An automatable, field camera track system for phenotyping crop lodging and crop movement

Susko, Alexander Q.; Gilbertson, Fletcher; Heuschele, D. Jo; Smith, Kevin P.; Marchetto, Peter

doi:10.1016/j.ohx.2018.e00029

Cited by 13 publications

(13 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…An automated camera track system [19] with a 360fly (360fly, Inc.) camera mounted 3 m off the ground, allowed us to capture hemispherical videos of 98 single row plots within a RCB design planted at four different planting dates (Fig. 1) (Table 1).…”

Section: Resultsmentioning

confidence: 99%

“…The camera track system was specifically designed for quantifying lodging and plant movement under field wind conditions, with open source design plans [19]. Four replicates were in view of the camera track (two inner and two outer replicates), with 2-minute videos taken at each of the four planting dates on five different windy days in July 2017 for a total of 20 videos capturing cereal movement (Table 2; Fig.…”

Section: Resultsmentioning

confidence: 99%

“…UAV systems are not ideal for capturing video data, especially when data on plant movement is desired under high wind or stormy conditions. Ground based, automatable camera systems are more amenable to capturing video under inclement weather, and 360° field of view video cameras are capable of imaging a full hemisphere per frame [19]. The use of a 360 video camera alleviates the need for multiple cameras to capture replicated plots and for synchronization of separate videos at exact moments in time, while remaining close enough to the canopy level to capture small differences in movement.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Quantifying cereal crop movement through hemispherical video analysis of agricultural plots

et al. 2019

Self Cite

View full text Add to dashboard Cite

Background Violent movement of crop stems can lead to failure under high winds. Known as lodging, this phenomenon is particularly detrimental to cool-season cereals such as oat, barley, and wheat; contributing to yield and economic losses. Phenotyping the movement of cereal crops in real-time could aid in the breeding and selecting of lodging resistant cereals. Since no methods exist to quantify dynamic, real time plant responses in an agricultural setting, we devised a video analysis protocol to quantify mean frequency and amplitude of plant movement for a 360° field of view camera system. Results We present both the image analysis method for identifying predefined regions of a 2D field design as they appear on 360° field of view video, as well as a signal processing pipeline to quantify movement from time varying color signals from plot canopies within these predefined field regions. We detected significant differences in the natural frequency and amplitude of plant movement from video of 16 cereal cultivars planted in a randomized complete block design on five different windy days. Natural frequencies quantified by this method averaged 1.37 Hz, while over 2.5-fold differences in amplitude within similar frequency ranges were detected across the 16 cereal cultivars. Conclusions This method is sensitive enough to systematically differentiate small frequency and amplitude differences in cultivar movement, and shows promise for investigating the physiological basis for differences in cereal movement and lodging resistance. The relative accuracy of the plot demarcation protocol suggests it could be used for other high-throughput phenotyping applications that require both high image resolution and a large field of view. Electronic supplementary material The online version of this article (10.1186/s13007-019-0437-5) contains supplementary material, which is available to authorized users.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Quantifying cereal crop movement through hemispherical video analysis of agricultural plots

et al. 2019

Self Cite

View full text Add to dashboard Cite

show abstract

“…The use of UAVs can replace laborious and subjective ground data collection and enable spatial assessment of lodging by an automated system. Susko et al [43] tried to assess crop lodging with a field camera track system. Liu et al [44] used visible and thermal infrared images derived from UAV for rice lodging estimation.…”

Section: Introductionmentioning

confidence: 99%

Quantifying Lodging Percentage and Lodging Severity Using a UAV-Based Canopy Height Model Combined with an Objective Threshold Approach

et al. 2019

View full text Add to dashboard Cite

Unmanned aerial vehicles (UAVs) open new opportunities in precision agriculture and phenotyping because of their flexibility and low cost. In this study, the potential of UAV imagery was evaluated to quantify lodging percentage and lodging severity of barley using structure from motion (SfM) techniques. Traditionally, lodging quantification is based on time-consuming manual field observations. Our UAV-based approach makes use of a quantitative threshold to determine lodging percentage in a first step. The derived lodging estimates showed a very high correlation to reference data (R2 = 0.96, root mean square error (RMSE) = 7.66%) when applied to breeding trials, which could also be confirmed under realistic farming conditions. As a second step, an approach was developed that allows the assessment of lodging severity, information that is important to estimate yield impairment, which also takes the intensity of lodging events into account. Both parameters were tested on three ground sample distances. The lowest spatial resolution acquired from the highest flight altitude (100 m) still led to high accuracy, which increases the practicability of the method for large areas. Our new lodging assessment procedure can be used for insurance applications, precision farming, and selecting for genetic lines with greater lodging resistance in breeding research.

show abstract

“…Using UAV data for the spatial assessment of lodging is a very suitable method to automate the detection of lodging and replace laborious and subjective ground data collection. Already Susko et al (2018) tried to assess crop lodging with a field camera track system. Additionally, Yang et al (2015) used polarimetric index from RADARSAT-2 data for monitoring wheat lodging.…”

Section: Introductionmentioning

confidence: 99%

Quantifying Lodging Percentage, Lodging Development and Lodging Severity Using a Uav-Based Canopy Height Model

Wilke

Siegmann

Frimpong

et al. 2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

Abstract. Unmanned Aerial Vehicles (UAVs) are increasingly used, and open new opportunities, in agriculture and phenotyping because of the flexible data acquisition. In this study the potential of ultra-high spatially resolved UAV image data was investigated to quantify lodging percentage, lodging development and lodging severity of barley using Structure from Motion techniques. The term lodging is defined as the permanent displacement of a plant from the upright position. Traditionally lodging quantification is based on observations that need, and vary with observers in the field. An objective threshold approach was proposed in this study to improve the accuracy in lodging determination. Across breeding trials, manual reference measurements and UAV based lodging percentage showed a very high correlation (R2&thinsp;=&thinsp;0.96). In addition, the multi-temporal lodging percentage development was used to estimate the recovery rate and to determine the influence of different lodging events. Based on the parameter lodging percentage an approach was developed that allowed the assessment of lodging severity, an information that is important to estimate the yield impairment. Lodging severity can be used for insurance applications, precision farming and breeder research. This trait, together with differentiated recovery are novel traits next to lodging severity that will aid the selection for genetic lines.

show abstract

An automatable, field camera track system for phenotyping crop lodging and crop movement

Cited by 13 publications

References 3 publications

Quantifying cereal crop movement through hemispherical video analysis of agricultural plots

Quantifying cereal crop movement through hemispherical video analysis of agricultural plots

Quantifying Lodging Percentage and Lodging Severity Using a UAV-Based Canopy Height Model Combined with an Objective Threshold Approach

Quantifying Lodging Percentage, Lodging Development and Lodging Severity Using a Uav-Based Canopy Height Model

Contact Info

Product

Resources

About