Trait Based Modelling Approach for Selection of Elite Germplasm Accessions in Soybean [Glycine max (L). Merrill]

2021 ◽  
Author(s):  
K. Shruthi ◽  
R. Siddaraju ◽  
K. Naveena ◽  
T.M. Ramanappa ◽  
C. Gireesh ◽  
...  
Keyword(s):  
Random Forest ◽  
Linear Regression ◽  
Seed Yield ◽  
Crop Improvement ◽  
Regression Tree ◽  
Morphological Characters ◽  
Morphometric Traits ◽  
Random Forest Models ◽  
Augmented Design ◽  
Selection Of

Background: Identification of suitable factors that influence significantly to the response is crucial for the traits based breeding program to make a better decision about improvement in productivity. Multiple linear regression (MLR) is the benchmark method commonly using to identify suitable factors for crop improvement. It doesn’t work always due to stringent assumption (Multicollinearity, Linearity) behind the MLR model. Here we tried to develop an efficient model for the selection of major traits that contribute to seed yield in soybean by comparing different models.Methods: Field experiment was conducted using 98 soybean core population through augmented design.18 morphometric traits obtain from soybean core population were considered under the study as regressors.Multiple linear regression (MLR), Principle component Regression (PCR), Regression tree and Random Forest models were compared to select traits based on prediction accuracy.Result: All the models identified the number of pods per plant (NPP) has the most influencing variable to the soybean yield. However random forest has a much higher prediction power (RMSE=4.59, MAPE=0.18) compared to other models under study. The results of random forest revealed that the number of pods per plant, number of branches per plant and other associated characters like plant height at harvest as highly influencing traits for seed yield in soybean.Finally, tried to identify genotypesthat possess superiority about most influencing morphological characters on seed yield using cluster analysis.

scholarly journals Development of global temperature and pH calibrations based on bacterial 3-hydroxy fatty acids in soils

2020 ◽  
Author(s):  
Pierre Véquaud ◽  
Sylvie Derenne ◽  
Alexandre Thibault ◽  
Christelle Anquetil ◽  
Giuliano Bonanomi ◽  
...  
Keyword(s):  
Fatty Acids ◽  
Random Forest ◽  
Linear Regression ◽  
Membrane Lipids ◽  
Global Scale ◽  
Hydroxy Fatty Acids ◽  
Linear Regression Models ◽  
Wide Range ◽  
Forest Models ◽  
Random Forest Models

Abstract. 3-hydroxy fatty acids (3-OH FAs) with 10 to 18 C atoms are membrane lipids mainly produced by Gram-negative bacteria. They have been recently proposed as temperature and pH proxies in terrestrial settings. Nevertheless, the existing correlations between pH/temperature and indices derived from 3-OH FA distribution (RIAN, RAN15 and RAN17) are based on a small soil dataset (ca. 70 samples) and only applicable regionally. The aim of this study was to investigate the applicability of 3-OH FAs as mean annual air temperature (MAAT) and pH proxies at the global level. This was achieved using an extended soil dataset of 168 topsoils distributed worldwide, covering a wide range of temperatures (5 °C to 30 °C) and pH (3 to 8). The response of 3-OH FAs to temperature and pH was compared to that of established branched GDGT-based proxies (MBT'5Me/CBT). Strong linear relationships between 3-OH FA-derived indices (RAN15, RAN17 and RIAN) and MAAT/pH could only be obtained locally, for some of the individual transects. This suggests that these indices cannot be used as paleoproxies at the global scale using simple linear regression models, in contrast with the MBT'5Me and CBT. However, strong global correlations between 3-OH FA relative abundances and MAAT/pH were shown by using other algorithms (multiple linear regression, k-NN and random forest models). The applicability of the k-NN and random forest models for paleotemperature reconstruction was tested and compared with the MAAT record from a Chinese speleothem. The calibration based on the random forest model appeared to be the most robust. It showed similar trends with previously available records and highlighted known climatic events poorly visible when using local 3-OH FA calibrations. Altogether, these results demonstrate the potential of 3-OH FAs as paleoproxies in terrestrial settings.

PHENOTYPIC CHARACTERIZATION OF FOENICULUM VULGARE (FENNEL) GERMPLASM

2017 ◽  
Vol 23 (1) ◽  
Author(s):  
SUMIT DESWAL ◽  
T.P. MALIK ◽  
S.K. TEHLAN ◽  
PREETI YADAV
Keyword(s):  
Plant Height ◽  
Seed Yield ◽  
Morphological Characters ◽  
Phenotypic Characterization ◽  
Foeniculum Vulgare ◽  
Plant Seeds ◽  
Vegetative Characters ◽  
Range Variation ◽  
Selection Of

An experiment was conducted with sixty genotypes of fennel for phenotypic characterization of different vegetative characters such as plant height, branches per plant, primary branches per plant, secondary branches per plant, umbels per plant, umbellate per plant, seeds per umbellate, seeds per umbel and seed yield. Variability observed for quantitative traits showed high range variation for plant height, umbels per plant, umbellate per plant, seeds per umbellate, seeds per umbel and seed yield. Characterization of germplasm based on morphological parameters signifies the extent of variability present in the population and also provides needful information for selection of desirable genotypes for varietal development and also genotypes which can be conserved for unique traits. The identification keys based on morphological characters are very useful for identification of genotypes and have a pivotal role to identify genotypes in the field without any use of costly chemicals and are fairly comparable with their results.

