Rapid Diagnosis of Nitrogen Nutrition Status in Summer Maize over Its Life Cycle by a Multi-Index Synergy Model Using Ground Hyperspectral and UAV Multispectral Sensor Data
Global climate change and the spread of COVID-19 have caused widespread concerns about food security. The development of smart agriculture could contribute to food security; moreover, the targeted and accurate management of crop nitrogen is a topic of concern in the field of smart agriculture. Unman...
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| Format: | Article |
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MDPI AG
2022-01-01
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| Series: | Atmosphere |
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| Online Access: | https://www.mdpi.com/2073-4433/13/1/122 |
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| author | Nana Han Baozhong Zhang Yu Liu Zhigong Peng Qingyun Zhou Zheng Wei |
| author_facet | Nana Han Baozhong Zhang Yu Liu Zhigong Peng Qingyun Zhou Zheng Wei |
| author_sort | Nana Han |
| collection | DOAJ |
| description | Global climate change and the spread of COVID-19 have caused widespread concerns about food security. The development of smart agriculture could contribute to food security; moreover, the targeted and accurate management of crop nitrogen is a topic of concern in the field of smart agriculture. Unmanned aerial vehicle (UAV) spectroscopy has demonstrated versatility in the rapid and non-destructive estimation of nitrogen in summer maize. Previous studies focused on the entire growth season or early stages of summer maize; however, systematic studies on the diagnosis of nitrogen that consider the entire life cycle are few. This study aimed to: (1) construct a practical diagnostic model of the nitrogen life cycle of summer maize based on ground hyperspectral data and UAV multispectral sensor data and (2) evaluate this model and express a change in the trend of nitrogen nutrient status at a spatiotemporal scale. Here, a comprehensive data set consisting of a time series of crop biomass, nitrogen concentration, hyperspectral reflectance, and UAV multispectral reflectance from field experiments conducted during the growing seasons of 2017–2019 with summer maize cultivars grown under five different nitrogen fertilization levels in Beijing, China, were considered. The results demonstrated that the entire life cycle of summer maize was divided into four stages, viz., V6 (mean leaf area index (LAI) = 0.67), V10 (mean LAI = 1.94), V12 (mean LAI = 3.61), and VT-R6 (mean LAI = 3.94), respectively; moreover, the multi-index synergy model demonstrated high accuracy and good stability. The best spectral indexes of these four stages were GBNDVI, TCARI, NRI, and MSAVI2, respectively. The thresholds of the spectral index of nitrogen sufficiency in the V6, V10, V12, VT, R1, R2, and R3–R6 stages were 0.83–0.44, −0.22 to −5.23, 0.42–0.35, 0.69–0.87, 0.60–0.75, 0.49–0.61, and 0.42–0.53, respectively. The simulated nitrogen concentration at the various growth stages of summer maize was consistent with the actual spatial distribution. |
| first_indexed | 2024-03-10T01:56:26Z |
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| institution | Directory Open Access Journal |
| issn | 2073-4433 |
| language | English |
| last_indexed | 2024-03-10T01:56:26Z |
| publishDate | 2022-01-01 |
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| series | Atmosphere |
