Yield Prediction Using NDVI Values from GreenSeeker and MicaSense Cameras at Different Stages of Winter Wheat Phenology
This work aims to compare and statistically analyze Normalized Difference Vegetation Index (NDVI) values provided by GreenSeeker handheld crop sensor measurements and calculate NDVI values derived from the MicaSense RedEdge-MX Dual Camera, to predict in-season winter wheat (<i>Triticum aestivu...
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MDPI AG
2024-03-01
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| Series: | Drones |
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| Online Access: | https://www.mdpi.com/2504-446X/8/3/88 |
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| author | Sándor Zsebő László Bede Gábor Kukorelli István Mihály Kulmány Gábor Milics Dávid Stencinger Gergely Teschner Zoltán Varga Viktória Vona Attila József Kovács |
| author_facet | Sándor Zsebő László Bede Gábor Kukorelli István Mihály Kulmány Gábor Milics Dávid Stencinger Gergely Teschner Zoltán Varga Viktória Vona Attila József Kovács |
| author_sort | Sándor Zsebő |
| collection | DOAJ |
| description | This work aims to compare and statistically analyze Normalized Difference Vegetation Index (NDVI) values provided by GreenSeeker handheld crop sensor measurements and calculate NDVI values derived from the MicaSense RedEdge-MX Dual Camera, to predict in-season winter wheat (<i>Triticum aestivum</i> L.) yield, improving a yield prediction model with cumulative growing degree days (CGDD) and days from sowing (DFS) data. The study area was located in Mosonmagyaróvár, Hungary. A small-scale field trial in winter wheat was constructed as a randomized block design including Environmental: N-135.3, P<sub>2</sub>O<sub>5</sub>-77.5, K<sub>2</sub>O-0; Balance: N-135.1, P<sub>2</sub>O<sub>5</sub>-91, K<sub>2</sub>O-0; Genezis: N-135, P<sub>2</sub>O<sub>5</sub>-75, K<sub>2</sub>O-45; and Control: N, P, K 0 kg/ha. The crop growth was monitored every second week between April and June 2022 and 2023, respectively. NDVI measurements recorded by GreenSeeker were taken at three pre-defined GPS points for each plot; NDVI values based on the MicaSense camera Red and NIR bands were calculated for the same points. Results showed a significant difference (<i>p</i> ≤ 0.05) between the Control and treated areas by GreenSeeker measurements and Micasense-based calculated NDVI values throughout the growing season, except for the heading stage. At the heading stage, significant differences could be measured by GreenSeeker. However, remotely sensed images did not show significant differences between the treated and Control parcels. Nevertheless, both sensors were found suitable for yield prediction, and 226 DAS was the most appropriate date for predicting winter wheat’s yield in treated plots based on NDVI values and meteorological data. |
| first_indexed | 2024-04-24T18:23:55Z |
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| id | doaj.art-cc08a31d93014e1d96fe2a9e35c3a804 |
| institution | Directory Open Access Journal |
| issn | 2504-446X |
| language | English |
| last_indexed | 2024-04-24T18:23:55Z |
| publishDate | 2024-03-01 |
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| series | Drones |
| spelling | doaj.art-cc08a31d93014e1d96fe2a9e35c3a8042024-03-27T13:33:57ZengMDPI AGDrones2504-446X2024-03-01838810.3390/drones8030088Yield Prediction Using NDVI Values from GreenSeeker and MicaSense Cameras at Different Stages of Winter Wheat PhenologySándor Zsebő0László Bede1Gábor Kukorelli2István Mihály Kulmány3Gábor Milics4Dávid Stencinger5Gergely Teschner6Zoltán Varga7Viktória Vona8Attila József Kovács9Department of Plant Sciences, Albert Kázmér Faculty of Agricultural and Food Sciences, Széchenyi István University, 9200 Mosonmagyaróvár, HungaryDepartment of Plant Sciences, Albert Kázmér Faculty of Agricultural and Food Sciences, Széchenyi István University, 9200 Mosonmagyaróvár, HungaryDepartment of Plant Sciences, Albert Kázmér Faculty of Agricultural and Food Sciences, Széchenyi István University, 9200 Mosonmagyaróvár, HungaryDepartment of Plant Sciences, Albert Kázmér Faculty of Agricultural and Food Sciences, Széchenyi István University, 9200 Mosonmagyaróvár, HungaryDepartment