Utilizing vegetation indices with optimal wavelengths to predict nitrogen uptake at the flowering stage and wheat yield
Techniques for determining the amount of nitrogen topdressing based on remote sensing during the flowering stage of wheat require highly accurate yield predictions. Optimal wavelength combinations for accurately predicting nitrogen uptake and wheat yield using remote sensing methods remain inconsist...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-08-01
|
| Series: | Plant Production Science |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/1343943X.2025.2543329 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849339124709851136 |
|---|---|
| author | Akina Mizumoto Hiroko Sawada Ryo Terasaki Kou Nakazono Hiroe Yoshida Akihiro Ohsumi Akira Fukushima |
| author_facet | Akina Mizumoto Hiroko Sawada Ryo Terasaki Kou Nakazono Hiroe Yoshida Akihiro Ohsumi Akira Fukushima |
| author_sort | Akina Mizumoto |
| collection | DOAJ |
| description | Techniques for determining the amount of nitrogen topdressing based on remote sensing during the flowering stage of wheat require highly accurate yield predictions. Optimal wavelength combinations for accurately predicting nitrogen uptake and wheat yield using remote sensing methods remain inconsistent. This study aimed to estimate the wheat yield and nitrogen uptake using a portable spectrometer capable of capturing a wide range of wavelengths from 340 to 850 nm. Spectral data were collected at the flowering stage in 2022 and 2023 for the ‘Ayahikari,’ ‘Satonosora,’ and ‘Yumekaori’ varieties. The ratio spectral indices (RSIN and RSIY, identified as vegetation indices with strong correlations to nitrogen uptake at the flowering stage and wheat yield, respectively) were analyzed from the dataset for 2023. Both indices exhibiting the highest coefficient of determination (R2) were derived from the combinations of two wavelengths within the 730–810 nm range. The yield prediction model using the RSIN or RSIY, based on the 2023 dataset, showed goodness-of-fit for the 2022 dataset, achieving an R2 of 0.61 and an RMSE of 1.4 g m− 2 for nitrogen uptake alongside an R2 of 0.50 and an RMSE of 61 g m− 2 for wheat yield. The RSIN and RSIY vegetation indices outperformed the well-known NDVI, GNDVI, RENDVI, and plant height × SPAD value × spike number index in explaining the variation in wheat yield and nitrogen uptake. These findings present important implications for enhancing agricultural practices by providing more accurate and efficient methods for predicting nitrogen uptake and wheat yield. |
| format | Article |
| id | doaj-art-2aa5e4e175cc4e1eb95ce6f32b57559c |
| institution | Kabale University |
| issn | 1343-943X 1349-1008 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Plant Production Science |
| spelling | doaj-art-2aa5e4e175cc4e1eb95ce6f32b57559c2025-08-20T03:44:13ZengTaylor & Francis GroupPlant Production Science1343-943X1349-10082025-08-0111110.1080/1343943X.2025.2543329Utilizing vegetation indices with optimal wavelengths to predict nitrogen uptake at the flowering stage and wheat yieldAkina Mizumoto0Hiroko Sawada1Ryo Terasaki2Kou Nakazono3Hiroe Yoshida4Akihiro Ohsumi5Akira Fukushima6Western Region Agricultural Research Center (Kinki, Chugoku, and Shikoku Regions), National Agriculture and Food Research Organization (NARO), Fukuyama, JapanCentral Region Agricultural Research Center (Kanto, Tokai, and Hokuriku Regions), NARO, Tsukuba, JapanAgricultural Research Institute, Toyama Prefectural Agricultural, Forestry, and Fisheries Research Center, Toyama, JapanCentral Region Agricultural Research Center (Kanto, Tokai, and Hokuriku Regions), NARO, Tsukuba, JapanCentral Region Agricultural Research Center (Kanto, Tokai, and Hokuriku Regions), NARO, Tsukuba, JapanCentral Region Agricultural Research Center (Kanto, Tokai, and Hokuriku Regions), NARO, Tsukuba, JapanCentral Region Agricultural Research Center (Kanto, Tokai, and Hokuriku