Using structure-from-motion to estimate cover crop biomass and characterize canopy structure

April M. Dobbs, Daniel Ginn, Søren Kelstrup Skovsen, Ramawatar Yadav, Prashant Jha, Muthukumar V. Bagavathiannan, Steven B. Mirsky, Chris S. Reberg-Horton, Ramon G. Leon*

*Corresponding author for this work

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

Abstract

Context: Variability in biomass production poses a challenge for growers when using cover crops for weed control. However, most methods for assessing cover crop biomass are laborious and impractical on a field scale. Objective: The goal of the present study was to determine the feasibility of using Structure-from-Motion (SfM) photogrammetry to estimate biomass in cereal rye (Secale cereale L.) and winter wheat (Triticum aestivum L.) cover crops by correlating biomass with 3-D point cloud pixel density and crop height. Methods: Point clouds were generated using a SfM algorithm from RGB (red, green, and blue) videos collected by a hand-held GoPro camera over sixteen crop fields in North Carolina, Iowa, and Maryland, USA, throughout two growing seasons (2021–2023). Crop height, leaf area index (LAI), and photosynthetically active radiation (PAR) were also measured. Results: Biomass was positively correlated with crop height for both cereal rye (R2 = 0.621) and wheat (R2 = 0.55). LAI was positively correlated with biomass accumulation and crop height for both species, increasing linearly in rye and exponentially in wheat. Conversely, PAR penetration below the canopy decreased with biomass accumulation and crop height in both species, with a more rapid extinction in wheat than rye. Point cloud pixel density showed a positive linear relationship with biomass in rye but saturated after 2.5 tonnes ha−1 (2500 kg ha−1). In wheat, point cloud pixel density was weakly and negatively correlated with biomass due to a denser canopy causing faster saturation of tissue detection by SfM point clouds. However, considering crop height and point cloud density integrating them both in the model allowed obtaining a positive relationship with biomass through levels of 8 tonnes ha−1 (8000 kg ha−1) in both species. When models were validated with independent data, predicted and measured biomass were positively correlated for both rye (R2 = 0.86) and wheat (R2 = 0.78). Conclusions: Based on the results, using SfM to generate 3-D point clouds can provide a more accurate estimation of biomass than canopy height alone by capturing species-level differences in canopy architecture. Implications: The results of this study suggest that SfM can potentially be used as a non-destructive tool for growers to monitor biomass production in cereal cover crops other systems such as energy/forage crops, which can help inform management decisions and conserve resources.

Original languageEnglish
Article number109099
JournalField Crops Research
Volume302
ISSN0378-4290
DOIs
Publication statusPublished - Oct 2023

Keywords

  • 3-D
  • Biomass
  • Cover crop
  • Point cloud
  • Structure-from-Motion
  • Weed suppression

Fingerprint

Dive into the research topics of 'Using structure-from-motion to estimate cover crop biomass and characterize canopy structure'. Together they form a unique fingerprint.

Cite this