Remote sensing techniques and stable isotopes as phenotyping tools to assess wheat yield performance: Effects of growing temperature and vernalization

Rezzouk, Fatima Zahra; Gracia‐Romero, Adrian; Kefauver, Shawn C.; Gutiérrez, Nieves Aparicio; Aranjuelo, Íker; Serret, María Dolores; Araus, José Luís

doi:10.1016/j.plantsci.2019.110281

Cited by 20 publications

(11 citation statements)

References 78 publications

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“…These results are also supported by the phenotypic correlations between the 108 individual plots. Negative correlations of the GGA and NDVI measured at anthesis with GY have been reported previously in wheat under Mediterranean conditions ( Rezzouk et al, 2020 ). The relationships of GGA assessed earlier during the crop cycle (at tillering) to GY were positive.…”

Section: Discussionsupporting

confidence: 76%

Comparative Performance of High-Yielding European Wheat Cultivars Under Contrasting Mediterranean Conditions

et al. 2021

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Understanding the interaction between genotype performance and the target environment is the key to improving genetic gain, particularly in the context of climate change. Wheat production is seriously compromised in agricultural regions affected by water and heat stress, such as the Mediterranean basin. Moreover, wheat production may be also limited by the nitrogen availability in the soil. We have sought to dissect the agronomic and physiological traits related to the performance of 12 high-yield European bread wheat varieties under Mediterranean rainfed conditions and different levels of N fertilization during two contrasting crop seasons. Grain yield was more than two times higher in the first season than the second season and was associated with much greater rainfall and lower temperatures. However, the nitrogen effect was rather minor. Genotypic effects existed for the two seasons. While several of the varieties from central/northern Europe yielded more than those from southern Europe during the optimal season, the opposite trend occurred in the dry season. The varieties from central/northern Europe were associated with delayed phenology and a longer crop cycle, while the varieties from southern Europe were characterized by a shorter crop cycle but comparatively higher duration of the reproductive period, associated with an earlier beginning of stem elongation and a greater number of ears per area. However, some of the cultivars from northern Europe maintained a relatively high yield capacity in both seasons. Thus, KWS Siskin from the UK exhibited intermediate phenology, resulting in a relatively long reproductive period, together with a high green area throughout the crop cycle.

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Section: Discussionsupporting

confidence: 76%

Comparative Performance of High-Yielding European Wheat Cultivars Under Contrasting Mediterranean Conditions

et al. 2021

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“…Accordingly, a* and u* measurements are also related to 'greenness', where the values go from high negative (green) to low negative or even positive values (lack of green). Furthermore, Rezzouk et al [64] observed that ground-based RGB imagery presented a higher resolution than aerial images, since they found that the number of pixels per plot decreased drastically when acquiring images aerially. In our case, this was probably not the case since the pixel resolution of RGB and UAV multispectral imagery were <1 cm and 5 cm, respectively.…”

Section: Discussionmentioning

confidence: 99%

Using Unmanned Aerial Vehicle and Ground-Based RGB Indices to Assess Agronomic Performance of Wheat Landraces and Cultivars in a Mediterranean-Type Environment

et al. 2021

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The adaptability and stability of new bread wheat cultivars that can be successfully grown in rainfed conditions are of paramount importance. Plant improvement can be boosted using effective high-throughput phenotyping tools in dry areas of the Mediterranean basin, where drought and heat stress are expected to increase yield instability. Remote sensing has been of growing interest in breeding programs since it is a cost-effective technology useful for assessing the canopy structure as well as the physiological traits of large genotype collections. The purpose of this study was to evaluate the use of a 4-band multispectral camera on-board an unmanned aerial vehicle (UAV) and ground-based RGB imagery to predict agronomic traits as well as quantify the best estimation of leaf area index (LAI) in rainfed conditions. A collection of 365 bread wheat genotypes, including 181 Mediterranean landraces and 184 modern cultivars, was evaluated during two consecutive growing seasons. Several vegetation indices (VI) derived from multispectral UAV and ground-based RGB images were calculated at different image acquisition dates of the crop cycle. The modified triangular vegetation index (MTVI2) proved to have a good accuracy to estimate LAI (R2 = 0.61). Although the stepwise multiple regression analysis showed that grain yield and number of grains per square meter (NGm2) were the agronomic traits most suitable to be predicted, the R2 were low due to field trials were conducted under rainfed conditions. Moreover, the prediction of agronomic traits was slightly better with ground-based RGB VI rather than with UAV multispectral VIs. NDVI and GNDVI, from multispectral images, were present in most of the prediction equations. Repeated measurements confirmed that the ability of VIs to predict yield depends on the range of phenotypic data. The current study highlights the potential use of VI and RGB images as an efficient tool for high-throughput phenotyping under rainfed Mediterranean conditions.

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“…Nevertheless, it was-to our knowledge-the first time that these two indices were related to visual breeder scores. In phenotyping studies, H and NDLab previously proved useful for predicting grain yield or for assessing disease severity in wheat and maize [39,[81][82][83]. MGRVI was the best performing RGB index, although the difference with VARI was minimal.…”

Section: Research Question 1: Visual-based Indices Are Good Proxies Fmentioning

confidence: 99%

Applying RGB- and Thermal-Based Vegetation Indices from UAVs for High-Throughput Field Phenotyping of Drought Tolerance in Forage Grasses

Swaef¹,

Maes

Aper³

et al. 2021

Remote Sensing

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The persistence and productivity of forage grasses, important sources for feed production, are threatened by climate change-induced drought. Breeding programs are in search of new drought tolerant forage grass varieties, but those programs still rely on time-consuming and less consistent visual scoring by breeders. In this study, we evaluate whether Unmanned Aerial Vehicle (UAV) based remote sensing can complement or replace this visual breeder score. A field experiment was set up to test the drought tolerance of genotypes from three common forage types of two different species: Festuca arundinacea, diploid Lolium perenne and tetraploid Lolium perenne. Drought stress was imposed by using mobile rainout shelters. UAV flights with RGB and thermal sensors were conducted at five time points during the experiment. Visual-based indices from different colour spaces were selected that were closely correlated to the breeder score. Furthermore, several indices, in particular H and NDLab, from the HSV (Hue Saturation Value) and CIELab (Commission Internationale de l’éclairage) colour space, respectively, displayed a broad-sense heritability that was as high or higher than the visual breeder score, making these indices highly suited for high-throughput field phenotyping applications that can complement or even replace the breeder score. The thermal-based Crop Water Stress Index CWSI provided complementary information to visual-based indices, enabling the analysis of differences in ecophysiological mechanisms for coping with reduced water availability between species and ploidy levels. All species/types displayed variation in drought stress tolerance, which confirms that there is sufficient variation for selection within these groups of grasses. Our results confirmed the better drought tolerance potential of Festuca arundinacea, but also showed which Lolium perenne genotypes are more tolerant.

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Remote sensing techniques and stable isotopes as phenotyping tools to assess wheat yield performance: Effects of growing temperature and vernalization

Abstract: Araus JL, Remote sensing techniques and stable isotopes as phenotyping tools to assess wheat yield performance: effects of growing temperature and vernalization,

Cited by 20 publications

References 78 publications

Comparative Performance of High-Yielding European Wheat Cultivars Under Contrasting Mediterranean Conditions

Comparative Performance of High-Yielding European Wheat Cultivars Under Contrasting Mediterranean Conditions

Using Unmanned Aerial Vehicle and Ground-Based RGB Indices to Assess Agronomic Performance of Wheat Landraces and Cultivars in a Mediterranean-Type Environment

Applying RGB- and Thermal-Based Vegetation Indices from UAVs for High-Throughput Field Phenotyping of Drought Tolerance in Forage Grasses

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