In situ remote sensing as a strategy to predict cotton seed yield
Crop harvest scheduling and profits and losses predications require strategies that estimate crop yield. This work aimed to investigate the contribution of phenological variables using path analysis and remote sensing techniques on cotton boll yield and to generate a model using decision trees that...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Universidade Federal de Uberlândia
2019-11-01
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| Series: | Bioscience Journal |
| Subjects: | |
| Online Access: | http://www.seer.ufu.br/index.php/biosciencejournal/article/view/42261 |
| _version_ | 1818623619670999040 |
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| author | Fabio Henrique Rojo Baio Eder Eujácio da Silva Pedro Henrique Alves Martins Carlos Antônio da Silva Junior Paulo Eduardo Teodoro |
| author_facet | Fabio Henrique Rojo Baio Eder Eujácio da Silva Pedro Henrique Alves Martins Carlos Antônio da Silva Junior Paulo Eduardo Teodoro |
| author_sort | Fabio Henrique Rojo Baio |
| collection | DOAJ |
| description | Crop harvest scheduling and profits and losses predications require strategies that estimate crop yield. This work aimed to investigate the contribution of phenological variables using path analysis and remote sensing techniques on cotton boll yield and to generate a model using decision trees that help predict cotton boll yield. The sampling field was installed in Chapadão do Céu, in an area of 90 ha. The following phenological variables were evaluated at 30 sample points: plant height at 26, 39, 51, 68, 82, 107, 128, and 185 days after emergence (DAE); number of floral buds at 68, 81, 107, 128, and 185 DAE; number of bolls at 185 DAE; Rededge vegetation index at 23, 35, 53, 91, and 168 DAE; and cotton boll yield. The main variables that can be used to predict cotton boll yield are the number of floral buds (at 107 days after emergence) and the Rededge vegetation index (at 53 and 91 days after emergence). To obtain higher cotton boll yields, the Rededge vegetation index must be greater than 39 at 53 days after emergence, and the plant must present at least 14 floral buds at 107 days after emergence. |
| first_indexed | 2024-12-16T18:43:57Z |
| format | Article |
| id | doaj.art-ca993afc57994291891f76fdcdb1d23c |
| institution | Directory Open Access Journal |
| issn | 1981-3163 |
| language | English |
| last_indexed | 2024-12-16T18:43:57Z |
| publishDate | 2019-11-01 |
| publisher | Universidade Federal de Uberlândia |
| record_format | Article |
| series | Bioscience Journal |
| spelling | doaj.art-ca993afc57994291891f76fdcdb1d23c2022-12-21T22:20:55ZengUniversidade Federal de UberlândiaBioscience Journal1981-31632019-11-0135610.14393/BJ-v35n6a2019-4226142261In situ remote sensing as a strategy to predict cotton seed yieldFabio Henrique Rojo BaioEder Eujácio da SilvaPedro Henrique Alves MartinsCarlos Antônio da Silva JuniorPaulo Eduardo TeodoroCrop harvest scheduling and profits and losses predications require strategies that estimate crop yield. This work aimed to investigate the contribution of phenological variables using path analysis and remote sensing techniques on cotton boll yield and to generate a model using decision trees that help predict cotton boll yield. The sampling field was installed in Chapadão do Céu, in an area of 90 ha. The following phenological variables were evaluated at 30 sample points: plant height at 26, 39, 51, 68, 82, 107, 128, and 185 days after emergence (DAE); number of floral buds at 68, 81, 107, 128, and 185 DAE; number of bolls at 185 DAE; Rededge vegetation index at 23, 35, 53, 91, and 168 DAE; and cotton boll yield. The main variables that can be used to predict cotton boll yield are the number of floral buds (at 107 days after emergence) and the Rededge vegetation index (at 53 and 91 days after emergence). To obtain higher cotton boll yields, the Rededge vegetation index must be greater than 39 at 53 days after emergence, and the plant must present at least 14 floral buds at 107 days after emergence.http://www.seer.ufu.br/index.php/biosciencejournal/article/view/42261precision agriculturepath analysisdecision treesgossypium hirsutum |
| spellingShingle | Fabio Henrique Rojo Baio Eder Eujácio da Silva Pedro Henrique Alves Martins Carlos Antônio da Silva Junior Paulo Eduardo Teodoro In situ remote sensing as a strategy to predict cotton seed yield Bioscience Journal precision agriculture path analysis decision trees gossypium hirsutum |
| title | In situ remote sensing as a strategy to predict cotton seed yield |
| title_full | In situ remote sensing as a strategy to predict cotton seed yield |
| title_fullStr | In situ remote sensing as a strategy to predict cotton seed yield |
| title_full_unstemmed | In situ remote sensing as a strategy to predict cotton seed yield |
| title_short | In situ remote sensing as a strategy to predict cotton seed yield |
| title_sort | in situ remote sensing as a strategy to predict cotton seed yield |
| topic | precision agriculture path analysis decision trees gossypium hirsutum |
| url | http://www.seer.ufu.br/index.php/biosciencejournal/article/view/42261 |
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