Integrating Sensor Data and Plant Physiology: How Digital Farming Can Track Heat & Water Stress in Field Crops

Abstract

Digital farming is transforming the way crop stress is detected, monitored, and managed by integrating plant physiology with sensor- and satellite-based diagnostics. Plants exhibit subtle physiological shifts—such as increased leaf temperature, reduced chlorophyll fluorescence, and declining photosynthetic activity—long before visual symptoms appear. This article illustrates how multispectral, thermal, fluorescence, and soil-moisture sensing technologies can be combined to create real-time stress maps that reflect these physiological indicators. Using examples from satellite platforms such as Sentinel-2, ECOSTRESS, OCO-2, and SMAP, as well as ground-based tools like SPAD meters and IoT soil probes, the article demonstrates how remote sensing indicators align closely with plant responses to heat and water stress. The integration of machine learning models further enhances early-warning capabilities, allowing farmers and policymakers to make informed decisions. Overall, the article highlights how merging physiological understanding with digital tools enables proactive, scalable, and precise crop stress management in a climate-vulnerable agricultural landscape.