scholarly journals Phenotyping of Plant Biomass and Performance Traits Using Remote Sensing Techniques in Pea (Pisum sativum, L.)

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2031 ◽  
Author(s):  
Juan José Quirós Vargas ◽  
Chongyuan Zhang ◽  
Jamin A. Smitchger ◽  
Rebecca J. McGee ◽  
Sindhuja Sankaran
Keyword(s):  
Seed Yield ◽  
Vegetation Index ◽  
Ground Truth ◽  
Image Features ◽  
Field Pea ◽  
Canopy Height ◽  
Yield Potential ◽  
Breeding Programs ◽  
Physiological Maturity ◽  
Primary Yield

Field pea cultivars are constantly improved through breeding programs to enhance biotic and abiotic stress tolerance and increase seed yield potential. In pea breeding, the Above Ground Biomass (AGBM) is assessed due to its influence on seed yield, canopy closure, and weed suppression. It is also the primary yield component for peas used as a cover crop and/or grazing. Measuring AGBM is destructive and labor-intensive process. Sensor-based phenotyping of such traits can greatly enhance crop breeding efficiency. In this research, high resolution RGB and multispectral images acquired with unmanned aerial systems were used to assess phenotypes in spring and winter pea breeding plots. The Green Red Vegetation Index (GRVI), Normalized Difference Vegetation Index (NDVI), Normalized Difference Red Edge Index (NDRE), plot volume, canopy height, and canopy coverage were extracted from RGB and multispectral information at five imaging times (between 365 to 1948 accumulated degree days/ADD after 1 May) in four winter field pea experiments and at three imaging times (between 1231 to 1648 ADD) in one spring field pea experiment. The image features were compared to ground-truth data including AGBM, lodging, leaf type, days to 50% flowering, days to physiological maturity, number of the first reproductive node, and seed yield. In two of the winter pea experiments, a strong correlation between image features and seed yield was observed at 1268 ADD (flowering). An increase in correlation between image features with the phenological traits such as days to 50% flowering and days to physiological maturity was observed at about 1725 ADD in these winter pea experiments. In the spring pea experiment, the plot volume estimated from images was highly correlated with ground truth canopy height (r = 0.83) at 1231 ADD. In two other winter pea experiments and the spring pea experiment, the GRVI and NDVI features were significantly correlated with AGBM at flowering. When selected image features were used to develop a least absolute shrinkage and selection operator model for AGBM estimation, the correlation coefficient between the actual and predicted AGBM was 0.60 and 0.84 in the winter and spring pea experiments, respectively. A SPOT-6 satellite image (1.5 m resolution) was also evaluated for its applicability to assess biomass and seed yield. The image features extracted from satellite imagery showed significant correlation with seed yield in two winter field pea experiments, however, the trend was not consistent. In summary, the study supports the potential of using unmanned aerial system-based imaging techniques to estimate biomass and crop performance in pea breeding programs.

scholarly journals Effects of Mutagens on Morphological traits of Psoralea corylifolia-A Medicinally Important Plant

2020 ◽  
Vol 26 (2) ◽  
Author(s):  
Ajey Karan Chaudhari ◽  
Anand Prakash Singh ◽  
B R Chaudhary
Keyword(s):  
Plant Height ◽  
Seed Yield ◽  
Morphological Traits ◽  
Mutation Breeding ◽  
Yield Potential ◽  
Mutagenic Potential ◽  
Breeding Programs ◽  
Methane Sulphonate ◽  
Flowering Initiation ◽  
Yield Quality

Mutation breeding like in other plants can significantly strengthen medicinal plants breeding programs and help to produce novel varieties with higher yield potential and improved yield quality. The dry and healthy seeds of P. corylifolia IC 111228 were subjected to mutagenic treatments namely ethyl methane sulphonate (EMS) and sodium azide (SA). The treatment concentrations 15mM, 30mM, 45mM and 60mM of EMS and 1mM, 2mM, 3mM and 4mM of SA were chosen to evaluate the mutagenic potential in either case. The morphological traits were evaluated in M1 generation viz. plant height, days to flowering initiation, seed yield/plant and 100-seed weight. In EMS treatment 15 mM increased the plant height and seed yield, while in SA treatment 4 mM increased the seed yield/plant and 100-seed yield.