of Precision Agriculture and Digital Farming, Institute of Agronomy, Hungarian University of Agriculture and Life Sciences, 2100 Gödöllő, HungaryDepartment of Plant Sciences, Albert Kázmér Faculty of Agricultural and Food Sciences, Széchenyi István University, 9200 Mosonmagyaróvár, HungaryDepartment of Biosystems and Precision Technologies, Albert Kázmér Faculty of Agricultural and Food Sciences, Széchenyi István University, 9200 Mosonmagyaróvár, HungaryDepartment of Water Management and Natural Ecosystems, Albert Kázmér Faculty of Agricultural and Food Sciences, Széchenyi István University, 9200 Mosonmagyaróvár, HungaryDepartment of Water Management and Natural Ecosystems, Albert Kázmér Faculty of Agricultural and Food Sciences, Széchenyi István University, 9200 Mosonmagyaróvár, HungaryDepartment of Biosystems and Precision Technologies, Albert Kázmér Faculty of Agricultural and Food Sciences, Széchenyi István University, 9200 Mosonmagyaróvár, HungaryThis work aims to compare and statistically analyze Normalized Difference Vegetation Index (NDVI) values provided by GreenSeeker handheld crop sensor measurements and calculate NDVI values derived from the MicaSense RedEdge-MX Dual Camera, to predict in-season winter wheat (<i>Triticum aestivum</i> L.) yield, improving a yield prediction model with cumulative growing degree days (CGDD) and days from sowing (DFS) data. The study area was located in Mosonmagyaróvár, Hungary. A small-scale field trial in winter wheat was constructed as a randomized block design including Environmental: N-135.3, P<sub>2</sub>O<sub>5</sub>-77.5, K<sub>2</sub>O-0; Balance: N-135.1, P<sub>2</sub>O<sub>5</sub>-91, K<sub>2</sub>O-0; Genezis: N-135, P<sub>2</sub>O<sub>5</sub>-75, K<sub>2</sub>O-45; and Control: N, P, K 0 kg/ha. The crop growth was monitored every second week between April and June 2022 and 2023, respectively. NDVI measurements recorded by GreenSeeker were taken at three pre-defined GPS points for each plot; NDVI values based on the MicaSense camera Red and NIR bands were calculated for the same points. Results showed a significant difference (<i>p</i> ≤ 0.05) between the Control and treated areas by GreenSeeker measurements and Micasense-based calculated NDVI values throughout the growing season, except for the heading stage. At the heading stage, significant differences could be measured by GreenSeeker. However, remotely sensed images did not show significant differences between the treated and Control parcels. Nevertheless, both sensors were found suitable for yield prediction, and 226 DAS was the most appropriate date for predicting winter wheat’s yield in treated plots based on NDVI values and meteorological data.https://www.mdpi.com/2504-446X/8/3/88winter wheatprecision agricultureGreenSeekerMicaSense RedEdge-MXNDVIyield prediction |
| spellingShingle | Sándor Zsebő László Bede Gábor Kukorelli István Mihály Kulmány Gábor Milics Dávid Stencinger Gergely Teschner Zoltán Varga Viktória Vona Attila József Kovács Yield Prediction Using NDVI Values from GreenSeeker and MicaSense Cameras at Different Stages of Winter Wheat Phenology Drones winter wheat precision agriculture GreenSeeker MicaSense RedEdge-MX NDVI yield prediction |
| title | Yield Prediction Using NDVI Values from GreenSeeker and MicaSense Cameras at Different Stages of Winter Wheat Phenology |
| title_full | Yield Prediction Using NDVI Values from GreenSeeker and MicaSense Cameras at Different Stages of Winter Wheat Phenology |
| title_fullStr | Yield Prediction Using NDVI Values from GreenSeeker and MicaSense Cameras at Different Stages of Winter Wheat Phenology |
| title_full_unstemmed | Yield Prediction Using NDVI Values from GreenSeeker and MicaSense Cameras at Different Stages of Winter Wheat Phenology |
| title_short | Yield Prediction Using NDVI Values from GreenSeeker and MicaSense Cameras at Different Stages of Winter Wheat Phenology |
| title_sort | yield prediction using ndvi values from greenseeker and micasense cameras at different stages of winter wheat phenology |
| topic | winter wheat precision agriculture GreenSeeker MicaSense RedEdge-MX NDVI yield prediction |
| url | https://www.mdpi.com/2504-446X/8/3/88 |
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