Evaluation of Gloriosa superba for Yield Attributing Characters and Quantification of Colchicine Originated from Different Agro Climatic Zones of Tamil Nadu and Andhra Pradesh

2017 ◽  
Vol 9 (3) ◽  
Author(s):  
Arun Kumar P. ◽  
Elangaimannan R.
Keyword(s):  
Seed Yield ◽  
Tamil Nadu ◽  
High Performance ◽  
Andhra Pradesh ◽  
Crop Improvement ◽  
Mean Value ◽  
Hplc Method ◽  
Gloriosa Superba ◽  
Climatic Zones ◽  
Colchicine Alkaloid

The study was conducted to evolve Gloriosa superba for yield characters and alkalodi content for selecting elite genotypes for comercial exploitatio n. The genotypes were sowm in Variyankaval village, Udayarpalayam taluk of Ariyalur district, Tamil Nadu. The highest mean value for fresh and dry seed yield was observed in Chittor local. The genotype Mulanur local has recorded the highest mean value for number of pods per plant and number of seeds per pod and Arupukotai local excelled the general mean for the traits seeds per pod, fresh and dry seed yield and also for tuber characters. An investigation was carried out to quantify the colchicine (alkaloid) present in tubers by High Performance Liquid Chromatography (HPLC) method. The genotypes collected from Arupukotai recorded the highest colchicine content (0.760 mg/g) followed by Chittoor (0.578 mg/g) and Mulanur (0.496 mg/g) and there by these three genotypes were utilized for further crop improvement.

INFLUENCE OF METHODS FOR SELECTION OF PLANTS AND WAYS OF SEEDING ON EFFICIENCY OF ORIGINAL SEEDS OF FLAX-DOLGUNETS GRROWING IN PRIMARY SEED BREEDING

2020 ◽  
Keyword(s):  
Seed Yield ◽  
Control Level ◽  
Row Spacing ◽  
High Germination ◽  
Breeding Efficiency ◽  
Flax Seeds ◽  
Narrow Row ◽  
Seed Propagation ◽  
Selection Of

The results of scientific research are presented, which made it possible to develop less labor-intensive methods for selecting flax plants to grow original (updated) seeds. Studies have shown that a positive selection of tall plants of flax, compared with the accepted counterpart (control), increased seed yield 1.7-1.9 times. Moreover, plant homogeneity according to the main characteristics (height and fiber content in the stem) characterizing the varietal quality of grown seeds turned out to be at the control level. A negative selection, involving the removal of atypical plants, provided an increase in the output volume of seeds compared to the control by 3.9-4.1 times. This selection method did not reduce the varietal quality of seed material compared to the accepted analogue. With both selection methods, after combining typical plants, seeds with the same high germination rates were obtained (96-99 %). The breeding efficiency of the grown flax seeds using narrow-row sowing methods is shown. Studies have established that narrow-row sowing of seeds with a row-spacing of 7.5 and 6.25 cm compared with sowing by a wide-row method significantly increased their yield by 2.8-3.0 and 2.3-3.0 kg / ha, respectively. The greatest influence on the formation of seed yield in narrow-row sowing (6.25 cm) was exerted by the method of sowing, the part of which was 76.1 %. As the length of seed propagation of flax in creased (up to the uterine elite 2 years) in narrow-row sowing (6.25 cm) compared to broad-row, there was no decrease in quality indicators - germination and seed strength.

Evaluation of Large-Sunflower Lines of Sunflower on Quantitative Morphological Traits

2020 ◽  
pp. 46-55
Keyword(s):  
Fertility Restoration ◽  
Morphological Characters ◽  
Direct Selection ◽  
Oilseed Crops ◽  
Turkish Origin ◽  
Self Pollination ◽  
Special Area ◽  
Pericarp Color ◽  
Selection For ◽  
Selection Of

