Physiology of biological variation

In agricultural products, variation exists in quality attributes between batches. Examples of this biological variation are well known and the general response is trying to suppress it as much as possible; to create uniformity using pre- andpostharvestmethods. This thesis shows a methodology that takes advantage of the biological variation, instead of treating it as a nuisance. This biological variation methodology was applied to understand the expected keeping quality of batches.The methodology currently consists of three steps. Firstly, repeated non-destructive measurements of quality properties of individuals need to be applied to find out how the quality attribute changes over time without having to worry about biological variation. Secondly, kinetic models need to be constructed that show the quality attribute changing over time as a combination of simultaneously occurring processes that, ideally, have a strong physiological background. The last step consists of translating the kinetic model that describes the behaviour of the quality attribute of individuals to batches usingstochastics. This methodology is applied for cucumbers and strawberries.Cucumber. The keeping quality for a cucumber, defined as the time the colour remains acceptable to the consumer, depends on the state of the chlorophyll metabolism. A generic model was build that describes thepostharvestcolour behaviour in time and temperature for individual cucumbers, irrespective of growing conditions and cultivar. The model enables prediction on the batch keeping quality, on the basis of initial colour measurements only. Strawberry. Postharvestlife of strawberries is largely limited by Botrytiscinereainfection. A colour modelwasbuilt that describes the simultaneous development of the red colour and the anti-fungal function of individual strawberries over time. Batch keeping quality predictions could be derived on the basis of initial colour measurements or from the time between harvest dates.Batch model. The batch model describes the influence of one source of biological variation, here assumed to be variation in light conditions during thepreharvestperiod, on the distribution of precursor concentrations by combining (product specific) kinetic models and a generic stochastic part. The batch model described batch behaviour in terms of current maturity, biological variation and maximal maturity towards keeping quality of cucumbers and strawberries. Applications of biological methodology may be numerous: proposing protocols for keeping quality predictions, characterisation of cultivar specific influences on keeping quality or, in general, starting of a new field that is concerned with the 'hidden' information that is present in all biological batches.

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Bibliographic Details
Main Author: Schouten, R.E.
Other Authors: van Kooten, Olaf
Format: Doctoral thesis biblioteca
Language:English
Subjects:colour, cucumbers, cucumis sativus, fragaria ananassa, image processing, keeping quality, kinetics, models, postharvest physiology, postharvest systems, stochastic models, strawberries, aardbeien, beeldverwerking, bewaarfysiologie, houdbaarheid (kwaliteit), kinetica, kleur, komkommers, modellen, stochastische modellen, systemen na de oogst,
Online Access:https://research.wur.nl/en/publications/physiology-of-biological-variation
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Summary:In agricultural products, variation exists in quality attributes between batches. Examples of this biological variation are well known and the general response is trying to suppress it as much as possible; to create uniformity using pre- andpostharvestmethods. This thesis shows a methodology that takes advantage of the biological variation, instead of treating it as a nuisance. This biological variation methodology was applied to understand the expected keeping quality of batches.The methodology currently consists of three steps. Firstly, repeated non-destructive measurements of quality properties of individuals need to be applied to find out how the quality attribute changes over time without having to worry about biological variation. Secondly, kinetic models need to be constructed that show the quality attribute changing over time as a combination of simultaneously occurring processes that, ideally, have a strong physiological background. The last step consists of translating the kinetic model that describes the behaviour of the quality attribute of individuals to batches usingstochastics. This methodology is applied for cucumbers and strawberries.Cucumber. The keeping quality for a cucumber, defined as the time the colour remains acceptable to the consumer, depends on the state of the chlorophyll metabolism. A generic model was build that describes thepostharvestcolour behaviour in time and temperature for individual cucumbers, irrespective of growing conditions and cultivar. The model enables prediction on the batch keeping quality, on the basis of initial colour measurements only. Strawberry. Postharvestlife of strawberries is largely limited by Botrytiscinereainfection. A colour modelwasbuilt that describes the simultaneous development of the red colour and the anti-fungal function of individual strawberries over time. Batch keeping quality predictions could be derived on the basis of initial colour measurements or from the time between harvest dates.Batch model. The batch model describes the influence of one source of biological variation, here assumed to be variation in light conditions during thepreharvestperiod, on the distribution of precursor concentrations by combining (product specific) kinetic models and a generic stochastic part. The batch model described batch behaviour in terms of current maturity, biological variation and maximal maturity towards keeping quality of cucumbers and strawberries. Applications of biological methodology may be numerous: proposing protocols for keeping quality predictions, characterisation of cultivar specific influences on keeping quality or, in general, starting of a new field that is concerned with the 'hidden' information that is present in all biological batches.