Abstract
There is a growing need for developing high-throughput tools for crop phenotyping that would increase the rate of genetic improvement. In most cases, the indicators used for this purpose are related with canopy structure (often acquired with RGB cameras and multispectral sensors allowing the calculation of NDVI), but using approaches related with the crop physiology are rare. High-resolution hyperspectral remote sensing imagery provides optical indices related to physiological condition through the quantification of photosynthetic pigment and chlorophyll fluorescence emission. This study demonstrates the use of narrow-band indicators of stress as a potential tool for phenotyping under rainfed conditions using two airborne datasets acquired over a wheat experiment with 150 plots comprising two species and 50 varieties (bread and durum wheat). The flights were performed at the early stem elongation stage and during the milking stage. Physiological measurements made at the time of flights demonstrated that the second flight was made during the terminal stress, known to largely determine final yield under rainfed conditions. The hyperspectral imagery enabled the extraction of thermal, radiance, and reflectance spectra from 260 spectral bands from each plot for the calculation of indices related to photosynthetic pigment absorption in the visible and red-edge regions, the quantification of chlorophyll fluorescence emission, as well as structural indices related to canopy structure. Under the conditions of this study, the structural indices (i.e., NDVI) did not show a good performance at predicting yield, probably because of the large effects of terminal water stress. Thermal indices, indices related to chlorophyll fluorescence (calculated using the FLD method), and carotenoids pigment indices (PRI and CAR) demonstrated to be better suited for screening complex traits such as crop yield. The study concludes that the indicators derived from high-resolution thermal and hyperspectral airborne imagery are efficient tools for field-based phenotyping providing additional information to standard NDVI imagery currently used.
Highlights
Wheat provides 20% of the global population’s calorie intake and a similar percentage of its daily protein [1]
This study demonstrated that thermal and hyperspectral imagery provides indices that display a close link with plant functioning, show potential for wheat yield screening and phenotyping under real field breeding trial conditions
High-resolution imagery was acquired with thermal and hyperspectral cameras installed on-board a manned aircraft that flew over a field trial for wheat phenotyping on two separate dates
Summary
Wheat provides 20% of the global population’s calorie intake and a similar percentage of its daily protein [1]. The global average rate of yield increase for wheat is 0.9% per year, while predictions of increase in demand reach 2.4% [2]. This means that the rate of genetic improvement required in the near future is greater than those currently being achieved [3]. Well-focused high-throughput phenotyping will be crucially important in developing new avenues for genetic improvement [4]. Field-based phenotyping (FBP) is recognized as the only approach capable of delivering the required throughput and an accurate description of trait expression in real-world cropping systems [6,8]. In spite of recent progress, FBP remains a bottleneck for future advance in breeding [9]
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