Using the SCOPE model for potato growth, productivity and yield monitoring under different levels of nitrogen fertilization
Most applications of remote sensing in agricultural crop monitoring use multispectral imaging techniques, but with upcoming hyperspectral missions, the opportunity arises to better estimate pigment absorption and crop structure by exploiting the full solar reflective spectrum. In this study, we demo...
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| Format: | Article |
| Language: | English |
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Elsevier
2022-11-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S156984322200187X |
| _version_ | 1811243547867742208 |
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| author | Egor Prikaziuk Georgios Ntakos Tamara ten Den Pytrik Reidsma Tamme van der Wal Christiaan van der Tol |
| author_facet | Egor Prikaziuk Georgios Ntakos Tamara ten Den Pytrik Reidsma Tamme van der Wal Christiaan van der Tol |
| author_sort | Egor Prikaziuk |
| collection | DOAJ |
| description | Most applications of remote sensing in agricultural crop monitoring use multispectral imaging techniques, but with upcoming hyperspectral missions, the opportunity arises to better estimate pigment absorption and crop structure by exploiting the full solar reflective spectrum. In this study, we demonstrate how hyperspectral time series can be used with the Soil Canopy Observation of Photochemistry and Energy fluxes (SCOPE) model to estimate crop yield variability among fields, crop varieties and nitrogen treatments generically, i.e. without a calibration with in situ, data. Field experiments were conducted in two potato fields in the Netherlands between May and September 2019. The fields were planted with five varieties of potato, under three nitrogen fertilization treatments. By fitting the model to the full VNIR-SWIR spectrum of measured hyperspectral reflectance, we retrieved the model input parameters of Leaf Area Index (LAI), leaf chlorophyll content (Cab) and leaf water content (Cw) and simulated the photosynthesis throughout the season using data of local Automatic Weather Stations (AWS). Statistical analysis of measured and retrieved traits of LAI, Cab and canopy water content showed that two fields responded differently to the treatments, exhibiting fewer classes than were expected based on the experimental design. Potato yield, which was estimated as the sum of photosynthesis flux multiplied by the harvest index of 0.64, correlated with the measured tuber dry weight with R2 0.36 and RMSE 2.5 t ha−1. This study demonstrates that even in the absence of crop or variety specific information, hyperspectral reflectance and local weather data ingested into SCOPE can explain a substantial part of the observed variability in yield among fields. |
| first_indexed | 2024-04-12T14:10:23Z |
| format | Article |
| id | doaj.art-f3cda50289a34aa9a70ba7ca4e7eb039 |
| institution | Directory Open Access Journal |
| issn | 1569-8432 |
| language | English |
| last_indexed | 2024-04-12T14:10:23Z |
| publishDate | 2022-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj.art-f3cda50289a34aa9a70ba7ca4e7eb0392022-12-22T03:29:56ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322022-11-01114102997Using the SCOPE model for potato growth, productivity and yield monitoring under different levels of nitrogen fertilizationEgor Prikaziuk0Georgios Ntakos1Tamara ten Den2Pytrik Reidsma3Tamme van der Wal4Christiaan van der Tol5Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, P.O. Box 217, Enschede, 7500 AE, The Netherlands; Corresponding author.Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, P.O. Box 217, Enschede, 7500 AE, The Netherlands; Business Unit Greenhouse Horticulture, Wageningen University and Research, Droevendaalsesteeg 1, Wageningen, 6708 PB, The NetherlandsPlant Production Systems, Wageningen University and Research, P.O. Box 430, Wageningen, 6700 AK, The NetherlandsPlant Production Systems, Wageningen University and Research, P.O. Box 430, Wageningen, 6700 AK, The NetherlandsAgrosystems Research, Wageningen University and Research, P.O. Box 430, Wageningen, 6700 AK, The Netherlands; AeroVision B.V., Amersfoort, 3811 HN, The NetherlandsFaculty of Geo-Information Science and Earth Observation (ITC), University of Twente, P.O. Box 217, Enschede, 7500 AE, The NetherlandsMost applications of remote sensing in agricultural crop monitoring use multispectral imaging techniques, but with upcoming hyperspectral missions, the opportunity arises to better estimate pigment absorption and crop structure by exploiting the full solar reflective spectrum. In this study, we demonstrate how hyperspectral time series can be used with the Soil Canopy Observation of Photochemistry and Energy fluxes (SCOPE) model to estimate crop yield variability among fields, crop varieties and nitrogen treatments generically, i.e. without a calibration with in situ, data. Field experiments were conducted in two potato fields in the Netherlands between May and September 2019. The fields were planted with five varieties of potato, under three nitrogen fertilization treatments. By fitting the model to the full VNIR-SWIR spectrum of measured hyperspectral reflectance, we retrieved the model input parameters of Leaf Area Index (LAI), leaf chlorophyll content (Cab) and leaf water content (Cw) and simulated the photosynthesis throughout the season using data of local Automatic Weather Stations (AWS). Statistical analysis of measured and retrieved traits of LAI, Cab and canopy water content showed that two fields responded differently to the treatments, exhibiting fewer classes than were expected based on the experimental design. Potato yield, which was estimated as the sum of photosynthesis flux multiplied by the harvest index of 0.64, correlated with the measured tuber dry weight with R2 0.36 and RMSE 2.5 t ha−1. This study demonstrates that even in the absence of crop or variety specific information, hyperspectral reflectance and local weather data ingested into SCOPE can explain a substantial part of the observed variability in yield among fields.http://www.sciencedirect.com/science/article/pii/S156984322200187XSCOPE modelYieldPotato (Solanum tuberosum L.)Time seriesHyperspectral reflectanceRetrieval |
| spellingShingle | Egor Prikaziuk Georgios Ntakos Tamara ten Den Pytrik Reidsma Tamme van der Wal Christiaan van der Tol Using the SCOPE model for potato growth, productivity and yield monitoring under different levels of nitrogen fertilization International Journal of Applied Earth Observations and Geoinformation SCOPE model Yield Potato (Solanum tuberosum L.) Time series Hyperspectral reflectance Retrieval |
| title | Using the SCOPE model for potato growth, productivity and yield monitoring under different levels of nitrogen fertilization |
| title_full | Using the SCOPE model for potato growth, productivity and yield monitoring under different levels of nitrogen fertilization |
| title_fullStr | Using the SCOPE model for potato growth, productivity and yield monitoring under different levels of nitrogen fertilization |
| title_full_unstemmed | Using the SCOPE model for potato growth, productivity and yield monitoring under different levels of nitrogen fertilization |
| title_short | Using the SCOPE model for potato growth, productivity and yield monitoring under different levels of nitrogen fertilization |
| title_sort | using the scope model for potato growth productivity and yield monitoring under different levels of nitrogen fertilization |
| topic | SCOPE model Yield Potato (Solanum tuberosum L.) Time series Hyperspectral reflectance Retrieval |
| url | http://www.sciencedirect.com/science/article/pii/S156984322200187X |
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