scholarly journals Dissecting the Genetics of Early Vigour to Design Drought-Adapted Wheat

2022 ◽  
Vol 12 ◽  
Author(s):  
Stjepan Vukasovic ◽  
Samir Alahmad ◽  
Jack Christopher ◽  
Rod J. Snowdon ◽  
Andreas Stahl ◽  
...  
Keyword(s):  
Leaf Area ◽  
Vegetation Index ◽  
Genome Wide Association Study ◽  
Rapid Development ◽  
Infrared Light ◽  
Stay Green ◽  
Genetic Determination ◽  
A Genome ◽  
Normalised Difference Vegetation Index ◽  
Early Vigour

Due to the climate change and an increased frequency of drought, it is of enormous importance to identify and to develop traits that result in adaptation and in improvement of crop yield stability in drought-prone regions with low rainfall. Early vigour, defined as the rapid development of leaf area in early developmental stages, is reported to contribute to stronger plant vitality, which, in turn, can enhance resilience to erratic drought periods. Furthermore, early vigour improves weed competitiveness and nutrient uptake. Here, two sets of a multi-reference nested association mapping (MR-NAM) population of bread wheat (Triticum aestivum ssp. aestivum L.) were used to investigate early vigour in a rain-fed field environment for 3 years, and additionally assessed under controlled conditions in a greenhouse experiment. The normalised difference vegetation index (NDVI) calculated from red/infrared light reflectance was used to quantify early vigour in the field, revealing a correlation (p < 0.05; r = 0.39) between the spectral measurement and the length of the second leaf. Under controlled environmental conditions, the measured projected leaf area, using a green-pixel counter, was also correlated to the leaf area of the second leaf (p < 0.05; r = 0.38), as well as to the recorded biomass (p < 0.01; r = 0.71). Subsequently, genetic determination of early vigour was tested by conducting a genome-wide association study (GWAS) for the proxy traits, revealing 42 markers associated with vegetation index and two markers associated with projected leaf area. There are several quantitative trait loci that are collocated with loci for plant developmental traits including plant height on chromosome 2D (log10 (P) = 3.19; PVE = 0.035), coleoptile length on chromosome 1B (–log10 (P) = 3.24; PVE = 0.112), as well as stay-green and vernalisation on chromosome 5A (–log10 (P) = 3.14; PVE = 0.115).

scholarly journals Genome-Wide Association Mapping for Heat and Drought Adaptive Traits in Pea

Genes ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1897
Author(s):  
Endale G. Tafesse ◽  
Krishna K. Gali ◽  
V. B. Reddy Lachagari ◽  
Rosalind Bueckert ◽  
Thomas D. Warkentin
Keyword(s):  
Association Mapping ◽  
Candidate Genes ◽  
Vegetation Index ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Nucleotide Polymorphisms ◽  
Adaptive Traits ◽  
Flowering Duration ◽  
Genome Wide ◽  
A Genome

Heat and drought, individually or in combination, limit pea productivity. Fortunately, substantial genetic diversity exists in pea germplasm for traits related to abiotic stress resistance. Understanding the genetic basis of resistance could accelerate the development of stress-adaptive cultivars. We conducted a genome-wide association study (GWAS) in pea on six stress-adaptive traits with the aim to detect the genetic regions controlling these traits. One hundred and thirty-five genetically diverse pea accessions were phenotyped in field studies across three or five environments under stress and control conditions. To determine marker trait associations (MTAs), a total of 16,877 valuable single nucleotide polymorphisms (SNPs) were used in association analysis. Association mapping detected 15 MTAs that were significantly (p ≤ 0.0005) associated with the six stress-adaptive traits averaged across all environments and consistent in multiple individual environments. The identified MTAs were four for lamina wax, three for petiole wax, three for stem thickness, two for the flowering duration, one for the normalized difference vegetation index (NDVI), and two for the normalized pigment and chlorophyll index (NPCI). Sixteen candidate genes were identified within a 15 kb distance from either side of the markers. The detected MTAs and candidate genes have prospective use towards selecting stress-hardy pea cultivars in marker-assisted selection.

scholarly journals DELINEATING ECO-SENSITIVE ZONES USING GEOSPATIAL METHODS – A TEST CASE OF JHILMIL JHEEL CONSERVATION RESERVE

2018 ◽  
Vol IV-5 ◽  
pp. 459-466
Author(s):  
V. Prakash ◽  
S. Saran ◽  
G. Talukdar
Keyword(s):  
Habitat Suitability ◽  
Vegetation Index ◽  
Rapid Development ◽  
Test Case ◽  
Anthropogenic Pressures ◽  
Focal Species ◽  
Maxent Model ◽  
Normalised Difference Vegetation Index ◽  
Long Time ◽  
Swamp Deer

