Bett, K.

Nielsen, K.

Shirtliffe, S.

English

eCommons@USASK

Using overhead images to determine volume and ground cover of lentil (Lens culinaris Medik.)

University of Saskatchewan Research Archive

kmn766@mail.usask.caKarsten NielsenMSc StudentUsing Overhead Images to Determine Volume and Ground Cover of Lentil (Lens culinaris Medik.)PhenotypingProblems• Qualitative ratings are often given to quantitative traits• Monotonous• Questionable consistency and objectivity between observers and over time• “Assesses physical and biochemical characteristics of a plant in its environment.” • Essential to breeders for variety development and improvement.Which dot is bigger?http://brainden.com/visual-illusions.htm#prettyPhotoWhich dot is bigger?http://brainden.com/visual-illusions.htm#prettyPhotohttp://ishiharatest.blogspot.ca/2011/03/ishihara-color-blindness-test.htmlhttp://ishiharatest.blogspot.ca/2011/03/ishihara-color-blindness-test.html29 = normal70 = red-green issuesSolution: Image-Based Phenotyping• Utilize UAV images• High-Throughput• High Temporal Resolution• Rapid• Reduces/Eliminates need for human observers • High Spatial Resolution = accurate, looks at entire plot• ConsistentGoal: Determine a Method to Estimate Plant Biomass Using Overhead Images• 2-Dimensional Approach• Measure area of vegetation• Make assumptions about shape and height• 3-Dimensional Approach• “cut” vegetation at ground-level• Measure 3 dimensional space (volume) filled by vegetation• Make some assumptions about densityGermplasm Observed• Subset of Lentil AGILE Lentil Diversity Panel (LDP):• 6 Diverse Varieties• 6 Biomass Collection dates• 3 Replicates• Microplots (approximately 1m x 1m)• Sutherland, Nasser, and Rosthern• Lentil AGILE (Application of Genomic Innovation in the Lentil Economy) Lentil Diversity Panel (LDP)• 324 Diverse Lines in 3 replicates• Microplots (approximately 1m x 1m)• Sutherland and RosthernGermplasm Observed• Subset of Lentil AGILE Lentil Diversity Panel (LDP):• 6 Diverse Varieties• 6 Biomass Collection dates• 3 Replicates• Microplots (approximately 1m x 1m)• Sutherland, Nasser, and Rosthern• Lentil AGILE (Application of Genomic Innovation in the Lentil Economy) Lentil Diversity Panel (LDP)• 324 Diverse Lines in 3 replicates• Microplots (approximately 1m x 1m)• Sutherland and RosthernGermplasm Observed• Subset of Lentil AGILE Lentil Diversity Panel (LDP):• 6 Diverse Varieties• 6 Biomass Collection dates• 3 Replicates• Microplots (approximately 1m x 1m)• Sutherland, Nasser, and Rosthern• Lentil AGILE (Application of Genomic Innovation in the Lentil Economy) Lentil Diversity Panel (LDP)• 324 Diverse Lines in 3 replicates• Microplots (approximately 1m x 1m)• Sutherland and RosthernDraganFly UAV• Manufactured in Saskatoon• Flys a pre-programmed flightplan without operator inputs• Converted Sony A5100; 24.3 megapixels; NIR-G-B• Stabilizing GimbalJune 5, 2017 July 4, 2017August 1, 2017 August 17, 2017Preliminary Research  - Overlapping Images are Stitched Using Pix4D Software2-Dimensional Approach: Image Segmentation and Data ExtractionStitched OrthomosaicDuan T, Zheng B, Guo W, Ninomiya S, Guo Y, Chapman C. 2017. Comparison of ground cover estimates from experiment plots in cotton, sorghum, sugarcane based on images and ortho-mosaics captured by UAV.. Functional Plant Biology. 44:169-183.2-Dimensional Approach: Image Segmentation and Data ExtractionStitched Orthomosaic Insert Labelled Polygon LayerDuan T, Zheng B, Guo W, Ninomiya S, Guo Y, Chapman C. 2017. Comparison of ground cover estimates from experiment plots in cotton, sorghum, sugarcane based on images and ortho-mosaics captured by UAV.. Functional Plant Biology. 44:169-183.2-Dimensional Approach: Image Segmentation and Data ExtractionStitched Orthomosaic Insert Labelled Polygon LayerCalculate Indices (gNDVI) and ThresholdDuan T, Zheng B, Guo W, Ninomiya S, Guo Y, Chapman C. 2017. Comparison of ground cover estimates from experiment plots in cotton, sorghum, sugarcane based on images and ortho-mosaics captured by UAV.. Functional Plant Biology. 