Crop Monitoring Strategy Based on Remote Sensing Data (Sentinel-2 and Planet), Study Case in a Rice Field after Applying Glycinebetaine

World agriculture is facing a great challenge since it necessary to find sustainable way increase food production. Current trends in advancing the sector are based on leveraging remote sensing technology and use of biostimulants. However, efficient implementation both these commercial scale for purposes productivity improvement remains challenge. Thus, by proposing crop monitoring strategy data, this paper aims verify anticipate impact applying Glycinebetaine biostimulant (GB) final yield. The study was carried out rice-producing area Eastern Spain (Valencia) 2021. GB applied drone 33 days after sowing (tillering phase). Phenology monitored production parameters were determined. Regarding satellite Sentinel-2 cloud-free images obtained from harvest, using bands at 10 m. Planet data used evaluate results Sentinel-2. show that improves productive yield (13.06% increase). design proposed dynamics correlations between visible (green red) NIR bands. analysis showed differences when comparing control areas, permitted determination moment which effect maturity) may be greater. In addition, an index constructed strategy, its mathematical expression being: NCMI = (NIR − (red + green))/(NIR red green). Compared with other VIs (NDVI, GNDVI EVI2), presents greater sensitivity changes green, bands, lower saturation phenomenon than NDVI better rice phenology management EVI2. These evaluated images, obtaining similar results. conclusion, study, we confirm improving plant nutrition biostimulants increasing components define (productive tillers, spikelets grains). Additionally, permits anticipation understanding behavior evolution phenological stages crop, accordance management.