scholarly journals Validation of Inductive cum Targeted Yield Model based FertiliserPrescription Equations for Pearl millet (var. CO 10) onInceptisol

2020 ◽  
Vol 107 (4-6) ◽  
Author(s):  
Kanchana B ◽  
Santhi R ◽  
Maragatham S ◽  
Chandrasekhar C.N
Keyword(s):  
Pearl Millet ◽  
Yield Model ◽  
Model Based

A methodology for model-based greenhouse design: Part 3, sensitivity analysis of a combined greenhouse climate-crop yield model

2011 ◽  
Vol 110 (4) ◽  
pp. 396-412 ◽  
Author(s):  
B.H.E. Vanthoor ◽  
E.J. van Henten ◽  
C. Stanghellini ◽  
P.H.B. de Visser
Keyword(s):  
Sensitivity Analysis ◽  
Crop Yield ◽  
Yield Model ◽  
Greenhouse Climate ◽  
Model Based

Rainstorm‐generated sediment yield model based on soil moisture proxies ( SMP )

2020 ◽  
Vol 34 (16) ◽  
pp. 3448-3463
Author(s):  
Sushindra Kumar Gupta ◽  
Pushpendra K. Singh ◽  
Jaivir Tyagi ◽  
Gunwant Sharma ◽  
Ajay Singh Jethoo
Keyword(s):  
Soil Moisture ◽  
Sediment Yield ◽  
Yield Model ◽  
Model Based

scholarly journals Association mapping for resin yield in Pinus roxburghii Sarg. using microsatellite markers

2014 ◽  
Vol 63 (1-6) ◽  
pp. 253-266 ◽  
Author(s):  
Anita Rawat ◽  
S. Barthwal ◽  
H. S. Ginwal
Keyword(s):  
Association Mapping ◽  
Ssr Markers ◽  
Association Analysis ◽  
Yield Model ◽  
Pinus Roxburghii ◽  
Phenotypic Data ◽  
Gene Effects ◽  
Model Based Clustering ◽  
Model Based ◽  
Nuclear Ssr

Abstract Association mapping is a method for detection of gene effects based on linkage disequilibrium (LD) that complements QTL analysis in the development of tools for molecular plant breeding. A total of 240 genotypes of Pinus roxburghii (Himalayan Chir Pine) from a natural population in Chakrata division (Tiunee range), Uttarakhand (India) were evaluated for resin yield. Based on the phenotypic data and stable resin production in consecutive years, 53 genotypes were selected after excluding the individuals with similar resin production. The selected 53 individuals were best representatives of the variation in resin yield in Chakrata population which varied between 0.25 and 8.0 kg/tree/year and were used for genotyping and association analysis using SSR markers. Out of 80 primers initially screened, a total of 19 polymorphic SSRs (11 cpSSR and 8 nSSR) were used in the study. Model based clustering using 19 polymorphic SSR markers identified five subpopulations among these genotypes. LD was evaluated using the entire population. The squared allele frequency correlation, r2 was estimated for each pair of SSR loci. The comparison wise significance (p-values) of SSR marker pairs was determined by performing 100,000 permutations. The genetic divergence ranged from 50 to 100%. The UPGMA based hierarchial clustering grouped the genotypes in accordance with their resin yield. Model based clustering suggested the existence of five subpopulations in the sample. However, the distribution of P. roxburghii genotypes into five subpopulations had no correlation with their resin yield thus ruling out the possibility of any ancestral relationship among the genotypes with similar resin yield. AMOVA suggested that the variation among P. roxburghii genotypes at the molecular level was related with the variation in resin yield and not their site of collection thus highlighting the genetic basis of the trait. LD based association analysis revealed two chloroplast SSRs Pt71936 and Pt87268 and one nuclear SSR pm09a to be in significant association with resin yield. The two associated chloroplast SSRs showed significant LD (p<0.01). One of the chloroplast SSR Pt87268 showing association with resin yield was also found to be in significant LD with the nuclear SSR pm07, further showing the probability of this marker also to be associated with resin yield.

A Productivity-Oriented Wafer Map Optimization Using Yield Model Based on Machine Learning

2019 ◽  
Vol 32 (1) ◽  
pp. 39-47 ◽  
Author(s):  
Jong-Seong Kim ◽  
Sung-Ju Jang ◽  
Tae-Woo Kim ◽  
Hyun-Jin Lee ◽  
Jong-Bae Lee
Keyword(s):  
Machine Learning ◽  
Yield Model ◽  
Model Based

A methodology for model-based greenhouse design: Part 2, description and validation of a tomato yield model

2011 ◽  
Vol 110 (4) ◽  
pp. 378-395 ◽  
Author(s):  
B.H.E. Vanthoor ◽  
P.H.B. de Visser ◽  
C. Stanghellini ◽  
E.J. van Henten
Keyword(s):  
Yield Model ◽  
Model Based ◽  
Tomato Yield

Strip Yield Model Applicability to Crack Growth Predictions for Various Types of Fatigue Loading

2016 ◽  
Vol 250 ◽  
pp. 120-126
Author(s):  
Tomasz Machniewicz ◽  
Małgorzata Skorupa ◽  
Adam Korbel
Keyword(s):  
Structural Steel ◽  
Crack Growth ◽  
Fatigue Loading ◽  
Constant Amplitude ◽  
Yield Model ◽  
Variable Amplitude Loading ◽  
Variable Amplitude ◽  
Model Based ◽  
Constraint Factors ◽  
Strip Yield Model

The capability of the strip yield (SY) model to predict crack growth in structural steel is investigated. To this end the SY model implementation developed by the present authors is applied to simulate crack growth observed in S355J2 steel specimens under constant amplitude and simple variable amplitude loading. A particular attention is given to the calibration of the model using the constraint factors and examining whether tuning the model, based on constant amplitude loading, allows the adequate predictions for variable amplitude loading.

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