Low-cost assessment of grain yield in durum wheat using RGB images

11 Pág.

The pattern of photosynthetic area of the canopy throughout the crop cycle is an important factor for determining grain yield in wheat. This work proposes the use of zenithal RGB images of the canopy taken in natural light conditions to derive vegetation indices as a low-cost approach to predict grain yield. A set of 23 varieties of durum wheat was monitored in three growing conditions (support irrigation, rainfed and late planting) and two sites (Aranjuez and Valladolid, Spain), totalling 6 field trials. For each plot, digital RGB images were taken periodically from seedling emergence to late grain filling. RGB-based Green Area (GA), Greener Area (GGA), Normalized Green Red Difference Index (NGRDI), Triangular Greenness Index (TGI) and a novel photosynthetic area index based on the CIE L * u * v * colour space (u * v * A) were compared to handheld spectroradiometer Normalised Difference Vegetation Index (NDVI) for reference. In the case of the irrigated and late planting trials the best phenotypic predictions of grain yield were achieved with the vegetation indices measured during the last part of the crop cycle (i.e. grain filling). For the rainfed trials the best phenotypic predictions were achieved with indices measured earlier (around heading). Among all the evaluated indices, the novel index performed the best. Considering the heritabilities of the evaluated RGB indices and their genetic correlations with grain yield, index-based predictions of grain yield were best in the early crop stages for both rainfed and irrigated conditions, while for late planting indices measured at different crop stages performed equally well.

The authors of this research would like to thank the field management staff at the experimental stations of Colmenar de Oreja (Aranjuez) of the Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA) and Zamadueñas (Valladolid) of the Instituto de Tecnología Agraria de Castilla y León (ITACyL) for their continued support of our research. This work was supported by MINECO, Spain [project number AGL2016-76527-R] as the primary funding support for the research project; and the project “Formación de Talento Humano de Alto Nivel” [project number BPIN 2013000100103] approved by the “Fondo de Ciencia, Tecnología e Innovación”, from the “Sistema General de Regalías”, “Gobernación del Tolima - Universidad del Tolima, Colombia” as the sole funding source of the first author JAF. JLA acknowledges the support from ICREA Academia, Generalitat de Catalunya, Spain.

Peer reviewed