Confectionery sunflower - a special area of use of sunflower, which requires the creation of marketable seeds quality features. One of the possible ways to create large-fruited sunflower is to create production hybrids and lines. Objective: to evaluate the created new large-fruited sunflower lines by a complex of morphological characters and determine the best lines for use as large-seeds hybrids as parent components or source material. In 2016-2019 years on the basis of the Institute of Oilseed Crops NAAS a study was conducted to assess the economic characteristics of large-fruited sunflower lines. We studied a collection of 27 lines of large-seeds sources. The lines were created by direct selection or crossing and sampling: Reyny of Argentinean origin, Zaporizhzhya confectionery variety, confectionery hybrid with striped pericarp color of Israeli origin, white seed of Turkish origin, synthetic population - donor of complex resistance. To study from the collection, lines were drawn that went through at least 7 generations with selection for seed size. Experience has shown that the shortest growing season for lines 174d and KP11 was 99 days, and the longest for lines I2K670 was 109 days. In the studied collection, the greatest mass of 1000 seeds has the KP11-146.47g line, which is the mother component and does not have branching. The second by weight of 1000 seeds (109 g) stood out line 168v, which also had branches and pollen fertility restoration genes and will be used as the paternal form. The third largest is also one basket line ZKN51-100. The collection included lines originating from the same combination, but with a different morphotype for the presence and absence of branching. So, based on the combination of KP11 x Zaporizhzhya Confectionery, three lines were obtained. A mass of 1000 seeds was observed in 98-86 g, with the branching line having the largest mass of 1000 seeds. The lines created with one combination VK678 x ZKN32: with a branch 168a had a mass of 1000 seeds 95g, and a line 168b - without a branch 109 g. Of the two lines obtained from the descendants of the combination KP11 x the striped hybrid both had branches, but the seeds were much smaller (weight of 1000 seeds 59 and 79 g). The collection also studied samples created on the basis of varieties and populations 160c, 174, 175b, the mass of 1000 seeds of which turned out to be more acceptable for large-fruited use from 83 to 99 g. Summing up the results of studying the collection of newly created lines, we can highlight the lines 162d, 168v, 175b, KP11 that are potentially promising for use in hybrids. The selections showed that large-fruited lines can be obtained from large-fruited varieties, self-pollination of large-fruited hybrids and crossing lines with hybrids and varieties. Self-pollination and selection of large-fruited lines in several generations does not provide the necessary variability for positive changes in selections. The result of the selection by weight of 1000 seeds in the offspring from crosses and from populations creates opportunities for new large-seeds sunflower.

SINGLE-FACTOR LINEAR REGRESSION MODEL OF HODGKIN’S LYMPHOMA IN ADOLESCENTS

2017 ◽  
Vol 63 (2) ◽  
pp. 320-325
Author(s):  
Svetlana Kuleva ◽  
Svetlana Ivanova ◽  
Andrey Karitskiy ◽  
Darya Zvyagintseva
Keyword(s):  
Radiation Therapy ◽  
Linear Regression ◽  
Predictive Factors ◽  
Hodgkin’S Lymphoma ◽  
Risk Group ◽  
Hodgkin's Lymphoma ◽  
Regression Equations ◽  
Single Factor ◽  
Number Of Cycles ◽  
Selection Of

With the use of regression and dispersion analyzes conducted in this study it was possible to identify predictive factors that significantly worsen the prognosis of Hodgkin’s lymphoma in adolescents however constructed regression equations did not pass the quality assessment of the models, which did not allow them to be used for the construction of point and interval predictions. In a cohort of patients enrolled in the study a risk-adapted treatment program based on the risk group for stratification was conducted. Negative aspects of the results of our study could be related to the already selected volume of the program for these patients. In turn our analysis proves the validity of the selection of therapeutic loads (a number of cycles of polychemotherapy, doses of radiation therapy) depending on the risk group, into which the adolescent is stratified.

scholarly journals Teasing Apart Silvopasture System Components Using Machine Learning for Optimization

Soil Systems ◽  
2021 ◽  
Vol 5 (3) ◽  
pp. 41
Author(s):  
Tulsi P. Kharel ◽  
Amanda J. Ashworth ◽  
Phillip R. Owens ◽  
Dirk Philipp ◽  
Andrew L. Thomas ◽  
...  
Keyword(s):  
Machine Learning ◽  
Linear Regression ◽  
Regression Tree ◽  
Plant Production ◽  
System Level ◽  
Learning Approaches ◽  
Nutrient Distribution ◽  
Wetness Index ◽  
Variable Approach ◽  
Animal Grazing

Silvopasture systems combine tree and livestock production to minimize market risk and enhance ecological services. Our objective was to explore and develop a method for identifying driving factors linked to productivity in a silvopastoral system using machine learning. A multi-variable approach was used to detect factors that affect system-level output (i.e., plant production (tree and forage), soil factors, and animal response based on grazing preference). Variables from a three-year (2017–2019) grazing study, including forage, tree, soil, and terrain attribute parameters, were analyzed. Hierarchical variable clustering and random forest model selected 10 important variables for each of four major clusters. A stepwise multiple linear regression and regression tree approach was used to predict cattle grazing hours per animal unit (h ha−1 AU−1) using 40 variables (10 per cluster) selected from 130 total variables. Overall, the variable ranking method selected more weighted variables for systems-level analysis. The regression tree performed better than stepwise linear regression for interpreting factor-level effects on animal grazing preference. Cattle were more likely to graze forage on soils with Cd levels <0.04 mg kg−1 (126% greater grazing hours per AU), soil Cr <0.098 mg kg−1 (108%), and a SAGA wetness index of <2.7 (57%). Cattle also preferred grazing (88%) native grasses compared to orchardgrass (Dactylis glomerata L.). The result shows water flow within the landscape position (wetness index), and associated metals distribution may be used as an indicator of animal grazing preference. Overall, soil nutrient distribution patterns drove grazing response, although animal grazing preference was also influenced by aboveground (forage and tree), soil, and landscape attributes. Machine learning approaches helped explain pasture use and overall drivers of grazing preference in a multifunctional system.

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