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Translucency is one of the major problems in fresh-cut fruit. This phenomenon affects the use of tomato fruit by the fresh-cut industries. Techniques for measuring translucency are not readily available. As a consequence, the processes that are important in the development of translucency are little understood, let alone described in detail. The colour of produce depends only on the absorption of light by colouring compounds. Translucency does not change the amount of colouring agents in the product, but it does change its appearance by changing the scattering properties. As a consequence the appearance, which is the result of light absorption and scattering combined, is affected by both translucency and colour development. Consumers do buy or reject products based on total appearance. In the short life time of cut fruits, the development of colouring compounds apart from possible oxidation effects will not be very large. Understanding the development of translucency is therefore of major importance for the fresh-cut industry. The development of translucency was visually assessed in tomato slices, obtained from tomatoes at three stages of maturity (mature green, breaker stage and full red) and stored at 5°C. In a second experiment, tomato slices were stored at three temperatures (5, 9 and 13°C) to assess the effects of temperature. In both experiments, non-cut tomatoes were also assessed. The data of both experiments were analysed using a very simple exponential model based on a massive approximation of the mechanism involved. The more precursor is present, the higher the obtainable translucency will be. A model was developed based on this simplified mechanism, and used to analyse all data. The stage of development (maturity) was found to have a major effect on translucency development regulated by the amount of precursor. The rate constant, however, was the same. The temperature only had a minor effect on the rate constant with the same amount of precursor. Explained parts (R2adj) obtained for mean data were well over 97%, for the individual data the explained part was somewhat less.

Greenhouse horticulture is an intensive production system with a relatively low resource input per unit of output compared to open field agriculture. It is an essential means of production for large urban conglomerates that are abounding in the present century, while water and chemical resources are dwindling. It is however essential to link these production systems to a consortium of traders, logistic providers and retailers in order to obtain a competitive edge by delivering according to the con-sumers expectations. It will be shown that competition on price, with a concomitant decrease in quality, results in a diminishing market and a viscous circle of declining price and quality. While a strong emphasis on quality will enhance the market and prices will rise as long as a clear and discernable quality of the final product, as it reaches the consumer, is maintained. By doing longitudinal studies of quality development in batches of products it becomes possible to combine deterministic with stochastic models capable of predicting quality evolution throughout the entire production and supply chain. Several examples will be given of this technique and it will be shown that vertical transparency in the supply chain can augment the profit for all participants, while keeping the entire chain competitive in a fast evolving market. By combining predictive quality information with the proper logistic technol-ogy, what we call ‘Quality Controlled Logistics’, it becomes possible to optimize the quality of the separate batches by positioning them in the shelves for the consumers at the moment of optimal maturity. What is necessary are new non-destructive measuring techniques that can determine batch quality characteristics at the period of harvest, or even before that, combined with physiology based models to predict quality evolution from harvest time on. Several models have been developed up till now and examples of their application will be given

Broccoli combines high levels of vitamins, fibres and glucosinolates (GLS) with a low calorie count. GLS are precursors for the characteristic broccoli flavour and have anti-carcinogenic properties. This study describes the effect of controlled atmo¬sphere (CA) and temperature on GLS concentrations in broccoli. Data on GLS behaviour and gas exchange were gathered for broccoli heads that were stored at three temperatures and subjected to four levels of O2 and three levels of CO2. The GLS behaviour of three GLS (raphanin, GB and neo-GB) was examined that showed exponential decrease over time, possibly representing the GLS interaction with myrosinase. The most striking feature is the large variation in GLS concentrations at harvest. The propagation of the variation in GLS over time is clearly affected by CA and temperature. Variation in GLS concentrations over time at the same gas condi¬tions and temperature was interpreted with the moment of harvest as main cause of random variation. Assuming that this random variation is normally distributed, the exponential function over time can be transformed into a batch model that describes the changes of variation over time (Schouten et al., 2004, Hertog et al. 2004). The effect of the CA was modelled using the standard gas exchange model. This calibrated gas exchange model was then linked via the reaction rate constant to the batch model to create an integrated batch model. This integrated batch model was subsequently calibrated to describe the variation of the GLS as function of O2, CO2, time, tempera¬ture and the batch parameters (average biological age and standard deviation). The percentage variance accounted for was on average 85%. Considering that this modelling effort is based on destructive GLS measurements, this is a rather high value. All GLS species were retained by suitable (low O2, high CO2) gas conditions, but remarkably, raphanin was found to be less affected by temperature, indicating that CA storage and low temperature would both retain this GLS species to the same extent, while low temperature storage is a better option for e.g. neo-GB

