scholarly journals A Method for Obtaining Field Wheat Freezing Injury Phenotype Based on RGB Camera and Software Control

2021 ◽  
Author(s):  
xiuqing fu ◽  
Yang Bai ◽  
Jing Zhou ◽  
Hongwen Zhang ◽  
Jieyu Xian
Keyword(s):  
High Throughput ◽  
Wheat Breeding ◽  
Image Features ◽  
Seedling Stage ◽  
Freezing Stress ◽  
Freezing Injury ◽  
Data Management System ◽  
Phenotypic Analysis ◽  
Phenotypic Data ◽  
Wheat Varieties

Abstract Low temperature freezing stress has adverse effects on wheat seedling growth and final yield. The traditional method to evaluate the wheat injury caused by the freezing stress is by visual observations, which is time-consuming and laborious. Therefore, to effectively and efficiently quantify the wheat freezing injury in the field environments, a high-throughput phenotyping system was developed in this paper , namely, RGB FREEZING INJURY SYSTEM. The system is able to automatically collect, processing, and analyze the wheat images collected using a mobile phenotype cabin in the field conditions. A data management system was also developed to store and manage the original images and the calculated phenotypic data in the system. A group of 128 wheat varieties were planted with replicates under a freezing environment. Canopy images of the wheat were collected at the seedling stage and three image features were extracted for each wheat samples, including ExG, ExR and ExV. The results show that the developed methods can clearly distinguish wheat samples with different wheat freezing injury scores. The automatic phenotypic analysis method of freezing injury provides a solution for high-throughput phenotypic analysis of field wheat and can quantify the stress caused by freezing injury at the seedling stage. The method has a certain guiding significance for wheat breeding.

scholarly journals A method for obtaining field wheat freezing injury phenotype based on RGB camera and software control

Plant Methods ◽  
2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Xiuqing Fu ◽  
Yang Bai ◽  
Jing Zhou ◽  
Hongwen Zhang ◽  
Jieyu Xian
Keyword(s):  
High Throughput ◽  
Wheat Seedling ◽  
Image Features ◽  
Freezing Stress ◽  
Freezing Injury ◽  
Data Management System ◽  
Freezing Damage ◽  
Phenotypic Analysis ◽  
Phenotypic Data ◽  
Wheat Varieties

Abstract Background Low temperature freezing stress has adverse effects on wheat seedling growth and final yield. The traditional method to evaluate the wheat injury caused by the freezing stress is by visual observations, which is time-consuming and laborious. Therefore, a more efficient and accurate method for freezing damage identification is urgently needed. Results A high-throughput phenotyping system was developed in this paper, namely, RGB freezing injury system, to effectively and efficiently quantify the wheat freezing injury in the field environments. The system is able to automatically collect, processing, and analyze the wheat images collected using a mobile phenotype cabin in the field conditions. A data management system was also developed to store and manage the original images and the calculated phenotypic data in the system. In this experiment, a total of 128 wheat varieties were planted, three nitrogen concentrations were applied and two biological and technical replicates were performed. And wheat canopy images were collected at the seedling pulling stage and three image features were extracted for each wheat samples, including ExG, ExR and ExV. We compared different test parameters and found that the coverage had a greater impact on freezing injury. Therefore, we preliminarily divided four grades of freezing injury according to the test results to evaluate the freezing injury of different varieties of wheat at the seedling stage. Conclusions The automatic phenotypic analysis method of freezing injury provides an alternative solution for high-throughput freezing damage analysis of field crops and it can be used to quantify freezing stress and has guiding significance for accelerating the selection of wheat excellent frost resistance genotypes.

scholarly journals Benchmarking of Multivariate Similarity Measures for High-Content Screening Fingerprints in Phenotypic Drug Discovery

2013 ◽  
Vol 18 (10) ◽  
pp. 1284-1297 ◽  
Author(s):  
Felix Reisen ◽  
Xian Zhang ◽  
Daniela Gabriel ◽  
Paul Selzer
Keyword(s):  
Feature Selection ◽  
Drug Discovery ◽  
High Throughput ◽  
Similarity Measures ◽  
Cellular Responses ◽  
Image Features ◽  
High Content Screening ◽  
Selection Methods ◽  
Phenotypic Analysis ◽  
Kendall’S Τ

