Hyperspectral Vegetation Indices to Assess Water and Nitrogen Status of Sweet Maize Crop
The deployment of novel technologies in the field of precision farming has risen to the top of global agendas in response to the impact of climate change and the possible shortage of resources such as water and fertilizers. The present research addresses the performance of water and nitrogen-sensiti...
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MDPI AG
2022-09-01
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| Series: | Agronomy |
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| Online Access: | https://www.mdpi.com/2073-4395/12/9/2181 |
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| author | Milica Colovic Kang Yu Mladen Todorovic Vito Cantore Mohamad Hamze Rossella Albrizio Anna Maria Stellacci |
| author_facet | Milica Colovic Kang Yu Mladen Todorovic Vito Cantore Mohamad Hamze Rossella Albrizio Anna Maria Stellacci |
| author_sort | Milica Colovic |
| collection | DOAJ |
| description | The deployment of novel technologies in the field of precision farming has risen to the top of global agendas in response to the impact of climate change and the possible shortage of resources such as water and fertilizers. The present research addresses the performance of water and nitrogen-sensitive narrow-band vegetation indices to evaluate the response of sweet maize (<i>Zea mays</i> var. <i>saccharata</i> L.) to different irrigation and nitrogen regimes. The experiment was carried out in Valenzano, Bari (Southern Italy), during the 2020 growing season. Three irrigation regimes (full irrigation, deficit irrigation, and rainfed) and two nitrogen levels (300 and 50 kg ha<sup>−1</sup>) were tested. During the growing season, a Field Spec Handheld 2 spectroradiometer operating in the range of 325–1075 nm was utilized to capture spectral data regularly. In addition, soil water content, biometric parameters, and physiological parameters were measured. The DATT index, based on near-infrared and red-edge wavelengths, performed better than other indices in explaining the variation in chlorophyll content, whereas the double difference index (DD) showed the greatest correlation with the leaf–gas exchange. The modified normalized difference vegetation index (NNDVI) and the ratio of water band index to normalized difference vegetation index (WBI/NDVI) showed the highest capacity to distinguish the interaction of irrigation x nitrogen, while the best discriminating capability of these indices was under a low nitrogen level. Moreover, red-edge-based indices had higher sensitivity to nitrogen levels compared to the structural and water band indices. Our study highlighted that it is critical to choose proper narrow-band vegetation indices to monitor the plant eco-physiological response to water and nitrogen stresses. |
| first_indexed | 2024-03-10T00:59:03Z |
| format | Article |
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| institution | Directory Open Access Journal |
| issn | 2073-4395 |
| language | English |
| last_indexed | 2024-03-10T00:59:03Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Agronomy |
| spelling | doaj.art-ceb1d53d3815437f8df7a34261be33cb2023-11-23T14:38:41ZengMDPI AGAgronomy2073-43952022-09-01129218110.3390/agronomy12092181Hyperspectral Vegetation Indices to Assess Water and Nitrogen Status of Sweet Maize CropMilica Colovic0Kang Yu1Mladen Todorovic2Vito Cantore3Mohamad Hamze4Rossella Albrizio5Anna Maria Stellacci6Department of Soil, Plant and Food Sciences, University of Bari Aldo Moro, 70126 Bari, ItalyDepartment Life Science Engineering, School of Life Sciences, Technical University of Munich, 85354 Freising, GermanyCIHEAM–Mediterranean Agronomic Institute of Bari, 70010 Valenzano, ItalyInstitute of Sciences of Food Production (ISPA), National Research Council (CNR), Via Amendola, 122/O, 70125 Bari, ItalyCIHEAM–Mediterranean Agronomic Institute of Bari, 70010 Valenzano, ItalyInstitute for Agricultural and Forestry Systems in the Mediterranean (ISAFOM), National Research Council (CNR), Piazzale Enrico Fermi 1, 80055 Portici, ItalyDepartment of Soil, Plant and Food Sciences, University of Bari Aldo Moro, 70126 Bari, ItalyThe deployment of novel technologies in the field of precision farming has risen to the top of global agendas in response to the impact of climate change and the possible shortage of resources such as water and fertilizers. The present research addresses the performance of water and nitrogen-sensitive narrow-band vegetation indices to evaluate the response of sweet maize (<i>Zea mays</i> var. <i>saccharata</i> L.) to different irrigation and nitrogen regimes. The experiment was carried out in Valenzano, Bari (Southern Italy), during the 2020 growing season. Three irrigation regimes (full irrigation, deficit irrigation, and rainfed) and two nitrogen levels (300 and 50 kg ha<sup>−1</sup>) were tested. During the growing season, a Field Spec Handheld 2 spectroradiometer operating in the range of 325–1075 nm was utilized to capture spectral data regularly. In addition, soil water content, biometric parameters, and physiological parameters were measured. The DATT index, based on near-infrared and red-edge wavelengths, performed better than other indices in explaining the variation in chlorophyll content, whereas the double difference index (DD) showed the greatest correlation with the leaf–gas exchange. The modified normalized difference vegetation index (NNDVI) and the ratio of water band index to normalized difference vegetation index (WBI/NDVI) showed the highest capacity to distinguish the interaction of irrigation x nitrogen, while the best discriminating capability of these indices was under a low nitrogen level. Moreover, red-edge-based indices had higher sensitivity to nitrogen levels compared to the structural and water band indices. Our study highlighted that it is critical to choose proper narrow-band vegetation indices to monitor the plant eco-physiological response to water and nitrogen stresses.https://www.mdpi.com/2073-4395/12/9/2181vegetation reflectancebio-physiological crop parametersred-edgewater band indicesnarrow-bands spectral indiceswater and nitrogen stress |
| spellingShingle | Milica Colovic Kang Yu Mladen Todorovic Vito Cantore Mohamad Hamze Rossella Albrizio Anna Maria Stellacci Hyperspectral Vegetation Indices to Assess Water and Nitrogen Status of Sweet Maize Crop Agronomy vegetation reflectance bio-physiological crop parameters red-edge water band indices narrow-bands spectral indices water and nitrogen stress |
| title | Hyperspectral Vegetation Indices to Assess Water and Nitrogen Status of Sweet Maize Crop |
| title_full | Hyperspectral Vegetation Indices to Assess Water and Nitrogen Status of Sweet Maize Crop |
| title_fullStr | Hyperspectral Vegetation Indices to Assess Water and Nitrogen Status of Sweet Maize Crop |
| title_full_unstemmed | Hyperspectral Vegetation Indices to Assess Water and Nitrogen Status of Sweet Maize Crop |
| title_short | Hyperspectral Vegetation Indices to Assess Water and Nitrogen Status of Sweet Maize Crop |
| title_sort | hyperspectral vegetation indices to assess water and nitrogen status of sweet maize crop |
| topic | vegetation reflectance bio-physiological crop parameters red-edge water band indices narrow-bands spectral indices water and nitrogen stress |
| url | https://www.mdpi.com/2073-4395/12/9/2181 |
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