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Record W7060717279

Patterns of accumulation of wheat gluten proteins during kernel development in response to weather variation

2010· dissertation· en· W7060717279 on OpenAlexfundno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2010
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
FundersAgriculture and Agri-Food CanadaScheme for Promotion of Academic and Research CollaborationStrong
KeywordsGlutenVariation (astronomy)Wheat glutenKernel (algebra)Wheat flourWheat germ
DOInot available

Abstract

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Investigating the patterns of variation of wheat gluten proteins during kernel development in relation to weather parameters acquired concurrently, should generate considerable worthwhile new knowledge on the environmental influences and biochemical nature of wheat quality variation for breadmaking.That investigation represented the focus ofthis thesis research.Two hard spring wheat cultivars (Superb and AC Vista) were grown at two locations (Winnipeg, MB and Swift Current, SK) in replicated plots under optimal soil fertility conditions in two consecutive seasons (2003 and2004).Wheat heads were sampled at3-4 day intervals during kernel development from anthesis to maturity.Heads were preserved by freezing at field sites and subsequent freeze drying, and were threshed by hand and finally ground to a standard parlicle size for protein analysis.Ground wheat was extracted in 50% 1-propanolproducing two fractions: 50% lpropanol soluble protein (mainly gliadins) and 50Yo 1-propanol insoluble protein (i.e.insoluble or HMW polymeric glutenin).A different fractionation isolated soluble glutenin from the 50% l-propanol soluble protein.Reduced soluble and insoluble glutenin was analyzed by reversed-phase HPLC resulting in quantification of individual and total HMW glutenin subunits (GS) and total LMW-GS.Thousand kernel weight ii Abstract (TKW), a measure of grain dry matter accumulation was also measured.Meteorological data acquired concurrently with measurement on the kernels included hourly measurements of solar radiation, air temperature, humidity, precipitation, useful heat (GDD5, growing degree days > 5 oc), evapotranspiration, and modeled water use, demand and deficit.Site-years produced very different weather conditions during the growing season and grain development periods resulting in substantial differences in grain filling duration and accumulation patterns of total protein and protein fractions.For the most part, there was relatively little difference in response between the two genotypes used in the study, despite differences in their HMW-GS composition.The very large range in total protein content at maturity across site-years (-9-17o/o) was very compelling and indicated the considerable influence that crop season weather can have molecular mechanisms of grain development and wheat quality in general.Grain filling duration (hence time of protein accumulation) was negatively and positively associated with temperature related variables and rainfall, respectively.Grain filling duration was also strongly negatively correlated with the rate of grain filling.Accumulation of total protein, and constituent protein fractions (gliadin, small polymeric glutenin, large polymeric glutenin, and residue) during kernel development were substantially affected by site-year differences in weather, although a common pattern of variation emerged confirmed the asynchronous nature of wheat protein synthesis.A continuously increasing ratio of glutenin to gliadin during kernel development also indicated a basic difference in regulation of gliadin and glutenin synthesis.Averaged across growing sites and years, protein by type started accumulating in the following order: gliadin, soluble glutenin, insoluble glutenin.Gliadin synthesis iii began as early as 7 DAA for one growing location (2003 Swift Cunent that experienced relatively warm and dry conditions) and was clearly underway for all site-years by 15 DAA.Synthesis of small glutenin polymers lagged slightly behind thar for gliadins by about 3 days, accumulate d al a comparable or somewhat slower rate compared to gliadins, and reached a peak at least one week later.After peak absolute accumulation (mg/kernel), gliadins remained at generally constant levels in all site-years, while soluble glutenin comprising small glutenin polymers, decreased signifìcantly for another l0 to 20 calendar days until maturity depending on growing location.Insoluble glutenin (large glutenin polymers) stafted to form in general in significant amounts much later than that for gliadins, beginning around 25 DAA, but at a higher rate.However, for one growing location (2003 Swift Current) where kernel development was accelerated, insoluble glutenin began to form at a high rate at about 15 DAA, but still later than that for soluble glutenin atthat location.Formation of insoluble glutenin invariably lagged behind that of soh-rble glutenin from 3 to 12 days depending on genotype and growing location.No peak accumulation was observed for insoluble glutenin, which continued to increase, but at a slower pace, until maturity.As well, the proportion of insoluble glutenin increased at the same time that the proportion of soluble glutenin decreased towards the latter part of kernel development, suggesting that the two events were mechanistically related, i.e. aggregation of smaller polymers (soluble glutenin) leads to formation of larger polymers (insoluble glutenin).Like the parent glutenin fraction, accumulation pattems for constituent HMW glutenin subunit composition were highly influenced by weather-induced site-year effects and some different trends were observed for individual HMW-GS loci.Most notable was over-expressed Bx7 subunit of AC Vista as it accumulated at a much higher iv rate compared to the other four HMW-GS in its complement.HMW-GS Dx5 and Bx7* of Superb also accumulated at a faster rate compared to the other three HMV/-GS.These effects were consistent among site-years.Small but apparently signif,rcant differences in relative rates of synthesis of Superb HMW-GS among site-years towards the end of the kernel development were observed.Identifying site-year independent trends in weather relationships to protein accumulation patterns during kernel development was challenging.Weather factors that were site characteristics included solar radiation (but not air temperature), wind speed (but not evapotranspiration), water demand, and water deficit; all had higher values in one location (Swift Current) compared to another (Winnipeg) averaged across years.In contrast, precipitation and air temperature were growing season characteristics.Rainfall was a poor predictor of protein accumulation patterns.Poor results were obtained were found when protein accumulation was examined for weather parameters varying by calendar days (i,e.DAA), When protein accumulation was expressed as percent of total protein and was analyzed in response to cumulative temperature-related weather parameters, such as thermal time (e.g.GDD5) strong site-year independent relationships were observed for gliadin, soluble glutenin and insoluble glutenin fractions.For insoluble glutenin, those relationships followed a linear trend.For gliadin and soluble glutenin, bell-shaped patterns of protein accumulation were evident, with soluble glutenin showing a more pron'ounced profile.The influence of growing season weather in western Canada on hard spring wheatgrown in optimally ferlilized fields was striking in its large effects on protein content and composition.The strong relationships found between GDD5 and related weather parameters, and protein fraction accumulation in total protein could potentially be used in developing models for predicting wheat breadmaking quality before harvest.Those models could be used for example, to improve the ability of the market place to match wheat quality requirements of specific customers to wheat grown in specific regions of Western Canada.VI

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.248
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2010
Admission routes1
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