Determination of yield and quality relationship with visible near infrared UAV images in sugar beet plots with different doses of nitrogen application

In plant production, cultigen development should be monitored and followed periodically throughout the vegetation period and precautions should be taken when necessary. Therefore, real-time, spatial and accurate determination of plant development is of great importance for precision agriculture today. In this study, the statistical relationship between the 2022 yield values of 12 different sugar beet (Beta vulgaris) trials established with 3 different N applications in Çumra district of Konya and the NDVI, Redge - NDVI, REMCARI and RETVI index values derived from UAV images of June, July, August and September of the same period was investigated. In the study, 4 imagings in RGB-Rededge-IR bands were performed to cover the germination-emergence, vegetative development, root swelling and ripening periods of sugar beet and the index values derived from a total of 240 images were correlated by taking the parcel averages. The success of the indices derived with UAV integrated VNIR camera data in yield estimations was tested on a periodic basis and it was determined that NDVI and REDGE NDVI values with UAV images of July could be used with r2>75 for early yield estimations. It was suggested that RETVI and REMCARI indices could be preferred with r2>75 in August and September, which include root swelling and ripening periods, which are advanced vegetation stages of sugar beet. As a result of the study, it was suggested that by interpreting the NDVI and REDGE NDVI values obtained from July images of sugar beet, product yield could be estimated early in large areas, the effects of cultural practices could be evaluated by comparing different parcels and could be used as a basis for planning by decision makers. However, the most important parameter in terms of determining economic value for sugar beet producers and factories was determined to have low inverse statistical relationships as r2 = 0.059-0.546 between polar concentration and vegetation indices. Therefore, it has been suggested that estimations based on index values alone are not sufficient for quality parameters and that further research is necessary on this subject. Keywords: Quality, sugar beet, UAV, vegetation indices, yield