scholarly journals Temporal phenomic predictions from unoccupied aerial systems can outperform genomic predictions

2021 ◽  
Author(s):  
Alper Adak ◽  
Seth C. Murray ◽  
Steven L. Anderson
Keyword(s):  
Near Infrared ◽  
Cross Validation ◽  
Vegetation Indices ◽  
Data Depth ◽  
Growth Time ◽  
Time Points ◽  
Genome Wide ◽  
Aerial Systems ◽  
First Time ◽  
Genomic Predictions

A major challenge of genetic improvement and selection is to accurately predict individuals with the highest fitness in a population without direct measurement. Over the last decade genomic predictions (GP) based on genome-wide markers have become reliable and routine. Now phenotyping technologies, including unoccupied aerial systems (UAS also known as drones), can characterize individuals with a data depth comparable to genomics when used throughout growth. This study, for the first time, demonstrated that the prediction power of temporal UAS phenomic data can achieve or exceed that of genomic data. UAS data containing red-green-blue (RGB) bands over fifteen growth time points and multispectral (RGB, red-edge and near infrared) bands over twelve time points were compared across 280 unique maize hybrids. Through cross validation of untested genotypes in tested environments (CV2), temporal phenomic prediction (TPP) outperformed GP (0.80 vs 0.71); TPP and GP performed similarly in three other cross validation scenarios. Genome wide association mapping using area under temporal curves of vegetation indices (VIs) revealed 24.5 percent of a total of 241 discovered loci (59 loci) had associations with multiple VIs, explaining up to 51 percent of grain yield variation, less than GP and TPP predicted. This suggests TPP, like GP, integrates small effect loci well improving plant fitness predictions. More importantly, temporal phenomic prediction appeared to work successfully on unrelated individuals unlike genomic prediction.

scholarly journals Temporal phenomic predictions from unoccupied aerial systems can outperform genomic predictions

2021 ◽  
Author(s):  
Alper Adak ◽  
Seth C. Murray ◽  
Steven L. Anderson
Keyword(s):  
Near Infrared ◽  
Cross Validation ◽  
Vegetation Indices ◽  
Data Depth ◽  
Growth Time ◽  
Time Points ◽  
Genome Wide ◽  
Aerial Systems ◽  
First Time ◽  
Genomic Predictions

Abstract A major challenge of genetic improvement and selection is to accurately predict individuals with the highest fitness in a population without direct measurement. Over the last decade genomic predictions (GP) based on genome-wide markers have become reliable and routine. Now phenotyping technologies, including unoccupied aerial systems (UAS also known as drones), can characterize individuals with a data depth comparable to genomics when used throughout growth. This study, for the first time, demonstrated that the prediction power of temporal UAS phenomic data can achieve or exceed that of genomic data. UAS data containing red-green-blue (RGB) bands over fifteen growth time points and multispectral (RGB, red-edge and near infrared) bands over twelve time points were compared across 280 unique maize hybrids. Through cross validation of untested genotypes in tested environments (CV2), temporal phenomic prediction (TPP) outperformed GP (0.80 vs 0.71); TPP and GP performed similarly in three other cross validation scenarios. Genome wide association mapping using area under temporal curves of vegetation indices (VIs) revealed 24.5 percent of a total of 241 discovered loci (59 loci) had associations with multiple VIs, explaining up to 51 percent of grain yield variation, less than GP and TPP predicted. This suggests TPP, like GP, integrates small effect loci well improving plant fitness predictions. More importantly, temporal phenomic prediction appeared to work successfully on unrelated individuals unlike genomic prediction.

scholarly journals Illumination Geometry and Flying Height Influence Surface Reflectance and NDVI Derived from Multispectral UAS Imagery

Drones ◽  
2019 ◽  
Vol 3 (3) ◽  
pp. 55 ◽  
Author(s):  
Daniel Stow ◽  
Caroline J. Nichol ◽  
Tom Wade ◽  
Jakob J. Assmann ◽  
Gillian Simpson ◽  
...  
Keyword(s):  
Near Infrared ◽  
Vegetation Indices ◽  
Flying Height ◽  
Unmanned Aerial Systems ◽  
Radiometric Calibration ◽  
Very High Spatial Resolution ◽  
Vegetation Surveys ◽  
Solar Noon ◽  
Aerial Systems ◽  
Reflectance Measurements

