An Integrated Framework for Automatic Irrigation for Solanaceae Crops using Feedback Learning with Multimodal Optimizations

Precision irrigation is fundamental in ensuring sustainable cultivation of Solanaceae crops that are very sensitive to water stress and salinity. However, existing irrigation systems lack spatial specificity, fail to integrate real physiological indicators in real time, and do not take into account dynamic environmental and morphological variations. Due to these deficiencies, inefficient water use, reduced yield, and low stress mitigations are experienced. These shortcomings are filled by introducing a multi-method, sensor Integrated framework to enable real-time, adaptive irrigation decisions. The proposed system comprises five synergistic modules. (1) Crop-Thermal Spectro Feedback Network (CTS-FNet) can now utilize canopy thermal and hyperspectral imaging to compute a Canopy Water Stress Index (CWSI-Solanaceae-Adjusted) and extract an Irrigation Priority Score (IPS) with 92.8% stress detection accuracy and strong correlation (r = 0.89) with the manual leaf water potential. (2) Root-Zone Salinity-Aware Moisture Balancing Model (RS-MBM) combines root-zone electric conductivity, soil moisture, and phenological stage with a Bayesian GAM and GBRT stack to optimize irrigation volume, thereby achieving 16.3% saline induced deviation reduction from yield. (3) Dynamic Morphological Irrigation Clustering Engine (DyMICE) clusters genotypes in terms of LAI, diameter of stem, and root length for rule-specific cluster-specific irrigation, which saves on the average about 19.7% water. (4) Carbon Flux–Linked Water Allocation Optimizer (CF-WAO) engages irrigation simultaneously with photosynthetic activity through CO₂ flux, Pn, and LUE, reducing the response lag to photosynthetic drop from 2.1 hours to 15 minutes. (5) Integrated Irrigation Decision Support System (IIDSS) integrates all upstream outputs and weather forecasts using fuzzy logic and graph models for real-time, zone-specific irrigation commands. Collectively, such a system can improve water use efficiency, improve stress detection, and support genotype-specific irrigation and take on the scale for precision agriculture in Solanaceae productions.