Impact of seeding rate and depth on mycosphaerella blight and seed yield of field pea

2006 ◽  
Vol 86 (3) ◽  
pp. 845-853 ◽  
Author(s):  
S. F. Hwang ◽  
R. L. Conner ◽  
K. F. Chang ◽  
B. D. Gossen ◽  
H. Su ◽  
...  
Keyword(s):  
Seed Yield ◽  
Field Trials ◽  
Field Pea ◽  
Yield Potential ◽  
Mycosphaerella Pinodes ◽  
Western Canada ◽  
Seedling Density ◽  
Seeding Rate ◽  
Foliar Fungicide ◽  
The Impact

Mycosphaerella blight (Mycosphaerella pinodes) occurs throughout western Canada and can severely reduce field pea (Pisum sativum) seed yield. Field trials were conducted at two sites (Edmonton, AB, and Morden, MB) from 2001 to 2003 to assess the impact of seeding rate and seeding depth on blight severity. Mycosphaerella blight severity in the canopy was greater at higher seeding rates; treatments seeded at 30 plants m-2 had lower levels of disease than those seeded at more than 100 seeds m-2. However, yield potential was reduced at low seeding densities. Depth of seeding did not affect seedling density, disease severity, yield or final seed weight. In addition, field trials were conducted at Edmonton to quantify yield losses associated with mycosphaerella blight in Alberta. In trials inoculated with M. pinodes, application of a foliar fungicide (chlorothalonil) increased yield by about 20% over the unprotected control. Key words: Pisum, Mycosphaerella, fungicide, crop management, yield loss

Estimating canola (Brassica napus L.) yield potential using an active optical sensor

2009 ◽  
Vol 89 (6) ◽  
pp. 1149-1160 ◽  
Author(s):  
C B Holzapfel ◽  
G P Lafond ◽  
S A Brandt ◽  
P R Bullock ◽  
R B Irvine ◽  
...  
Keyword(s):  
Seed Yield ◽  
Optical Sensors ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Growing Season ◽  
Yield Potential ◽  
Regression Analyses ◽  
Canola Seed ◽  
Soil Zone ◽  
Use Efficiency

Active optical sensors have potential as tools to increase N fertilizer use efficiency in crop production; however, empirical data are required to utilize the sensors for this purpose. Data were compiled from N fertilizer trials at five Canadian locations (2004-2007) to determine the feasibility of using optical sensors during the growing season to estimate the seed yield potential of canola (Brassica napus). The normalized difference vegetation index (NDVI) of each plot in each trial was measured using a hand-held optical sensor several times each season. The NDVI between the six-leaf stage and the beginning of flowering was divided by one of several different heat unit summations to normalize the measurements, and data were combined across locations. Linear and exponential regression analyses were completed for canola seed yield as a function of both the original and normalized NDVI measurements. When data from all locations were combined, NDVI was significantly correlated with canola seed yield (R2 = 0.35; P < 0.001) and normalizing NDVI did not improve the correlation. Categorizing the locations by soil zone (Brown-Dark Brown and thin-Black-Black) and completing separate regression analyses for each group increased the correlation coefficients for NDVI and seed yield (R2 = 0.36-0.43). Furthermore, dividing NDVI by the heat unit summations generally improved the correlation when the data were categorized by soil zone. The largest correlation coefficient occurred when NDVI was divided by growing degree days with a base temperature of 5°C (R2 = 0.53-0.67). Our results show that optical sensors can be used to estimate canola yield potential early enough in the growing season to have potential as an N management tool.Key words: Normalized difference vegetation index, agriculture, precision, nitrogen use efficiency

scholarly journals Inheritance of resistance to Fusarium wilt in some sesame crosses under field conditions

