Reflectance Measurements from Aerial and Proximal Sensors Provide Similar Precision in Predicting the Rice Yield Response to Mid-Season N Applications
Accurately detecting nitrogen (N) deficiency and determining the need for additional N fertilizer is a key challenge to achieving precise N management in many crops, including rice (<i>Oryza sativa</i> L.). Many remotely sensed vegetation indices (VIs) have shown promise in this regard;...
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MDPI AG
2023-07-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/13/6218 |
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| author | Telha H. Rehman Mark E. Lundy Andre Froes de Borja Reis Nadeem Akbar Bruce A. Linquist |
| author_facet | Telha H. Rehman Mark E. Lundy Andre Froes de Borja Reis Nadeem Akbar Bruce A. Linquist |
| author_sort | Telha H. Rehman |
| collection | DOAJ |
| description | Accurately detecting nitrogen (N) deficiency and determining the need for additional N fertilizer is a key challenge to achieving precise N management in many crops, including rice (<i>Oryza sativa</i> L.). Many remotely sensed vegetation indices (VIs) have shown promise in this regard; however, it is not well-known if VIs measured from different sensors can be used interchangeably. The objective of this study was to quantitatively test and compare the ability of VIs measured from an aerial and proximal sensor to predict the crop yield response to top-dress N fertilizer in rice. Nitrogen fertilizer response trials were established across two years (six site-years) throughout the Sacramento Valley rice-growing region of California. At panicle initiation (PI), unmanned aircraft system (UAS) Normalized Difference Red-Edge Index (NDRE<sub>UAS</sub>) and GreenSeeker (GS) Normalized Difference Vegetation Index (NDVI<sub>GS</sub>) were measured and expressed as a sufficiency index (SI) (VI of N treatment divided by VI of adjacent N-enriched area). Following reflectance measurements, each plot was split into subplots with and without top-dress N fertilizer. All metrics evaluated in this study indicated that both NDRE<sub>UAS</sub> and NDVI<sub>GS</sub> performed similarly with respect to predicting the rice yield response to top-dress N at PI. Utilizing SI measurements prior to top-dress N fertilizer application resulted in a 113% and 69% increase (for NDRE<sub>UAS</sub> and NDVI<sub>GS</sub>, respectively) in the precision of the rice yield response differentiation compared to the effect of applying top-dress N without SI information considered. When the SI measured via NDRE<sub>UAS</sub> and NDVI<sub>GS</sub> at PI was ≤0.97 and 0.96, top-dress N applications resulted in a significant (<i>p</i> < 0.05) increase in crop yield of 0.19 and 0.21 Mg ha<sup>−1</sup>, respectively. These results indicate that both aerial NDRE<sub>UAS</sub> and proximal NDVI<sub>GS</sub> have the potential to accurately predict the rice yield response to PI top-dress N fertilizer in this system and could serve as the basis for developing a decision support tool for farmers that could potentially inform better N management and improve N use efficiency. |
| first_indexed | 2024-03-11T01:28:07Z |
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| id | doaj.art-272bb465c3294924b24ee62e0b2497a2 |
| institution | Directory Open Access Journal |
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| last_indexed | 2024-03-11T01:28:07Z |
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| spelling | doaj.art-272bb465c3294924b24ee62e0b2497a22023-11-18T17:32:17ZengMDPI AGSensors1424-82202023-07-012313621810.3390/s23136218Reflectance Measurements from Aerial and Proximal Sensors Provide Similar Precision in Predicting the Rice Yield Response to Mid-Season N ApplicationsTelha H. Rehman0Mark E. Lundy1Andre Froes de Borja Reis2Nadeem Akbar3Bruce A. Linquist4Department of Plant Sciences, University of California, Davis, CA 95616, USADepartment of Plant Sciences, University of California, Davis, CA 95616, USADivision of Plant Science and Technology, University