Small unmanned aerial systems (UAS) have allowed the mapping of vegetation at very high spatial resolution, but a lack of standardisation has led to uncertainties regarding data quality. For reflectance measurements and vegetation indices (Vis) to be comparable between sites and over time, careful flight planning and robust radiometric calibration procedures are required. Two sources of uncertainty that have received little attention until recently are illumination geometry and the effect of flying height. This study developed methods to quantify and visualise these effects in imagery from the Parrot Sequoia, a UAV-mounted multispectral sensor. Change in illumination geometry over one day (14 May 2018) had visible effects on both individual images and orthomosaics. Average near-infrared (NIR) reflectance and NDVI in regions of interest were slightly lower around solar noon, and the contrast between shadowed and well-illuminated areas increased over the day in all multispectral bands. Per-pixel differences in NDVI maps were spatially variable, and much larger than average differences in some areas. Results relating to flying height were inconclusive, though small increases in NIR reflectance with height were observed over a black sailcloth tarp. These results underline the need to consider illumination geometry when carrying out UAS vegetation surveys.

scholarly journals Line observations of the 30-Dor complex and N159A5 with the MPE imaging NIR spectrometer FAST

1991 ◽  
Vol 148 ◽  
pp. 205-206 ◽  
Author(s):  
A. Krabbe ◽  
J. Storey ◽  
V. Rotaciuc ◽  
S. Drapatz ◽  
R. Genzel
Keyword(s):  
Spatial Resolution ◽  
Molecular Hydrogen ◽  
Near Infrared ◽  
Large Magellanic Cloud ◽  
Magellanic Cloud ◽  
Emission Lines ◽  
Resolving Power ◽  
Max Planck ◽  
First Time ◽  
Infrared Array

Images with subarcsec spatial resolution in the light of near-infrared atomic (Bry) and molecular hydrogen H2 (S(1) v=1-0) emission lines were obtained for some extended, pointlike objects in the Large Magellanic Cloud (LMC) for the first time. We used the Max-Planck-Institut für extraterrestrische Physik (MPE) near-infrared array spectrometer FAST (image scale 0.8”/pix, spectral resolving power 950) at the ESO/MPI 2.2m telescope, La Silla. We present some results on the 30-Dor complex and N159A5.

scholarly journals The effect of stellar multiplicity on protoplanetary discs: a near-infrared survey of the Lupus star-forming region

2020 ◽  
Vol 501 (2) ◽  
pp. 2305-2315
Author(s):  
Alice Zurlo ◽  
Lucas A Cieza ◽  
Megan Ansdell ◽  
Valentin Christiaens ◽  
Sebastián Pérez ◽  
...  
Keyword(s):  
Adaptive Optics ◽  
Molecular Cloud ◽  
Near Infrared ◽  
Main Sequence Stars ◽  
Multiple Systems ◽  
Star Forming ◽  
Very Large Telescope ◽  
Pms Stars ◽  
First Time ◽  
Infrared Survey

ABSTRACT We present results from a near-infrared (NIR) adaptive optics (AO) survey of pre-main-sequence stars in the Lupus molecular cloud with NACO at the Very Large Telescope (VLT) to identify (sub)stellar companions down to ∼20-au separation and investigate the effects of multiplicity on circumstellar disc properties. We observe for the first time in the NIR with AO a total of 47 targets and complement our observations with archival data for another 58 objects previously observed with the same instrument. All 105 targets have millimetre Atacama Large Millimetre/sub-millimetre Array (ALMA) data available, which provide constraints on disc masses and sizes. We identify a total of 13 multiple systems, including 11 doubles and 2 triples. In agreement with previous studies, we find that the most massive (Mdust > 50 M⊕) and largest (Rdust > 70 au) discs are only seen around stars lacking visual companions (with separations of 20–4800 au) and that primaries tend to host more massive discs than secondaries. However, as recently shown in a very similar study of >200 PMS stars in the Ophiuchus molecular cloud, the distributions of disc masses and sizes are similar for single and multiple systems for Mdust < 50 M⊕ and radii Rdust < 70 au. Such discs correspond to ∼80–90 per cent of the sample. This result can be seen in the combined sample of Lupus and Ophiuchus objects, which now includes more than 300 targets with ALMA imaging and NIR AO data, and implies that stellar companions with separations >20 au mostly affect discs in the upper 10${{\ \rm per\ cent}}$ of the disc mass and size distributions.

scholarly journals Variation in VKORC1 Is Associated with Vascular Dementia

2021 ◽  
Vol 80 (3) ◽  
pp. 1329-1337
Author(s):  
Jure Mur ◽  
Daniel L. McCartney ◽  
Daniel I. Chasman ◽  
Peter M. Visscher ◽  
Graciela Muniz-Terrera ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Vascular Dementia ◽  
Genetic Variant ◽  
Warfarin Dose ◽  
Uk Biobank ◽  
Parental History ◽  
Genome Wide ◽  
History Of ◽  
First Time ◽  
The Relationship

