Identification of Potato Plant Leaf Disease Using Different Artificial Intelligence (AI) Techniques: A Review
Keywords:
Computer Vision (CV), Artificial Intelligence (AI), Machine Learning (ML), Potato Plant Disease, Deep learning (DL), Neural NetworkAbstract
One of the nation's most vital industries is agriculture. Employment possibilities are abundant in emerging nations like India. The livelihoods of nearly 70% of the global population depend on agriculture. In this study, we have evaluatednumerous articles that have been released on potato plant leaf disease (PLD)diagnosis and classification utilising machine learning (ML)or Deep Learning (DL)methods. There are several causes of leaf diseases in plants, including bacteria, viruses, fungus, and more. Whether you are a farmer or a scientist, knowing how to spot sick leaves can be a daunting challenge.Farmers spraying their crops with pesticides pose a risk to human health and a financial burden on society. Specialists employ Potato Plant Disease Detection (PDD)methods to help in the fight against and early identification of the disease. This discovery will be a valuable tool for scientists trying to determine whether illnesses affect potato plant leaves by using picture segmentation, ML, DL, and neural network (NN)methods. This document presents an extensive literature review on the diverse diseases affecting potato plant leaves, categorized based on several prominent factors.
References
FaithpraiseFina, PhilipBirch, RupertYoung, Obu J, BasseyFaithpraise, ChrisChatwin. Automatic Plant Pest Detection and Recognition Using K-Means Clustering Algorithm and Correspondence Filters. Int J Adv BiotechnolRes. 2013; 4(2): 1052–1062.
LiL, Zhang S, Wang B.Plant Disease Detection and Classification by Deep Learning - A Review. IEEE Access. 2021; 9: 56683–56698. doi: 10.1109/ACCESS.2021.3069646.
Jung M,et al.Construction of deep learning-based disease detection model in plants. Sci Rep. 2023; 13(1): 7331. doi: 10.1038/s41598-023-34549-2.
SinghUP, ChouhanSS, Jain S, Jain S.Multilayer Convolution Neural Network for the Classification of Mango Leaves Infected by Anthracnose Disease. IEEE Access. 2019; 7: 43721–43729. doi: 10.1109/ACCESS.2019.2907383.
Sudi PS, et al.A CNN Model for Disease Detection in Potato Leaves. J Algebraic Statistics. 2022; 13(2): 1929–1935.
FerentinosKP.Deep learning models for plant disease detection and diagnosis. Comput Electron Agric. 2018; 145: 311–318. doi: 10.1016/j.compag.2018.01.009.
Aamir M,et al.An Adoptive Threshold-Based Multi-Level Deep Convolutional Neural Network for Glaucoma Eye Disease Detection and Classification. Diagnostics. 2020;10(8): 602. doi: 10.3390/diagnostics10080602.
Chen SW,et al.Counting Apples and Oranges with Deep Learning: A Data-Driven Approach. IEEE Robot Autom Lett. 2017; 2(2): 781–788. doi: 10.1109/LRA.2017.2651944.
DiasPA, Tabb A, Medeiros H.Multispecies Fruit Flower Detection Using a Refined Semantic Segmentation Network. IEEE Robot Autom Lett. 2018; 3(4): 3003–3010. doi: 10.1109/LRA.2018.2849498.
UbbensJ, Cieslak M, Prusinkiewicz P, Stavness I.The use of plant models in deep learning: An application to leaf counting in rosette plants. Plant Methods. 2018; 14(1): 6. doi: 10.1186/s13007-018-0273-z.
GolhaniK, BalasundramSK, Vadamalai G, Pradhan B.A review of neural networks in plant disease detection using hyperspectral data. Inf Process Agric. 2018; 5(3): 354–371. doi: 10.1016/j.inpa.2018.05.002.
RashidJ, Khan I, Ali G, AlmotiriSH, AlghamdiMA, Masood K.Multi-level deep learning model for potato leaf disease recognition. Electron. 2021;10(17): 2064. doi: 10.3390/electronics10172064.
Singh A,Kaur H.Potato plant leaves disease detection and classification using machine learning methodologies. In IOP Conf Ser: Mater Sci Eng. 2021;1022: 012121. doi: 10.1088/1757-899X/1022/1/012121.
AndrewJ, Eunice J, PopescuDE, ChowdaryMK, Hemanth J.Deep Learning-Based Leaf Disease Detection in Crops Using Images for Agricultural Applications. Agronomy. 2022;12(10): 2395. doi: 10.3390/agronomy12102395.
Gaikwad VP,Musande V.Potato Plant leaf disease detection using CNN Model. Eur Chem Bull. 2023;12(1): 516–527.
KaurG, Kaur S, Kaur A.Plant disease detection: A review of current trends. Int J Eng Technol. 2018;7(3.34):874–81.
GardieB, Asemie S, Azezew K, Solomon Z.Potato Plant Leaf Diseases Identification Using Transfer Learning. Indian J Sci Technol. 2022; 15(4): 158–165. doi: 10.17485/ijst/v15i4.1235.
Singh G,YogiKK.Performance evaluation of plant leaf disease detection using deep learning models. Arch Phytopathol Plant Prot. 2023; 56(3): 209–233. doi: 10.1080/03235408.2023.2183792.
Arshad MS, RehmanUA, FrazMM.Plant Disease Identification Using Transfer Learning. In 2021 International Conference on Digital Futures and Transformative Technologies, ICoDT2 2021. 2021; 1–5. doi: 10.1109/ICoDT252288.2021.9441512.
BangalA, Pagar D, Patil H, Pande N.Potato Leaf Disease Detection and Classification Using CNN. Int J Res Publ Rev. 2022;3(5): 1510–1515. [Online]. Available: www.ijrpr.com
Deep KumarNK.A Review Paper on Diagnostics of Potato Viruses. Int J Curr Res. 2012; 4(12): 430–437.