<p><strong>Abstract.</strong> Most of the protected areas (PAs) in India have a hard boundary; very rarely having a transition zone to minimise the negative human wildlife interface. With increasing anthropogenic pressures, areas surrounding PAs are becoming integral for conservation. Government of India introduced a concept of Eco-sensitive Zones (ESZ) around PAs to minimise anthropogenic pressures and regulate rapid development in these areas. However, delineation of ESZs is a complex process and may take a long time. In this paper, a novel geospatial approach has been presented to delineate ESZ using a species centric approach. A case study using Swamp deer (<i>Rucervus duvaucelli duvaucelli</i>) as focal species was explored for its potential to delineate ESZ around protected area Jhilmil Jheel Conservation Reserve (JJCR) located in Uttarakhand India. Maximum entropy or Maxent model was used to identify habitat suitability. Normalised difference vegetation index (NDVI), altitude, land cover and distance to roads were used as co-variates. Seasonal variations for habitat suitability were also considered. In this study habitat suitability map of swamp deer was further rationalised based on habitat fragmentation and management limitations and proposed as ESZ of JJCR. This approach for delineation of ESZ can be very useful for PAs in India which have focal species and are yet to declare their ESZ.</p>

The validation of a model estimating the Leaf Area Index of grasslands in southern China

2013 ◽  
Vol 35 (3) ◽  
pp. 245 ◽  
Author(s):  
Chengming Sun ◽  
Zhengguo Sun ◽  
Tao Liu ◽  
Doudou Guo ◽  
Shaojie Mu ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Vegetation Index ◽  
Mean Squared Error ◽  
Southern China ◽  
Carbon Sink ◽  
Measurement Data ◽  
Light Transmittance ◽  
Area Index ◽  
Normalised Difference Vegetation Index

In order to estimate the leaf area index (LAI) over large areas in southern China, this paper analysed the relationships between normalised difference vegetation index (NDVI) and the vegetation light transmittance and the extinction coefficient based on the use of moderate resolution imaging spectroradiometer data. By using the improved Beer–Lambert Law, a model was constructed to estimate the LAI in the grassy mountains and slopes of southern China with NDVI as the independent variable. The model was validated with field measurement data from different locations and different years in the grassland mountains and slopes of southern China. The results showed that there was a good correlation between the simulated and observed LAI values, and the values of R2 achieved were high. The relative root mean squared error was between 0.109 and 0.12. This indicated that the model was reliable. The above results provided the theoretical basis for the effective management of the grassland resources in southern China and the effective estimation of grassland carbon sink.

scholarly journals GWAS Analysis of Wheat Pre-breeding Germplasm for Terminal Drought Stress Using Next Generation Sequencing Technology

2020 ◽  
Author(s):  
Sajid Shokat ◽  
Deepmala Sehgal ◽  
Fulai Liu ◽  
Sukhwinder Singh
Keyword(s):  
Drought Stress ◽  
Candidate Genes ◽  
Vegetation Index ◽  
Genome Wide Association Study ◽  
Potential Candidate ◽  
Terminal Drought ◽  
Genome Wide ◽  
Population Structure Analysis ◽  
A Genome ◽  
Terminal Drought Stress

Bread wheat (Triticum aestivum L.) is one of the most important cereal crops for food security. Of all the stresses that curtail wheat productivity, drought has the most detrimental effects. Especially terminal drought stress i.e. at the time of flowering imposes a big challenge to sustain grain production. In the current study, 339 pre-breeding lines derived from three-way crosses of exotics x elite lines were evaluated in the irrigated and drought stress environments at Obregon, Mexico for the year 2016 and 2018. Drought significantly reduced yield (Y), spike length (SL), number of grains per spikes (NGS) and thousand kernel weight (TKW) by 46.4, 19.2, 23.5 and 25.9%, respectively in comparison to irrigated conditions. Kernel abortion (KA), highly correlated with Y, increased significantly (11.6%) under drought stress environment. Population structure analysis in this panel revealed three sub-populations and a genome wide linkage disequilibrium (LD) decay was at 2.5 cM. Single marker and haplotypes-based genome wide association study (GWAS) revealed significant associations on three chromosomes; 4A (HB10.7), 2D (HB6.10) and 3B (HB8.12) with Y, SL and TKW, respectively. Likewise, associations on chromosomes 6B (HB17.1) and 3A (HB7.11) were identified for NGS and on 3A (HB7.12) for KA. Five traits i.e. normalized difference vegetation index (NDVI), canopy temperature depression (CTD) days to heading (DTH), NGS, KA were associated at chromosome 3A both under irrigated and drought conditions however, different haplotypes were estimated. Twenty-six SNPs were part of 10 haplotype blocks associated with Y, SL, TKW, NGS and KA. In silico analysis of the associated SNPs/haplotypes showed hits with candidate genes known to confer abiotic stress resistance in model species and crops. Potential candidate genes include those coding for sulfite exporter TauE/SafE family in Arabidopsis thaliana, TBC domain containing protein in Oryza sativa subsp. Japonica and heat shock proteins in Aegilops tauschii subsp. tauschii were revealed. The SNPs linked to the promising genes identified in the study can be used for marker-assisted selection.

