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Post-harvest grain losses remain a significant challenge in agriculture, primarily due to inefficient and uncontrolled drying methods. Conventional techniques such as open sun drying are highly dependent on environmental conditions and require continuous manual intervention, often resulting in non- uniform drying, moisture retention, fungal contamination, and degradation of grain quality. Furthermore, existing mechanical drying systems are often expensive and designed for single-grain applications, limiting their suitability for small- scale and rural farmers.
This paper presents a Smart Solar-Assisted Multi-Grain Drying System that integrates sensor-based monitoring, automated control, and renewable energy utilization. The proposed system enables user selection of different grain types and automatically adjusts drying parameters based on predefined moisture and temperature requirements. Real-time sensing
ensures effective regulation of heating and airflow mechanisms, leading to uniform and efficient drying. The incorporation of solar energy reduces dependency on conventional power sources, making the system cost-effective and suitable for energy-constrained rural environments.
Experimental results demonstrate that the proposed system improves drying efficiency, reduces manual effort, and minimizes post-
harvest losses. The integration of automation, multi-grain adaptability, and sustainable energy provides a practical and scalable solution for enhancing grain drying and storage practices in modern agriculture.
"Smart Automatic Solar -Assisted Grain Drying System", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 4, page no.a683-a686, April-2026, Available :http://www.ijrti.org/papers/IJRTI2604097.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator