scholarly journals Transcriptomic data of leaves from eight sunflower lines and their sixteen hybrids under water deficit

OCL ◽  
2020 ◽  
Vol 27 ◽  
pp. 48
Author(s):  
Louise Gody ◽  
Harold Duruflé ◽  
Nicolas Blanchet ◽  
Clément Carré ◽  
Ludovic Legrand ◽  
...  

This article describes how the transcriptomic data were produced on sunflower plants subjected to water deficit. Twenty-four sunflower (Helianthus annuus) genotypes were selected to represent genetic diversity within cultivated sunflower and included both inbred lines and their hybrids. Drought stress was applied to plants in pots at the vegetative stage using the high-throughput phenotyping platform Heliaphen. Here, we provide transcriptomic data from sunflower leaves. These data differentiate both plant water status and the different genotypes. They constitute a valuable resource to the community to study adaptation of crops to drought and the transcriptomic basis of heterosis.

2020 ◽  
Author(s):  
Thierry Balliau ◽  
Harold Duruflé ◽  
Nicolas Blanchet ◽  
Mélisande Blein-Nicolas ◽  
Nicolas B. Langlade ◽  
...  

AbstractThis article describes how the proteomic data were produced on sunflower plants subjected to water deficit. Twenty-four sunflower genotypes were selected to represent genetic diversity within cultivated sunflower. They included both inbred lines and their hybridsWater deficit was applied to plants in pots at the vegetative stage using the high-throughput phenotyping platform Heliaphen. Here, we provide proteomic data from sunflower leaves corresponding to the identification of 3062 proteins and the quantification of 1211 of them in these 24 genotypes grown in two watering conditions. These data differentiate both treatment and the different genotypes and constitute a valuable resource to the community to study adaptation of crops to drought and the molecular basis of heterosis.


OCL ◽  
2021 ◽  
Vol 28 ◽  
pp. 12
Author(s):  
Thierry Balliau ◽  
Harold Duruflé ◽  
Nicolas Blanchet ◽  
Mélisande Blein-Nicolas ◽  
Nicolas B. Langlade ◽  
...  

This article describes a proteomic data set produced from sunflower plants subjected to water deficit. Twenty-four sunflower genotypes were selected to represent genetic diversity within cultivated sunflower. They included both inbred lines and their hybrids. Water deficit was applied to plants in pots at the vegetative stage using the high-throughput phenotyping platform Heliaphen. We present here the identification of 3062 proteins and the quantification of 1211 of them in the leaves of the 24 genotypes grown under two watering conditions. These data allow the study of both the effects of genetic variations and watering conditions. They constitute a valuable resource for the community to study adaptation of crops to drought and the molecular basis of heterosis.


2021 ◽  
Vol 22 (15) ◽  
pp. 8266
Author(s):  
Minsu Kim ◽  
Chaewon Lee ◽  
Subin Hong ◽  
Song Lim Kim ◽  
Jeong-Ho Baek ◽  
...  

Drought is a main factor limiting crop yields. Modern agricultural technologies such as irrigation systems, ground mulching, and rainwater storage can prevent drought, but these are only temporary solutions. Understanding the physiological, biochemical, and molecular reactions of plants to drought stress is therefore urgent. The recent rapid development of genomics tools has led to an increasing interest in phenomics, i.e., the study of phenotypic plant traits. Among phenomic strategies, high-throughput phenotyping (HTP) is attracting increasing attention as a way to address the bottlenecks of genomic and phenomic studies. HTP provides researchers a non-destructive and non-invasive method yet accurate in analyzing large-scale phenotypic data. This review describes plant responses to drought stress and introduces HTP methods that can detect changes in plant phenotypes in response to drought.


2021 ◽  
Author(s):  
Pablo Berríos ◽  
Abdelmalek Temnani ◽  
Susana Zapata ◽  
Manuel Forcén ◽  
Sandra Martínez-Pedreño ◽  
...  

<p>Mandarin is one of the most important Citrus cultivated in Spain and the sustainability of the crop is subject to a constant pressure for water resources among the productive sectors and to a high climatic demand conditions and low rainfall (about 250 mm per year). The availability of irrigation water in the Murcia Region is generally close to 3,500 m<sup>3</sup> per ha and year, so it is only possible to satisfy 50 - 60% of the late mandarin ETc, which requires about 5,500 m<sup>3</sup> per ha. For this reason, it is necessary to provide tools to farmers in order to control the water applied in each phenological phase without promoting levels of severe water stress to the crop that negatively affect the sustainability of farms located in semi-arid conditions. Stem water potential (SWP) is a plant water status indicator very sensitive to water deficit, although its measurement is manual, discontinuous and on a small-scale.  In this way, indicators measured on a larger scale are necessary to achieve integrating the water status of the crop throughout the farm. Thus, the aim of this study was to determine the sensitivity to water deficit of different hyperspectral single bands (HSB) and their relationship with the midday SWP in mandarin trees submitted to severe water stress in different phenological phases. Four different irrigation treatments were assessed: i) a control (CTL), irrigated at 100% of the ETc throughout the growing season to satisfy plant water requirements and three water stress treatments that were irrigated at 60% of ETc throughout the season – corresponding to the real irrigation water availability – except  during: ii) the end of phase I and beginning of phase II (IS IIa), iii) the first half of phase II (IS IIb) and iv) phase III of fruit growth (IS III), which irrigation was withheld until values of -1.8 MPa of SWP or a water stress integral of 60 MPa day<sup>-1</sup>. When these threshold values were reached, the spectral reflectance values were measured between 350 and 2500 nm using a leaf level spectroradiometer to 20 mature and sunny leaves on 4 trees per treatment. Twenty-four HVI and HSB were calculated and a linear correlation was made between each of them with SWP, where the ρ940 and ρ1250 nm single bands reflectance presented r-Pearson values of -0.78** and -0.83***, respectively. Two linear regression curves fitting were made: SWP (MPa) = -11.05 ∙ ρ940 + 7.8014 (R<sup>2</sup> =0.61) and SWP (MPa) = -13.043 ∙ ρ1250 + 8.9757 (R<sup>2</sup> =0.69). These relationships were obtained with three different fruit diameters (35, 50 and 65 mm) and in a range between -0.7 and -1.6 MPa of SWP. Results obtained show the possibility of using these single bands in the detection of water stress in adult mandarin trees, and thus propose a sustainable and efficient irrigation scheduling by means of unmanned aerial vehicles equipped with sensors to carry out an automated control of the plant water status and with a suitable temporal and spatial scale to apply precision irrigation.</p>


Author(s):  
Kelly Easterday ◽  
Chippie Kislik ◽  
Tod E. Dawson ◽  
Sean Hogan ◽  
Maggi Kelly

Unmanned aerial vehicles (UAVs) equipped with multispectral sensors present an opportunity to monitor vegetation with on-demand high spatial and temporal resolution. In this study, we use multispectral imagery from quadcopter UAVs to monitor the progression of a water manipulation experiment on a common shrub, Baccharis pilularis (coyote brush), at the Blue Oak Ranch Reserve (BORR) near San Jose, California. We recorded multispectral data from the plants at several altitudes with nearly hourly intervals to explore the relationship between two common spectral indices, NDVI and NDRE, and plant water content and water potential, as physiological metrics of plant water status, across a gradient of water deficit. An examination of the spatial and temporal thresholds at which water limitations were most detectable revealed that the best separation between levels of water deficit were at higher resolution (lower flying height), and in the morning (NDVI) and early morning (NDRE). We found that both measures were able to identify moisture deficit in plants and distinguish them from control and watered plants; however, NDVI was better able to distinguish between treatments than NDRE and was more positively correlated with field measurements of plant water content than NDRE. Finally, we explored how relationships between spectral indices and water status changed when the imagery was scaled to courser resolutions provided by satellite-based imagery (PlanetScope) and found that PlanetScope data was able to capture the overall trend in treatments but was not able to capture subtle changes in water content. These kinds of experiments that evaluate the relationship between direct field measurements and UAV camera sensitivity are needed to enable translation of field-based physiology measurements to landscape or regional scales.


Rice ◽  
2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Paulo Henrique Ramos Guimarães ◽  
Isabela Pereira de Lima ◽  
Adriano Pereira de Castro ◽  
Anna Cristina Lanna ◽  
Patrícia Guimarães Santos Melo ◽  
...  

Abstract Background The root system plays a major role in plant growth and development and root system architecture is reported to be the main trait related to plant adaptation to drought. However, phenotyping root systems in situ is not suited to high-throughput methods, leading to the development of non-destructive methods for evaluations in more or less controlled root environments. This study used a root phenotyping platform with a panel of 20 japonica rice accessions in order to: (i) assess their genetic diversity for a set of structural and morphological root traits and classify the different types; (ii) analyze the plastic response of their root system to a water deficit at reproductive phase and (iii) explore the ability of the platform for high-throughput phenotyping of root structure and morphology. Results High variability for the studied root traits was found in the reduced set of accessions. Using eight selected traits under irrigated conditions, five root clusters were found that differed in root thickness, branching index and the pattern of fine and thick root distribution along the profile. When water deficit occurred at reproductive phase, some accessions significantly reduced root growth compared to the irrigated treatment, while others stimulated it. It was found that root cluster, as defined under irrigated conditions, could not predict the plastic response of roots under drought. Conclusions This study revealed the possibility of reconstructing the structure of root systems from scanned images. It was thus possible to significantly class root systems according to simple structural traits, opening up the way for using such a platform for medium to high-throughput phenotyping. The study also highlighted the uncoupling between root structures under non-limiting water conditions and their response to drought.


2015 ◽  
Vol 66 (18) ◽  
pp. 5581-5593 ◽  
Author(s):  
Vincent Vadez ◽  
Jana Kholová ◽  
Grégoire Hummel ◽  
Uladzimir Zhokhavets ◽  
S.K. Gupta ◽  
...  

2017 ◽  
Vol 189 ◽  
pp. 137-147 ◽  
Author(s):  
Xun Wu ◽  
Wenjing Zhang ◽  
Wen Liu ◽  
Qiang Zuo ◽  
Jianchu Shi ◽  
...  

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