2010 ◽  
Vol 42 (No. 3) ◽  
pp. 99-105 ◽  
Author(s):  
M.A.S. El-Bramawy
Keyword(s):  
Fusarium Wilt ◽  
Seed Yield ◽  
Large Scale ◽  
Natural Infection ◽  
Wilt Disease ◽  
Yield Potential ◽  
Breeding Programs ◽  
Two Generations ◽  
Positive Correlations ◽  
Large Scale Cultivation

Lines of two generations (F<sub>3</sub> and F<sub>4</sub>) from 15 crosses were screened for two successive seasons (2004 and 2005) for their reaction to Fusarium wilt disease under natural infection by <i>Fusarium oxysporum<i> f.sp. <i>sesami<i>. There was sufficient variability among all crosses and some lines could be valuable for further breeding programs for wilt disease resistance. Offspring of the crosses P<sub>1</sub> × P<sub>6</sub>, P<sub>2</sub> × P<sub>4</sub> and P<sub>3</sub> × P<sub>6</sub> seem to be stable in their reaction to the disease in the years of evaluation, though with some segregation from one generation to another. The crosses P<sub>1</sub> × P<sub>5</sub>, P<sub>2</sub> × P<sub>6</sub>, P<sub>3</sub> × P<sub>4</sub> and P<sub>3</sub> × P<sub>6</sub> showed a resistant reaction through both generations as well as both seasons. They might be helpful and utilised for large scale cultivation or/and in hybridisation programs to develop resistant varieties with good yield potential. Heritability estimates were very high (more than 95%) in both generations during the two seasons, except for seed yield/plant in the F<sub>3 in the first season. This indicated that selection for both Fusarium wilt resistance and seed yield from these lines could be feasible and lead to resistant cultivars with seed yield potential. The results showed highly significant and positive correlations between lower infection in the F<sub>4</sub>’s and in F<sub>3</sub>’s through the two seasons. The highest significant correlation of the evaluated traits allowed the selection of some lines to be used in breeding programs. Also, highly significant positive correlations were detected between seed yield/plot of the F<sub>4</sub>’s in 2004 and the seed yield/plot of F<sub>4’s in 2005, but did not reach the significant level in the F<sub>3</sub>’s.

Field pea seeding management

2002 ◽  
Vol 82 (4) ◽  
pp. 639-644 ◽  
Author(s):  
A. M. Johnston ◽  
G. W. Clayton ◽  
G. P. Lafond ◽  
K. N. Harker ◽  
T. J. Hogg ◽  
...  
Keyword(s):  
Pisum Sativum ◽  
Seed Yield ◽  
Seed Weight ◽  
Field Pea ◽  
Yield Potential ◽  
Row Spacing ◽  
Seeding Rate ◽  
Pisum Sativum L ◽  
Seed Placement ◽  
The Impact

The impact of seed placement and seeding rate on crop yield is not clearly understood for field pea (Pisum sativum L.). A field experiment was conducted at Melfort, SK, and Lacombe, AB, in 1998 and 1999, to evaluate the effect of three seed placements (distinct row: 23 cm and 30 cm with a hoe opener; and spread band: a 20-cm spread using a 28-cm sweep on a 23-cm row spacing) and three seeding rates (50, 100, and, 150 seeds m-2) on pea seedling density, seed yield and seed weight of a leafy prostrate and semi-leafless upright cultivar. A follow-up experiment was conducted at seven sites across Saskatchewan in 2001 to further examine the influence of a wider range of seeding rates (20, 30, 40, 50, 60, 70, 80, 90, 100, and 120 target plants m-2). Pea productivity for both cultivars was not affected by the different seed placements, despite a 4 mg greater seed weight for distinct row seed placements compared with spread band placement across all 1998–1999 sites. Moreover, the absence of a seed placement by seeding rate interaction indicated that greater spacing between plants was not associated with improved pea yield when seeding rate was increased, regardless of the cultivar. Yield component compensation occurred where increased plant density from higher seeding rates reduced seed weight. In the 2001 study, seed yield benefits were small at seeding rates greater than 50 target plants m-2. There was a tendency for lower yields with seeding rates less than 50, especially at sites with higher yield potential. Yields of field peas grown under relatively weed-free conditions should be optimized with a seeding rate of 50 to 75 seeds m-2. Key words: Pea (Pisum sativum L.), plant arrangement, row spacing, opener type, seeding rate