Regions), NARO, Tsukuba, JapanTechniques for determining the amount of nitrogen topdressing based on remote sensing during the flowering stage of wheat require highly accurate yield predictions. Optimal wavelength combinations for accurately predicting nitrogen uptake and wheat yield using remote sensing methods remain inconsistent. This study aimed to estimate the wheat yield and nitrogen uptake using a portable spectrometer capable of capturing a wide range of wavelengths from 340 to 850 nm. Spectral data were collected at the flowering stage in 2022 and 2023 for the ‘Ayahikari,’ ‘Satonosora,’ and ‘Yumekaori’ varieties. The ratio spectral indices (RSIN and RSIY, identified as vegetation indices with strong correlations to nitrogen uptake at the flowering stage and wheat yield, respectively) were analyzed from the dataset for 2023. Both indices exhibiting the highest coefficient of determination (R2) were derived from the combinations of two wavelengths within the 730–810 nm range. The yield prediction model using the RSIN or RSIY, based on the 2023 dataset, showed goodness-of-fit for the 2022 dataset, achieving an R2 of 0.61 and an RMSE of 1.4 g m− 2 for nitrogen uptake alongside an R2 of 0.50 and an RMSE of 61 g m− 2 for wheat yield. The RSIN and RSIY vegetation indices outperformed the well-known NDVI, GNDVI, RENDVI, and plant height × SPAD value × spike number index in explaining the variation in wheat yield and nitrogen uptake. These findings present important implications for enhancing agricultural practices by providing more accurate and efficient methods for predicting nitrogen uptake and wheat yield.https://www.tandfonline.com/doi/10.1080/1343943X.2025.2543329Nitrogen uptakeportable spectrometervegetation indexwheatyield prediction |
| spellingShingle | Akina Mizumoto Hiroko Sawada Ryo Terasaki Kou Nakazono Hiroe Yoshida Akihiro Ohsumi Akira Fukushima Utilizing vegetation indices with optimal wavelengths to predict nitrogen uptake at the flowering stage and wheat yield Plant Production Science Nitrogen uptake portable spectrometer vegetation index wheat yield prediction |
| title | Utilizing vegetation indices with optimal wavelengths to predict nitrogen uptake at the flowering stage and wheat yield |
| title_full | Utilizing vegetation indices with optimal wavelengths to predict nitrogen uptake at the flowering stage and wheat yield |
| title_fullStr | Utilizing vegetation indices with optimal wavelengths to predict nitrogen uptake at the flowering stage and wheat yield |
| title_full_unstemmed | Utilizing vegetation indices with optimal wavelengths to predict nitrogen uptake at the flowering stage and wheat yield |
| title_short | Utilizing vegetation indices with optimal wavelengths to predict nitrogen uptake at the flowering stage and wheat yield |
| title_sort | utilizing vegetation indices with optimal wavelengths to predict nitrogen uptake at the flowering stage and wheat yield |
| topic | Nitrogen uptake portable spectrometer vegetation index wheat yield prediction |
| url | https://www.tandfonline.com/doi/10.1080/1343943X.2025.2543329 |
| work_keys_str_mv | AT akinamizumoto utilizingvegetationindiceswithoptimalwavelengthstopredictnitrogenuptakeatthefloweringstageandwheatyield AT hirokosawada utilizingvegetationindiceswithoptimalwavelengthstopredictnitrogenuptakeatthefloweringstageandwheatyield AT ryoterasaki utilizingvegetationindiceswithoptimalwavelengthstopredictnitrogenuptakeatthefloweringstageandwheatyield AT kounakazono utilizingvegetationindiceswithoptimalwavelengthstopredictnitrogenuptakeatthefloweringstageandwheatyield AT hiroeyoshida utilizingvegetationindiceswithoptimalwavelengthstopredictnitrogenuptakeatthefloweringstageandwheatyield AT akihiroohsumi utilizingvegetationindiceswithoptimalwavelengthstopredictnitrogenuptakeatthefloweringstageandwheatyield AT akirafukushima utilizingvegetationindiceswithoptimalwavelengthstopredictnitrogenuptakeatthefloweringstageandwheatyield |