Barley malting quality: are we selecting the best?

2003 ◽  
Vol 54 (12) ◽  
pp. 1261 ◽  
Author(s):  
B. R. Cullis ◽  
A. B. Smith ◽  
J. F. Panozzo ◽  
P. Lim
Keyword(s):  
Mixed Model ◽  
Field Trials ◽  
Trial Interaction ◽  
Malting Quality ◽  
Quality Trait ◽  
Base Line ◽  
Response To Selection ◽  
Variance Heterogeneity ◽  
Sources Of Variation ◽  
Mapping Populations

This paper presents an analysis of several key barley malting traits from 2 mapping populations grown as a series of multi-environment field trials. The analysis is based on a mixed model that includes terms for all sources of variation in the trait data, namely varieties, variety by trial interaction, variation between plots in the field, and variation between samples in the laboratory processes required to measure the traits. The base-line model is extended to accommodate variance heterogeneity and correlated effects for many of the terms in the model. The results show that accounting for these phenomena may cause substantial changes in variety rankings. The methods of design and analysis proposed in this paper for barley quality trait data do not have common usage so if adopted in future there is an opportunity for substantial improvements in response to selection.

scholarly journals Statistical methods for analysis of multi-harvest data from perennial pasture variety selection trials

2015 ◽  
Vol 66 (9) ◽  
pp. 947 ◽  
Author(s):  
Joanne De Faveri ◽  
Arūnas P. Verbyla ◽  
Wayne S. Pitchford ◽  
Shoba Venkatanagappa ◽  
Brian R. Cullis
Keyword(s):  
Statistical Methods ◽  
Temporal Correlation ◽  
Field Trials ◽  
Model Fit ◽  
Natural Sources ◽  
Variety Selection ◽  
Sources Of Variation ◽  
Harvest Data ◽  
Insight Into

Variety selection in perennial pasture crops involves identifying best varieties from data collected from multiple harvest times in field trials. For accurate selection, the statistical methods for analysing such data need to account for the spatial and temporal correlation typically present. This paper provides an approach for analysing multi-harvest data from variety selection trials in which there may be a large number of harvest times. Methods are presented for modelling the variety by harvest effects while accounting for the spatial and temporal correlation between observations. These methods provide an improvement in model fit compared to separate analyses for each harvest, and provide insight into variety by harvest interactions. The approach is illustrated using two traits from a lucerne variety selection trial. The proposed method provides variety predictions allowing for the natural sources of variation and correlation in multi-harvest data.

Intentionally Deadheading SAGD ESPs - An Unconventional Approach to Improve Run Life

2021 ◽  
Author(s):  
J. Daine Studer ◽  
Jesus E. Chacin ◽  
Roger Walters ◽  
Hoai Ann Nguyen
Keyword(s):  
Fiber Optics ◽  
Field Tests ◽  
Field Trials ◽  
Base Line ◽  
Cooling Rates ◽  
Temperature Changes ◽  
Plant Maintenance ◽  
High Cooling Rates ◽  
Log Normal ◽  
Log Normal Distribution

Abstract SAGD ESPs run at the highest motor temperatures current technology allows. However, they cool very rapidly when shutdown. High cooling rates promote motor oil volumetric contraction, eventually leading to wellbore fluid ingress and short-circuited motors. The Paper presents successful field tests designed to decrease ESP cooling rates by inducing controlled deadheads, rather than shutting down ESPs. Various extended deadhead field trials (up to 70+ days duration) validated the approach, while confirming that no deadhead related ESP damage was induced. ESP temperature changes were measured using fiber optics strings installed as part of the usual completion in 60+ wells, during a four week-long field-wide plant maintenance turn-around. While cooling rates varied somewhat from well to well, they all showed very similar behavior and were very well fitted with a log-normal distribution, R2factor > 95%. Most ESP temperatures decreased between 50°C to 120°C in a week. This data was used as a general baseline to support the deadheading field trials. An ESP was fitted internally with an RTD at the base of the motor and externally with a clamped fiber optics string. This ESP was operated normally at 55 Hz for a few months. An 8-hour shut down test established an initial base line cooling rate of 6.6°C/hour. Subsequent 6-hour deadhead tests at 30Hz and 45 Hz showed decreased cooling rates of 4.0°C/hour and 2.2°C/hour, respectively. This result clearly established the potential to deadhead at different frequencies to obtain different lower cooling rates. Finally, two extended deadhead tests (3 and 10 weeks in duration) were executed to help determine if it was possible to induce damage in SAGD ESPs by deadheading, as is usually the case in most non-thermal applications. These ESPs operated normally after the extended tests and one was dismantled upon failure, looking for any signs of deadhead damage. Results presented show that deadheading SAGD ESPs provides the opportunity to safely minimize ESP thermal cycles, which could lead to a significant improvement in ESP run life.

scholarly journals The effect of stand structure on the grain quality of spring barley