High-content screening (HCS) is a powerful tool for drug discovery being capable of measuring cellular responses to chemical disturbance in a high-throughput manner. HCS provides an image-based readout of cellular phenotypes, including features such as shape, intensity, or texture in a highly multiplexed and quantitative manner. The corresponding feature vectors can be used to characterize phenotypes and are thus defined as HCS fingerprints. Systematic analyses of HCS fingerprints allow for objective computational comparisons of cellular responses. Such comparisons therefore facilitate the detection of different compounds with different phenotypic outcomes from high-throughput HCS campaigns. Feature selection methods and similarity measures, as a basis for phenotype identification and clustering, are critical for the quality of such computational analyses. We systematically evaluated 16 different similarity measures in combination with linear and nonlinear feature selection methods for their potential to capture biologically relevant image features. Nonlinear correlation-based similarity measures such as Kendall’s τ and Spearman’s ρ perform well in most evaluation scenarios, outperforming other frequently used metrics (such as the Euclidian distance). We also present four novel modifications of the connectivity map similarity that surpass the original version, in our experiments. This study provides a basis for generic phenotypic analysis in future HCS campaigns.

scholarly journals An Exploration of Deep-Learning Based Phenotypic Analysis to Detect Spike Regions in Field Conditions for UK Bread Wheat

2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Tahani Alkhudaydi ◽  
Daniel Reynolds ◽  
Simon Griffiths ◽  
Ji Zhou ◽  
Beatriz de la Iglesia
Keyword(s):  
Deep Learning ◽  
Bread Wheat ◽  
Field Experiments ◽  
Wheat Yield ◽  
Wheat Breeding ◽  
Phenotypic Analysis ◽  
Convolutional Network ◽  
Wheat Varieties ◽  
Validation Data ◽  
Climate Conditions

Wheat is one of the major crops in the world, with a global demand expected to reach 850 million tons by 2050 that is clearly outpacing current supply. The continual pressure to sustain wheat yield due to the world’s growing population under fluctuating climate conditions requires breeders to increase yield and yield stability across environments. We are working to integrate deep learning into field-based phenotypic analysis to assist breeders in this endeavour. We have utilised wheat images collected by distributed CropQuant phenotyping workstations deployed for multiyear field experiments of UK bread wheat varieties. Based on these image series, we have developed a deep-learning based analysis pipeline to segment spike regions from complicated backgrounds. As a first step towards robust measurement of key yield traits in the field, we present a promising approach that employ Fully Convolutional Network (FCN) to perform semantic segmentation of images to segment wheat spike regions. We also demonstrate the benefits of transfer learning through the use of parameters obtained from other image datasets. We found that the FCN architecture had achieved a Mean classification Accuracy (MA) >82% on validation data and >76% on test data and Mean Intersection over Union value (MIoU) >73% on validation data and and >64% on test datasets. Through this phenomics research, we trust our attempt is likely to form a sound foundation for extracting key yield-related traits such as spikes per unit area and spikelet number per spike, which can be used to assist yield-focused wheat breeding objectives in near future.

scholarly journals Morphological and Physiological Root Traits and Their Relationship with Nitrogen Uptake in Wheat Varieties Released from 1915 to 2013

Agronomy ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1149
Author(s):  
Guglielmo Puccio ◽  
Rosolino Ingraffia ◽  
Dario Giambalvo ◽  
Gaetano Amato ◽  
Alfonso S. Frenda
Keyword(s):  
Durum Wheat ◽  
Root System ◽  
N Uptake ◽  
Specific Root Length ◽  
Root Traits ◽  
Wheat Breeding ◽  
N Availability ◽  
Wheat Varieties ◽  
Uptake Efficiency ◽  
Positive Effects

