Estimation of sugar beet biomass and yield comparing NDVI measurements and physical soil parameters Abschätzung von zuckerrübenbiomasse und -ertrag durch vergleich von NDVI-messungen und bodenphysikalischen parametern

Tugrul K. M.

Zuckerindustrie, vol.146, no.2, pp.100-109, 2021 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 146 Issue: 2
  • Publication Date: 2021
  • Doi Number: 10.36961/si26238
  • Journal Name: Zuckerindustrie
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, CAB Abstracts, Food Science & Technology Abstracts
  • Page Numbers: pp.100-109
  • Keywords: land cover, precision agriculture, remote sensing, landsat images, classification, mapping, LAND-COVER, CROP, FIELDS
  • Eskisehir Osmangazi University Affiliated: Yes


© 2021 Verlag Dr. Albert Bartens KG. All rights reserved.This study was conducted to estimate the relationship of soil sample analysis and satellite imagery with sugar beet yield (BY). The red NDVI obtained monthly from Landsat OLI satellite images during the 2017 and 2018 sugar beet growing seasons were used to establish relationships between imagery and georeferenced soil sample analyses and sugar beet harvest sites. The study was carried out in the field of Sugar Institute Ilgin Experiment Station, Turkey, in 2017 and 2018. Soil samples were obtained in a 0.4 ha grid, and sugar beet yield and recoverable sugar yield (RSY) were obtained from the same sampling areas. The results showed that there were relationships between some soil analysis factors and BY and beet quality. The overall results showed that the amount of clay, electric conductivity (EC), and organic matter in the field might be indicators of BY and beet quality. A statistically significant moderate positive correlation was also obtained between NDVI (Normalized Difference Vegetation Index) images and BY and RSY values in all images obtained by satellite near the harvest date.