A predictive model of the effects of genotypic,pre‐ and postharvest stages on barley β‐glucan levels |
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Authors: | Uma Tiwari Enda Cummins |
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Affiliation: | Biosystems Engineering, UCD School of Agriculture, Food Science and Veterinary Medicine, University College Dublin, Belfield, Dublin 4, Ireland |
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Abstract: | BACKGROUND: β‐Glucan is a bioactive component of cereal grains that has many potential uses and health‐promoting benefits. Recent research has focused on improving the nutritional value of food by increasing human exposure to β‐glucan. This study looks at the development of a farm‐level baseline model (including scenario analysis) to evaluate the impact of pre‐ and postharvest stages (including genotypic factors, environmental conditions, agronomic factors and storage) on β‐glucan levels in barley. Monte Carlo simulation techniques were employed to model various stages in pre‐ and postharvest processes and to simulate the factors influencing the level of β‐glucan content in both hulled barley (HB) and hull‐less barley (HLB) genotypes. RESULTS: The baseline model found that the mean simulated level of β‐glucan was 40.99 and 56.77 g kg?1 for HB and HLB genotypes respectively. A sensitivity analysis highlighted that genotype was the most important parameter in determining the final β‐glucan content (correlation coefficients of 0.66 and 0.78 for HB and HLB respectively), more so than any of the agronomic factors analysed. The scenario analysis highlighted the importance of harvest date (scenario 2) and storage conditions (scenario 3), with a potential 32.6 and 32.7% decrease in β‐glucan (compared with the baseline model) if harvesting is carried out early during physiological maturity (i.e. at growth stage 92) and a potential 20.1 and 19.5% increase in β‐glucan for HB and HLB respectively if storage time is minimised. CONCLUSION: This study predicted the influence of genotypic, pre‐ and postharvest operations on β‐glucan content and thus allows strategies to be identified to influence β‐glucan content in barley products. Copyright © 2008 Society of Chemical Industry |
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Keywords: | barley β ‐glucan simulation scenarios sensitivity analysis |
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