scholarly journals Crop Performance Evaluation of Chickpea and Dry Pea Breeding Lines Across Seasons and Locations Using Phenomics Data

2021 ◽  
Vol 12 ◽  
Author(s):  
Chongyuan Zhang ◽  
Rebecca J. McGee ◽  
George J. Vandemark ◽  
Sindhuja Sankaran
Keyword(s):  
Seed Yield ◽  
Vegetation Index ◽  
Multispectral Imaging ◽  
Agronomic Traits ◽  
Imaging System ◽  
The United States ◽  
Data Availability ◽  
Image Processing Algorithm ◽  
Breeding Programs ◽  
Canopy Area

The Pacific Northwest is an important pulse production region in the United States. Currently, pulse crop (chickpea, lentil, and dry pea) breeders rely on traditional phenotyping approaches to collect performance and agronomic data to support decision making. Traditional phenotyping poses constraints on data availability (e.g., number of locations and frequency of data acquisition) and throughput. In this study, phenomics technologies were applied to evaluate the performance and agronomic traits in two pulse (chickpea and dry pea) breeding programs using data acquired over multiple seasons and locations. An unmanned aerial vehicle-based multispectral imaging system was employed to acquire image data of chickpea and dry pea advanced yield trials from three locations during 2017–2019. The images were analyzed semi-automatically with custom image processing algorithm and features were extracted, such as canopy area and summary statistics associated with vegetation indices. The study demonstrated significant correlations (P &lt; 0.05) between image-based features (e.g., canopy area and sum normalized difference vegetation index) with yield (r up to 0.93 and 0.85 for chickpea and dry pea, respectively), days to 50% flowering (r up to 0.76 and 0.85, respectively), and days to physiological maturity (r up to 0.58 and 0.84, respectively). Using image-based features as predictors, seed yield was estimated using least absolute shrinkage and selection operator regression models, during which, coefficients of determination as high as 0.91 and 0.80 during model testing for chickpea and dry pea, respectively, were achieved. The study demonstrated the feasibility to monitor agronomic traits and predict seed yield in chickpea and dry pea breeding trials across multiple locations and seasons using phenomics tools. Phenomics technologies can assist plant breeders to evaluate the performance of breeding materials more efficiently and accelerate breeding programs.

scholarly journals Effect of Integrated Crop Management Practices on Growth, Seed Yield and Economics of Field Pea (Pisam sativum L.)

2020 ◽  
Author(s):  
S.K. Sharma ◽  
Rakesh Kumar ◽  
Parveen Kumar
Keyword(s):  
Seed Yield ◽  
Management Practices ◽  
Field Experiments ◽  
Block Design ◽  
Crop Management ◽  
Field Pea ◽  
Yield Potential ◽  
High Yield ◽  
Higher Plant ◽  
Integrated Crop Management

