The impact of biological variation on postharvest behaviour of Belgian endive: The case of multiple stochastic variables

Data generated in postharvest research is often characterised by its large biological variation. This variation generally obscures the behaviour of interest, complicating both the statistical and conceptual interpretation of the data. This paper outlines a general model approach of how to account for the propagation of biological variation when analysing experimental postharvest data. Previous work on the case of a single stochastic variable was extended to the situation of two stochastic variables. The proposed technique was applied to experimental data on stem growth of Belgian endive. By explicitly using the information on biological variation, the number of model parameters to be estimated (only two) did not change while the fitness of the model to describe the experimental data was improved tremendously as compared to the traditional fitting of a model without stochastic variables.The model could describe the complex behaviour of a batch showing propagation of biological variation in stem length of Belgian endive as a function of time and temperature during postharvest storage. Differences between batches could not be related directly to either grower, harvest or culture type but probably depends on a complex interaction with preharvest factors.     

Managing biological variation in skin background colour along the postharvest chain of ‘Jonagold’ apples

Skin background colour is an important quality aspect in the grading of ‘Jonagold’ apples, with consumers usually preferring fruit with a green background colour. However, apple handlers are usually faced with large fruit-to-fruit variability of background colour within a population of fruit. In this study, a stochastic modelling approach was used to describe how the initial fruit-to-fruit variability in the background colour of ‘Jonagold’ apples present at harvest, propagates throughout the postharvest chain. Two hundred and twenty ‘Jonagold’ apple fruit were harvested and stored at 1 °C or 4 °C, under different controlled atmosphere (CA) conditions for 6 months, followed by 2 weeks exposure to shelf-life conditions, during which the background colour and ethylene production of the individual fruit were measured. A kinetic model was developed to describe the postharvest loss of skin greenness, by assuming that the loss was principally due to chlorophyll breakdown, the rate of which was dependent on the endogenous ethylene concentration. Stochastic model parameters were identified, and by treating these parameters as fruit-specific, the model could account for more than 95% of the variability of the data. By treating the stochastic model parameters as random factors, the Monte Carlo method was used to model and describe the propagation of the fruit-to-fruit variability of the background colour within a population of fruit. The model developed in this study might allow better management of variability in quality along the postharvest chain, by predicting how the initial fruit-to-fruit variability within a batch of apples will propagate throughout the postharvest chain, as a function of storage and shelf-life conditions.     

Towards flexible management of postharvest variation in fruit firmness of three apple cultivars

Stochastic modeling provides a useful tool in managing biological variation in the postharvest chain. In the current study, the fruit-to-fruit variability in the postharvest firmness of apples was modeled. Apples from three cultivars (‘Jonagold’, ‘Braeburn’, and ‘Kanzi’) were harvested at different levels of maturity, and stored at different temperatures and controlled atmosphere (CA) conditions. By using a kinetic model describing firmness breakdown as a function of time, temperature, controlled atmosphere conditions and endogenous ethylene concentration, the main stochastic variables were identified as the initial firmness and the rate constants for firmness breakdown and ethylene production. Treating these variables as random model parameters, the Monte Carlo method was used to simulate the propagation of the fruit-to-fruit variability in flesh firmness within a batch of apples during storage under different CA conditions and subsequent shelf-life exposure. The model was validated using independent data sets from apples picked in a different season. The model developed in this study can be used to predict the probability of having apples of certain firmness after long term storage for different scenarios of temperatures and CA conditions.     

Postharvest performance of the yellow-fleshed ‘Hort16A’ kiwifruit in relation to fruit maturation