of Missouri, Columbia, MO 65211, USADepartment of Agronomy, University of Agriculture, Faisalabad 38040, PakistanDepartment of Plant Sciences, University of California, Davis, CA 95616, USAAccurately detecting nitrogen (N) deficiency and determining the need for additional N fertilizer is a key challenge to achieving precise N management in many crops, including rice (<i>Oryza sativa</i> L.). Many remotely sensed vegetation indices (VIs) have shown promise in this regard; however, it is not well-known if VIs measured from different sensors can be used interchangeably. The objective of this study was to quantitatively test and compare the ability of VIs measured from an aerial and proximal sensor to predict the crop yield response to top-dress N fertilizer in rice. Nitrogen fertilizer response trials were established across two years (six site-years) throughout the Sacramento Valley rice-growing region of California. At panicle initiation (PI), unmanned aircraft system (UAS) Normalized Difference Red-Edge Index (NDRE<sub>UAS</sub>) and GreenSeeker (GS) Normalized Difference Vegetation Index (NDVI<sub>GS</sub>) were measured and expressed as a sufficiency index (SI) (VI of N treatment divided by VI of adjacent N-enriched area). Following reflectance measurements, each plot was split into subplots with and without top-dress N fertilizer. All metrics evaluated in this study indicated that both NDRE<sub>UAS</sub> and NDVI<sub>GS</sub> performed similarly with respect to predicting the rice yield response to top-dress N at PI. Utilizing SI measurements prior to top-dress N fertilizer application resulted in a 113% and 69% increase (for NDRE<sub>UAS</sub> and NDVI<sub>GS</sub>, respectively) in the precision of the rice yield response differentiation compared to the effect of applying top-dress N without SI information considered. When the SI measured via NDRE<sub>UAS</sub> and NDVI<sub>GS</sub> at PI was ≤0.97 and 0.96, top-dress N applications resulted in a significant (<i>p</i> < 0.05) increase in crop yield of 0.19 and 0.21 Mg ha<sup>−1</sup>, respectively. These results indicate that both aerial NDRE<sub>UAS</sub> and proximal NDVI<sub>GS</sub> have the potential to accurately predict the rice yield response to PI top-dress N fertilizer in this system and could serve as the basis for developing a decision support tool for farmers that could potentially inform better N management and improve N use efficiency.https://www.mdpi.com/1424-8220/23/13/6218ricenitrogensufficiency indextop-dressUASGreenSeeker |
| spellingShingle | Telha H. Rehman Mark E. Lundy Andre Froes de Borja Reis Nadeem Akbar Bruce A. Linquist Reflectance Measurements from Aerial and Proximal Sensors Provide Similar Precision in Predicting the Rice Yield Response to Mid-Season N Applications Sensors rice nitrogen sufficiency index top-dress UAS GreenSeeker |
| title | Reflectance Measurements from Aerial and Proximal Sensors Provide Similar Precision in Predicting the Rice Yield Response to Mid-Season N Applications |
| title_full | Reflectance Measurements from Aerial and Proximal Sensors Provide Similar Precision in Predicting the Rice Yield Response to Mid-Season N Applications |
| title_fullStr | Reflectance Measurements from Aerial and Proximal Sensors Provide Similar Precision in Predicting the Rice Yield Response to Mid-Season N Applications |
| title_full_unstemmed | Reflectance Measurements from Aerial and Proximal Sensors Provide Similar Precision in Predicting the Rice Yield Response to Mid-Season N Applications |
| title_short | Reflectance Measurements from Aerial and Proximal Sensors Provide Similar Precision in Predicting the Rice Yield Response to Mid-Season N Applications |
| title_sort | reflectance measurements from aerial and proximal sensors provide similar precision in predicting the rice yield response to mid season n applications |
| topic | rice nitrogen sufficiency index top-dress UAS GreenSeeker |
| url | https://www.mdpi.com/1424-8220/23/13/6218 |
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