استفاده از هوش مصنوعی برای افزایش اثربخشی اصلاح نباتات برای توسعه محصولات غذایی هوشمند مقاوم در برابر آب و هوا

Altman A, Fan L, Foyer C, et al. (2021) Past and future milestones of plant breeding. Trends Plant Sci 26(6), 530-538.

Angin P, Anisi MH, Göksel F, et al. (2020) Agrilora: a digital twin framework for smart agriculture. J Wirel Mob Netw Ubiquitous Comput Dependable Appl 11(4), 77-96.

Camgözlü Y, Kutlu Y (2023) Leaf Image Classification Based on Pre-trained Convolutional Neural Network Models. Natural and Engineering Sciences 8(3), 214-232.

Cortés AJ, López-Hernández F, Blair MW (2022) Genome–environment associations, an innovative tool for studying heritable evolutionary adaptation in orphan crops and wild relatives. Front Genet 13, e910386.

Dossa K, Diouf D, Wang L, et al. (2017) The emerging oilseed crop Sesamum indicum enters the "Omics" era. Front Plant Sci 8, e1154.

El Bilali H, Allahyari MS (2018) Transition towards sustainability in agriculture and food systems: Role of information and communication technologies. Inf Process Agric 5(4), 456-464.

Esposito S, Carputo D, Cardi T, Tripodi P (2019) Applications and trends of machine learning in genomics and phenomics for next-generation breeding. Plants 9(1), e34.

Farooq MS, Uzair M, Raza A, et al. (2022) Uncovering the research gaps to alleviate the negative impacts of climate change on food security: a review. Front Plant Sci 13, e927535.

Ghotbaldini H, Mohammadabadi MR, Nezamabadi-pour H, et al. (2019) Predicting breeding value of body weight at 6-month age using Artificial Neural Networks in Kermani sheep breed. Acta Scientiarum Anim Sci 41, e45282.

Godwin ID, Rutkoski J, Varshney RK, Hickey LT (2019) Technological perspectives for plant breeding. Theor Appl Genet 132(3), 555-557.

Harfouche AL, Jacobson DA, Kainer D, et al. (2019) Accelerating climate resilient plant breeding by applying next-generation artificial intelligence. Trends Biotechnol 37(11), 1217-1235.

Kwon MS, Lee, BT, Lee SY, Kim HU (2020) Modeling regulatory networks using machine learning for systems metabolic engineering. Curr Opin Plant Biol 65, 163-170.

Mohammadabadi M, Kheyrodin H, Afanasenko V, et al. (2024) The role of artificial intelligence in genomics. Agric Biotechnol J 16 (2), 195-279.

Mumtaj Begum H (2022) Scientometric analysis of the research paper output on artificial intelligence: A study. Indian J Inform Sources Serv 12(1), 52–58.

Muthamilarasan M, Singh NK, Prasad M (2019) Multi-omics approaches for strategic improvement of stress tolerance in underutilized crop species: a climate change perspective. Adv Genet 103, 1-38.

Niazian M, Niedbała G (2020) Machine learning for plant breeding and biotechnology. Agriculture 10(10), e436.

Oliveira AL (2019). Biotechnology, big data and artificial intelligence. Biotechnology journal, 14(8), 1800613.

Parmley KA, Higgins RH, Ganapathysubramanian B, Sarkar S, et al. (2019) Machine learning approach for prescriptive plant breeding. Sci Rep 9(1), 17132. https://doi.org/10.1038/s41598-019-53451-4.

Peng H, Wang K, Chen Z, Cao Y, et al. (2020) MBKbase for rice: an integrated omics knowledgebase for molecular breeding in rice.  Nucleic Acids Res 48(D1), D1085-D1092.

Priya R, Ramesh D (2020) ML based sustainable precision agriculture: A future generation perspective. Sustain Comput Informatics Syst 28, e100439.

Pour Hamidi S, Mohammadabadi MR, Asadi Foozi M, Nezamabadi-pour H (2017) Prediction of breeding values for the milk production trait in Iranian Holstein cows applying artificial neural networks. J Livestock Sci Technol 5 (2), 53-61.

Radhika A, Masood MS (2022) Crop Yield Prediction by Integrating Et-DP Dimensionality Reduction and ABP-XGBOOST technique. J Internet Serv Inf Secur 12(4), 177-196.

Raza A, Tabassum J, Kudapa H, Varshney RK (2021) Can omics deliver temperature resilient ready-to-grow crops?. Crit Rev Biotechnol 41(8), 1209-1232.

Razzaq A, Kaur P, Akhter N, et al. (2021) Next-generation breeding strategies for climate-ready crops. Front Plant Sci 12, e620420.

Razzaq A, Sadia B, Raza A, et al. (2019) Metabolomics: A way forward for crop improvement. Metabolites 9(12), e303.

Reinoso-Peláez EL, Gianola D, González-Recio O (2022) Genome-enabled prediction methods based on machine learning. Methods Mol Biol 2467, 189-218.

Resende RT, Piepho HP, Rosa GJ, Silva-Junior OB, et al. (2021) Enviromics in breeding: applications and perspectives on envirotypic-assisted selection. Theor Appl Genet 134,          95-112.

Schmidt J, Blessing F, Fimpler L, Wenzel F (2020) Nanopore sequencing in a clinical routine laboratory: challenges and opportunities. Clin Lab 66(6), e191114.

Shen Y, Zhou G, Liang C, Tian Z (2022) Omics-based interdisciplinarity is accelerating plant breeding. Curr Opin Plant Biol 66, e102167.

Stergiou C, Psannis KE (2017) Recent advances delivered by mobile cloud computing and internet of things for big data applications: a survey. Int J Netw Manag 27(3), e1930.

Surendar A, Saravanakumar V, Sindhu S, Arvinth N (2024) A Bibliometric study of publication- citations in a range of journal articles. Indian J Inform Source Serv 14(2), 97-103.

Syed A, Raza T, Bhatti TT, Eash NS (2022) Climate Impacts on the agricultural sector of Pakistan: Risks and solutions. Environ Chall 6, e100433.

Teshome DT, Zharare GE, Naidoo S (2020) The threat of the combined effect of biotic and abiotic stress factors in forestry under a changing climate. Front Plant Sci 11, e601009.

Tong H, Nikoloski Z (2021) Machine learning approaches for crop improvement: Leveraging phenotypic and genotypic big data. J Plant Physiol 257, e153354.

Uchida K, Sawada Y, Ochiai K, et al. (2020) Identification of a unique type of isoflavone O-methyltransferase, GmIOMT1, based on multi-omics analysis of soybean under biotic stress. Plant Cell Physiol  61(11), 1974-1985.

Van Dijk ADJ, Kootstra G, Kruijer W, De Ridder D (2021) Machine learning in plant science and plant breeding. Iscience 24(1), e101890.

Veerasamy K, Fredrik ET (2023) Intelligent Farming based on Uncertainty Expert System with Butterfly Optimization Algorithm for Crop Recommendation. J Internet Serv Inf Secur 13(3), 158-169.

Wang H, Cimen E, Singh N, Buckler E (2020) Deep learning for plant genomics and crop improvement. Curr Opin Plant Biol 54, 34-41.

Xu Y, Zhang X, Li H, Zheng H, et al. (2022) Smart breeding driven by big data, artificial intelligence, and integrated genomic-enviromic prediction. Mol Plant 15(11), 1664-1695.