Data · dataset · 2023
PaddyNet: An Organized Dataset of Paddy Leaves for a Smart Fertilizer Recommendation System
Listed in Teesside University Research Data Repository
PaddyNet - the dataset has been developed to help farmers in and fertilizer recommendation.
Description
The entire data set is collected from the paddy fields in the Aman season by our own developed application with the tremendous help of Bangladesh Agricultural Research Institute (BARI), Jashore, Bangladesh and the office of the Upazila Agriculture officer near Jashore. We have used our application in Nokia 3 (8MP Camera) and Samsung S8 (12MP Camera) devices for collecting data.
The dataset has been carefully labeled our total data set corresponding to the LCC level with the help of domain experts. Data validation has been carried out by the two principal scientific officers at Bangladesh Agricultural Research Institute (BARI) Jashore. The color of the paddy leaf depends on the maturity as well as Nitrogen concentration.
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However, Nitrogen concentration can be determined by analyzing leave colors. Therefore, having a dataset of paddy leaf images is helpful for analyzing leaf colors. to determine nitrogen concentration or nitrogen fertilizer recommendation At first, a total of 560 top most paddy leaf images were taken. The resolution of the images were 500*500 pixels and we used our developed mobile application where each of 2 to 5 LCC levels has 158, 162, 124 and 116 number of images respectively.
Moreover, we have augmented initially our 560 paddy leaf images to 6000 where each LCC level has 1500 images after augmentation and saved in the jpg file format.
Links
Where it is published
- DOI doi.org/10.17632/ksz57tk5vc.2 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Computer Science & AI · Computer vision · Earth & Environmental Science · Image processing · Life Sciences · Pattern recognition
- Inferred from text
- Image 65%
Provenance · 1 source records, 12 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/ksz57tk5vc.2 | 14 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:field:460304 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Computer Vision'] |
| concepts[field].anzsrc:field:460306 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Image Processing'] |
| concepts[field].anzsrc:field:460308 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Pattern Recognition'] |
| concepts[field].local:field:computer-science-ai | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[modality].local:modality:image | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (65%) |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |