Selecting High Forage-Yielding Alfalfa Populations in a Mediterranean Drought-Prone Environment Using High-Throughput Phenotyping

Noushahi H.A.; Inostroza, L; Barahona, V; Espinoza S; Ovalle, C; Quitral, K; Lobos, G.A; Guerra F.P.; Kefauver, SC; del Pozo, A

Keywords: forage yield, canopy temperature, Unmanned aerial vehicles (UAV), RGB images, thermal camera

Abstract

Alfalfa is a deep-rooted perennial forage crop with diverse drought-tolerant traits. This study evaluated 250 alfalfa half-sib populations over three growing seasons (2021–2023) under irrigated and rainfed conditions in the Mediterranean drought-prone region of Central Chile (Cauquenes), aiming to identify high-yielding, drought-tolerant populations using remote sensing. Specifically, we assessed RGB-derived indices and canopy temperature difference (CTD; Tc ? Ta) as proxies for forage yield (FY). The results showed considerable variation in FY across populations. Under rainfed conditions, winter FY ranged from 1.4 to 6.1 Mg ha?1 and total FY from 3.7 to 14.7 Mg ha?1. Under irrigation, winter FY reached up to 8.2 Mg ha?1 and total FY up to 25.1 Mg ha?1. The AlfaL4-5 (SARDI7), AlfaL57-7 (WL903), and AlfaL62-9 (Baldrich350) populations consistently produced the highest yields across regimes. RGB indices such as hue, saturation, b*, v*, GA, and GGA positively correlated with FY, while intensity, lightness, a*, and u* correlated negatively. CTD showed a significant negative correlation with FY across all seasons and water regimes. These findings highlight the potential of RGB imaging and CTD as effective, high-throughput field phenotyping tools for selecting drought-resilient alfalfa genotypes in Mediterranean environments. © 2025 by the authors.

Más información

Título según WOS: Selecting High Forage-Yielding Alfalfa Populations in a Mediterranean Drought-Prone Environment Using High-Throughput Phenotyping
Título según SCOPUS: Selecting High Forage-Yielding Alfalfa Populations in a Mediterranean Drought-Prone Environment Using High-Throughput Phenotyping
Título de la Revista: Remote Sensing
Volumen: 17
Número: 9
Editorial: Multidisciplinary Digital Publishing Institute (MDPI)
Fecha de publicación: 2025
Idioma: English
DOI:

10.3390/rs17091517

Notas: ISI, SCOPUS