How Do Soil Properties and Canopy Status Influence Potato Traits while Continuously Monitoring Soil Moisture with Iot-Based Sensors?

Soil-related properties associated with potato yield and quality are implicitly linked to soil water storage (SWS) determined by soil texture (ST). This soil property also affects the potato canopy, which could be evaluated indirectly using Unmanned Aerial Vehicles (UAVs). The objective of this study carried out in 2022 was to define explanatory soil- and canopy state-related properties (NDVI – Normalized Difference Vegetation Index), that determine with the highest extent potato ( Solanum tuberosum L.) traits: total yield (TY), dry matter (DM) content, and average tuber weight (ATW) over a rainfed production field located in central Poland (52°4′ 50.94" N, 21°10′ 6.73" E). Soil water storage was derived from continuously measured volumetric water content (VWC) using moisture sensors installed at three depths (10, 20, and 30 cm), which were connected via the Internet to exchange data (IoT-based sensors). Thus, the second objective of this study was to evaluate how temporal changes in SWS and the duration of periods when SWS falls below the level that limits plant growth affected TY in sampling areas characterized by different ST. Potatoes were grown under a suboptimal water supply during crucial stages for yield formation. More explanatory soil- and canopy state-related properties significantly, and to a greater extent, affected ATW and TY than DM content. SWS, determined between the stages of leaf development and canopy closure, played a more critical role in forming ATW and TY than soil chemical properties. NDVI derived from four out of five UAV images (58–100 days after planting – DAP) showed a very high correlation (r values of 0.79–0.90) with yield and ATW, and this canopy status indicator outperformed all soil-based variables. The model, based on sand and silt content, soil fertility in Cu and Zn, and NDVI measured at the time of fruit development, and soil water storage recorded between leaf development and canopy closure, showed the lowest RMSE of 5.85 t∙ha −1 and 7.98 g for TY and ATW prediction, respectively. A model based solely on NDVI evaluation between canopy closure and the end of flowering, and SWS determined simultaneously, was a strong alternative for forecasting TY (RMSE = 6.67 t∙ha −1 ) and ATW (RMSE = 9.23 g). In the sampling area with the highest TY, characterized by loamy sand ST, the deficit of SWS started at 46 DAP and lasted only for 12 days. In contrast, the sampling area with the lowest TY, with sandy ST, experienced SWS deficit from 34 DAP, and this period of plant-limited growth lasted for 34 days.