2019 ◽  
Vol 65 (No. 4) ◽  
pp. 205-210
Author(s):  
Jan Křen ◽  
Martin Houšť ◽  
Ludvík Tvarůžek ◽  
Zdeněk Jergl
Keyword(s):  
Protein Content ◽  
Management Practices ◽  
Plant Density ◽  
Stand Structure ◽  
Spring Barley ◽  
Field Trials ◽  
Nitrogen Fertilizers ◽  
Malting Quality ◽  
Gross Margin ◽  
High Level

The results of 81 different crop management practices in spring barley grown in small-plot field trials on fertile soils in central Moravia were assessed during 2014–2016 with the aim to achieve the highest gross margin (GM – calculated as the difference between revenues and direct costs). GM was most affected by protein content in the grain below 12% corresponding to malting quality. Analyses identified greater determination level of non-linear relationships between stand structure elements and the content of nitrogen substances in the grain. This indicates that the probability of obtaining high quality malting barley is increased when a high level of sinks (number of grains/m<sup>2</sup>) corresponding to availability of sources, mainly water, is formed by optimal plant density (300–400/m<sup>2</sup>) and balanced combination of both structural elements of crop stand, i.e. – number of spikes per plant (2–4) and number of grains per spike (18–26). In case that the high level of sinks will be formed predominantly by one element, the risk of higher protein content in grain increases. This constitutes the requirement of early sowing and uniform, synchronized tillering and efficient use of nitrogen fertilizers.

Quantitative trait loci of barley malting quality trait components in the Stellar/01Ab8219 mapping population

2014 ◽  
Vol 34 (1) ◽  
pp. 59-73 ◽  
Author(s):  
Emir Islamovic ◽  
Donald E. Obert ◽  
Allen D. Budde ◽  
Mark Schmitt ◽  
Robert Brunick ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Mapping Population ◽  
Malting Quality ◽  
Quality Trait ◽  
Trait Loci

A note on the analysis of germination data from complex experimental designs

2017 ◽  
Vol 27 (4) ◽  
pp. 321-327 ◽  
Author(s):  
Signe M. Jensen ◽  
Christian Andreasen ◽  
Jens C. Streibig ◽  
Eshagh Keshtkar ◽  
Christian Ritz
Keyword(s):  
Random Effects ◽  
Mixed Models ◽  
Mixed Model ◽  
Experimental Designs ◽  
Germination Test ◽  
Random Effects Models ◽  
Event Time ◽  
Sources Of Variation ◽  
Germination Experiments ◽  
Time Point

AbstractIn recent years germination experiments have become more and more complex. Typically, they are replicated in time as independent runs and at each time point they involve hierarchical, often factorial experimental designs, which are now commonly analysed by means of linear mixed models. However, in order to characterize germination in response to time elapsed, specific event-time models are needed and mixed model extensions of these models are not readily available, neither in theory nor in practice. As a practical workaround we propose a two-step approach that combines and weighs together results from event-time models fitted separately to data from each germination test by means of meta-analytic random effects models. We show that this approach provides a more appropriate appreciation of the sources of variation in hierarchically structured germination experiments as both between- and within-experiment variation may be recovered from the data.

scholarly journals Modelling spatial trends in sorghum breeding field trials using a two-dimensional P-spline mixed model

2017 ◽  
Vol 130 (7) ◽  
pp. 1375-1392 ◽  
Author(s):  
Julio G. Velazco ◽  
María Xosé Rodríguez-Álvarez ◽  
Martin P. Boer ◽  
David R. Jordan ◽  
Paul H. C. Eilers ◽  
...  
Keyword(s):  
Mixed Model ◽  
Field Trials ◽  
Two Dimensional ◽  
Spatial Trends ◽  
Sorghum Breeding

scholarly journals Tensor P-Spline Smoothing for Spatial Analysis of Plant Breeding Trials

2021 ◽  
Author(s):  
Hans-Peter Piepho ◽  
Martin Boer ◽  
Emlyn R. Williams
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Null Space ◽  
Spatial Interaction ◽  
Natural Extension ◽  
Covariance Structure ◽  
Spatial Modelling ◽  
Field Trials ◽  
Agricultural Field ◽  
Randomized Field Trials

Large agricultural field trials may display irregular spatial trends that cannot be fully captured by a purely randomization-based analysis. For this reason, paralleling the development of analysis-of-variance procedures for randomized field trials, there is a long history of spatial modelling for field trials, starting with the early work of Papadakis on nearest neighbour analysis, which can be cast in terms of first or second differences among neighbouring plot values. This kind of spatial modelling is amenable to a natural extension using P-splines, as has been demonstrated in recent publications in the field. Here, we consider the P-spline framework, focussing on model options that are easy to implement in linear mixed model packages. Two examples serve to illustrate and evaluate the methods. A key conclusion is that first differences are rather competitive with second differences. A further key observation is that second differences require special attention regarding the representation of the null space of the smooth terms for spatial interaction, and that an unstructured variance-covariance structure is required to ensure invariance to translation and rotation of eigenvectors associated with that null space. We develop a strategy that permits fitting this model with ease, but the approach is more demanding than that needed for fitting models using first differences. Hence, even though in other areas second differences are very commonly used in the application of P-splines, our main conclusion is that with field trials first differences have advantages for routine use.

