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Showing 122 results for Type of Study: Extentional

Niloufar Taiebikhah, Maryam Mirtalebi,
Volume 14, Issue 1 (2-2025)
Abstract

The management of plant diseases using eco-friendly approaches has gained particular importance in sustainable agriculture for reducing dependence on chemical inputs. Vermicompost and its derivatives, including vermicompost tea and vermiwash, improve soil health and plant growth through bioactive compounds derived from earthworms and large populations of beneficial microorganisms, which effectively suppress plant pathogenic fungi, bacteria, and nematodes. Research evidence has demonstrated that these products can reduce the severity of diseases such as Fusarium wilt, bacterial canker, and root-knot nematodes while enhancing seedling growth parameters. The quality of vermicompost and its derivatives is influenced by factors such as raw materials, degree of maturation, and production methods; appropriate selection of these factors enhances their efficacy in pathogen control. The synergistic benefits of bioactive compounds and beneficial microbiota make vermicompost an effective tool for reducing chemical pesticide use and increasing agricultural productivity. Expanding production, farmer education, and supportive policies can further strengthen the role of these products in promoting sustainable agriculture by providing a practical strategy to improve plant health, mitigate diseases, and protect the environment.

Mehdi Sadravi,
Volume 14, Issue 1 (2-2025)
Abstract

Diseases are a serious threat to the sustainable and healthy production of plant yields and the food security of the world's people, and annually reduce a significant part of their production in terms of quantity and quality. Classical methods of diagnosing plant diseases based on pathogen isolation in the laboratory and visual field monitoring of disease progression and implementation of management methods are very time-consuming, require specialized personnel and expensive. Artificial intelligence-based software uses image analysis, environmental sensors and disease forecasting modeling to quickly diagnose diseases at the farm level, integrate meteorological data, soil and crop parameters to predict the time of disease outbreak, provide appropriate suggestions for disease management based on previously available data and implement management methods quickly and accurately using the Internet of Things, drones and robots. Artificial intelligence-based softwares, help to quickly and accurately diagnose plant diseases before they cause damage, establish predictive systems for diseases, predict the exact time of their occurrence and spread, and implement timely and correct management methods, enabling increased production of healthy plant products, while reducing costs to ensure food security for the world's people.


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