Postharvest performance of fruit is dependent on the maturity or physiological state of the fruit at harvest in conjunction with the postharvest management applied. For yellow-fleshed kiwifruit, the flesh colour is a significant quality attribute, and for ‘Hort16A’, flesh colour has been used for timing harvest. Variability in the postharvest performance of ‘Hort16A’ kiwifruit suggests that flesh colour alone is not as strongly indicative of postharvest performance as soluble solids content (SSC) was found to be for ‘Hayward’ kiwifruit 30 years ago. The postharvest performance of ‘Hort16A’ kiwifruit, assessed as the fruit firmness and chilling injury expression during storage, has been associated with a range of fruit characteristics: flesh colour, SSC, firmness, seed colour, fresh weight, dry matter, starch and soluble carbohydrates measured at harvest throughout maturation. The changing responses of the fruit SSC to temperature, and softening to ethylene, have also been determined. The data illustrate the complex nature of ‘Hort16A’ fruit maturation, even when looking only at simple, easy-to-measure fruit attributes. While a yellow flesh colour is a commercial necessity for ‘Hort16A’ kiwifruit, flesh colour is not a robust indicator of postharvest performance and is not tightly linked to SSC or firmness. Changes in the capacity of fruit to respond to temperature or ethylene are not reflected in on-vine changes. Softening in storage is strongly linked to the softening rate occurring on the vine at the time of harvest. Any association between at-harvest characteristics and chilling susceptibility is less clear, and chilling tolerance appears more associated with the completion of growth and carbohydrate accumulation than with increased soluble solids accumulation rates as in ‘Hayward’. Approaches to extend the understanding of the link between maturation, harvest indices and postharvest performance are discussed.     

A new method for modelling biological variation using quantile functions

We describe a general method for modelling biological variability as a function of time using fruit populations as examples. The method can incorporate variations in the biological age or maturity of fruit or other produce, as well as variations in the biological property being measured. Key developments are the use of quantile functions to describe the stochastic elements of the model, the assignment of probabilities to individual measurements based on their rank order within a sample, the use of individual measurements rather than means in the fitting process, and the fact that a single model equation with a single set of parameters describes the distribution of measurements across an entire population as a function of time. Using a representative fruit sample taken at a specific time and generalised model parameters, the technique allows the prediction of future fruit population distributions and the prediction of the date when a defined percentage of the fruit population meet a particular specification.The model development process demonstrates how to account for both biological age variability and measure (hue) variability simultaneously, the latter including components of measurement uncertainty and variability not related to biological age. Using quantile functions as the stochastic elements provides a wide range of distributional options.The method is described in detail using, as examples, a Complementary Log–Log sigmoid to model changes in ‘Hort16A’ kiwifruit hue angle preharvest, and a Logistic sigmoid to model changes in ‘Tradiro’ tomato skin hue data postharvest.The kiwifruit data comprised ten samples of 90 destructive hue angle measurements taken across the growing season from each of eight maturity areas (MAs). Allowing MA-specific parameter sets, the entire data set was modelled with an adjusted rsd of 0.46°. Further exploration of the sensitivity of model parameters showed that the model parameter t_m, which defines the timing of the ‘maturity’ of each MA, needed to be MA-specific.The tomato colour data comprised 120 fruit measured non-destructively on seven occasions postharvest. Initial model fits using a Normal distribution for the biological age component gave an rsd of 1.05°. The rsd was reduced to 0.61° using a four-parameter generalised lambda quantile function to describe the biological age variability and 0.63° when using a truncated Normal, suggesting that the underlying distribution was not Normal.The models are readily fitted using any statistical or computational package that offers non-linear optimisation including Microsoft Excel with Solver. The technique can be used as effectively with destructive as with non-destructive measurement data, in preharvest and postharvest situations, and can provide visualisation as well as computational tools. It can be applied to any populations that vary with time and where the units of the populations exhibit variability. These modelling techniques have formed the basis for decision support tools that have been operating commercially since 2007.     

A methodological approach for the identification and quantification of sources of biological variance in postharvest research

A correct identification and quantification of the different sources of variance in an experimental dataset is of utmost importance, for instance, when comparing treatment groups, or in the case where there is a need for describing the (future) behaviour of a batch of biological products. The total data variance can be split up into two different parts, one describing the biological variance due to the natural heterogeneity of the batch and the other describing the uncertainty due to the imperfect measurement of the attribute considered. The classical approach to include biological variance in postharvest research is to use a two stage approach in which in a first stage a (non-linear) model is built for each product individually, whereafter inferences are based on the parameters obtained from the first stage. In this contribution, we propose a methodological approach to identify and quantify the different sources of biological variance, using the concept of (non-linear) mixed effects models. Such models are a useful tool to handle repeated measures data containing a high biological variance. The concept is demonstrated on a practical dataset of postharvest firmness changes in mangoes. It is shown that aside from the differences in biological age of the mangoes, the decay rate also varies among mangoes. Furthermore, it is shown that the biological variance is the dominating source of variance during the experiment.     

