Photosynthetic energy assessment in shallot farming using combining Sentinel-2 data with NetBeat™ in a highland tropical agroecosystem: Case study at food estate Hutajulu, North Sumatra, Indonesia

Efficient monitoring is essential to achieve optimal growth and productivity in shallot cultivation (Allium ascalonicum L.), particularly within large-scale agricultural developments, such as the Food Estate program in Hutajulu, North Sumatra, Indonesia. This study aimed to analyse the dynamics of photosynthetic energy absorption in shallot farming by combining Sentinel-2 level 2A data with NetBeat™, an advanced decision support platform developed by Netafim. Three vegetation indices—MSAVI (Modified Soil-Adjusted Vegetation Index), NDVI (Normalised Difference Vegetation Index), and NDRE (Normalised Difference Red Edge)—were employed to evaluate the photosynthetic performance of three shallot varieties: Lokananta, Sanren F1, and Maserati. The study began by establishing coordinate-based sample plots of 0.2–0.25 hectares in the Food Estate area, where sensors were strategically placed to collect environmental and crop data. Each coordinate point consisted of six samples of the same shallot variety arranged in a grid pattern. Observations were conducted over 120 days, covering four distinct growth stages: leaf formation, vegetative growth, tuber formation, and canopy ageing. Data were collected from laboratory analyses and field trials, supported by Netbeat technology integrated into a digital farming system. The results revealed that overall photon energy absorption efficiency was relatively low, with significant disparities among the varieties. Among the indices, MSAVI provided a more accurate assessment of photosynthetic activity compared to NDVI and NDRE. Notably, the Sanren F1 variety demonstrated the highest potential for efficient cultivation, suggesting its suitability for future shallot production in the Food Estate region of Hutajulu.