Models for predicting biometric variables in cowpea using multispectral aerial images.
Models based on vegetation indices (VI) from digital aerial images are promising for predicting biometric variables in agricultural crops. The objective of this study was to generate prediction models for leaf area index (LAI) and shoot dry weight (SDW) of cowpea crops (cultivar BRS-Inhuma) based on VI derived from aerial images captured by a multispectral camera attached to a drone. The study was conducted at the experimental station of the Brazilian Agricultural Research Corporation (Embrapa Mid-North), in Teresina, PI, Brazil (5°05’S, 42°29’W, and altitude of 72 m) from September to October 2022. LAI was measured in the field and in laboratory, while SDW was measured in eight samples at 13, 19, 26, 33, 40, 47, 51, and 61 days after sowing.
| Main Authors: | , , , , , |
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| Other Authors: | |
| Format: | Folhetos biblioteca |
| Language: | eng |
| Published: |
2023
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| Subjects: | Spatial variability, Variabilidade espacial, RPA, Agricultura de Precisão, Sensoriamento Remoto, Precision agriculture, Remote sensing, |
| Online Access: | http://www.infoteca.cnptia.embrapa.br/infoteca/handle/doc/1167239 |
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