Background: The genetic variant rs9923231 (VKORC1) is associated with differences in the coagulation of blood and consequentially with sensitivity to the drug warfarin. Variation in VKORC1 has been linked in a gene-based test to dementia/Alzheimer’s disease in the parents of participants, with suggestive evidence for an association for rs9923231 (p = 1.8×10–7), which was included in the genome-wide significant KAT8 locus. Objective: Our study aimed to investigate whether the relationship between rs9923231 and dementia persists only for certain dementia sub-types, and if those taking warfarin are at greater risk. Methods: We used logistic regression and data from 238,195 participants from UK Biobank to examine the relationship between VKORC1, risk of dementia, and the interplay with warfarin use. Results: Parental history of dementia, APOE variant, atrial fibrillation, diabetes, hypertension, and hypercholesterolemia all had strong associations with vascular dementia (p < 4.6×10–6). The T-allele in rs9923231 was linked to a lower warfarin dose (βperT - allele = –0.29, p < 2×10–16) and risk of vascular dementia (OR = 1.17, p = 0.010), but not other dementia sub-types. However, the risk of vascular dementia was not affected by warfarin use in carriers of the T-allele. Conclusion: Our study reports for the first time an association between rs9923231 and vascular dementia, but further research is warranted to explore potential mechanisms and specify the relationship between rs9923231 and features of vascular dementia.

scholarly journals Understanding Vine Hyperspectral Signature through Different Irrigation Plans: A First Step to Monitor Vineyard Water Status

2021 ◽  
Vol 13 (3) ◽  
pp. 536
Author(s):  
Eve Laroche-Pinel ◽  
Mohanad Albughdadi ◽  
Sylvie Duthoit ◽  
Véronique Chéret ◽  
Jacques Rousseau ◽  
...  
Keyword(s):  
Near Infrared ◽  
Water Status ◽  
Vegetation Indices ◽  
Remote Sensing Data ◽  
Short Wave ◽  
Spatial And Temporal Scales ◽  
Spectral Bands ◽  
Main Challenge ◽  
Spectral Scale ◽  
Grape Varieties

The main challenge encountered by Mediterranean winegrowers is water management. Indeed, with climate change, drought events are becoming more intense each year, dragging the yield down. Moreover, the quality of the vineyards is affected and the level of alcohol increases. Remote sensing data are a potential solution to measure water status in vineyards. However, important questions are still open such as which spectral, spatial, and temporal scales are adapted to achieve the latter. This study aims at using hyperspectral measurements to investigate the spectral scale adapted to measure their water status. The final objective is to find out whether it would be possible to monitor the vine water status with the spectral bands available in multispectral satellites such as Sentinel-2. Four Mediterranean vine plots with three grape varieties and different water status management systems are considered for the analysis. Results show the main significant domains related to vine water status (Short Wave Infrared, Near Infrared, and Red-Edge) and the best vegetation indices that combine these domains. These results give some promising perspectives to monitor vine water status.

Prediction of neutral detergent fiber content in corn stover using near-infrared spectroscopy technique

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Xuyang Pan ◽  
Laijun Sun ◽  
Guobing Sun ◽  
Panxiang Rong ◽  
Yuncai Lu ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Prediction Model ◽  
Spectral Data ◽  
Corn Stover ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Cross Validation ◽  
Fiber Content ◽  
Partial Least Square ◽  
Neutral Detergent Fiber

AbstractNeutral detergent fiber (NDF) content was the critical indicator of fiber in corn stover. This study aimed to develop a prediction model to precisely measure NDF content in corn stover using near-infrared spectroscopy (NIRS) technique. Here, spectral data ranging from 400 to 2500 nm were obtained by scanning 530 samples, and Monte Carlo Cross Validation and the pretreatment were used to preprocess the original spectra. Moreover, the interval partial least square (iPLS) was employed to extract feature wavebands to reduce data computation. The PLSR model was built using two spectral regions, and it was evaluated with the coefficient of determination (R2) and root mean square error of cross validation (RMSECV) obtaining 0.97 and 0.65%, respectively. The overall results proved that the developed prediction model coupled with spectral data analysis provides a set of theoretical foundations for NIRS techniques application on measuring fiber content in corn stover.

scholarly journals Assessing Leaf Biomass of Agave sisalana Using Sentinel-2 Vegetation Indices

2021 ◽  
Vol 13 (2) ◽  
pp. 233
Author(s):  
Ilja Vuorinne ◽  
Janne Heiskanen ◽  
Petri K. E. Pellikka
Keyword(s):  
Near Infrared ◽  
Vegetation Indices ◽  
Fibre Production ◽  
Additive Models ◽  
Leaf Biomass ◽  
Ground Vegetation ◽  
Perennial Crop ◽  
Red Edge ◽  
Agave Sisalana ◽  
Sentinel 2