Estimation of Eucalypt Forest Leaf Area Index on the South Coast of New South Wales using Landsat MSS Data

1997 ◽  
Vol 45 (5) ◽  
pp. 757 ◽  
Author(s):  
Nicholas Coops ◽  
Antoine Delahaye ◽  
Eddy Pook
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Vegetation Index ◽  
Near Infrared ◽  
New South ◽  
New South Wales ◽  
Monitoring Site ◽  
Area Index ◽  
South Wales ◽  
Normalised Difference Vegetation Index

Research over the last decade has shown that regional estimation of Leaf Area Index (LAI) is possible using the ratio of red and near infrared radiation derived from satellite or airborne sensors. At landscape levels, however, this relationship has been more difficult to establish due to (i) logistic difficulties in measuring seasonal variation in LAI across the landscape over an extended period of time and (ii) difficulties in establishing the effect of understorey, canopy closure, and soil on the spectral radiation at fine spatial resolutions (< 100 m). This paper examines the first issue by utilising a temporal sequence of LAI data of a Eucalyptus mixed hardwood forest (E. maculata Hook., E. paniculata Sm., E. globoidea Blakely, E. pilularis Sm., E. sieberi L.Johnson) in south-eastern New South Wales and comparing it to historical Landsat Multi-Spectral Scanner (MSS) data covering a 9 year period. Field LAI was compared to the Normalised Difference Vegetation Index (NDVI) and the Simple Ratio (SR) derived from the MSS data. Linear relationships were shown to be appropriate to relate both transformations to the LAI data with r2 -values of 0.71 and 0.53 respectively. Using the NDVI relationship, LAI values were estimated along a transect originating from the monitoring site and these were compared to percentage canopy cover values derived from aerial photography.

Plant and soil influences on estimating biomass of wheat in plant breeding plots using field spectral radiometers

1996 ◽  
Vol 47 (7) ◽  
pp. 1017 ◽  
Author(s):  
SM Bellairs ◽  
NC Turner ◽  
PT Hick ◽  
RCG Smith
Keyword(s):  
Vegetation Index ◽  
Coefficient Of Determination ◽  
Wheat Crop ◽  
Growth Stages ◽  
Experimental Conditions ◽  
Area Index ◽  
Operational Conditions ◽  
Normalised Difference Vegetation Index ◽  
Early Vigour ◽  
Dark Soil

Field spectral radiometers were used to estimate the biomass of wheat at early growth stages, as wheat breeders require a rapid, non-destructive technique to rank wheat genotypes for early vigour. Under experimental conditions, good relationships were obtained between reflectance and biomass prior to the wheat crop achieving a green area index of 1.5. When used above different soil types, good results were achieved on very uniform dark and light soils under experimental conditions, but greater differentiation between plots differing in biomass was achieved on darker soils. Similarly, under operational conditions in wheat breeders' plots, the best results were achieved against a dark soil background. Structural differences between plants also influenced solar radiation reflectance. At the Merredin site with the dark soil background, where the best correlation between reflectance and biomass was achieved, the relationship was much stronger for the more uniform genotypes at the second stage of selection than for the more heterogeneous genotypes at the first stage of selection. On these plots, the vegetation spectral indices NDVI (normalised difference vegetation index) and TSAVI (transformed soil-adjusted vegetation index) had a coefficient of determination 90-95% as good as the best regression using two wavebands. To optimise the field spectroradiometry technique for estimating early biomass, it should be applied at a weed-free site, with a uniform dark soil background and on material that is relatively homogenous in structure. We conclude that, unless these precautions are taken, the technique will have limited utility in breeding programs.

scholarly journals Identification of QTL hotspots affecting agronomic traits and high-throughput vegetation indices in rainfed wheat

2021 ◽  
Author(s):  
Ruben Rufo ◽  
Andrea Lopez ◽  
Marta S. Lopes ◽  
Joaquim Bellvert ◽  
Jose Miguel Soriano
Keyword(s):  
Abiotic Stress ◽  
Grain Yield ◽  
Candidate Gene ◽  
High Throughput ◽  
Complex Traits ◽  
Vegetation Index ◽  
Genome Wide Association Study ◽  
Agronomic Traits ◽  
Wheat Breeding ◽  
A Genome