Background: Field pea (Pisam sativum L.) has high yield potential and is grown for food, feed and vegetable. To meet the need of pulses in human diet, the use of integrated crop management practices is indispensable. Therefore, integrated crop management practices are the only option for increasing the field pea production and sustainability. The current study aimed to study the effect the different crop management practices on growth, seed yield and economics of field pea crop.Methods: In this field experiments were conducted during rabi 2013-14 to 2015-16 at Research Farm of Pulse Section, Department of Genetics and Plant Breeding, CCS Haryana Agricultural University, Hisar. The experiment consisted of eight crop management practices viz. control, NM (Nutrient Management): RDF (20:40 kg NP ha-1), WM (Weed Management): Pendimethalin @ 1.0 kg a.i. ha-1 + one hand weeding at 30 DAS), PM (Pest Management): spray of quinalphos 25 EC one litre per ha in 250-300 litres of water as and when required, NM + WM, NM + PM, WM + PM, NM + WM + PM was laid out in a randomized block design with three replications.Result: Our investigations under field study revealed that significantly taller plants and higher plant height, number of branches per plant, number of pods per plant, 100 seed weight, seed and straw yield were recorded under integration of NM + WM + PM being at par with that of integration of NM + WM over remaining crop management practices either singly or in combinations of both or control. Integration of NM + WM + PM recorded lower weeds dry weight (42.9 kg ha-1) at harvest and higher weed control efficiency (92.2%) compared to all other crop management practices. The practice of integration of NM + WM + PM gave highest net returns of `49196 ha-1 compared to other crop management practices.

Can High-Resolution Satellite Multispectral Imagery Be Used to Phenotype Canopy Traits and Yield Potential in Field Conditions?

2021 ◽  
Vol 64 (3) ◽  
pp. 879-891
Author(s):  
Sindhuja Sankaran ◽  
Afef Marzougui ◽  
J. Preston Hurst ◽  
Chongyuan Zhang ◽  
James C. Schnable ◽  
...  
Keyword(s):  
Machine Learning ◽  
High Resolution ◽  
Satellite Imagery ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Yield Potential ◽  
Breeding Programs ◽  
Time Points ◽  
High Resolution Satellite Imagery

HighlightsVegetation indices (NDVI, GNDVI, and SAVI) extracted from high-resolution satellite imagery were significantly associated with vegetation indices extracted from UAV imagery.High-resolution satellite data can be used to predict maize yield at breeding plot scale.Breeding plot sizes and the variability between maize genotypes may be associated with prediction accuracies.Abstract. The recent availability of high spatial and temporal resolution satellite imagery has widened its applications in agriculture. Plant breeding and genetics programs are currently adopting unmanned aerial vehicle (UAV) based imagery data as a complement to ground data collection. With breeding trials across multiple geographic locations, UAV imaging is not always convenient. Hence, we anticipate that, similar to UAV imaging, phenotyping of individual test plots from high-resolution satellite imagery may also provide value to plant genetics and breeding programs. In this study, high spatial resolution satellite imagery (~38 to 48 cm pixel-1) was compared to imagery acquired using a UAV for its ability to phenotype maize grown in two-row and six-row breeding plots. Statistics (mean, median, sum) of color (red, green, blue), near-infrared, and vegetation indices such as normalized difference vegetation index (NDVI), green normalized difference vegetation index (GNDVI), and soil adjusted vegetation index (SAVI) were extracted from imagery from both sources (UAV and satellite) for comparison at three time points. In general, a strong correlation between satellite and UAV imagery extracted NDVI, GNDVI, and SAVI features (especially with mean and median statistics, p &lt; 0.001) was observed at different time points. The correlation of both UAV and satellite image features with yield potential was maximum (p &lt; 0.001) at the third time point (milk/dough growth stages). For example, Pearson’s correlation coefficients between mean NDVI, GNDVI, and SAVI features with yield potential were 0.52, 0.54, and 0.51 for data derived from UAV imagery, and 0.34, 0.41, and 0.40 for data derived from satellite imagery, respectively. Machine learning algorithms, including least absolute shrinkage and selection operator (Lasso) regression, were evaluated for yield prediction using vegetation index features that were significantly correlated with observed yield. The relationship between satellite imagery with crop performance can be a function of plot size in addition to crop variability. Nevertheless, with the ongoing improvement of satellite technologies, there is a possibility for the integration of satellite data into breeding programs, thus improving phenotyping efficiencies. Keywords: Image processing, Machine learning, Plant breeding, Statistical analysis, Unmanned aerial vehicles.