KhanW.Image Segmentation Techniques: A Survey. J Image Graph. 2014; 1(4): 166–170. doi: 10.12720/joig.1.4.166-170.
Lomte SS,JanwaleAP.Plant Leaves Image Segmentation Techniques: A Review. Artic Int J Comput Sci Eng. 2017; 5(5): 147–150.
SemwalA, Chamoli A, Semwal A.A survey : On Image Denoising And Its Various Techniques. Int Res J Eng Technol. 2017;4(7): 1512–1515.
Ngugi LC, Abelwahab M, Abo-Zahhad M.Recent advances in image processing techniques for automated leaf pest and disease recognition – A review. Inf Process Agric. 2021; 8(1): 27–51. doi: 10.1016/j.inpa.2020.04.004.
SarkerIH.Machine Learning: Algorithms, Real-World Applications and Research Directions. SN Comput Sci. 2021; 2(3): 160. doi: 10.1007/s42979-021-00592-x.
ShekharS, Singh A, GuptaAK.A Deep Neural Network (DNN) Approach for Recommendation Systems. In Lecture Notes in Networks and Systems. Singapore:Springer; 2022; 385–396. doi: 10.1007/978-981-16-9756-2_37.
Sri KrishnaA, Sunag M, RaniNS, PushpaBR.On-spot Citrus Canker Disease Detection using YOLOv7. In Proceedings of the 2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023. 2023; 944–949. doi: 10.1109/ICAAIC56838.2023.10141105.
DeepaAR, ChaurasiaMA, VamsiSBN, KumarBM, ReddyVS, Anand KT.Plant Diseases and Pests Detection Using Machine Learning. In 2023 3rd Asian Conference on Innovation in Technology (ASIANCON). 2023; 1–4. doi: 10.1109/ASIANCON58793.2023.10270264.
Singh G,Chabra D.Plant Disease Detection using Convolution Neural Network Approach. In 6th International Conference on Inventive Computation Technologies, ICICT 2023 - Proceedings. 2023; 352–355. doi: 10.1109/ICICT57646.2023.10134217.
Sahu SL,Chintala Bhargavi R.Prediction of Diseases in Potato Plant using Pre-trained and Traditional Machine Learning Models. In 2023 4th International Conference for Emerging Technology, INCET 2023. 2023; 1–8. doi: 10.1109/INCET57972.2023.10170149.
MoawadN, Zaki H, Abed El Moniem Essa T, Said M.Detection of Potato Tuber Diseases Using Machine Learning Models. In 2023 International Conference on Artificial Intelligence Science and Applications in Industry and Society (CAISAIS). 2023; 1–7. doi: 10.1109/CAISAIS59399.2023.10269994.
BajpaiA, Tyagi M, Khare M, Singh A.A Robust and Accurate Potato Leaf Disease Detection System Using Modified AlexNet Model. 2023; 264–269. doi: 10.1109/iccce58854.2023.10246064.
SaeedZ, KhanMU, Raza A, Sajjad N, Naz S, Salal A.Identification of Leaf Diseases in Potato Crop Using Deep Convolutional Neural Networks (DCNNs). In ICET 2021, 16th International Conference on Emerging Technologies 2021, Proceedings. 2021; 1–6. doi: 10.1109/ICET54505.2021.9689807.
Moupojou E,et al.FieldPlant: A Dataset of Field Plant Images for Plant Disease Detection and Classification With Deep Learning. IEEE Access. 2023; 11: 35398–35410. doi: 10.1109/ACCESS.2023.3263042.
RajaPV, Sangeetha K, NinisaBA, Samiksha M, SanjuthaSS.Convolutional Neural Networks based Classification and Detection of Plant Disease. In Proceedings 6th International Conference on Computing Methodologies and Communication, ICCMC 2022. 2022; 1484–1488. doi: 10.1109/ICCMC53470.2022.9753846.
GoyalB, Kumar Pandey A, Kumar R, Gupta M.Disease Detection in Potato Leaves Using an Efficient Deep Learning Model. In 2023 International Conference on Data Science and Network Security (ICDSNS). 2023; 1–5. doi: 10.1109/ICDSNS58469.2023.10245369.
LakshmanaraoA, BabuMR, KiranTSR.Plant Disease Prediction and classification using Deep Learning ConvNets. In Proceedings, 2021 1st IEEE International Conference on Artificial Intelligence and Machine Vision, AIMV 2021. 2021; 1–6. doi: 10.1109/AIMV53313.2021.9670918.
DuraiS, Sujithra T, Mohamed Iqbal M.Image Classification for Potato Plant Leaf Disease Detection using Deep Learning. In International Conference on Sustainable Computing and Smart Systems, ICSCSS 2023 Proceedings. 2023; 154–158. doi: 10.1109/ICSCSS57650.2023.10169446.
TarikMI, Akter S, Al Mamun A, Sattar A.Potato disease detection using machine learning. In Proceedings of the 3rd International Conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2021. 2021; 800–803. doi: 10.1109/ICICV50876.2021.9388606.
IslamM, Dinh A, Wahid K, Bhowmik P.Detection of potato diseases using image segmentation and multiclass support vector machine. In Canadian Conference on Electrical and Computer Engineering. 2017; 1–4. doi: 10.1109/CCECE.2017.7946594.
AsifMKR, RahmanMA, HenaMH.CNN based disease detection approach on potato leaves. In Proceedings of the 3rd International Conference on Intelligent Sustainable Systems, ICISS 2020. 2020; 428–432. doi: 10.1109/ICISS49785.2020.9316021.
