Use of remote sensing to characterize the phenological development and to predict sweet potato yield in two growing seasons

• Main Author: Tedesco, Danilo [UNESP]
• Publication Date: 2021
• Other Authors: de Oliveira, Maílson Freire [UNESP], dos Santos, Adão Felipe, Costa Silva, Edgard Henrique, de Souza Rolim, Glauco [UNESP], da Silva, Rouverson Pereira [UNESP]
• Format: Article
• Language: eng
• Source: Repositório Institucional da UNESP
• Download full: http://dx.doi.org/10.1016/j.eja.2021.126337; http://hdl.handle.net/11449/233184
• topic: Crop growth; Digital agriculture; Phenology; Reflectance; Smart harvesting; Yield prediction

Sweet potato is a tuberous root with versatility in food products, but also with applications in the energy industry, such as in ethanol production. Developing mechanisms to assess the performance of this crop is important, difficult, and costly, as its commercial product grows below ground. The use of remote sensing to evaluate the development of sweet potato has not yet been reported in the literature. In our study, we showed that spectral vegetation indices are good proxies to monitor the temporal dynamics of crop growth and differentiate phenological stages, regardless of the growing season. The development phases were divided into three stages according to the vegetation indices: (I) initial stage (<200 GDD), when vegetation has little influence on VIs; (II) growth stage (from 200 to 500 GDD), when vegetation has high influence on VIs due to its growth; and (III) stabilization stage (> 500 GDD), when major changes in VIs no longer occur because vegetative growth has ceased. Besides that, we found that these indices can predict crop yield before harvest. In two growing seasons, the smallest errors in yield estimates occurred during the growth stage. In the summer season with NDVI at 355 GDD with errors of 2.63 t ha−1 and in the winter season when GNDVI at 440 GDD had errors of 3.06 t ha−1.