Precision maize stand analysis using remote sensing methods: plant density measurement with spectral data integration - Illés, Árpád; Horváth, Éva; Bojtor, Csaba; Zagyi, Péter; Széles, Adrienn (Precision Crop Production, 2025)
The aim of this study was to use remote sensing with a drone equipped with a multispectral camera to take a stand survey of maize after the phenological stage of emergence, and to count the number of emerged plants and determine its accuracy. Our investigations were carried out at the University of Debrecen, Látókép Production Experimental Station in a sowing date long-term experiment. In the 2024 growing season, Sowing Date I was on 4 April and Sowing Date II on 12 April. The same maize hybrids with 8-8 different genotypes were used for each sowing date. There is a strong correlation between number of plants/plot and number of plants/rowx2 for the two plant density measurements presented in this paper, with an r value of 0.977*** (p < 0.001). Among the plant density and NDVI values, the correlation between number of plants/rowx2 at the second measurement time (July 4) was significant at r=-0.418***. The analysis of the relationship between number of rows and yield showed that the hybrids included in the study compensated well for differences in number of rows due to sowing or emergence and this did not translate into an increase or decrease in yield. By using the plant density count method and results to identify emergence imbalances, farmers can correct their crop stand management strategies in a timely manner. Knowing the exact number of plants can also be important for subsequent agrotechnical decisions.