Unmanned aerial vehicle imagery prediction of sorghum leaf area index under water stress, seeding density, and nitrogen fertilization conditions in the Sahel
2024
Dembele, Joseph, Sékou B. | Gano, Boubacar | Mbaye, Modou | Doumbia, Mohamed | Dembele, Léonce, Lamine | Kouressy, Mamoutou | Teme, Niaba | Vaksmann, Michel | Diouf, Diaga | Audebert, Alain | Centre d'Etude Regional Pour l'Amelioration de l'Adaptation A la Secheresse (CERAAS) | Institut sénégalais de recherches agricoles [Dakar] (ISRA) | Institut d'Economie Rurale (IER) | Université Cheikh Anta Diop de Dakar [Sénégal] (UCAD) | Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier ; Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Montpellier (UM) | Département Systèmes Biologiques (Cirad-BIOS) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad) | This research activity was funded by CIRAD, also in part by Bill and Melinda Gates foundation under Sorghum Genotyping Tools project, and benefit the facilities of the Centre d’Etude Régional pour l’Amélioration de l’Adaptation à la Sécheresse (CERAAS).
International audience
显示更多 [+] 显示较少 [-]英语. Sahelian Africa must meet the challenge of providing enough food to meet its growing population. Therefore, novel breeding and intensive production methods are needed to mitigate this challenge. The objective of this study was to calibrate and validate sorghum varieties leaf area index (LAI) values estimated from Unmanned Aerial Vehicle (UAV) at different growing seasons in Senegal and Mali. To achieve this objective, four experiments were conducted with 14 sorghum (sorghum bicolor) varieties between 2017 and 2019. At the study sites, LAI was measured and crop reflectance was measured with a multispectral camera mounted on a UAV. The study showed that normalized difference vegetation index (NDVI) and simple ratio (SR) were highly correlated to the area index. The results of validation model revealed a better prediction of measured LAI from NDVI (R-2 = 0.92) and SR (R-2 = 0.89) vegetation indices in 2019 dry season in Senegal. In addition, the LAI predictions for Mali from NDVI (p < 0.01) and SR (p < 0.01) were highly correlated. Findings showed that vegetation indices can be used to estimate LAI in Mali and Sahel.
显示更多 [+] 显示较少 [-]