Biomass is a principal variable in crop monitoring and management and in assessing carbon cycling. Remote sensing combined with field measurements can be used to estimate biomass over large areas. This study assessed leaf biomass of Agave sisalana (sisal), a perennial crop whose leaves are grown for fibre production in tropical and subtropical regions. Furthermore, the residue from fibre production can be used to produce bioenergy through anaerobic digestion. First, biomass was estimated for 58 field plots using an allometric approach. Then, Sentinel-2 multispectral satellite imagery was used to model biomass in an 8851-ha plantation in semi-arid south-eastern Kenya. Generalised Additive Models were employed to explore how well biomass was explained by various spectral vegetation indices (VIs). The highest performance (explained deviance = 76%, RMSE = 5.15 Mg ha−1) was achieved with ratio and normalised difference VIs based on the green (R560), red-edge (R740 and R783), and near-infrared (R865) spectral bands. Heterogeneity of ground vegetation and resulting background effects seemed to limit model performance. The best performing VI (R740/R783) was used to predict plantation biomass that ranged from 0 to 46.7 Mg ha−1 (mean biomass 10.6 Mg ha−1). The modelling showed that multispectral data are suitable for assessing sisal leaf biomass at the plantation level and in individual blocks. Although these results demonstrate the value of Sentinel-2 red-edge bands at 20-m resolution, the difference from the best model based on green and near-infrared bands at 10-m resolution was rather small.

scholarly journals Feasibility of Using VIS/NIR Spectroscopy and Multivariate Analysis for Pesticide Residue Detection in Tomatoes

Processes ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 196
Author(s):  
Araz Soltani Nazarloo ◽  
Vali Rasooli Sharabiani ◽  
Yousef Abbaspour Gilandeh ◽  
Ebrahim Taghinezhad ◽  
Mariusz Szymanek ◽  
...  
Keyword(s):  
Near Infrared ◽  
Cross Validation ◽  
Low Cost ◽  
Moving Average ◽  
Nir Spectroscopy ◽  
Control Treatment ◽  
Residue Detection ◽  
Non Destructive ◽  
Reflective Spectroscopy

The purpose of this work was to investigate the detection of the pesticide residual (profenofos) in tomatoes by using visible/near-infrared spectroscopy. Therefore, the experiments were performed on 180 tomato samples with different percentages of profenofos pesticide (higher and lower values than the maximum residual limit (MRL)) as compared to the control (no pesticide). VIS/near infrared (NIR) spectral data from pesticide solution and non-pesticide tomato samples (used as control treatment) impregnated with different concentrations of pesticide in the range of 400 to 1050 nm were recorded by a spectrometer. For classification of tomatoes with pesticide content at lower and higher levels of MRL as healthy and unhealthy samples, we used different spectral pre-processing methods with partial least squares discriminant analysis (PLS-DA) models. The Smoothing Moving Average pre-processing method with the standard error of cross validation (SECV) = 4.2767 was selected as the best model for this study. In addition, in the calibration and prediction sets, the percentages of total correctly classified samples were 90 and 91.66%, respectively. Therefore, it can be concluded that reflective spectroscopy (VIS/NIR) can be used as a non-destructive, low-cost, and rapid technique to control the health of tomatoes impregnated with profenofos pesticide.

scholarly journals Genome-wide identification of the GATA transcription factor family and their expression patterns under temperature and salt stress in Aspergillus oryzae

AMB Express ◽  
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chunmiao Jiang ◽  
Gongbo Lv ◽  
Jinxin Ge ◽  
Bin He ◽  
Zhe Zhang ◽  
...  
Keyword(s):  
Salt Stress ◽  
Expression Patterns ◽  
Interaction Network ◽  
Protein Protein Interaction ◽  
Genome Wide ◽  
Gata Transcription Factor ◽  
Starting Point ◽  
Evolutionary Features ◽  
First Time

AbstractGATA transcription factors (TFs) are involved in the regulation of growth processes and various environmental stresses. Although GATA TFs involved in abiotic stress in plants and some fungi have been analyzed, information regarding GATA TFs in Aspergillusoryzae is extremely poor. In this study, we identified and functionally characterized seven GATA proteins from A.oryzae 3.042 genome, including a novel AoSnf5 GATA TF with 20-residue between the Cys-X2-Cys motifs which was found in Aspergillus GATA TFs for the first time. Phylogenetic analysis indicated that these seven A. oryzae GATA TFs could be classified into six subgroups. Analysis of conserved motifs demonstrated that Aspergillus GATA TFs with similar motif compositions clustered in one subgroup, suggesting that they might possess similar genetic functions, further confirming the accuracy of the phylogenetic relationship. Furthermore, the expression patterns of seven A.oryzae GATA TFs under temperature and salt stresses indicated that A. oryzae GATA TFs were mainly responsive to high temperature and high salt stress. The protein–protein interaction network of A.oryzae GATA TFs revealed certain potentially interacting proteins. The comprehensive analysis of A. oryzae GATA TFs will be beneficial for understanding their biological function and evolutionary features and provide an important starting point to further understand the role of GATA TFs in the regulation of distinct environmental conditions in A.oryzae.

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