Abstract

Lodging stress seriously affects the yield, quality, and mechanical harvesting of maize, and is a major natural disaster causing maize yield reduction. The aim of this study was to obtain light detection and ranging (LiDAR) data of lodged maize using an unmanned aerial vehicle (UAV) equipped with a RIEGL VUX-1UAV sensor to analyze changes in the vertical structure of maize plants with different degrees of lodging, and thus to use plant height to quantitatively study maize lodging. Based on the UAV-LiDAR data, the height of the maize canopy was retrieved using a canopy height model to determine the height of the lodged maize canopy at different times. The profiles were analyzed to assess changes in maize plant height with different degrees of lodging. The differences in plant height growth of maize with different degrees of lodging were evaluated to determine the plant height recovery ability of maize with different degrees of lodging. Furthermore, the correlation between plant heights measured on the ground and LiDAR-estimated plant heights was used to verify the accuracy of plant height estimation. The results show that UAV-LiDAR data can be used to achieve maize canopy height estimation, with plant height estimation accuracy parameters of R2 = 0.964, RMSE = 0.127, and nRMSE = 7.449%. Thus, it can reflect changes of plant height of lodging maize and the recovery ability of plant height of different lodging types. Plant height can be used to quantitatively evaluate the lodging degree of maize. Studies have shown that the use of UAV-LiDAR data can effectively estimate plant heights and confirm the feasibility of LiDAR data in crop lodging monitoring.

Highlights

  • According to a report from the National Bureau of Statistics, China’s maize planting area in 2019 was 41.284 million hectares, with a total output of 260.77 million tons, which makes maize the largest food crop in China [1]

  • The most apparent effect of maize lodging was that the plant heights changed greatly, and the point cloud data directly reflect these changes in plant height

  • The point cloud data processed on August 28 and September 14 were analyzed in the LiDAR360 software, and the results are shown in

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Summary

Introduction

According to a report from the National Bureau of Statistics, China’s maize planting area in 2019 was 41.284 million hectares, with a total output of 260.77 million tons, which makes maize the largest food crop in China [1]. The frequent occurrence of extreme weather events caused by global warming has increased the probability of maize lodging. During this period, severe weather events such as strong winds and rainstorms occur frequently, and are the main cause of maize lodging [2,3]. Maize lodging seriously affects the normal progress of plant photosynthesis and nutrient transport. It can Agriculture 2020, 10, 146; doi:10.3390/agriculture10050146 www.mdpi.com/journal/agriculture

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