An absolute-sink-strength regulated crop growth model was developed to address the problem of sweet pepper synchronised yield oscillations (flushes). Yield oscillations in sweet pepper production are caused by crop physiology (fruit abortion at times of heavy fruit load per plant) and result in periodic oversupply at the market level, as synchronisation occurs within, but also between glasshouses, due to weather conditions. Smart growers may not only aim to maximise production yields, but also to desynchronise their temporal yield pattern from that of the market, in order to target higher prices during low supply periods. The parameters that growers can change are those concerning pruning, harvesting at a green marketable stage, and climate control, whereas breeders may adjust physiological constants. The model consists of three ordinary differential equations and two partial differential equations, with fruit dry weight as second independent variable. Both the number of fruits per square meter and the average ripeness of fruits with a particular weight are discretised into 40 weight classes. Sinks, from vegetative, fruit growth and maintenance draw on a common assimilate pool, eliminating the need for a relative-sink strength `top-down¿ partitioning approach. The vegetative biomass is considered as two parts, for growing and non-growing biomass respectively. The model arrives at plausible output values for known biological variables and simulates assimilate-dependent abortion and thus fruit set explicitly, although not yet fully validated. A bifurcation analysis is conducted to identify the regions in parameter space where either yield oscillations or a stable growth pattern occurs.

Data generated in postharvest research is characterised by its large sources of biological variance. This variance generally obscures the behaviour of interest, complicating both the statistical and conceptual interpretation of the data. To be able to manage the postharvest chain, clear inside is required in the propagation of biological variance during postharvest. Recently, biological variance has gained interest within the postharvest community. To analyse experimental data taking into account biological variance several (statistical) modelling techniques have been applied by different authors. These vary from models that can be solved analytically to analyse the effect of experimental design parameters (e.g., mixed effects models), via hybrid techniques which combine analytical and numerical techniques, to pure numerical models for dynamic simulations based on differential equations (like the variance propagation algorithm). Each of these techniques has its own possibilities and limitations in terms of the type of variance that can be accounted for, their technical complexity, and their applicability to practical situations. The different techniques are suitable to different degrees to answer specific questions in specific settings. Using tomato colour as an example, the different techniques are applied and compared to highlight their strong and weak points in interpreting biological variance. The added value of these techniques are discussed within the framework of managing biological variance in the postharvest chain.

A generic program for mathematical model-supported innovation profiling in fresh food supply chains is presented. Building on top of a crop growth model, strategies to address the problem of sweet pepper yield oscillations (flushes) are analysed quantitatively from both isolated or combined perspectives of the chain players: plant breeders, horticultural growers and traders. Yield oscillations in sweet pepper production, caused by crop physiology, and presumably synchronized by weather conditions, result in periodic oversupply at the market level. Growers try to desynchronise their own temporal yield pattern from that of the market, in order to target higher prices during low supply periods. A complication is that the quality of fruit products, in terms of size and colour/ripeness, may be affected when altering growing practices such as pruning, harvest timing, and climate control. Upstream, breeders can change physiological constants. Downstream, post harvest storage may produce value by better price targeting. The IACCP approach is presented, and is based on systematic decomposition of income, profits, cost and revenues with help of a simulation model. Especially the decomposition of revenues into isolated effects of production yield, price targeting, and various quality characteristics such as fruit size and fruit ripeness/colour shows how synergies between innovation strategies of collaborating (or competing!) players within a supply chain are created (or destroyed). Although the model is not yet fully validated in detail, such simulations may well support discussions on collaborative innovation strategies and on prioritisation of the research agenda.

To investigate the changes in lycopene concentration of fresh-cut tomato during storage, tomato fruits at different stages of maturity were cut into 7 mm slices and stored at temperatures varying from 2°C to 16°C. To assess the effect of cutting, intact fruit were stored in an additional experiment at 5°C. Cutting did not change the accumulation of lycopene in fruit stored at 5°C, compared to intact fruit. The lycopene concentration of the tomato slices stored at different temperatures showed net increases of lycopene concentration for all maturity stages tested at temperatures of 8°C and higher. At lower temperatures no increases or small decreases were observed. The lycopene concentration was considered to be the net result of production and degradation of lycopene. Kinetic models for different pathways were tested. The reaction rate constant for lycopene formation at 8°C was estimated at 2.16 ± 0.24 . 10 -2 μg/mg.day. The estimated activation energy for the lycopene formation (92.4 ± 7.3 kJ/mol) indicates that this process is highly dependent on temperature. The degradation rate constant was estimated at 2.99 ± 0.61 . 10 -2 (l/day) and, over the temperature range studied, the degradation rate was not dependent on temperature.

