Estimation of aboveground biomass of Alfalfa using field robotics
Alfalfa is a high-yielding forage crop that is widely grown in the United States for grazing, hay and silage making. A proper maintenance of these grasslands is necessary to ensure optimum productivity and profits. The pre-harvest estimation of biomass yield helps in quantifying the profits and opti...
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Elsevier
2024-12-01
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author | Jasanmol Singh Ali Bulent Koc Matias Jose Aguerre John P. Chastain |
author_facet | Jasanmol Singh Ali Bulent Koc Matias Jose Aguerre John P. Chastain |
author_sort | Jasanmol Singh |
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description | Alfalfa is a high-yielding forage crop that is widely grown in the United States for grazing, hay and silage making. A proper maintenance of these grasslands is necessary to ensure optimum productivity and profits. The pre-harvest estimation of biomass yield helps in quantifying the profits and optimizing the forage allocation in advance. Most traditional methods of forage estimation are relatively laborious and time-consuming. Recent developments in contact and remote sensing technologies opened numerous paths for performing aboveground biomass estimation tasks with flexibility and easiness. This study focused on the development of crop height measurement systems for estimating the aboveground biomass yield of Alfalfa (Medicago sativa L.). Five different systems for measuring crop height were evaluated on their ability to estimate aboveground wet and dry biomass. The crop height measurement systems used in this study were Structure-from-Motion, Ultrasound Sensor and Ski, Inertial Measurement Unit and Ski, Inertial Measurement Units and Roller, and a Depth Camera. The results indicated that the system using the Inertial Measurement Unit sensor and ski (IMU-Ski) performed the best among ground-based methods (R2= 0.79; SeY= 3166 kg-wet/ha). The Structure-from-Motion (SfM) method using UAV also provided satisfactory results for biomass predictions (R2= 0.74; SeY= 2543 kg-wet/ha). The models based on IMU-Ski and UAV-based SfM methods were facilitated with vegetation coverage as an additional independent variable to evaluate their effect on biomass predictions. The results indicated that the vegetation coverage did not improve the predictions in any of these systems. Thus, the models based on only the crop height (IMU-Ski and UAV-SfM) were the recommended approaches for Alfalfa biomass estimations. The addition of data points for wide ranges of crop height and vegetation coverage is recommended for future studies to improve the results and ensure the adaptability of these systems in varying environmental conditions. |
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spelling | doaj-art-0d2cece802b34e758dc8de3d84278d8c2024-12-13T11:08:00ZengElsevierSmart Agricultural Technology2772-37552024-12-019100597Estimation of aboveground biomass of Alfalfa using field roboticsJasanmol Singh0Ali Bulent Koc1Matias Jose Aguerre2John P. Chastain3Department of Agricultural Sciences, Clemson University, Clemson SC 29634, USADepartment of Agricultural Sciences, Clemson University, Clemson SC 29634, USA; Corresponding author.Department of Animal and Veterinary Sciences, Clemson University, Clemson SC 29634, USADepartment of Agricultural Sciences, Clemson University, Clemson SC 29634, USAAlfalfa is a high-yielding forage crop that is widely grown in the United States for grazing, hay and silage making. A proper maintenance of these grasslands is necessary to ensure optimum productivity and profits. The pre-harvest estimation of biomass yield helps in quantifying the profits and optimizing the forage allocation in advance. Most traditional methods of forage estimation are relatively laborious and time-consuming. Recent developments in contact and remote sensing technologies opened numerous paths for performing aboveground biomass estimation tasks with flexibility and easiness. This study focused on the development of crop height measurement systems for estimating the aboveground biomass yield of Alfalfa (Medicago sativa L.). Five different systems for measuring crop height were evaluated on their ability to estimate aboveground wet and dry biomass. The crop height measurement systems used in this study were Structure-from-Motion, Ultrasound Sensor and Ski, Inertial Measurement Unit and Ski, Inertial Measurement Units and Roller, and a Depth Camera. The results indicated that the system using the Inertial Measurement Unit sensor and ski (IMU-Ski) performed the best among ground-based methods (R2= 0.79; SeY= 3166 kg-wet/ha). The Structure-from-Motion (SfM) method using UAV also provided satisfactory results for biomass predictions (R2= 0.74; SeY= 2543 kg-wet/ha). The models based on IMU-Ski and UAV-based SfM methods were facilitated with vegetation coverage as an additional independent variable to evaluate their effect on biomass predictions. The results indicated that the vegetation coverage did not improve the predictions in any of these systems. Thus, the models based on only the crop height (IMU-Ski and UAV-SfM) were the recommended approaches for Alfalfa biomass estimations. The addition of data points for wide ranges of crop height and vegetation coverage is recommended for future studies to improve the results and ensure the adaptability of these systems in varying environmental conditions.http://www.sciencedirect.com/science/article/pii/S2772375524002028AlfalfaAboveground biomassUAVGround roverSfMUltrasonic |
spellingShingle | Jasanmol Singh Ali Bulent Koc Matias Jose Aguerre John P. Chastain Estimation of aboveground biomass of Alfalfa using field robotics Smart Agricultural Technology Alfalfa Aboveground biomass UAV Ground rover SfM Ultrasonic |
title | Estimation of aboveground biomass of Alfalfa using field robotics |
title_full | Estimation of aboveground biomass of Alfalfa using field robotics |
title_fullStr | Estimation of aboveground biomass of Alfalfa using field robotics |
title_full_unstemmed | Estimation of aboveground biomass of Alfalfa using field robotics |
title_short | Estimation of aboveground biomass of Alfalfa using field robotics |
title_sort | estimation of aboveground biomass of alfalfa using field robotics |
topic | Alfalfa Aboveground biomass UAV Ground rover SfM Ultrasonic |
url | http://www.sciencedirect.com/science/article/pii/S2772375524002028 |
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