Identifying genotypes with a greater ability to absorb nitrogen (N) may be important to reducing N loss in the environment and improving the sustainability of agricultural systems. This study extends the knowledge of variability among wheat genotypes in terms of morphological or physiological root traits, N uptake under conditions of low soil N availability, and in the amount and rapidity of the use of N supplied with fertilizer. Nine genotypes of durum wheat were chosen for their different morpho-phenological characteristics and year of their release. The isotopic tracer 15N was used to measure the fertilizer N uptake efficiency. The results show that durum wheat breeding did not have univocal effects on the characteristics of the root system (weight, length, specific root length, etc.) or N uptake capacity. The differences in N uptake among the studied genotypes when grown in conditions of low N availability appear to be related more to differences in uptake efficiency per unit of weight and length of the root system than to differences in the morphological root traits. The differences among the genotypes in the speed and the ability to take advantage of the greater N availability, determined by N fertilization, appear to a certain extent to be related to the development of the root system and the photosynthesizing area. This study highlights some variability within the species in terms of the development, distribution, and efficiency of the root system, which suggests that there may be sufficient grounds for improving these traits with positive effects in terms of adaptability to difficult environments and resilience to climate change.

scholarly journals Evaluation of a Novel Molecular Marker Associated with the Tan Spot Disease Response in Wheat

Agriculture ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 513
Author(s):  
Pao Theen See ◽  
Caroline S. Moffat
Keyword(s):  
Molecular Marker ◽  
Hexaploid Wheat ◽  
Wheat Breeding ◽  
Tan Spot ◽  
Growth Stages ◽  
Disease Score ◽  
Wheat Varieties ◽  
Disease Response ◽  
Spot Disease ◽  
Tan Spot Disease

After nearly 40 years of DNA molecular marker development in plant breeding, the wheat research community has amassed an extensive collection of molecular markers which have been widely and successfully used for selection of agronomic, physiological and disease resistance traits in wheat breeding programs. Tan spot is a major fungal disease of wheat and a significant global economic challenge and is caused by the necrotrophic fungal pathogen Pyrenophora tritici-repentis (Ptr). Here, the potential for using a PCR-based marker (Ta1AS3422) present on the short arm of wheat chromosome 1A, was evaluated for effectiveness in distinguishing tan spot disease susceptibility. The marker was initially screened against 40 commercial Australian hexaploid wheat varieties, and those that amplified the marker had an overall lower disease score (2.8 ± 0.7 for seedlings and 2.4 ± 0.4 for plants at the tillering stage), compared to those lacking the marker which exhibited a higher disease score (3.6 ± 0.8 for both growth stages). The potential of Ta1AS3422 as a marker for the tan spot disease response was further assessed against a panel of 100 commercial Australian hexaploid wheat varieties. A significant association was observed between marker absence/presence and tan spot disease rating (Pearson’s chi-squared test, χ2 (6) = 20.53, p = 0.002), with absence of Ta1AS3422 associated with susceptibility. This simple and cost-effective PCR-based marker may be useful for varietal improvement against tan spot, although further work is required to validate its effectiveness.

scholarly journals High-Throughput Phenotyping Methods for Breeding Drought-Tolerant Crops

2021 ◽  
Vol 22 (15) ◽  
pp. 8266
Author(s):  
Minsu Kim ◽  
Chaewon Lee ◽  
Subin Hong ◽  
Song Lim Kim ◽  
Jeong-Ho Baek ◽  
...  
Keyword(s):  
Drought Stress ◽  
High Throughput ◽  
Large Scale ◽  
Crop Yields ◽  
Plant Traits ◽  
Rapid Development ◽  
Plant Responses ◽  
Phenotypic Data ◽  
Agricultural Technologies ◽  
High Throughput Phenotyping

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.

scholarly journals Unravelling the hidden inter and intra-varietal diversity of durum wheat commercial varieties used in Portugal

2019 ◽  
Vol 17 (04) ◽  
pp. 386-389
Author(s):  
Miguel Bento ◽  
Sónia Gomes Pereira ◽  
Wanda Viegas ◽  
Manuela Silva
Keyword(s):  
Durum Wheat ◽  
Repetitive Sequences ◽  
Inter Simple Sequence Repeat ◽  
Wheat Breeding ◽  
Genomic Diversity ◽  
Varietal Diversity ◽  
Wheat Varieties ◽  
Coding Sequences ◽  
Coding Regions ◽  
High Level

