The effect of growth stage and plant counting accuracy of maize inbred lines on LAI and biomass prediction View Full Text


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Article Info

DATE

2022-06-09

AUTHORS

Yingpu Che, Qing Wang, Long Zhou, Xiqing Wang, Baoguo Li, Yuntao Ma

ABSTRACT

Accurate maize plant counting plays an essential role in prediction of leaf area index (LAI), aboveground biomass (AGB) and yield. Plant counting of maize inbred lines at early growth stage will result in counting bias caused by death and growth of small seedlings. Therefore, the estimation of LAI and AGB might be negatively affected by plant counting bias at early growth stage. In this study, morphologic discrimination model (MDM) and interpolation discriminant model (IDM) were proposed for plant counting of maize inbred lines at second to fourth (V2–V4) leaf and fourth to sixth (V4–V6) leaf stages with different uncrewed aerial vehicles (UAV) flight heights. Automatic optimum angle calculation of each row, location-based plant cluster segmentation and mosaic method were presented to improve the estimation accuracy of plant counting. Then, the impact of accurate plant counting was evaluated in LAI and AGB prediction at the two growth stages. The results indicated that germination rate difference of some inbred lines could reach up to 38% between V2–V4 and V4–V6 leaf stages. The proposed method accurately estimated the plant counting in the UAV images during V2–V4 leaf stage (R2 = 0.98, RMSE = 7.7, rRMSE = 2.6%) and V4–V6 leaf stage (R2 = 0.86, RMSE = 2.0, rRMSE = 5.5%). The estimated LAI and AGB with plant numbers calculated at V4–V6 leaf stage correlated better with the field measurements (R2 = 0.85 and R2 = 0.9, respectively) compared with those estimated at V2–V4 leaf stage (R2 = 0.8 and R2 = 0.86, respectively). This research indicates that better estimation of LAI and AGB in the field were obtained by accurate plant counting in the late growth stage using UAV images and provides valuable insight for more accurate prediction of yield and crop management and breeding. More... »

PAGES

1-27

References to SciGraph publications

  • 2004-11. Distinctive Image Features from Scale-Invariant Keypoints in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • 2018-09-18. Improved estimation of rice aboveground biomass combining textural and spectral analysis of UAV imagery in PRECISION AGRICULTURE
  • 2021-08-10. Remote estimation of leaf area index (LAI) with unmanned aerial vehicle (UAV) imaging for different rice cultivars throughout the entire growing season in PLANT METHODS
  • 2020-07-09. Comparing methods to estimate perennial ryegrass biomass: canopy height and spectral vegetation indices in PRECISION AGRICULTURE
  • 2021-01-29. Greenness identification using visible spectral colour indices for site specific weed management in PLANT PHYSIOLOGY REPORTS
  • 2019-04-04. Assessment of maize yield and phenology by drone-mounted superspectral camera in PRECISION AGRICULTURE
  • 2017-10-26. Effects of seedling age and cultivation density on agronomic characteristics and grain yield of mechanically transplanted rice in SCIENTIFIC REPORTS
  • 2020-07-14. Identification of candidate tolerance genes to low-temperature during maize germination by GWAS and RNA-seq approaches in BMC PLANT BIOLOGY
  • 2019-06-19. Estimation of crop plant density at early mixed growth stages using UAV imagery in PLANT METHODS
  • 2019-02-12. The estimation of crop emergence in potatoes by UAV RGB imagery in PLANT METHODS
  • 2017-09-07. Genome-wide association study Identified multiple Genetic Loci on Chilling Resistance During Germination in Maize in SCIENTIFIC REPORTS
  • 2018-03-21. Analysis of Long Term Study Indicates Both Agronomic Optimal Plant Density and Increase Maize Yield per Plant Contributed to Yield Gain in SCIENTIFIC REPORTS
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