Development and Validation of a Model to Combine NDVI and Plant Height for High-Throughput Phenotyping of Herbage Yield in a Perennial Ryegrass Breeding Program
Sensor-based phenotyping technologies may offer a non-destructive, high-throughput and efficient assessment of herbage yield (HY) to replace current inefficient phenotyping methods. This paper assesses the feasibility of combining normalised difference vegetative index (NDVI) from multispectral imag...
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| Format: | Article |
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MDPI AG
2019-10-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/11/21/2494 |
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| author | Alem Gebremedhin Pieter Badenhorst Junping Wang Khageswor Giri German Spangenberg Kevin Smith |
| author_facet | Alem Gebremedhin Pieter Badenhorst Junping Wang Khageswor Giri German Spangenberg Kevin Smith |
| author_sort | Alem Gebremedhin |
| collection | DOAJ |
| description | Sensor-based phenotyping technologies may offer a non-destructive, high-throughput and efficient assessment of herbage yield (HY) to replace current inefficient phenotyping methods. This paper assesses the feasibility of combining normalised difference vegetative index (NDVI) from multispectral imaging and ultrasonic sonar estimates of plant height to estimate HY of single plants in a large perennial ryegrass breeding program. For sensor calibration, fresh HY (FHY) and dry HY (DHY) were acquired destructively, and plant height was measured at four dates each in 2017 and 2018 from a selected subset of 480 plants. Global multiple linear regression models based on K-fold and random split cross-validation methods were used to evaluate the relationship between observed vs. predicted HY. The coefficient of determination (R<sup>2</sup>) = 0.67−0.68 and a root mean square error (RMSE) between 5.43−7.60 g was obtained for the validation of predicted vs. observed DHY. The mean absolute error (MAE) and mean percentage error (MPE) ranged between 3.59−5.44 g and 22−28%, respectively. For the FHY, R<sup>2</sup> values ranged from 0.63 to 0.70, with an RMSE between 23.50 and 33 g, MAE between 15.11 and 24.34 g and MPE between ~22% and 31%. Combining NDVI and plant height is a robust method to enable high-throughput phenotyping of herbage yield in perennial ryegrass breeding programs. |
| first_indexed | 2024-12-13T10:49:10Z |
| format | Article |
| id | doaj.art-78f06763a0974055850a81a7485e0e95 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-12-13T10:49:10Z |
| publishDate | 2019-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-78f06763a0974055850a81a7485e0e952022-12-21T23:49:58ZengMDPI AGRemote Sensing2072-42922019-10-011121249410.3390/rs11212494rs11212494Development and Validation of a Model to Combine NDVI and Plant Height for High-Throughput Phenotyping of Herbage Yield in a Perennial Ryegrass Breeding ProgramAlem Gebremedhin0Pieter Badenhorst1Junping Wang2Khageswor Giri3German Spangenberg4Kevin Smith5Agriculture Victoria Research, Hamilton Centre, Hamilton 3300, AustraliaAgriculture Victoria Research, Hamilton Centre, Hamilton 3300, AustraliaAgriculture Victoria Research, Hamilton Centre, Hamilton 3300, AustraliaAgriculture Victoria Research, AgriBio, Centre for AgriBioscience, Bundoora 3083, AustraliaAgriculture Victoria Research, AgriBio, Centre for AgriBioscience, Bundoora 3083, AustraliaAgriculture Victoria Research, Hamilton Centre, Hamilton 3300, AustraliaSensor-based phenotyping technologies may offer a non-destructive, high-throughput and efficient assessment of herbage yield (HY) to replace current inefficient phenotyping methods. This paper assesses the feasibility of combining normalised difference vegetative index (NDVI) from multispectral imaging and ultrasonic sonar estimates of plant height to estimate HY of single plants in a large perennial ryegrass breeding program. For sensor calibration, fresh HY (FHY) and dry HY (DHY) were acquired destructively, and plant height was measured at four dates each in 2017 and 2018 from a selected subset of 480 plants. Global multiple linear regression models based on K-fold and random split cross-validation methods were used to evaluate the relationship between observed vs. predicted HY. The coefficient of determination (R<sup>2</sup>) = 0.67−0.68 and a root mean square error (RMSE) between 5.43−7.60 g was obtained for the validation of predicted vs. observed DHY. The mean absolute error (MAE) and mean percentage error (MPE) ranged between 3.59−5.44 g and 22−28%, respectively. For the FHY, R<sup>2</sup> values ranged from 0.63 to 0.70, with an RMSE between 23.50 and 33 g, MAE between 15.11 and 24.34 g and MPE between ~22% and 31%. Combining NDVI and plant height is a robust method to enable high-throughput phenotyping of herbage yield in perennial ryegrass breeding programs.https://www.mdpi.com/2072-4292/11/21/2494multispectral imagingherbage yieldhigh-throughput phenotypingndviplant heightultrasonic sonar |
| spellingShingle | Alem Gebremedhin Pieter Badenhorst Junping Wang Khageswor Giri German Spangenberg Kevin Smith Development and Validation of a Model to Combine NDVI and Plant Height for High-Throughput Phenotyping of Herbage Yield in a Perennial Ryegrass Breeding Program Remote Sensing multispectral imaging herbage yield high-throughput phenotyping ndvi plant height ultrasonic sonar |
| title | Development and Validation of a Model to Combine NDVI and Plant Height for High-Throughput Phenotyping of Herbage Yield in a Perennial Ryegrass Breeding Program |
| title_full | Development and Validation of a Model to Combine NDVI and Plant Height for High-Throughput Phenotyping of Herbage Yield in a Perennial Ryegrass Breeding Program |
| title_fullStr | Development and Validation of a Model to Combine NDVI and Plant Height for High-Throughput Phenotyping of Herbage Yield in a Perennial Ryegrass Breeding Program |
| title_full_unstemmed | Development and Validation of a Model to Combine NDVI and Plant Height for High-Throughput Phenotyping of Herbage Yield in a Perennial Ryegrass Breeding Program |
| title_short | Development and Validation of a Model to Combine NDVI and Plant Height for High-Throughput Phenotyping of Herbage Yield in a Perennial Ryegrass Breeding Program |
| title_sort | development and validation of a model to combine ndvi and plant height for high throughput phenotyping of herbage yield in a perennial ryegrass breeding program |
| topic | multispectral imaging herbage yield high-throughput phenotyping ndvi plant height ultrasonic sonar |
| url | https://www.mdpi.com/2072-4292/11/21/2494 |
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