Assessment of Nitrogen Nutrition Index of Winter Wheat Canopy from Visible Images for a Dynamic Monitoring of N Requirements
Hand-held chlorophyll meters or leaf-clip-type sensors indirectly and instantaneously measure leaf N content. They can provide an N nutrition index (NNI) value that is crucial information for adjusting the amount of N fertilizer to the actual N status of the plant. Although these measurements are no...
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| Format: | Article |
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MDPI AG
2023-05-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/15/10/2510 |
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| author | Christelle Gée Emmanuel Denimal Maël de Yparraguirre Laurence Dujourdy Anne-Sophie Voisin |
| author_facet | Christelle Gée Emmanuel Denimal Maël de Yparraguirre Laurence Dujourdy Anne-Sophie Voisin |
| author_sort | Christelle Gée |
| collection | DOAJ |
| description | Hand-held chlorophyll meters or leaf-clip-type sensors indirectly and instantaneously measure leaf N content. They can provide an N nutrition index (NNI) value that is crucial information for adjusting the amount of N fertilizer to the actual N status of the plant. Although these measurements are non-invasive and non-destructive, they require numerous repetitions at the canopy scale. The objective of this work was to explore the potential of visible images to predict nitrogen status in winter wheat crops from estimating NNI and to compare these results with those deduced from classical methods. Based on a dark green colour index (DGCI), which combines hue, saturation and brightness, a normalized DGCI (nDGCI) was proposed as the ratio between the measurements of the study microplot and those of the over-fertilized microplot. The methodology was performed on winter wheat microplots with a nitrogen gradient. Half of the microplots were grown with a single cultivar (LG Absalon) and the other half with a mixture of four wheat cultivars. The impact of optical device (digital camera or smartphone), the white balance (Manual or Automatic), the crop growth stage (two-nodes or heading) and cultivars (single or mixed) on the relationship between (DGCI, nDGCI) and NNI was evaluated. The results showed a close correlation between the nDGCI values and the NNI_NTester values, especially on a single cultivar (LG Absalon; R<sup>2</sup> = 0.73 up to 0.91 with smartphone). It suggested that the relationship is highly sensitive to the wheat cultivar. This approach with no specific calibration of images is promising for the estimation of N requirements in wheat field. |
| first_indexed | 2024-03-11T03:22:13Z |
| format | Article |
| id | doaj.art-3aea88f4d7e14582a6a0eddcd4486424 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-11T03:22:13Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-3aea88f4d7e14582a6a0eddcd44864242023-11-18T03:06:07ZengMDPI AGRemote Sensing2072-42922023-05-011510251010.3390/rs15102510Assessment of Nitrogen Nutrition Index of Winter Wheat Canopy from Visible Images for a Dynamic Monitoring of N RequirementsChristelle Gée0Emmanuel Denimal1Maël de Yparraguirre2Laurence Dujourdy3Anne-Sophie Voisin4Agroécologie, INRAE, Institut Agro, Université Bourgogne Franche-Comté, F-21000 Dijon, FranceInstitut Agro, Cellule d’appui à la Recherche en Science des Données, F-21000 Dijon, FranceAgroécologie, INRAE, Institut Agro, Université Bourgogne Franche-Comté, F-21000 Dijon, FranceInstitut Agro, Cellule d’appui à la Recherche en Science des Données, F-21000 Dijon, FranceAgroécologie, INRAE, Institut Agro, Université Bourgogne Franche-Comté, F-21000 Dijon, FranceHand-held chlorophyll meters or leaf-clip-type sensors indirectly and instantaneously measure leaf N content. They can provide an N nutrition index (NNI) value that is crucial information for adjusting the amount of N fertilizer to the actual N status of the plant. Although these measurements are non-invasive and non-destructive, they require numerous repetitions at the canopy scale. The objective of this work was to explore the potential of visible images to predict nitrogen status in winter wheat crops from estimating NNI and to compare these results with those deduced from classical methods. Based on a dark green colour index (DGCI), which combines hue, saturation and brightness, a normalized DGCI (nDGCI) was proposed as the ratio between the measurements of the study microplot and those of the over-fertilized microplot. The methodology was performed on winter wheat microplots with a nitrogen gradient. Half of the microplots were grown with a single cultivar (LG Absalon) and the other half with a mixture of four wheat cultivars. The impact of optical device (digital camera or smartphone), the white balance (Manual or Automatic), the crop growth stage (two-nodes or heading) and cultivars (single or mixed) on the relationship between (DGCI, nDGCI) and NNI was evaluated. The results showed a close correlation between the nDGCI values and the NNI_NTester values, especially on a single cultivar (LG Absalon; R<sup>2</sup> = 0.73 up to 0.91 with smartphone). It suggested that the relationship is highly sensitive to the wheat cultivar. This approach with no specific calibration of images is promising for the estimation of N requirements in wheat field.https://www.mdpi.com/2072-4292/15/10/2510wheatDGCIproximal sensingfertilizationnitrogen nutrition indexN-tester |
| spellingShingle | Christelle Gée Emmanuel Denimal Maël de Yparraguirre Laurence Dujourdy Anne-Sophie Voisin Assessment of Nitrogen Nutrition Index of Winter Wheat Canopy from Visible Images for a Dynamic Monitoring of N Requirements Remote Sensing wheat DGCI proximal sensing fertilization nitrogen nutrition index N-tester |
| title | Assessment of Nitrogen Nutrition Index of Winter Wheat Canopy from Visible Images for a Dynamic Monitoring of N Requirements |
| title_full | Assessment of Nitrogen Nutrition Index of Winter Wheat Canopy from Visible Images for a Dynamic Monitoring of N Requirements |
| title_fullStr | Assessment of Nitrogen Nutrition Index of Winter Wheat Canopy from Visible Images for a Dynamic Monitoring of N Requirements |
| title_full_unstemmed | Assessment of Nitrogen Nutrition Index of Winter Wheat Canopy from Visible Images for a Dynamic Monitoring of N Requirements |
| title_short | Assessment of Nitrogen Nutrition Index of Winter Wheat Canopy from Visible Images for a Dynamic Monitoring of N Requirements |
| title_sort | assessment of nitrogen nutrition index of winter wheat canopy from visible images for a dynamic monitoring of n requirements |
| topic | wheat DGCI proximal sensing fertilization nitrogen nutrition index N-tester |
| url | https://www.mdpi.com/2072-4292/15/10/2510 |
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