The general objective in GreenCHAINge Work package 1, is to develop a more generic quality control system for the AH supply chain that will improve the assurances for consistent quality. One of the subprojects is the study of mangoes, being one of the exotic products delivered to Albert Heijn and serving as a model for other exotic products with the AH fresh food logistics. Mangoes produced in Brazil are transported in reefer containers to the Netherlands.

Food quality is influenced by abiotic conditions such as: temperature, relative humidity, gasses (oxygen, carbon dioxide, etc.). These were monitored in experiments with strawberry and avocado by Smart-r-tag sensors manufactured by SensaData and provided to WUR. The data from the sensors were used as input for prediction of fruit quality and shelf life with a quality loss model. The objective of this research is to test if SensaDatas sensor tags are able to capture abiotic conditions as input for quality prediction for strawberry and avocado. The study did not include developing new quality models based on the acquired data. Models described in literature and developed by WUR are used for quality prediction. The sensors used in the study are the Smart-r-tag Ver1, capturing temperature and relative humidity information and the Smart-r-tag Ver2, recording temperature, relative humidity, oxygen - and carbon dioxide concentration. In two experiments, one with strawberry and one with avocado, the quality of the produce was evaluated and the abiotic storage conditions were monitored using the Smart-r-tags. During storage the strawberries showed different levels of decay depending on the storage temperature, especially the storage condition at 20 °C affected the fruit severely. Avocados stored at different temperatures showed different levels of firmness loss. During the periods in which temperature was high (22 °C and 18 °C) the decrease in firmness was the highest. The Smart-r-tags are able to measure and log the abiotic conditions (temperature, oxygen and carbon dioxide) in which the produce was stored. However, for relative humidity there are also some nonrealistic readings, readings above 100%. Furthermore concerning the monitoring of oxygen and carbon dioxide contents (inside modified atmosphere packaging), the carbon dioxide measurements are inaccurate when the actual carbon dioxide contents are higher than 10% and/or when relative humidity in the packaging headspace is saturated. For quality modelling purpose, the parameter temperature was used as input variable. This data was as input useful for quality prediction. The quality prediction did not exactly match the observed quality, as the quality models were not optimised for these specific produces and abiotic conditions. The models can be adapted or other models could be used to fit the data better. The following recommendations can be given based on the work that was performed: 1. Validate relative humidity sensors when measuring at high humidity. In supply chains with perishable product like fruit and vegetables humidity is commonly above 90% RH and often higher than 95 % RH. It is important that the sensors operate well in this RH range for them to be useful in practice. Certainly a humidity cannot be higher than 100% RH. 2. Validate if the carbon dioxide sensor is measuring the correct concentration when measuring under high humidity. We found a discrepancy between our reference and the output of the Smart-r-tag ver2 sensor. 3. Select and use a quality prediction model that fits the need and support the decision making of the intended customer for the tags. There are many models described in literature, but they serve a certain purpose. Generic models are relatively easy to use, but might be too general for the case on hand. This has to be evaluated in a follow-up project, with practical pilots. In a possible follow-up WUR is willing to assist SensaData with selecting and setting up the best quality prediction models in combination with the needs of the customer.

Table grapes produced in South Africa and South America are transported in Reefer containers to the Netherlands. This takes two to three weeks’ time, depending on the route and the transport company.Usually SO2-pads are used to suppress development of fungal infection during long term transport. The use of SO2-pads is increasingly under pressure. In literature several alternatives have been presented.Previous research (ExperiCo, 2015) showed elevated levels of CO2 to give promising results. However, finding the right concentration is a trade-off between Botrytis suppression and the evolution of an off taste.The goal of this study:To investigate whether elevated levels of CO2 can suppress Botrytis infection in Allison seedless table grapes from Spain during storage without causing off flavour. Allison seedless table grapes from Spain (week 45 in 2016), suffered a lot from fungal infection. This fungal infection was already visible in the starting material.High CO2 applied in a flow through system (12% CO2 and 18% O2) could supress fungal infection during storage to certain extent.The results of this experiment are promising. However, since infection levels were very high already at the start of the experiment, it has to be repeated before final conclusions can be drawn concerning the effectivity of the treatment and the effect on taste.

In the GreenCHAINge project Wageningen UR Food & Biobased Research (FBR) cooperates with the industry in order to get a better performance in quality for fresh fruits and vegetables. For table-grapes, one of the problems limiting shelf life is the formation of brown grapes, so-called ‘chocolate berries’, in a punnet. The objective is to understand what is causing the formation of this browning.With this in mind, various classes of browning were identified and compared to the chocolate berry phenotype. Based on these findings, the hypothesis that mechanical damage causes the chocolate berry phenotype was tested using two types of mechanical stress: constant pressure and impact stress. While constant pressure showed no consequent increase in browning, the increased browning after impact stress indicates that impact stress may contribute to chocolate berry formation.

The goal of this study is:1. to investigate the effects of optimal and sub-optimal transport temperature, i.e. -0.5 °C vs. 3.5 °C during two and three weeks, on the quality of Thompson seedless grapes from Greece.2. to investigate the effect of a decreased transport temperature, i.e. -1.5 °C, during two and three weeks on the quality of Thompson seedless grapes from Greece.Table grapes produced in South Africa and South America are transported in Reefer containers to the Netherlands. This will take two to three weeks’ time, depending on the route and the transport company.The temperature setpoint of these containers is usually -0.5 to 0.5 °C. At the start of the season in January, when Brix values are under 14°, the transport temperature will be set to be around 1.5 °C, to prevent low temperature decay.However, the temperature will only reach this setpoint close to the cooling unit, at de rear end of the container. Moving towards the door of the container, at the front end, temperatures will be higher and hot spots can occur when loading of the container is sub optimal. Temperature deviations of 2 to 3 °C from the setpoint have been reported, which will also affect product temperature.A better temperature distribution throughout de load, that approaches the set point temperature, could lead to a more homogeneous product temperature. To see whether this results in a better and more homogeneous product quality during the retail phase, grapes were stored at either -0.5 or 3.5 °C for both two and three weeks. Furthermore, since Thompson seedless table grapes have relatively high Brix values, the question arose whether grapes with such high levels of soluble sugars can be transported at a lower temperature, i.e. -1.5 °C, without showing quality issues.Our results show that on average, the quality of Thompson seedless table grapes from Greece is better when stored for two and three weeks at -1.5 and -0.5 °C than stored for those periods at 3.5 °C. However, within each temperature treatment the quality differences between replicates were large, involving punnets of moderate to bad quality in each treatment.On average, the quality of the grapes is better when stored for two weeks than for three weeks.The biological variation of the starting material appeared to be high, complicating outcomes of this postharvest study. It is currently unclear what exactly causes this variation in this case.The Brix values in week 38 to 42 were on average 19°. At start of the experiment, the question was whether grapes with relatively high levels of soluble sugars could be transported at a lower temperature, i.e. -1.5 °C, without showing quality issues. These grapes, with an average Brix value of 19° performed the same at -0.5°C as at -1.5°C, without showing more disorders at -1.5°C.