Prediction of leaf nitrogen in sugarcane (Saccharum spp.) by Vis-NIR-SWIR spectroradiometry
Nitrogen is one of the essential nutrients for the production of agricultural crops, participating in a complex interaction among soil, plant and the atmosphere. Therefore, its monitoring is important both economically and environmentally. The aim of this work was to estimate the leaf nitrogen conte...
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Elsevier
2024-03-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844024028500 |
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| author | Peterson Ricardo Fiorio Carlos Augusto Alves Cardoso Silva Rodnei Rizzo José Alexandre Melo Demattê Ana Cláudia dos Santos Luciano Marcelo Andrade da Silva |
| author_facet | Peterson Ricardo Fiorio Carlos Augusto Alves Cardoso Silva Rodnei Rizzo José Alexandre Melo Demattê Ana Cláudia dos Santos Luciano Marcelo Andrade da Silva |
| author_sort | Peterson Ricardo Fiorio |
| collection | DOAJ |
| description | Nitrogen is one of the essential nutrients for the production of agricultural crops, participating in a complex interaction among soil, plant and the atmosphere. Therefore, its monitoring is important both economically and environmentally. The aim of this work was to estimate the leaf nitrogen contents in sugarcane from hyperspectral reflectance data during different vegetative stages of the plant. The assessments were performed from an experiment designed in completely randomized blocks, with increasing nitrogen doses (0, 60, 120 and 180 kg ha−1). The acquisition of the spectral data occurred at different stages of crop development (67, 99, 144, 164, 200, 228, 255 and 313 days after cutting; DAC). In the laboratory, the hyperspectral responses of the leaves and the Leaf Nitrogen Contents (LNC) were obtained. The hyperspectral data and the LNC values were used to generate spectral models employing the technique of Partial Least Squares Regression (PLSR) Analysis, also with the calculation of the spectral bands of greatest relevance, by the Variable Importance in Projection (VIP). In general, the increase in LNC promoted a smaller reflectance in all wavelengths in the visible (400–680 nm). Acceptable models were obtained (R2 > 0.70 and RMSE <1.41 g kg−1), the most robust of which were those generated from spectra in the visible (400–680 nm) and red-edge (680–750 nm), with values of R2 > 0.81 and RMSE <1.24 g kg−1. An independent validation, leave-one-date-out cross validation (LOOCV), was performed using data from other collections, which confirmed the robustness and the possibility of LNC prediction in new data sets, derived, for instance, from samplings subsequent to the period of study. |
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| language | English |
| last_indexed | 2024-04-24T23:15:48Z |
| publishDate | 2024-03-01 |
| publisher | Elsevier |
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| series | Heliyon |
| spelling | doaj.art-0d4db53416ea42a0bdfe6019f57f6d612024-03-17T07:56:23ZengElsevierHeliyon2405-84402024-03-01105e26819Prediction of leaf nitrogen in sugarcane (Saccharum spp.) by Vis-NIR-SWIR spectroradiometryPeterson Ricardo Fiorio0Carlos Augusto Alves Cardoso Silva1Rodnei Rizzo2José Alexandre Melo Demattê3Ana Cláudia dos Santos Luciano4Marcelo Andrade da Silva5Department of Biosystems Engineering, “Luiz de Queiroz” College of Agriculture, University of São Paulo, 13418900, Piracicaba, São Paulo, Brazil; Corresponding author.Department of Biosystems Engineering, “Luiz de Queiroz” College of Agriculture, University of São Paulo, 13418900, Piracicaba, São Paulo, BrazilEnvironmental Analysis and Geoprocessing Laboratory, Center for Nuclear Energy in Agriculture, University of São Paulo, Piracicaba, São Paulo, BrazilDepartment of Soil Science, “Luiz de Queiroz” College of Agriculture, University of São Paulo, 13418900, Piracicaba, São Paulo, BrazilDepartment of Biosystems Engineering, “Luiz de Queiroz” College of Agriculture, University of São Paulo, 13418900, Piracicaba, São Paulo, BrazilDepartment of Exact Science, “Luiz de Queiroz” College of Agriculture, University of São Paulo, 13418900, Piracicaba, São Paulo, BrazilNitrogen is one of the essential nutrients for the production of agricultural crops, participating in a complex interaction among soil, plant and the atmosphere. Therefore, its monitoring is important both economically and environmentally. The aim of this work was to estimate the leaf nitrogen contents in sugarcane from hyperspectral reflectance data during different vegetative stages of the plant. The assessments were performed from an experiment designed in completely randomized blocks, with increasing nitrogen doses (0, 60, 120 and 180 kg ha−1). The acquisition of the spectral data occurred at different stages of crop development (67, 99, 144, 164, 200, 228, 255 and 313 days after cutting; DAC). In the laboratory, the hyperspectral responses of the leaves and the Leaf Nitrogen Contents (LNC) were obtained. The hyperspectral data and the LNC values were used to generate spectral models employing the technique of Partial Least Squares Regression (PLSR) Analysis, also with the calculation of the spectral bands of greatest relevance, by the Variable Importance in Projection (VIP). In general, the increase in LNC promoted a smaller reflectance in all wavelengths in the visible (400–680 nm). Acceptable models were obtained (R2 > 0.70 and RMSE <1.41 g kg−1), the most robust of which were those generated from spectra in the visible (400–680 nm) and red-edge (680–750 nm), with values of R2 > 0.81 and RMSE <1.24 g kg−1. An independent validation, leave-one-date-out cross validation (LOOCV), was performed using data from other collections, which confirmed the robustness and the possibility of LNC prediction in new data sets, derived, for instance, from samplings subsequent to the period of study.http://www.sciencedirect.com/science/article/pii/S2405844024028500Remote sensingNitrogen fertilizationSpectral reflectanceCross validation |
| spellingShingle | Peterson Ricardo Fiorio Carlos Augusto Alves Cardoso Silva Rodnei Rizzo José Alexandre Melo Demattê Ana Cláudia dos Santos Luciano Marcelo Andrade da Silva Prediction of leaf nitrogen in sugarcane (Saccharum spp.) by Vis-NIR-SWIR spectroradiometry Heliyon Remote sensing Nitrogen fertilization Spectral reflectance Cross validation |
| title | Prediction of leaf nitrogen in sugarcane (Saccharum spp.) by Vis-NIR-SWIR spectroradiometry |
| title_full | Prediction of leaf nitrogen in sugarcane (Saccharum spp.) by Vis-NIR-SWIR spectroradiometry |
| title_fullStr | Prediction of leaf nitrogen in sugarcane (Saccharum spp.) by Vis-NIR-SWIR spectroradiometry |
| title_full_unstemmed | Prediction of leaf nitrogen in sugarcane (Saccharum spp.) by Vis-NIR-SWIR spectroradiometry |
| title_short | Prediction of leaf nitrogen in sugarcane (Saccharum spp.) by Vis-NIR-SWIR spectroradiometry |
| title_sort | prediction of leaf nitrogen in sugarcane saccharum spp by vis nir swir spectroradiometry |
| topic | Remote sensing Nitrogen fertilization Spectral reflectance Cross validation |
| url | http://www.sciencedirect.com/science/article/pii/S2405844024028500 |
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