An India soyabean dataset for identification and classification of diseases using computer-vision algorithms

被引:2
作者
Kotwal, Jameer [1 ]
Kashyap, Ramgopal [1 ]
Pathan, Mohd. Shafi [2 ]
机构
[1] Amity Univ Chhattisgarh, Raipur 493225, India
[2] MIT ADT Univ, MITSOC, Pune 412201, India
来源
DATA IN BRIEF | 2024年 / 53卷
关键词
Soyabean leaf (Glycine max); Datasets; Image classification; Machine learning; Deep learning;
D O I
10.1016/j.dib.2024.110216
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Intelligent agriculture heavily relies on the science of agricultural disease image recognition. India is also responsible for large production of French beans, accounting for 37.25% of total production. In India from south region of Maharashtra state this crop is cultivated thrice in year. Soyabean plant is planted between the months of June through July, during the months of October and September during the rabi season, as well as in February. In the Maharashtrian regions of Pune, Satara, Ahmednagar, Solapur, and Nashik, among others, Soyabean plant is a common crop. In Maharashtra, Soyabean plant is grown over an area of around 31,050 hectares. This research presents a dataset of leaves from soyabean plants that are both insect-damaged and healthy. Images were taken over the course of fewer than two to three seasons on several farms. There are 3363 photos altogether in the seven folders that make up the dataset. Six categories comprise the dataset: I) Healthy plants II) Vein Necrosis III) Dry leaf IV) Septoria brown spot V) Root images VI) Bacterial leaf blight. This study's goal is to give academics and students accessibility to our dataset so they may use it for their studies and to build machine learning models. (c) 2024 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )
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页数:7
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