Improved management of mango fruit though orchard and packinghouse treatments to reduce lenticel discoloration and prevent decay

Mango fruit are exposed to complex postharvest handling management, intended to improve postharvest quality retention during export shipment. Susceptibility to lenticel discoloration and to Alternaria side rots and Phomopsis stem-end rot under current handling conditions led us to re-evaluate and modify the chain of postharvest treatments, from the orchard to the packinghouse. The previously developed hot-water brushing (HWB) treatment was found effective in reducing incidence of Alternaria and stem-end rots, but it significantly induced development of red lenticels. Two factors were key to improving fruit quality, by simultaneously reducing lenticel discoloration and decay development: (a) postharvest water and/or NaOH washes in the orchard, and (b) hot-water spray (HWS) applied over rollers without brushes in the packinghouse. The present results indicate that optimal management involves combinations of water washes in the orchard with packinghouse HWS treatment; this significantly reduced the severity of lenticel discoloration by 50–60%, and the incidence and extent of postharvest side rots caused by Alternaria by 60% or more. These results indicate that appropriate handling of fruit can appreciably improve their quality during prolonged storage and shipment.     

Modelling the acceptance period of truss tomato batches

Tomato batches are characterised by large variation in the quality attributes colour and firmness. Acceptability of tomato batches is consequently affected by the colour maturity and firmness maturity. In this paper, a model for the acceptance period (AP) is presented that describes the acceptability of tomato batches as the time that all quality attributes are considered acceptable as a function of the maturity at harvest. This model takes into account that tomatoes can first be unacceptable due to being over-ripe, then be acceptable, and then be unacceptable again, due to being over-ripe. Furthermore, the AP model takes also into account that consumers may not consume all tomatoes in a truss at the same time, some immediately and some in 3–4 days time. This is accomplished by combining the acceptance period for future and immediate consumption and taking the intersection of those two as the overall AP to indicate whether tomato batches are suited for both types of consumption. The AP model combines the effects of biological variation, varying consumer limits and the variation in the time of consumption into a practical method to assess acceptability of tomato batches at harvest.The AP model was based on three experiments. In the first and second experiment several tomato batches, differing in harvest maturity, were harvested and stored at three different temperatures. Colour and firmness was measured non-destructively and repeatedly over time so as to estimate the colour and firmness maturity at harvest for each batch. The third experiment was used to determine the consumer limits for today's consumption and consumption over the weekend. By combining the results from all experiments it was possible to estimate the AP as a function of the maturity at harvest, storage temperature and storage duration.The AP model might be used as a tool for growers to assess the acceptability of tomato batches periodically to analyse and solve quality issues or by optimising the compliance to consumer acceptance by varying the storage temperature and transport time to the retailers. Both applications may help to increase profitability in terms of repeated purchase by consumers.     

Biological variance in the colour of Granny Smith apples: Modelling the effect of senescence and chilling injury

The colour of ‘Granny Smith’ apples, harvested from three orchards at two stages of maturity, was measured individually using the CIE L*a*b* system during storage in regular atmosphere at three temperatures: 1, 4 and 10 °C. A model was developed based on a simplified mechanism to describe the development of the apple colour during storage as affected by senescence (aging) and chilling injury. Monitoring of individual apples made it possible to include and to describe the biological variance of colour in batches of apples and to correct the colour of each apple individually for its own biological shift factor (biological age; random effect). The biological shift factor is related to the initial condition and range of colour change. The rate of the colour development was estimated in common (fixed effects) for all batches using non-linear mixed effects regression analysis. The variance accounted for by the developed model, including effects of temperature, harvest maturity and orchard location, was more than 95% on 3211 observations. The overall reaction rate constant of decolouration, combining the effects of senescence and chilling injury, was found to depend on temperature. The temperature that showed the lowest overall reaction rate of decolouration is 8 °C, which is in contrast with the currently recommended storage temperature for ‘Granny Smith’ apples.     

