Concepts and Methods of Statistical Designs

Abstract Key message Integrating genomics technologies and breeding methods to tweak core parameters of the breeder’s equation could accelerate delivery of climate-resilient and nutrient rich crops for future food security. Abstract Accelerating genetic gain in crop improvement programs with respect to climate resilience and nutrition traits, and the realization of the improved gain in farmers’ fields require integration of several approaches. This article focuses on innovative approaches to address core components of the breeder’s equation. A prerequisite to enhancing genetic variance (σ2g) is the identification or creation of favorable alleles/haplotypes and their deployment for improving key traits. Novel alleles for new and existing target traits need to be accessed and added to the breeding population while maintaining genetic diversity. Selection intensity (i) in the breeding program can be improved by testing a larger population size, enabled by the statistical designs with minimal replications and high-throughput phenotyping. Selection priorities and criteria to select appropriate portion of the population too assume an important role. The most important component of breeder′s equation is heritability (h2). Heritability estimates depend on several factors including the size and the type of population and the statistical methods. The present article starts with a brief discussion on the potential ways to enhance σ2g in the population. We highlight statistical methods and experimental designs that could improve trait heritability estimation. We also offer a perspective on reducing the breeding cycle time (t), which could be achieved through the selection of appropriate parents, optimizing the breeding scheme, rapid fixation of target alleles, and combining speed breeding with breeding programs to optimize trials for release. Finally, we summarize knowledge from multiple disciplines for enhancing genetic gains for climate resilience and nutritional traits.

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A review of statistical designs for improving the efficiency of phase II studies in oncology

Statistical Methods in Medical Research ◽

10.1177/0962280215588247 ◽

2015 ◽

Vol 25 (3) ◽

pp. 1010-1021 ◽

Cited By ~ 4

Author(s):

James MS Wason ◽

Thomas Jaki

Keyword(s):

Phase Ii ◽

Phase Ii Studies ◽

Statistical Designs

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Statistical designs for two-color microarray experiments involving technical replication

Computational Statistics & Data Analysis ◽

10.1016/j.csda.2006.05.017 ◽

2006 ◽

Vol 51 (3) ◽

pp. 2078-2090 ◽

Cited By ~ 7

Author(s):

Shin-Fu Tsai ◽

Chen-Tuo Liao ◽

Feng-Shun Chai

Keyword(s):

Microarray Experiments ◽

Statistical Designs ◽

Technical Replication

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Decolourization of aqueous dye solutions by a novel adsorbent: Application of statistical designs and surface plots for the optimization and regression analysis

Journal of Hazardous Materials ◽

10.1016/j.jhazmat.2005.03.008 ◽

2005 ◽

Vol 122 (1-2) ◽

pp. 75-83 ◽

Cited By ~ 107

Author(s):

K. Ravikumar ◽

B. Deebika ◽

K. Balu

Keyword(s):

Regression Analysis ◽

Statistical Designs ◽

Dye Solutions

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of Statistical Designs

Handbook of Bolts and Bolted Joints ◽

10.1201/9781482273786-236 ◽

1998 ◽

pp. 846-846

Keyword(s):

Statistical Designs

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Statistically Designed Extraction of Herbs Using Ultrasound Waves: A Review

Current Pharmaceutical Design ◽

10.2174/1381612827666210222114441 ◽

2021 ◽

Vol 27 ◽

Author(s):

Ashwani Arya ◽

Rubal Chahal ◽

Arun Nanda ◽

Deepak Kaushik ◽

May Bin- Jumah ◽

...

Keyword(s):

Published Data ◽

Optimization Approach ◽

Solvent Ratio ◽

Sound Waves ◽

Ultrasound Assisted Extraction ◽

Ultrasound Waves ◽

Yield And Quality ◽

Assisted Extraction ◽

Ultrasound Assisted ◽

Statistical Designs

Background: Extraction is the foremost step to isolate the natural constituents from a medicinal plant and leads the process of development of herbal formulation from bench to bed. Introduction: In the field of extraction, the optimization approach helps in achieving better yield and quality where a response of concern is determined or influenced by various variables. This review aimed at congregating the application of different statistical designs (CCD/BBD) to optimize the Ultrasound assisted extraction (UAE) parameters for the recovery of various plant actives belonging to different categories. Methodology: The literature published during last decade in the various reputed databases (Web of Science, Pubmed, Scopus) was reviewed and compiled to reveal the role of response surface methodology in optimizing the influential parameters involved in the ultrasound assisted extraction of herbs. Conclusion: From the present investigations, it can be concluded that the different variables such as sonication power, temperature, time, solute to solvent ratio are generally optimized in UAE of herbs. Moreover, it has also been evidenced from the review of published data that the flavonoids/phenolic acids (>50%) leads the race for the extraction of plants using sound waves. It can be said that the statistically designed UAE has vast prospective in bringing about a green mutiny in herbal drug industry and the modeling of various parameters shall be able to absolutely build up a complete drug innovation course (bench to bed).

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Statistical Optimization of HVAF Sprayed Cr3C2-NiCr Coatings for Minimizing Decarburization

Thermal Spray 2000: Proceedings from the International Thermal Spray Conference ◽

10.31399/asm.cp.itsc2000p0543 ◽

2000 ◽

Author(s):

S.J. Matthews ◽

M.M. Hyland

Keyword(s):

Factorial Design ◽

Statistical Design ◽

Process Variable ◽

Traverse Speed ◽

Deposition Efficiency ◽

Spray Parameters ◽

Statistical Design Of Experiments ◽

Spray Coatings ◽

Wide Range ◽

Statistical Designs

Abstract High-velocity air fuel (HVAF) spraying was selected for spray trials of a Cr3C2-NiCr powder. To determine the effect of spray parameters on coating characteristics, particularly porosity and phase degradation, a statistical design of experiments was implemented. A wide range of statistical designs have been applied to the optimization of thermal spray coatings with a great deal of success. In this instance, a lack of prior knowledge and the need to assess many process-variable interactions efficiently led to the selection of a two-level full factorial design. High and low settings for each variable, including spray distance, traverse speed, and powder feedrate, were chosen based on the ranges typically used to spray similar materials. The resulting coatings were assessed for microhardness, porosity, residual stress, deposition efficiency, and phase transformation, after which several follow-up runs were conducted to explore trends brought to light by the initial factorial design.

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