scholarly journals Effect of non-genetic factors on prolificacy and pre-weaning kid mortality of Khari goats in Nawalpur, Nepal

2021 ◽  
Vol 4 (1) ◽  
pp. 87-95
Author(s):  
Nirajan Bhattarai
Keyword(s):  
Maximum Likelihood ◽  
Computer Program ◽  
Selective Breeding ◽  
Genetic Factors ◽  
Mixed Model ◽  
Coat Color ◽  
Fixed Effect ◽  
Least Square ◽  
Sources Of Variation

Present study was carried out mainly aiming at studying the effect of non-genetic factors on prolificacy and pre-weaning kid mortality of Khari goats in Nawalpur, Nepal. The traits were recorded for 1005 does were measured and analyzed using fixed effect Least Square Mixed Model and Maximum Likelihood Computer Program (LSMMML PC-2). Results revealed that overall mean prolificacy and pre-weaning kid mortality in this study were 145 and 6.2%, respectively. According to the results, non-genetic factors such as altitude, coat color and dam’s parity were the important sources of variation with respect to pre-weaning kid mortality and prolificacy of Khari goats in this study. Thus, the results of present study suggested the scope of improvement in prolificacy and pre-weaning kid mortality through selective breeding.

scholarly journals 15 EFFECT OF SEMEN THAW METHOD ON CONCEPTION RATE IN DAIRY HEIFER HERDS

2005 ◽  
Vol 17 (2) ◽  
pp. 157 ◽  
Author(s):  
M. Kaproth ◽  
H. Rycroft ◽  
G. Gilbert ◽  
G. Abdel-Azim ◽  
B. Putnam ◽  
...  
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Semen Quality ◽  
Sperm Quality ◽  
Field Trials ◽  
Conception Rate ◽  
Warm Water ◽  
Dairy Heifer

Semen processed with procedures permitting a flexible thaw method is used to breed millions of cows yearly. “Pocket thawing” is widely used as an alternative to warm-water thawing with such semen. To pocket thaw, a straw is retrieved from cryostorage, immediately wrapped in a folded paper towel, and moved to a thermally protected pocket for 2 to 3 min of thawing within the pocket before AI gun loading. Published field data are lacking for comparisons of such a thaw method with those for semen prepared to permit flexible-thawing. We measured the effect of warm-water or pocket thaw on conception rate in four dairy heifer herds using semen prepared with methods previously optimized for flexible-thawing success. Semen processing (Anderson S et al. 1994 J. Dairy Sci. 77, 2302–2307) includes two-step whole-milk extension, static vapor tank freezing (0.5-mL straws), and IMV Digitcool mechanical freezing (0.25-mL straws). It is unclear which specific processing steps permit flexible thawing. These procedures have been developed using breeding results from decades of field trials by professional inseminators using both pocket and warm-water thaw. Semen prepared from each of 12 sires produced equal straw units at 10 and 15 million total sperm per straw, in both 0.5- and 0.25-mL straw packages. Professional inseminators used each combination evenly over 16 months. Additional commercial semen (55% of total) from the same source was used. The thaw methods alternated weekly. Thaw effect on conception status, from 70 day non-return data for 11,215 services (67.6% conception rate), was estimated by a generalized linear mixed model. Neither thaw method nor total sperm per straw significantly affected conception rate (P = 0.658, 0.769, respectively). Bull, herd, inseminator within herd, year, season, and straw size did significantly affect conception rate (P < 0.05). No thaw method interactions with herd, sperm number, season, and straw package size were significant (P = 0.297, 0.526, 0.365, 0.723, respectively). This suggests that if semen has been prepared with procedures specific to flexible-thawing, it can be either pocket thawed or warm-water thawed within a range of herdsman or inseminator practices, season, or straw packaging choices. Even at 10 million, the lowest total sperm per straw, pocket thaw was equally as successful as warm-water thaw. We generally observe that in vitro sperm quality, as expected, is maximal for rapidly thawed straws, with slower thawing resulting in lower values. However, while it appears that conventional measures of in vitro semen quality are improved with fast thaw rates, these measures do not appear to correspond to higher in vivo fertility for semen prepared intentionally to be flexibly thawed. We conclude that, for semen prepared with procedures that permit flexible thawing, the thaw method, whether pocket or warm-water thaw, does not affect conception under commercial conditions and with routine semen handling methods. We thank the herd owners and their staff, the inseminators, and Hap Allen, Ron Hunt, Gordon Nickerson, and Bryan Krick of Genex for their help and cooperation.

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