machine-Learning-Algorithms-on-Insect-Morphometrics-Data", | 125 | pe-official/Machine-Learning-Algorithms-on-Insect-Morphometrics-Data", | ||
126 | "url_type": null | 126 | "url_type": null | ||
127 | }, | 127 | }, | ||
128 | { | 128 | { | ||
129 | "cache_last_updated": null, | 129 | "cache_last_updated": null, | ||
130 | "cache_url": null, | 130 | "cache_url": null, | ||
131 | "created": "2022-05-18T05:55:37.808750", | 131 | "created": "2022-05-18T05:55:37.808750", | ||
132 | "date_last_updated": "2022-05-18", | 132 | "date_last_updated": "2022-05-18", | ||
133 | "date_uploaded_resource": "2022-05-18", | 133 | "date_uploaded_resource": "2022-05-18", | ||
134 | "description": "Analysis of landmark-based morphometric | 134 | "description": "Analysis of landmark-based morphometric | ||
135 | measurements taken on body parts of insects have been a useful | 135 | measurements taken on body parts of insects have been a useful | ||
136 | taxonomic approach alongside DNA barcoding in insect identification. | 136 | taxonomic approach alongside DNA barcoding in insect identification. | ||
137 | Statistical analysis of morphometrics have largely been dominated by | 137 | Statistical analysis of morphometrics have largely been dominated by | ||
138 | traditional methods and approaches such as principal component | 138 | traditional methods and approaches such as principal component | ||
139 | analysis (PCA), canonical variate analysis (CVA) and discriminant | 139 | analysis (PCA), canonical variate analysis (CVA) and discriminant | ||
140 | analysis (DA). However, advancement in computing power creates a | 140 | analysis (DA). However, advancement in computing power creates a | ||
141 | paradigm shift to apply modern tools such as machine learning. Herein, | 141 | paradigm shift to apply modern tools such as machine learning. Herein, | ||
142 | we assess the predictive performance of four machine learning | 142 | we assess the predictive performance of four machine learning | ||
143 | classifiers; K-nearest neighbor (KNN), random forest (RF), support | 143 | classifiers; K-nearest neighbor (KNN), random forest (RF), support | ||
144 | vector machine (the linear, polynomial and radial kernel SVMs) and | 144 | vector machine (the linear, polynomial and radial kernel SVMs) and | ||
145 | artificial neural network (ANNs) on fruit fly morphometrics that were | 145 | artificial neural network (ANNs) on fruit fly morphometrics that were | ||
146 | previously analysed using PCA and CVA. KNN and RF performed poorly | 146 | previously analysed using PCA and CVA. KNN and RF performed poorly | ||
147 | with overall model accuracy lower than \u201cno-information rate\u201d | 147 | with overall model accuracy lower than \u201cno-information rate\u201d | ||
148 | (NIR) (p value\u2009>\u20090.1). The SVM models had a predictive | 148 | (NIR) (p value\u2009>\u20090.1). The SVM models had a predictive | ||
149 | accuracy of\u2009>\u200995%, significantly higher than NIR | 149 | accuracy of\u2009>\u200995%, significantly higher than NIR | ||
150 | (p\u2009<\u20090.001), Kappa\u2009>\u20090.78 and area under curve | 150 | (p\u2009<\u20090.001), Kappa\u2009>\u20090.78 and area under curve | ||
151 | (AUC) of the receiver operating characteristics was\u2009>\u20090.91; | 151 | (AUC) of the receiver operating characteristics was\u2009>\u20090.91; | ||
152 | while ANN model had a predictive accuracy of 96%, significantly higher | 152 | while ANN model had a predictive accuracy of 96%, significantly higher | ||
153 | than NIR, Kappa of 0.83 and AUC was 0.98. Wing veins 2, 3, 8, 10, 14 | 153 | than NIR, Kappa of 0.83 and AUC was 0.98. Wing veins 2, 3, 8, 10, 14 | ||
154 | and tibia length were of higher importance than other variables based | 154 | and tibia length were of higher importance than other variables based | ||
155 | on both SVM and ANN models. We conclude that SVM and ANN models could | 155 | on both SVM and ANN models. We conclude that SVM and ANN models could | ||
156 | be used to discriminate fruit fly species based on wing vein and tibia | 156 | be used to discriminate fruit fly species based on wing vein and tibia | ||
157 | length measurements or any other morphologically similar pest taxa. | 157 | length measurements or any other morphologically similar pest taxa. | ||
158 | These algorithms could be used as candidates for developing an | 158 | These algorithms could be used as candidates for developing an | ||
159 | integrated and smart application software for insect discrimination | 159 | integrated and smart application software for insect discrimination | ||
160 | and identification. Variable importance analysis results in this study | 160 | and identification. Variable importance analysis results in this study | ||
161 | would be useful for future studies for deciding what must be | 161 | would be useful for future studies for deciding what must be | ||
162 | measured.", | 162 | measured.", | ||
163 | "format": "HTML", | 163 | "format": "HTML", | ||
164 | "hash": "", | 164 | "hash": "", | ||
165 | "id": "cb7e4445-4440-4098-8b72-441a2597bb47", | 165 | "id": "cb7e4445-4440-4098-8b72-441a2597bb47", | ||
166 | "last_modified": null, | 166 | "last_modified": null, | ||
167 | "metadata_modified": "2022-05-18T05:55:37.803541", | 167 | "metadata_modified": "2022-05-18T05:55:37.803541", | ||
168 | "mimetype": null, | 168 | "mimetype": null, | ||
169 | "mimetype_inner": null, | 169 | "mimetype_inner": null, | ||
170 | "name": "[Article] - Leveraging machine learning tools and | 170 | "name": "[Article] - Leveraging machine learning tools and | ||
171 | algorithms for analysis of fruit fly morphometrics", | 171 | algorithms for analysis of fruit fly morphometrics", | ||
172 | "package_id": "4bd2ffd3-fc6c-4189-bce1-f54ca34ea011", | 172 | "package_id": "4bd2ffd3-fc6c-4189-bce1-f54ca34ea011", | ||
173 | "position": 3, | 173 | "position": 3, | ||
174 | "resource_type": null, | 174 | "resource_type": null, | ||
175 | "restricted": "{\"allowed_users\": \"\", \"level\": | 175 | "restricted": "{\"allowed_users\": \"\", \"level\": | ||
176 | \"public\"}", | 176 | \"public\"}", | ||
177 | "size": null, | 177 | "size": null, | ||
178 | "state": "active", | 178 | "state": "active", | ||
179 | "url": "", | 179 | "url": "", | ||
180 | "url_type": null | 180 | "url_type": null | ||
181 | } | 181 | } | ||
182 | ], | 182 | ], | ||
183 | "state": "active", | 183 | "state": "active", | ||
184 | "tags": [], | 184 | "tags": [], | ||
185 | "third_party": "no", | 185 | "third_party": "no", | ||
186 | "title": "African fruit fly program", | 186 | "title": "African fruit fly program", | ||
187 | "type": "dataset", | 187 | "type": "dataset", | ||
188 | "url": null, | 188 | "url": null, | ||
189 | "version": null | 189 | "version": null | ||
190 | } | 190 | } |