Greenhouse climate control affects postharvest tomato quality

In this study, important quality properties such as firmness, sugar and acid levels were measured and analysed in tomatoes harvested from three greenhouses during a five month period and stored at 16 °C for over 20 days. Tomatoes were harvested from three identical, neighbouring, greenhouses which were either conventionally ventilated (open greenhouse) or mechanically cooled (semi-closed greenhouses). Sugar and acids levels were hardly affected by greenhouse type. Compared to the open greenhouse, semi-closed greenhouses produced heavier and less mature (firmer) fruit at the commercial harvesting stage based on colour. Fruit maturity differences could be linked to the vertical temperature gradient and to CO₂ levels in the different greenhouses. This indicates that CO₂ levels and temperature affect the synchronisation between colour and firmness maturity at harvest. The acceptance period, i.e., the time period both tomato colour and firmness are considered acceptable by consumers, will likely be positively affected when growers switch from conventionally ventilated to semi-closed production systems. Additional to greenhouse effects also effects of the harvest month were observed. The sugar to acid ratio was highest and glucose to fructose ratio was lowest in July, the month with the highest irradiance, irrespective of greenhouse type. The estimated value for the maximum firmness (F_max) varied from 17.9 N in August to 31.2 N in June. This monthly variation in F_max explains an important part of the variation found in the postharvest behaviour of tomatoes. Interestingly, the monthly variation in F_max showed the same trend as found for the monthly initial sugar levels. It might be hypothesised that the monthly variation in glucose and fructose levels causes variation in that part of firmness that is generated by cell turgor. The monthly variation in F_max, sugar and acid levels could not be linked to climate conditions and remains to be elucidated.     

An improved dynamic model of transformer hotspot temperature based on top oil temperature

The winding hot spot temperature of the oil immersed power transformer is an important parameter. It has a great influence on the transformer insulation aging and a close relationship with the transformer top oil temperature. The changes of non linear thermal resistance, open circuit impedance, and oil viscosity and winding losses with temperature are also taken into account. An improved model added on the transformer top oil temperature to calculate transformer winding hot spot temperature by using the viscosity and loss correction factors is proposed. Model parameters are estimated by Levenberg Marquardt method. In the end, by comparing with the measured data tested under different conditions, the model shows good consistency under underload (90%), rated load (100%) and overload (110%) conditions respectively, and describes the temperature variation more accurately in the dynamic loading profiles.     

西藏林芝地区野生食用菌物流现状分析

以西藏林芝地区野生食用菌为研究对象,通过实地调研当地食用菌采摘户和经营者获取第一手数据,分析了当地食用菌的采摘和销售现状、物流模式及采后处理情况。调研发现,林芝地区的野生食用菌主要通过采摘户自发采摘,一般采取现摘现卖,物流半径短、物流模式单一、采后处理简单,产业处于初级阶段。根据调研结果,就林芝地区食用菌产业提出发展建议。     

Importance of fruit variability in the assessment of apple quality by sensory evaluation

The assessment of produce quality is a major aspect of applied postharvest biology. Horticultural researchers working on organoleptic quality of fruit need objective methods for the evaluation of sensory properties. The development of sensory methodologies specifically for apples highlighted the problem of handling variation due to fruit variability and assessor differences. The aim of this study was to investigate the weight of within-batch variability in sensory evaluation of apples and to propose a methodology that accounts for this variability. Prior to sensory analysis, for three apple cultivars, apples were sorted into homogenous acoustic firmness categories within each cultivar. The discrimination ability of the trained panel was observed not only between cultivars but also within each cultivar for crunchiness, firmness, juiciness and acidity. Following these results, a mixed hierarchical model for the analysis of the sensory data was proposed to measure the contribution of fruit variability to the variability of sensory scores. The results showed the efficiency of the model in quantifying within-batch variability. Fruit sampling and presentation methods as well as data handling procedures are suggested for obtaining reliable sensory results in the assessment of apple quality.     

Where systems biology meets postharvest

According to the dictionary, a system is something like “a group or combination of interrelated, interdependent, or interacting elements forming a collective entity”. In postharvest, fresh harvested food crops can be considered isolated small scale systems. Postharvest research aims to understand the quality of these ‘systems’ as influenced by postharvest conditions. The phenotypic quality of horticultural produce is based on genetic traits that are expressed through a cascade of reactions subject to complex regulatory mechanisms and diverse environmental conditions. Ultimately, to fully understand postharvest phenomena, a systemic approach that links genetic and environmental responses and identifies the underlying biological networks is required. Thanks to the development of high throughput omics techniques such system-wide approaches have become a viable option to support traditional postharvest research. This review provides an overview of systems biology and how it can lead postharvest research into a new era.     