| spelling | doaj.art-eb34ca02898546b9bb46d0a04cb98c052023-11-23T12:57:31ZengMDPI AGAtmosphere2073-44332022-01-0113112210.3390/atmos13010122Rapid Diagnosis of Nitrogen Nutrition Status in Summer Maize over Its Life Cycle by a Multi-Index Synergy Model Using Ground Hyperspectral and UAV Multispectral Sensor DataNana Han0Baozhong Zhang1Yu Liu2Zhigong Peng3Qingyun Zhou4Zheng Wei5State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, ChinaState Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, ChinaState Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, ChinaState Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, ChinaState Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, ChinaState Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, ChinaGlobal climate change and the spread of COVID-19 have caused widespread concerns about food security. The development of smart agriculture could contribute to food security; moreover, the targeted and accurate management of crop nitrogen is a topic of concern in the field of smart agriculture. Unmanned aerial vehicle (UAV) spectroscopy has demonstrated versatility in the rapid and non-destructive estimation of nitrogen in summer maize. Previous studies focused on the entire growth season or early stages of summer maize; however, systematic studies on the diagnosis of nitrogen that consider the entire life cycle are few. This study aimed to: (1) construct a practical diagnostic model of the nitrogen life cycle of summer maize based on ground hyperspectral data and UAV multispectral sensor data and (2) evaluate this model and express a change in the trend of nitrogen nutrient status at a spatiotemporal scale. Here, a comprehensive data set consisting of a time series of crop biomass, nitrogen concentration, hyperspectral reflectance, and UAV multispectral reflectance from field experiments conducted during the growing seasons of 2017–2019 with summer maize cultivars grown under five different nitrogen fertilization levels in Beijing, China, were considered. The results demonstrated that the entire life cycle of summer maize was divided into four stages, viz., V6 (mean leaf area index (LAI) = 0.67), V10 (mean LAI = 1.94), V12 (mean LAI = 3.61), and VT-R6 (mean LAI = 3.94), respectively; moreover, the multi-index synergy model demonstrated high accuracy and good stability. The best spectral indexes of these four stages were GBNDVI, TCARI, NRI, and MSAVI2, respectively. The thresholds of the spectral index of nitrogen sufficiency in the V6, V10, V12, VT, R1, R2, and R3–R6 stages were 0.83–0.44, −0.22 to −5.23, 0.42–0.35, 0.69–0.87, 0.60–0.75, 0.49–0.61, and 0.42–0.53, respectively. The simulated nitrogen concentration at the various growth stages of summer maize was consistent with the actual spatial distribution.https://www.mdpi.com/2073-4433/13/1/122hyperspectral sensorUAV multispectral sensornitrogen concentrationsynergy modelsummer maize |
| spellingShingle | Nana Han Baozhong Zhang Yu Liu Zhigong Peng Qingyun Zhou Zheng Wei Rapid Diagnosis of Nitrogen Nutrition Status in Summer Maize over Its Life Cycle by a Multi-Index Synergy Model Using Ground Hyperspectral and UAV Multispectral Sensor Data Atmosphere hyperspectral sensor UAV multispectral sensor nitrogen concentration synergy model summer maize |
| title | Rapid Diagnosis of Nitrogen Nutrition Status in Summer Maize over Its Life Cycle by a Multi-Index Synergy Model Using Ground Hyperspectral and UAV Multispectral Sensor Data |
| title_full | Rapid Diagnosis of Nitrogen Nutrition Status in Summer Maize over Its Life Cycle by a Multi-Index Synergy Model Using Ground Hyperspectral and UAV Multispectral Sensor Data |
| title_fullStr | Rapid Diagnosis of Nitrogen Nutrition Status in Summer Maize over Its Life Cycle by a Multi-Index Synergy Model Using Ground Hyperspectral and UAV Multispectral Sensor Data |
| title_full_unstemmed | Rapid Diagnosis of Nitrogen Nutrition Status in Summer Maize over Its Life Cycle by a Multi-Index Synergy Model Using Ground Hyperspectral and UAV Multispectral Sensor Data |
| title_short | Rapid Diagnosis of Nitrogen Nutrition Status in Summer Maize over Its Life Cycle by a Multi-Index Synergy Model Using Ground Hyperspectral and UAV Multispectral Sensor Data |
| title_sort | rapid diagnosis of nitrogen nutrition status in summer maize over its life cycle by a multi index synergy model using ground hyperspectral and uav multispectral sensor data |
| topic | hyperspectral sensor UAV multispectral sensor nitrogen concentration synergy model summer maize |
| url | https://www.mdpi.com/2073-4433/13/1/122 |
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