Evaluation of Coffee Plants Transplanted to an Area with Surface and Deep Liming Based on Multispectral Indices Acquired Using Unmanned Aerial Vehicles
The use of new technologies to monitor and evaluate the management of coffee crops allowed for a significant increase in productivity. Precision coffee farming has leveraged the development of this commodity by using remote sensing and Unmanned Aerial Vehicles (UAVs). However, the success of coffee...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-10-01
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| Series: | Agronomy |
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| Online Access: | https://www.mdpi.com/2073-4395/13/10/2623 |
| _version_ | 1797575045869993984 |
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| author | Rafael Alexandre Pena Barata Gabriel Araújo e Silva Ferraz Nicole Lopes Bento Daniel Veiga Soares Lucas Santos Santana Diego Bedin Marin Drucylla Guerra Mattos Felipe Schwerz Giuseppe Rossi Leonardo Conti Gianluca Bambi |
| author_facet | Rafael Alexandre Pena Barata Gabriel Araújo e Silva Ferraz Nicole Lopes Bento Daniel Veiga Soares Lucas Santos Santana Diego Bedin Marin Drucylla Guerra Mattos Felipe Schwerz Giuseppe Rossi Leonardo Conti Gianluca Bambi |
| author_sort | Rafael Alexandre Pena Barata |
| collection | DOAJ |
| description | The use of new technologies to monitor and evaluate the management of coffee crops allowed for a significant increase in productivity. Precision coffee farming has leveraged the development of this commodity by using remote sensing and Unmanned Aerial Vehicles (UAVs). However, the success of coffee farming in the country also resulted from management practices, including liming management in the soils. This study aimed to evaluate the response of coffee seedlings transplanted to areas subjected to deep liming in comparison to conventional (surface) liming, using vegetation indices (VIs) generated by multispectral images acquired using UAVs. The study area was overflown bimonthly by UAVs to measure the plant height, crown diameter, and chlorophyll content in the field. The VIs were generated and compared with the data measured in the field using linear time graphs and a correlation analysis. Linear regression was performed to predict the biophysical parameters as a function of the VIs. A significant difference was found only in the chlorophyll content. Most indices were correlated with the biophysical parameters, particularly the green chlorophyll index (GCI) and the canopy area calculated via vectorization. Therefore, UAVs proved to be effective coffee monitoring tools and can be recommended for coffee producers. |
| first_indexed | 2024-03-10T21:30:45Z |
| format | Article |
| id | doaj.art-d560df76010f40408f4232861d496d32 |
| institution | Directory Open Access Journal |
| issn | 2073-4395 |
| language | English |
| last_indexed | 2024-03-10T21:30:45Z |
| publishDate | 2023-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Agronomy |
| spelling | doaj.art-d560df76010f40408f4232861d496d322023-11-19T15:22:47ZengMDPI AGAgronomy2073-43952023-10-011310262310.3390/agronomy13102623Evaluation of Coffee Plants Transplanted to an Area with Surface and Deep Liming Based on Multispectral Indices Acquired Using Unmanned Aerial VehiclesRafael Alexandre Pena Barata0Gabriel Araújo e Silva Ferraz1Nicole Lopes Bento2Daniel Veiga Soares3Lucas Santos Santana4Diego Bedin Marin5Drucylla Guerra Mattos6Felipe Schwerz7Giuseppe Rossi8Leonardo Conti9Gianluca Bambi10Agricultural Engineering Department, Federal University of Lavras, Lavras 37203-202, BrazilAgricultural Engineering Department, Federal University of Lavras, Lavras 37203-202, BrazilAgricultural Engineering Department, Federal University of Lavras, Lavras 37203-202, BrazilAgricultural Engineering Department, Federal University of Lavras, Lavras 37203-202, BrazilAgricultural Engineering Department, Federal University of Lavras, Lavras 37203-202, BrazilAgricultural Research Company of Minas Gerais (EPAMIG), Viçosa 36571-000, BrazilAgricultural Department, Federal University of Lavras, Lavras 37203-202, BrazilAgricultural Engineering Department, Federal University of Lavras, Lavras 37203-202, BrazilDepartment of Agriculture, Food, Environment and Forestry, University of Florence, 50145 Florence, ItalyDepartment of Agriculture, Food, Environment and Forestry, University of Florence, 50145 Florence, ItalyDepartment of Agriculture, Food, Environment and Forestry, University of Florence, 50145 Florence, ItalyThe use of new technologies to monitor and evaluate the management of coffee crops allowed for a significant increase in productivity. Precision coffee farming has leveraged the development of this commodity by using remote sensing and Unmanned Aerial Vehicles (UAVs). However, the success of coffee farming in the country also resulted from management practices, including liming management in the soils. This study aimed to evaluate the response of coffee seedlings transplanted to areas subjected to deep liming in comparison to conventional (surface) liming, using vegetation indices (VIs) generated by multispectral images acquired using UAVs. The study area was overflown bimonthly by UAVs to measure the plant height, crown diameter, and chlorophyll content in the field. The VIs were generated and compared with the data measured in the field using linear time graphs and a correlation analysis. Linear regression was performed to predict the biophysical parameters as a function of the VIs. A significant difference was found only in the chlorophyll content. Most indices were correlated with the biophysical parameters, particularly the green chlorophyll index (GCI) and the canopy area calculated via vectorization. Therefore, UAVs proved to be effective coffee monitoring tools and can be recommended for coffee producers.https://www.mdpi.com/2073-4395/13/10/2623liming managementremote sensingUnmanned Aerial Vehicleseedling transplantingvegetation indices |
| spellingShingle | Rafael Alexandre Pena Barata Gabriel Araújo e Silva Ferraz Nicole Lopes Bento Daniel Veiga Soares Lucas Santos Santana Diego Bedin Marin Drucylla Guerra Mattos Felipe Schwerz Giuseppe Rossi Leonardo Conti Gianluca Bambi Evaluation of Coffee Plants Transplanted to an Area with Surface and Deep Liming Based on Multispectral Indices Acquired Using Unmanned Aerial Vehicles Agronomy liming management remote sensing Unmanned Aerial Vehicle seedling transplanting vegetation indices |
| title | Evaluation of Coffee Plants Transplanted to an Area with Surface and Deep Liming Based on Multispectral Indices Acquired Using Unmanned Aerial Vehicles |
| title_full | Evaluation of Coffee Plants Transplanted to an Area with Surface and Deep Liming Based on Multispectral Indices Acquired Using Unmanned Aerial Vehicles |
| title_fullStr | Evaluation of Coffee Plants Transplanted to an Area with Surface and Deep Liming Based on Multispectral Indices Acquired Using Unmanned Aerial Vehicles |
| title_full_unstemmed | Evaluation of Coffee Plants Transplanted to an Area with Surface and Deep Liming Based on Multispectral Indices Acquired Using Unmanned Aerial Vehicles |
| title_short | Evaluation of Coffee Plants Transplanted to an Area with Surface and Deep Liming Based on Multispectral Indices Acquired Using Unmanned Aerial Vehicles |
| title_sort | evaluation of coffee plants transplanted to an area with surface and deep liming based on multispectral indices acquired using unmanned aerial vehicles |
| topic | liming management remote sensing Unmanned Aerial Vehicle seedling transplanting vegetation indices |
| url | https://www.mdpi.com/2073-4395/13/10/2623 |
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