Yield predictions of four hybrids of maize (Zea mays) using multispectral images obtained from UAV in the Coast of Peru
Early assessment of crop development is a key aspect of precision agriculture. Shortening the time of response before a deficit of irrigation, nutrients and damage by diseases is one of the usual concerns in agriculture. Early prediction of crop yields can increase profitability for the farmer’s eco...
| Autores principales: | , , , , , , , , , |
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| Formato: | Artículo |
| Lenguaje: | Inglés |
| Publicado: |
MDPI
2023
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/20.500.12955/2200 https://doi.org/10.3390/agronomy12112630 |
| _version_ | 1855490234801717248 |
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| author | Saravia Navarro, David Salazar Coronel, Wilian Valqui Valqui, Lamberto Quille Mamani, Javier Alvaro Porras Jorge, Zenaida Rossana Corredor Arizapana, Flor Anita Barboza Castillo, Elgar Vásquez Pérez, Héctor Vladimir Casas Diaz, Andrés V. Arbizu Berrocal, Carlos Irvin |
| author_browse | Arbizu Berrocal, Carlos Irvin Barboza Castillo, Elgar Casas Diaz, Andrés V. Corredor Arizapana, Flor Anita Porras Jorge, Zenaida Rossana Quille Mamani, Javier Alvaro Salazar Coronel, Wilian Saravia Navarro, David Valqui Valqui, Lamberto Vásquez Pérez, Héctor Vladimir |
| author_facet | Saravia Navarro, David Salazar Coronel, Wilian Valqui Valqui, Lamberto Quille Mamani, Javier Alvaro Porras Jorge, Zenaida Rossana Corredor Arizapana, Flor Anita Barboza Castillo, Elgar Vásquez Pérez, Héctor Vladimir Casas Diaz, Andrés V. Arbizu Berrocal, Carlos Irvin |
| author_sort | Saravia Navarro, David |
| collection | Repositorio INIA |
| description | Early assessment of crop development is a key aspect of precision agriculture. Shortening the time of response before a deficit of irrigation, nutrients and damage by diseases is one of the usual concerns in agriculture. Early prediction of crop yields can increase profitability for the farmer’s economy. In this study, we aimed to predict the yield of four maize commercial hybrids (Dekalb7508, Advanta9313, MH_INIA619 and Exp_05PMLM) using vegetation indices (VIs). A total of 10 VIs (NDVI, GNDVI, GCI, RVI, NDRE, CIRE, CVI, MCARI, SAVI, and CCCI) were considered for evaluating crop yield and plant cover at 31, 39, 42, 46 and 51 days after sowing (DAS). A multivariate analysis was applied using principal component analysis (PCA), linear regression, and r-Pearson correlation. Highly significant correlations were found between plant cover with VIs at 46 (GNDVI, GCI, RVI, NDRE, CIRE and CCCI) and 51 DAS (GNDVI, GCI, NDRE, CIRE, CVI, MCARI and CCCI). The PCA showed clear discrimination of the dates evaluated with VIs at 31, 39 and 51 DAS. The inclusion of the CIRE and NDRE in the prediction model contributed to estimating the performance, showing greater precision at 51 DAS. The use of unmanned aerial vehicles (UAVs) to monitor crops allows us to optimize resources and helps in making timely decisions in agriculture in Peru. |
| format | Artículo |
| id | INIA2200 |
| institution | Institucional Nacional de Innovación Agraria |
| language | Inglés |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | MDPI |
| publisherStr | MDPI |
| record_format | dspace |
| spelling | INIA22002024-01-26T20:16:42Z Yield predictions of four hybrids of maize (Zea mays) using multispectral images obtained from UAV in the Coast of Peru Saravia Navarro, David Salazar Coronel, Wilian Valqui Valqui, Lamberto Quille Mamani, Javier Alvaro Porras Jorge, Zenaida Rossana Corredor Arizapana, Flor Anita Barboza Castillo, Elgar Vásquez Pérez, Héctor Vladimir Casas Diaz, Andrés V. Arbizu Berrocal, Carlos Irvin Vegetation indices Precision farming Hybrid Phenotyping Remote sensing https://purl.org/pe-repo/ocde/ford#4.01.06 Precision agricultura Phenotyping Remote sensing Zea mays Agricultura de