scholarly journals Mapping QTL for spike fertility and related traits in two doubled haploid wheat (Triticum aestivum L.) populations

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Nicole Pretini ◽  
Leonardo S. Vanzetti ◽  
Ignacio I. Terrile ◽  
Guillermo Donaire ◽  
Fernanda G. González
Keyword(s):  
Doubled Haploid ◽  
Marker Assisted Selection ◽  
Triticum Aestivum L ◽  
Physiological Model ◽  
Yield Potential ◽  
Breeding Programs ◽  
Per Se ◽  
Genomic Regions ◽  
Fertility Traits ◽  
Selection Of

Abstract Background In breeding programs, the selection of cultivars with the highest yield potential consisted in the selection of the yield per se, which resulted in cultivars with higher grains per spike (GN) and occasionally increased grain weight (GW) (main numerical components of the yield). In this study, quantitative trait loci (QTL) for GW, GN and spike fertility traits related to GN determination were mapped using two doubled haploid (DH) populations (Baguette Premium 11 × BioINTA 2002 and Baguette 19 × BioINTA 2002). Results In total 305 QTL were identified for 14 traits, out of which 12 QTL were identified in more than three environments and explained more than 10% of the phenotypic variation in at least one environment. Eight hotspot regions were detected on chromosomes 1A, 2B, 3A, 5A, 5B, 7A and 7B in which at least two major and stable QTL sheared confidence intervals. QTL on two of these regions (R5A.1 and R5A.2) have previously been described, but the other six regions are novel. Conclusions Based on the pleiotropic analysis within a robust physiological model we conclude that two hotspot genomic regions (R5A.1 and R5A.2) together with the QGW.perg-6B are of high relevance to be used in marker assisted selection in order to improve the spike yield potential. All the QTL identified for the spike related traits are the first step to search for their candidate genes, which will allow their better manipulation in the future.

scholarly journals Breeding of High Cooking and Eating Quality in Rice by Marker-Assisted Backcrossing (MABc) Using KASP Markers

Plants ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 804
Author(s):  
Me-Sun Kim ◽  
Ju-Young Yang ◽  
Ju-Kyung Yu ◽  
Yi Lee ◽  
Yong-Jin Park ◽  
...  
Keyword(s):  
Genetic Background ◽  
Amylose Content ◽  
Yield Potential ◽  
Eating Quality ◽  
Breeding Cycle ◽  
Recurrent Parent ◽  
Rice Varieties ◽  
Breeding Programs ◽  
Genome Wide ◽  
Cooking And Eating Quality

The primary goals of rice breeding programs are grain quality and yield potential improvement. With the high demand for rice varieties of premium cooking and eating quality, we developed low-amylose content breeding lines crossed with Samgwang and Milkyqueen through the marker-assisted backcross (MABc) breeding program. Trait markers of the SSIIIa gene referring to low-amylose content were identified through an SNP mapping activity, and the markers were applied to select favorable lines for a foreground selection. To rapidly recover the genetic background of Samgwang (recurrent parent genome, RPG), 386 genome-wide markers were used to select BC1F1 and BC2F1 individuals. Seven BC2F1 lines with targeted traits were selected, and the genetic background recovery range varied within 97.4–99.1% of RPG. The amylose content of the selected BC2F2 grains ranged from 12.4–16.8%. We demonstrated the MABc using a trait and genome-wide markers, allowing us to efficiently select lines of a target trait and reduce the breeding cycle effectively. In addition, the BC2F2 lines confirmed by molecular markers in this study can be utilized as parental lines for subsequent breeding programs of high-quality rice for cooking and eating.

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