Transferability of Models for Estimating Paddy Rice Biomass from Spatial Plant Height Data

Abstract

It is known that plant height is a suitable parameter for estimating crop biomass. The aim of this study was to confirm the validity of spatial plant height data, which is derived from terrestrial laser scanning (TLS), as a non-destructive estimator for biomass of paddy rice on the field scale. Beyond that, the spatial and temporal transferability of established biomass regression models were investigated to prove the robustness of the method and evaluate the suitability of linear and exponential functions. In each growing season of two years, three campaigns were carried out on a field experiment and on a farmer's conventionally managed field. Crop surface models (CSMs) were generated from the TLS-derived point clouds for calculating plant height with a very high spatial resolution of 1 cm. High coefficients of determination between CSM-derived and manually measured plant heights (R 2 : 0.72 to 0.91) confirm the applicability of the approach. Yearly averaged differences between the measurements were ~7% and ~9%. Biomass regression models were established from the field experiment data sets, based on strong coefficients of determination between plant height and dry biomass (R : 0.60 to 0.90 and 0.56 to 0.85 for linear and exponential models, respectively). Hence, the suitability of TLS-derived spatial plant height as a non-destructive estimator for biomass of paddy rice on the field scale was verified and the transferability demonstrated.

Simulating an Autonomously Operating Low-Cost Static Terrestrial LiDAR for Multitemporal Maize Crop Height Measurements

“…The study area was then extracted from the registered data and exported as an ASCII file containing XYZ coordinates and the timestamp per point for further point density reduction. This workflow is similar to Tilly et al [38,49,50].…”

“…Eitel et al [40] noted the necessity of multiple ATLS when monitoring highly dynamic 3D ecosystem processes changing on a minute or hourly basis. A set-up of multiple TLS systems was employed by Tilly et al [38]. The level of accuracy reached in our studies can be obtained when using one single static position at a height of 3.6 m. For CHM accuracy the measurement set-up should be at least 3.6 m for crops reaching a maximum height of approximately 2.8 m, as shown.…”

“…This is a major asset, increasing the usability of LiDAR technology in precision agriculture as Mulla [21] and Tilly et al [38] also concluded. At the same time, the elevated scan position compensated for unfavorable scan geometry due to a low viewing angle similarly constructed by Eltner et al [52].…”

“…The elevated scanner set-up was similarly employed in other studies. Tilly et al scanned from a position 3 m above ground [38] as well as 4 m above ground [50]. Analogously, Hämmerle et al [4] mounted the scanner on a platform elevated 4 m above ground.…”

Application of a Dielectric Measurement Technique for Calculating Water Loss from Two Texture-contrasting Soils Grown with Upland Rice

“…Both soils had a relatively similar height in the second month of measurements, but in the third month of the study the plant height for the sandy loam soil increased significantly to about 10 cm higher than for the loamy sand soil. A study by Tilly et al (2015) showed that plant height had a very strong relation to biomass production of rice (R 2 : 0.72 to 0.91) and recommended the variable as a non-destructive estimator for biomass of paddy rice. In particular, the plant height influenced the aboveground biomass significantly as reported by Lou et al (2016), while this biomass could be responsible for evapotranspiration, therefore the plant height presented in Table 2 might explain the variations in soil water loss between two study soils.…”