With the present developments in CA technology it becomes possible to fine tune the storage conditions to the specific needs of the product. This generates the need to know the exact quality conditions of the product before storage starts. By measuring the initial quality we can determine these conditions optimally. At present the most likely candidates to assess the initial quality with fast and non-destructive measurements are colour, chlorophyll fluorescence, and maybe NIR spectroscopy. Two examples are presented where initial colour measurements on all products in a batch can be shown to be indicative for the keeping quality of that batch. The first example focuses on how initial colour measurements using a 3CCD video camera can be utilised to predict the keeping quality of a batch of cucumbers where colour itself is regarded as the most important quality attribute. The second example focuses on how colour measurements can be used to predict the keeping quality of a batch of strawberries where the ability to suppress a Botrytis cinerea infection is the most important quality attribute. Furthermore, attention is given to the use of modulated chlorophyll fluorescence imaging as a possible initial quality indicator for rose leafy stem cuttings. The level of inhomogeneity in the quantum yield of photochmistry od PSII of leaves of rose cuttings may be an indictor of the capability of the cutting to recover from severance, and to form roots and generate regrowth

Flower size and number of flowers per plant are important external quality aspects in cut chrysanthemum. The present work is conducted in a glasshouse and aims at investigating how these quality aspects can be predicted. To evaluate individual flower size, different levels of supplementary lighting (control and assimilation light), plant density (32, 48 and 64 plants m-2) and lateral flower bud removal (leaving 1 flower, 4 flowers and control) were applied. To analyse the effect of assimilate supply on number of flowers per plant, three light intensities (no shade control, 65␕ight, and 45␕ight) where combined with three plant densities (32, 64, and 80 plants m-2). Individual flower size was negatively influenced by competition for assimilates in the treatments with a fixed number of flowers per plant (1 or 4 flowers). In such treatments, plants grown under no supplementary assimilation light, higher plant density, or with higher number of flowers per plant resulted in significantly lower individual flower dry mass and area. However, when no lateral flower buds were removed (control), higher assimilate supply resulted in more flowers rather than in larger flowers. Number of flowers per plant (including flower buds) showed a positive linear increase with total dry mass per plant. The combination of 32 plants m-2 and no shade resulted in the highest number of flowers per plant (33 flowers) in contrast with 80 plants m-2 and 45␕ight intensity (only 9 flowers).

Post-harvest life of strawberries is largely limited by Botrytis cinerea infection. It is assumed that there are two factors influencing the batch keeping quality: the botrytis pressure and the resistance of the strawberry against infection. The latter factor will be discussed here. A model is presented that describes the development of red colour and anti-fungal function of individual strawberries over time. The model was fitted to colour data from strawberries batches from the same growing conditions stored per batch at 5, 10 or 16 °C after harvest. Batches are considered to be all strawberries from one harvest. Spoilage per batch was recorded during storage. The fitted initial spoilage per batch was found to relate to the fitted amount of precursor of both the colour and the anti-fungal compounds. Batch keeping quality could be predicted from the initial batch colour distributions. An explanation for the predictive ability of the model without having to use a term describing the pH is presented from pigment HPLC measurements.

The prediction of the keeping quality for a cucumber, the time the colour remains acceptable, is until now not possible because of the unknown stage of maturity of the fruit. This is a fundamental problem common to all products that have a decrease of the limiting quality attribute according to the autocatalytic mechanism. For individual cucumbers this problem remains unsolved, but on a batch level an approach to obtain the stage of maturity of a batch is described. The stage of maturity of a batch of cucumbers can be obtained by observing the skewness of the colour distribution. This is demonstrated for four batches differing in growing conditions. The colour distributions obtained from high nutrient density treatments indicate an early stage of maturity because of the typical skewness. The approach to predict the stage of maturity from colour distributions was extended to predict the batch keeping quality, the number of days for which 95% of a batch has an acceptable colour. For four growing conditions the batch keeping quality for cucumbers was calculated by fitting colour data to a model that allows for biological variation between cucumbers. The hypothesis is that characterisation of the colour distribution provides sufficient information to specify the batch keeping quality. This is under further investigation.