Fungal Infection Diseases- Nightmare for Cannabis Industries: Artificial Intelligence Applications

Ravindra B. Malabadi, Nethravathi Tl, Kiran P. Kolkar, Raju K. Chalannavar, Bhagyavana S. Mudigoudra, Gholamreza Abdi, Antonia Neidilê Ribeiro Munhoz and Himansu Baijnath
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Ravindra B. Malabadi: Department of Applied Botany, Mangalore University, Mangalagangotri-574199, Mangalore, Karnataka State, India
Nethravathi Tl: Department of Artificial Intelligence (AI) and Machine Learning (ML), SJC Institute of Technology, Chikkaballapur-5621010, Karnataka State, India
Kiran P. Kolkar: Department of Botany, Karnatak Science College, Dharwad-580003, Karnataka State, India
Raju K. Chalannavar: Department of Applied Botany, Mangalore University, Mangalagangotri-574199, Mangalore, Karnataka State, India
Bhagyavana S. Mudigoudra: Department of Computer Science, Maharani Cluster University, Bangalore- 560 001, Karnataka State, India
Gholamreza Abdi: Department of Biotechnology, Persian Gulf Research Institute, Persian Gulf University, Bushehr, 75169, Iran
Antonia Neidilê Ribeiro Munhoz: Department of Chemistry, Environment and Food, Federal Institute of Amazonas, Campus Manaus Centro, Amazonas, Brazil- 69020-120
Himansu Baijnath: Ward Herbarium, School of Life Sciences, University of KwaZulu-Natal, Westville Campus, Private Bag X54001, Durban 4000, South Africa

International Journal of Research and Innovation in Applied Science, 2023, vol. 8, issue 8, 111-131

Abstract: This review paper highlights the fungal diseases of both indoor and outdoor Cannabis cultivation environments and discusses the Artificial intelligence (AI) based crop disease detection and management. Pathogens are a pain in the neck of every Cannabis breeder. They affect the quality and quantity of yield, thus defeating the aim of cultivation. Some of the fungal pathogen that can attack Cannabis crops are Botrytis, Alternaria, Fusarium, Penicillium, Cladosporium, and Aspergillus. Fungal diseases are Powdery Mildew, Damping off, and Mildew. Of these fungal pathogens, the most common inflorescence disease is gray mold, caused by Botrytis cinerea. Botrytis cinerea and Erysiphe species complex are currently the most widespread pathogens of Cannabis worldwide. The greatest challenge facing Cannabis and hemp producers is the management of insect pests and pathogens that attack the roots, leaves and inflorescences. The common disease management strategies are-remove and destroy infected plants. Irradiate dried buds with gamma or electro-beam radiation. Another method is to apply biological control agents at rooting and vegetative stages of growth. Pesticides have been found in all Cannabis products, from flowers to edibles, vapes, and smokes. The pesticide pandemic in the Cannabis industry needs urgent attention. Cannabis can contain fungal pathogens and residues of pesticides, fungicides that cause serious and often fatal infections in persons with immunocompromised conditions, such as cancer, transplant, or infection with HIV. Contamination of Cannabis plants and products (i.e., recreational- and pharmaceutical-grades) with mycotoxigenic organisms, including species of Aspergillus, Penicillium, and Fusarium, pose serious health challenges. The manual Cannabis disease identification process is time-consuming and tedious work. Instead, automated methods save both time and effort. The technology of Artificial Intelligence (AI) in the detection and management of disease has already been employed in many crops. The machine learning (ML)-based models were proposed for the identification and classification of plant diseases. The PlantVillage dataset is the largest and most studied plant disease dataset, which is used as a reference for the disease detection and management of plant diseases.

Date: 2023
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