Soil Analysis, Disease Detection and Pesticide Recommendation for Farmers using AI and ML
Year: 2025
Type: article
Abstract: Our project aims to analyze the soil and detect plant disease and pesticidesrecommendation using AIML. The model gives the related information of the crop that canbe grown in that soil using the soil test results. Plant disease detection help farmers useappropriate pesticide. As Agriculture is the backbone of our country. We aim to benefitfarmers to minimize the losses in farming by providing rich recommendations and insightsabout the crops using current technology like machine learning which allows more efficientand precise farming with less manpower with high- quality production. ArtificialIntelligence and machine learning are efficient ways to monitor and identify possible crophealth issues or nutrient deficiencies in the soil and minimize post-harvest processing, tofortify agricultural sustainability and maximize productivity. Advancement in the area ofmachine learning has helped improve gains in agriculture. Machine learning is the currenttechnology which is benefiting farmers to minimize the losses in farming by providing richrecommendations and insights about the crops.
Author: CSEIJ
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: green
OpenAlex ID: W6912359205
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