Abstract

The estimation accuracy of plant dry matter by spectra- or remote sensing-based methods tends to decline when canopy coverage approaches closure; this is known as the saturation problem. This study aimed to enhance the estimation accuracy of plant dry matter and subsequently use the critical nitrogen dilution curve (CNDC) to diagnose N in Choy Sum by analyzing the combined information of canopy imaging and plant height. A three-year experiment with different N levels (0, 25, 50, 100, 150, and 200 kg center dot ha(-1)) was conducted on Choy Sum. Variables of canopy coverage (CC) and plant height were used to build the dry matter and N estimation model. The results showed that the yields of N-0 and N-25 were significantly lower than those of high-N treatments (N-50, N-100, N-150, and N-200) for all three years. The variables of CC x Height had a significant linear relationship with dry matter, with R-2 values above 0.87. The good performance of the CC x Height-based model implied that the saturation problem of dry matter prediction was well-addressed. By contrast, the relationship between dry matter and CC was best fitted by an exponential function. CNDC models built based on CC x Height information could satisfactorily differentiate groups of N deficiency and N abundance treatments, implying their feasibility in diagnosing N status. N application rates of 50-100 kgN/ha are recommended as optimal for a good yield of Choy Sum production in the study region.

Keywords

Choy Sum; critical nitrogen dilution curve; plant height; canopy coverage; N fertilization

Published in

Remote Sensing
2022, Volume: 14, number: 16, article number: 3964
Publisher: MDPI

SLU Authors

• Peng, Junxiang

  • Department of Agricultural Research for Northern Sweden, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Environmental Sciences
Remote Sensing


Publication identifier

DOI: https://doi.org/10.3390/rs14163964

Permanent link to this page (URI)

https://res.slu.se/id/publ/118944