AbstractAssessing durum wheat genomic diversity is crucial in a changing environmental particularly in the Mediterranean region where it is largely used to produce pasta. Durum wheat varieties cultivated in Portugal and previously assessed regarding thermotolerance ability were screened for the variability of coding sequences associated with technological traits and repetitive sequences. As expected, reduced variability was observed regarding low molecular weight glutenin subunits (LMW-GS) but a specific LMW-GS allelic form associated with improved pasta-making characteristics was absent in one variety. Contrastingly, molecular markers targeting repetitive elements like microsatellites and retrotransposons – Inter Simple Sequence Repeat (ISSR) and Inter Retrotransposons Amplified Polymorphism (IRAP) – disclosed significant inter and intra-varietal diversity. This high level of polymorphism was revealed by the 20 distinct ISSR/IRAP concatenated profiles observed among the 23 individuals analysed. Interestingly, median joining networks and PCoA analysis grouped individuals of the same variety and clustered varieties accordingly with geographical origin. Globally, this work demonstrates that durum wheat breeding strategies induced selection pressure for some relevant coding sequences while maintaining high levels of genomic variability in non-coding regions enriched in repetitive sequences.

A comparison of some small-scale tests for bread-making quality used in wheat breeding

1980 ◽  
Vol 95 (1) ◽  
pp. 29-34 ◽  
Author(s):  
J. A. Blackman ◽  
A. A. Gill
Keyword(s):  
Protein Quality ◽  
Small Sample Size ◽  
Sodium Dodecyl ◽  
Wheat Breeding ◽  
Small Sample ◽  
Small Scale ◽  
Loaf Volume ◽  
Bread Making ◽  
Wheat Varieties ◽  
Sedimentation Volume

SummaryTwenty-five winter wheat varieties and breeders' lines including hard and soft texture, good or poor bread and biscuit-making types were grown at two locations in the U.K. in 1977 to provide the test samples. Small-scale tests of bread-making quality including extensometer, sodium dodecyl sulphate (SDS) sedimentation volume, residue protein, urea dispersible protein and Pelshenke tests, were compared with loaf volumes and loaf scores.Averaged over the two sites, a modified extensometer test and the SDS test gave the closest correlation with loaf volume and loaf score and were only poorly correlated with Hagberg Falling Number and percentage protein. The SDS test gave the closest correlation between sites followed by the extensometer readings; loaf volume and score had much lower values. The SDS values and extensometer readings give a better measure of the genetic differences in protein quality of varieties than loaf volume and score, being less affected by growing conditions. With its small sample size and high throughput, the SDS sedimentation volume is likely to be the most useful screening test for wheat breeding programmes.

scholarly journals Population structure of Chinese southwest wheat germplasms resistant to stripe rust and powdery mildew using the DArT-seq technique

2018 ◽  
Vol 48 (4) ◽  
Author(s):  
Tianqing Chen ◽  
Piyada Alisha Tantasawat ◽  
Wei Wang ◽  
Xu Gao ◽  
Liyi Zhang
Keyword(s):  
Population Structure ◽  
Disease Resistance ◽  
Polymorphic Information Content ◽  
Wheat Breeding ◽  
Wheat Varieties ◽  
Group I ◽  
Population Structure Analysis ◽  
Specific Allele ◽  
The Mean ◽  
Different Origins

ABSTRACT: Understanding genetic variability in existing wheat accessions is critical for collection, conservation and use of wheat germplasms. In this study, 138 Chinese southwest wheat accessions were investigated by genotyping using two resistance gene makers (Pm21 and Yr26) and DArT-seq technique. Finally, about 50% cultivars (lines) amplified the specific allele for the Yr26 gene (Gwm11) and 40.6% for the Pm21 gene (SCAR1265). By DArT-seq analysis, 30,485 markers (6486 SNPs and 23999 DArTs) were obtained with mean polymorphic information content (PIC) value 0.33 and 0.28 for DArT and SNP marker, respectively. The mean Dice genetic similarity coefficient (GS) was 0.72. Two consistent groups of wheat varieties were identified using principal coordinate analysis (PCoA) at the level of both the chromosome 6AS and the whole-genome, respectively. Group I was composed of non-6VS/6AL translocation lines of different origins, while Group II was composed of 6VS/6AL translocation (T6VS/6AL) lines, most of which carried the Yr26 and Pm21 genes and originated from Guizhou. Besides, a model-based population structure analysis revealed extensive admixture and further divided these wheat accessions into six subgroups (SG1, SG2, SG3, SG4, SG5 and SG6), based on their origin, pedigree or disease resistance. This information is useful for wheat breeding in southwestern China and association mapping for disease resistance using these wheat germplasms in future.

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