44:169-183.2-Dimensional Approach: Image Segmentation and Data ExtractionStitched Orthomosaic Insert Labelled Polygon LayerCalculate Indices (gNDVI) and ThresholdData OutputDuan T, Zheng B, Guo W, Ninomiya S, Guo Y, Chapman C. 2017. Comparison of ground cover estimates from experiment plots in cotton, sorghum, sugarcane based on images and ortho-mosaics captured by UAV.. Functional Plant Biology. 44:169-183.2-Dimensional Approach: Image Segmentation and Data ExtractionStitched Orthomosaic Insert Labelled Polygon LayerCalculate Indices (gNDVI) and ThresholdData OutputDuan T, Zheng B, Guo W, Ninomiya S, Guo Y, Chapman C. 2017. Comparison of ground cover estimates from experiment plots in cotton, sorghum, sugarcane based on images and ortho-mosaics captured by UAV. Functional Plant Biology. 44:169-183.Result of Indices and Thresholding CalculationsGreen Pixel Area Compared to Ground Truth Biomass Data at Sutherland, 2017Green Pixel Area Compared to Ground Truth Biomass Data at Sutherland, 2017Green Pixel Area Compared to Ground Truth Biomass Data at Sutherland, 2017Green Pixel Area Compared to Ground Truth Biomass Data at Sutherland, 2017Green Pixel Area Compared to Ground Truth Biomass Data at Sutherland, 2017Green Pixel Area Compared to Ground Truth Biomass Data at Sutherland, 2017Three-Dimensional Analysis to Measure Plot  VolumeThree-Dimensional Analysis to Measure Plot  VolumeTorres-Sanchez J, Lopez-Granados F, Serrano N, Arquero O, Pena J. 2015. High-Throughput 3-D monitoring of agricultural tree plantations with unmanned aerial vehicle (UAV) technology.PLOS ONE. DOI:10.1371Structure from Motion (SfM)• Multiple perspectives to interpret structure• Humans see with stereovision• Some birds (pigeons, waterfowl, etc.) see depth by bobbing their head (SfM)https://www.mathworks.com/help/vision/ug/structure-from-motion.htmlhttps://www.quora.com/If-most-birds-cant-see-depth-how-do-they-catch-food-and-not-crash-into-things3-Dimensional Analysis for Phenotyping• More perspectives than 2-D approach• more accurate than 2-D• Fewer assumptions• Requires much more computing powerUtilized Volume Estimation Tool in Pix4DResults of Volume Measurement Compared to Ground-Truthed Biomass Measurement*Error Bars show Standard ErrorResults of Volume Measurement Compared to Ground-Truthed Biomass Measurement*Error Bars show Standard ErrorResults of Volume Measurement Compared to Ground-Truthed Biomass Measurement*Error Bars show Standard ErrorResults of Volume Measurement Compared to Ground-Truthed Biomass Measurement*Error Bars show Standard ErrorResults of Volume Measurement Compared to Ground-Truthed Biomass Measurement*Error Bars show Standard ErrorResults of Volume Measurement Compared to Ground-Truthed Biomass Measurement*Error Bars show Standard ErrorBiomass Accumulation Throughout the Growing SeasonBiomass Accumulation Throughout the Growing SeasonBiomass Accumulation Throughout the Growing SeasonBiomass Accumulation Throughout the Growing SeasonSlope Decrease Indicates Breakdown in Ability to Predict Biomass Later in the SeasonConclusion• 2-D approach is a good measure of ground cover and is indicative of early season biomass• 3-D approach correlates better with biomass throughout the season better than the 2-D approach• Future work will involve analysing growth curves• Volume and ground cover are different from each other and are not the same trait as biomassTake-Home Message• Overhead imaging techniques have great potential for use for trait selection in breeding programs• Volume, ground cover, and biomass can all useful in calculating plant growth rate – a desirable trait for breeders.Thank You • Pulse Crop Field Lab Crew & Graduate Students• Agronomy Field Crew & Graduate Students• Department of Computer Sciences, U of S• Dr. Kirstin Bett• Dr. Steve Shirtliffe• Menglu Wang• Dr. Hema Duddu

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Using overhead images to determine volume and ground cover of lentil (Lens culinaris Medik.)

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