Artificial Neural Networks Models for Flow Stress during High Temperature Plastic Deformation of Al-Li Alloy

Using gained experimental data to develop the models of stable flow stresses at high temperature plastic deformation by statistical methods for alloy materials, precision of the models is poor and at the same time the processes of modeling are complicated with great workload. On the basis of the data obtained on Gleeble-1500 Thermal Simulator,the predicting models for the relation between stable flow stress during high temperature plastic deformation and deformation strain, strain rate and temperature for 1420 Al-Li alloy have been developed with BP Artificial Neural Network method. The results show that the model on basis of BPNN is practical and it reflects the real feature of the deforming process. It states that the difference between the real value and the output of the model is in order of 5 percent.     

机体弹性变形对主轴承润滑特性的影响

为揭示机体弹性变形对曲轴主轴承润滑特性的影响,在考虑整机体和曲轴弹性的条件下,建立发动机曲柄连杆机构多柔体动力学模型,耦合基于质量守恒边界条件的广义雷诺方程和Greenwood/Tripp接触模型,分析机体弹性变形对曲轴主轴承润滑特性的影响。结果表明：与刚性机体相比,计入机体弹性变形后,各主轴承的润滑特性随曲轴转角的变化趋势与将缸体处理为刚性时基本一致;润滑油平均端泄量和总摩擦功耗在一个工作循环内均变化较小;润滑油最小油膜厚度、最大油膜压力和轴承的最大粗糙接触压力在一个工作循环内的某些时刻变化明显。     

Image-based phenotyping: use of colour signature in evaluation of melon fruit colour

Fruit colour, both external and internal, is important because it relates directly to the commercial value of the product. In breeding and in pre- and postharvest studies of fruit colour, an effective method for evaluating colour is needed to replace subjective evaluations by eye. We used a series of data processing and statistical analyses used in content-based image retrieval to evaluate melon flesh colour, and assessed the efficacy of this approach. This method relies on summarizing colour information from images into colour signatures, calculating the earth mover’s distance (EMD) between colour signatures, and multi-dimensional scaling (MDS) based on an EMD matrix. Performing MDS on a set of fruit flesh images revealed important colour features, such as the yellowish-green strength in green-fleshed melons and the relative size of the green and red parts in red-fleshed melons, without the need for an explicit definition of these features. The proportion of variance due to differences among cultivars was higher by MDS than by traditional evaluation, indicating that this new method performed best at detecting colour differences among cultivars. The method provides effective, objective indicators of fruit colour, and shows considerable promise for use in research and breeding programs.     

Theoretical and Experimental Study on Air TemperatureCharacteristics inside a Car during Parking and Starting

This paper puts forward a theoretical analysis model for air temperature characteristic inside a car during parking and starting. The analysis solution shows that the variation of air temperature inside a car with time follows index number law and becomes stable when the time is long enough. The theoretical analysis not only reveals the law of air temperature variation in clear physical meaning, but also coincides well with the experimental results.     

Virtual Construction Model and Simulation Analysis for Equipment Management of Earthmoving Operations

Based on Petri net theory and workflow model, a 9 tuple colored Petri net simulation model of earthmoving operations was presented focusing on the equipment management in the earthmoving construction. The dynamic changes of workflow and information flow in the construction process were illustrated in the model, and the constraint relationship between equipment and construction conditions was taken into account. Based on the information of the number of equipment and cost, the simulation for the construction situation, estimated completion time, cost, and equipment productivity were conducted. The model was operated based on the CPN Tools platform. And sensitivity analysis and model validation on the model were carried out by simulating the data collected in a real case, which demonstrates that the model can improve the accuracy of the simulation results in the earthmoving operation construction process.     

The Numerical Simulation of Casting Process for Making Metal Matrix Composites

In this paper,a numerical simulation of the casting process for making the MMC.using the PEM, is studied.The convection of liquid metal and the release of latent heat of solidification are taken into account.The algorithm and program for axisymmetric casting model are developed to the problem of coupling between flow and heat transfer,as well as phase change.The variational curves of temperature,the position of flow front and the distrsbutions of volume fraction of solid metal in matrix and their variation with time are obtained.The influences of technological paarmeters to casting are discussed.