Planning, Construction, and Statistical Analysis of Comparative Experiments

Giesbrecht, Francis G.; Gumpertz, Marcia L.

doi:10.1002/0471476471

Cited by 68 publications

(62 citation statements)

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“…The CV after using alpha lattice design was still too high suggesting that experiment was not carried out efficiently. The efficiency of alpha design in second experiment could be improved by using neighbor or spatial analysis or row and column analyses [4,6,11,[16][17][18][19][20]. The rank orders of mean based on Alpha design (least square means) and RCBD (simple means) also change, which is relevant when selecting genotypes for the purpose of recommendations for the farmers.…”

Section: Resultsmentioning

confidence: 99%

Efficiency of Alpha Lattice Design in Rice Field Trials in Pakistan

et al. 2010

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Two rice trials were conducted from 2005 to 2006 in rice research institute, Kala Shah Kako Pakistan to evaluate the efficiency of alpha lattice design in field experiments. The average standard error of difference between genotypes mean is used to calculate relative efficiency of alpha lattice design. Both experiments clearly identified the advantages of small blocks. The average gain in efficiency was 119% with maximum 128%. Mean ranks comparison for both randomized complete block and alpha lattice design were performed. It was observed that the ranks were not constant across the experiments. The results emphasize that the traditional randomized complete block designs (RCBD) should be replaced by alpha lattice in the agricultural field experiments when number of varieties to be tested in an experiment increases to more than five or ten. In such a situation finding a homogeneous block is quite difficult in field experiments.Keywords: Rice; Alpha lattice design; RCBD; Pakistan.© 2011 JSR Publications. ISSN: 2070-0237 (Print); 2070-0245 (Online). All rights reserved.doi:10.3329/jsr.v3i1.4773 J. Sci. Res. 3 (1), 91-95 (2011)

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Section: Resultsmentioning

confidence: 99%

Efficiency of Alpha Lattice Design in Rice Field Trials in Pakistan

et al. 2010

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“…Thus, the 2111 accessions were evaluated for CMS in two years, in which 995 accessions were evaluated in 2016 and another 1116 accessions were evaluated in the following season (2017). Each accession was planted in two replicates using a randomized incomplete block design [50] in plots of four rows wide with 25 cm between rows and two meters long. For both seasons, 2016 and 2017, each incomplete block consisted of 50 accessions in addition to the three check cultivars, i.e., "Sids13", Gimmiza 9", and "Giza 168".…”

Section: Plant Materials and Field Growth Conditionsmentioning

confidence: 99%

Cell Membrane Stability and Association Mapping for Drought and Heat Tolerance in a Worldwide Wheat Collection

et al. 2017

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Worldwide periods of heat and drought are projected to be more frequent, longer, and occurring earlier, which could deleteriously affect the productivity of cool-season crops including wheat (Triticum spp.). The coexistence of heat and drought stresses affects plant biochemical and physiological processes including cell membrane function. The increased permeability and leakage of ions out of the cell has been used as a measure of cell membrane stability (CMS) and as a screen test for stress tolerance. The main objectives of this research were to: (1) screen a global spring wheat panel for CMS by exposing leaf tissue to heat treatment and osmotic pressure (PEG 600), (2) identify potential quantitative trait loci (QTL)/genes linked with CMS using genome-wide association mapping, and (3) estimate the relationship between the field performance and measured CMS. The results indicated highly significant differences among the 2111 spring wheat accessions regarding CMS. Moreover, several SNPs were found to be significantly linked with CMS. The annotation of the significant SNPs indicated that most of these SNPs are linked with important functional genes, which control solute transport through the cell membrane and other plant biochemical activities related to abiotic stress tolerance. Overall, this study demonstrated the use of genome-wide association mapping for the identification of potentially new genomic regions associated with CMS. Tolerant genotypes identified in this study proved to be more productive under preliminary field stress conditions. Thus, the identified membrane-stable accessions could be used as parental genotypes in breeding programs for heat or drought stress tolerance.

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“…Regression coefficients for the regression model can be calculated by Equation (1)- (2) [17][18][19][20].…”

Section: Flow Time Estimation Of Transformers Using the Regression Eqmentioning

confidence: 99%

Residual Based Flow Time Estimation Algorithm for Labor Intensive Project Type Production Systems

Karaoğlan¹

2016

deufmd

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Regression-based methods are widely used for flow time estimation of customer orders. However, for the customer orders that will be produced for the first time in a labor intensive project type production system with new design parameters, it is hard to make thoroughly accurate flow time prediction at the quotation stage. This is caused by having so many uncontrollable factors in a production system, that are not placed in the mathematical models. These uncontrollable factors cause high differences between the observed and expected flow time. In this study, a new algorithm -that combines the regression analysis and the artificial neural networks -is proposed. By this way, the prediction performance of fitted regression model is improved and the lack-of-fit is decreased.Keywords: Regression analysis, neural network applications, flow time, project type production ÖZ Regresyon tabanlı metodlar, müşteri siparişlerinin akış zamanının hesaplanmasında yaygın olarak kullanılmaktadır. Ancak emek yoğun proje tipi üretim yapan işletmelerde, ilk defa yeni tasarım parametreleri ile üretilecek olan ürünlerin akış zamanını, üretime başlamadan önce müşteriye fiyat teklifi verme aşamasında tahmin etmek zor bir problemdir. Bu durum, üretim sisteminin matematiksel modellerde yer verilemeyen pek çok kontrol edilemeyen değişken içermesinden kaynaklanır. Bu kontrol edilemeyen değişkenler ise beklenen akış zamanı ile regresyon tabanlı denklemlerle tahmin edilen zamanlar arasında hatırı sayılır bir tahmin hatasını ortaya çıkarır. Bu çalışmada, regresyon denkleminin tahmin hatasını minimize etmek üzere, yapay sinir ağları ile regresyon analizini birleştiren bir algoritma önerilmiştir. Bu yolla regresyon denkleminin tahmin performansı arttırılmış ve tahmin hataları minimize edilmiştir.Anahtar Kelimeler: regresyon analizi, yapay sinir ağları, akış zamanı, proje tipi üretim

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Planning, Construction, and Statistical Analysis of Comparative Experiments

Cited by 68 publications

References 0 publications

Efficiency of Alpha Lattice Design in Rice Field Trials in Pakistan

Efficiency of Alpha Lattice Design in Rice Field Trials in Pakistan

Cell Membrane Stability and Association Mapping for Drought and Heat Tolerance in a Worldwide Wheat Collection

Residual Based Flow Time Estimation Algorithm for Labor Intensive Project Type Production Systems

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