precisión Fenotipado Teledetección Early assessment of crop development is a key aspect of precision agriculture. Shortening the time of response before a deficit of irrigation, nutrients and damage by diseases is one of the usual concerns in agriculture. Early prediction of crop yields can increase profitability for the farmer’s economy. In this study, we aimed to predict the yield of four maize commercial hybrids (Dekalb7508, Advanta9313, MH_INIA619 and Exp_05PMLM) using vegetation indices (VIs). A total of 10 VIs (NDVI, GNDVI, GCI, RVI, NDRE, CIRE, CVI, MCARI, SAVI, and CCCI) were considered for evaluating crop yield and plant cover at 31, 39, 42, 46 and 51 days after sowing (DAS). A multivariate analysis was applied using principal component analysis (PCA), linear regression, and r-Pearson correlation. Highly significant correlations were found between plant cover with VIs at 46 (GNDVI, GCI, RVI, NDRE, CIRE and CCCI) and 51 DAS (GNDVI, GCI, NDRE, CIRE, CVI, MCARI and CCCI). The PCA showed clear discrimination of the dates evaluated with VIs at 31, 39 and 51 DAS. The inclusion of the CIRE and NDRE in the prediction model contributed to estimating the performance, showing greater precision at 51 DAS. The use of unmanned aerial vehicles (UAVs) to monitor crops allows us to optimize resources and helps in making timely decisions in agriculture in Peru. 2023-06-05T17:55:30Z 2023-06-05T17:55:30Z 2022-10-26 info:eu-repo/semantics/article Saravia, D., Salazar, W., Valqui-Valqui, L., Quille-Mamani, J., Porras-Jorge, R., Corredor, F. A., Barboza, E., Vásquez, H. V., Casas Diaz, A. V., & Arbizu, C. I. (2022). Yield predictions of four hybrids of maize (Zea mays) using multispectral images obtained from UAV in the Coast of Peru. Agronomy, 12(11), 2630. doi: 10.3390/agronomy12112630 2073-4395 https://hdl.handle.net/20.500.12955/2200 https://doi.org/10.3390/agronomy12112630 eng urn:issn:2073-4395 Agronomy info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/ application/pdf application/pdf MDPI CH Instituto Nacional de Innovación Agraria Repositorio Institucional - INIA |
| spellingShingle | Vegetation indices Precision farming Hybrid Phenotyping Remote sensing https://purl.org/pe-repo/ocde/ford#4.01.06 Precision agricultura Phenotyping Remote sensing Zea mays Agricultura de precisión Fenotipado Teledetección Saravia Navarro, David Salazar Coronel, Wilian Valqui Valqui, Lamberto Quille Mamani, Javier Alvaro Porras Jorge, Zenaida Rossana Corredor Arizapana, Flor Anita Barboza Castillo, Elgar Vásquez Pérez, Héctor Vladimir Casas Diaz, Andrés V. Arbizu Berrocal, Carlos Irvin Yield predictions of four hybrids of maize (Zea mays) using multispectral images obtained from UAV in the Coast of Peru |
| title | Yield predictions of four hybrids of maize (Zea mays) using multispectral images obtained from UAV in the Coast of Peru |
| title_full | Yield predictions of four hybrids of maize (Zea mays) using multispectral images obtained from UAV in the Coast of Peru |
| title_fullStr | Yield predictions of four hybrids of maize (Zea mays) using multispectral images obtained from UAV in the Coast of Peru |
| title_full_unstemmed | Yield predictions of four hybrids of maize (Zea mays) using multispectral images obtained from UAV in the Coast of Peru |
| title_short | Yield predictions of four hybrids of maize (Zea mays) using multispectral images obtained from UAV in the Coast of Peru |
| title_sort | yield predictions of four hybrids of maize zea mays using multispectral images obtained from uav in the coast of peru |
| topic | Vegetation indices Precision farming Hybrid Phenotyping Remote sensing https://purl.org/pe-repo/ocde/ford#4.01.06 Precision agricultura Phenotyping Remote sensing Zea mays Agricultura de precisión Fenotipado Teledetección |
| url | https://hdl.handle.net/20.500.12955/2200 https://doi.org/10.3390/agronomy12112630 |
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