Bridging soil health and disease forecasting: a survey of sensors based framework

Precision Agriculture is founded on soil exploration that offers insight into the biological, chemical and physical properties of soil that affect the wellbeing of crops and their susceptibility to diseases. The analysis of soil can be used to diagnose nutritional deficiency, pH level and moisture state that enhances the growth of pathogens. In-field real-time mapping of soil variability has been significantly optimized using IoT technology, high-resolution sensors as well as UAVs. The tools can be used to conduct site-specific and dynamic monitoring to support informed agriculture. The sensor data can be used to predict soil suitability, nutrient and irrigation mapping through machine learning. But the majority of surveillance systems continue to monitor the surface symptoms or post-harvest without paying attention to the activity that occurs on the sub-surface, which contributes significantly in the diagnosis of the disease during its initial stages. As emphasized in paper, there’s need that multimodal diagnostic systems become possible, which combines real-time information from data above and below ground. It will be shut and the outcome will be superior and more timely notification mechanism, superior and clearer functioning intervention and superior and more intense agriculture. Sensors-based and soil-based solutions can transform precision agriculture in the future.

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Publication Details

Journal
IET conference proceedings.
Published
2026-02-01
DOI
https://doi.org/10.1049/icp.2025.4751
Primary Topic
Soil Geostatistics and Mapping
Type
article
Field-Weighted Citation Impact
0.00
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article

Bridging soil health and disease forecasting: a survey of sensors based framework

Nutan V. Dolzake, Mrunal Bewoor
IET conference proceedings.
Soil Geostatistics and Mapping
article

Bridging soil health and disease forecasting: a survey of sensors based framework

Nutan V. Dolzake, Mrunal Bewoor
article en

Abstract

Precision Agriculture is founded on soil exploration that offers insight into the biological, chemical and physical properties of soil that affect the wellbeing of crops and their susceptibility to diseases. The analysis of soil can be used to diagnose nutritional deficiency, pH level and moisture state that enhances the growth of pathogens. In-field real-time mapping of soil variability has been significantly optimized using IoT technology, high-resolution sensors as well as UAVs. The tools can be used to conduct site-specific and dynamic monitoring to support informed agriculture. The sensor data can be used to predict soil suitability, nutrient and irrigation mapping through machine learning. But the majority of surveillance systems continue to monitor the surface symptoms or post-harvest without paying attention to the activity that occurs on the sub-surface, which contributes significantly in the diagnosis of the disease during its initial stages. As emphasized in paper, there’s need that multimodal diagnostic systems become possible, which combines real-time information from data above and below ground. It will be shut and the outcome will be superior and more timely notification mechanism, superior and clearer functioning intervention and superior and more intense agriculture. Sensors-based and soil-based solutions can transform precision agriculture in the future.

IET conference proceedings.Vol. 2025(43)
Bharati Vidyapeeth (Deemed to be University) (IN)
Zero hunger
Openalex Percentile: Top 71%
Soil Geostatistics and Mapping
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