Understanding the genetic basis of agronomic traits is essential for wheat breeding programmes to develop new cultivars with enhanced grain yield under climate change conditions. The use of high-throughput phenotyping (HTP) technologies for the assessment of agronomic performance through drought-adaptive traits opens new possibilities in plant breeding. HTP together with a genome-wide association study (GWAS) mapping approach can become a useful method to dissect the genetic control of complex traits in wheat to enhance grain yield under drought stress. This study aimed to identify molecular markers associated with agronomic and remotely sensed vegetation index (VI)-related traits under rainfed conditions in bread wheat and to use an in silico candidate gene (CG) approach to search for upregulated CGs under abiotic stress. The plant material consisted of 170 landraces and 184 modern cultivars from the Mediterranean basin that were phenotyped for agronomic and VI traits derived from multispectral images over three and two years, respectively. GWAS identified 2579 marker-trait associations (MTAs). The QTL overview index statistic detected 11 QTL hotspots involving more than one trait in at least two years. A candidate gene analysis detected 12 CGs upregulated under abiotic stress in 6 QTL hotspots. The current study highlights the utility of VI to identify chromosome regions that contribute to yield and drought tolerance under rainfed Mediterranean conditions.

Leaf area index as a function of precipitation within a hydrological model

2013 ◽  
Vol 45 (4-5) ◽  
pp. 660-672 ◽  
Author(s):  
Tobias Törnros ◽  
Lucas Menzel
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Vegetation Index ◽  
Hydrological Model ◽  
Area Index ◽  
Annual Variations ◽  
Long Run ◽  
Normalised Difference Vegetation Index ◽  
Dry Conditions ◽  
Good Agreement

The Leaf Area Index (LAI) was derived from the Normalised Difference Vegetation Index (NDVI) obtained from Advanced Very High Resolution Radiometer (AVHRR) data for the years 1982–2004. The NDVI-derived LAI showed a very good agreement (correlation coefficient r up to 0.96) with MODIS LAI. To address the relation between precipitation and LAI, linear correlation analysis between gridded precipitation and the NDVI-derived LAI was conducted for several land uses and each month of the year. Based on the regression coefficients, LAI could be simulated as a function of precipitation. During validation, the simulated LAI showed a very good agreement (r ≥ 0.75) with the NDVI-derived LAI. The simulated dynamic LAI was thereafter implemented in a hydrological model. For comparison, a model run with a static LAI without any inter-annual variations was also conducted. During abnormally dry conditions, the dynamic LAI was lower than the static LAI and less transpiration was therefore simulated. It is shown that a dynamic LAI contributes to a more realistic simulation approach during individual weather events but also that in the long run the simulated transpiration is much more strongly influenced by inter-annual variations in weather than by the additional vegetation dynamics in a semi-arid region.

Quantifying genetic effects of ground cover on soil water evaporation using digital imaging

2010 ◽  
Vol 37 (8) ◽  
pp. 703 ◽  
Author(s):  
Daniel J. Mullan ◽  
Matthew P. Reynolds
Keyword(s):  
Soil Water ◽  
Leaf Area ◽  
Rapid Development ◽  
Ground Cover ◽  
Genetic Differences ◽  
Soil Evaporation ◽  
Water Evaporation ◽  
Analysis Tool ◽  
Area Index ◽  
Normalised Difference Vegetation Index

Rapid development of leaf area and/or aboveground biomass has the potential to improve water harvest of rain fed wheat in Mediterranean-type environments through reduced soil evaporation. However, quantitative relationships between genetic differences in early ground cover and soil water evaporation have not been established. Furthermore, accurate phenotyping of ground cover and early vigour have typically been achieved via destructive sampling methods, which are too time-consuming to undertake within breeding programs. Digital image analysis has previously been identified as an alternative indirect method of analysis, whereby computer analysis is ued to determine percentage ground cover. This study uses a digital ground cover (DGC) analysis tool for high throughput screening of four large wheat populations. The DGC methodology was validated via comparisons with alternative measures of canopy cover, such as normalised difference vegetation index (NDVI) (r2 = 0.69), biomass (r2 = 0.63), leaf area index (r2 = 0.80) and light penetration through the canopy (r2 = 0.70). The wheat populations were utilised to estimate the potential variation in soil evaporation associated with genetic differences in early ground cover, which was validated using established models. Estimates of genetic differences in soil evaporation within the four populations (6.90–24.8 mm) suggest that there is sufficient genetic variation to increase water harvest through targeting faster ground cover. Implications for improved wheat yields and breeding are discussed.

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