Serviced supply chains: Monitoring and modelling to improve the quality of Australian fresh produce into Asian markets (AM15002)
What was it all about?
From 2017 to 2021, this investment increased the value and profitability of Australian horticulture exports by improving supply chain handlings practices and performance. The project worked with citrus, mango, summerfruit and table grape exporters to increase the consistency of fresh produce quality arriving into Asian markets.
This project has driven increased knowledge, skills and confidence within several exporters to access modern monitoring and decision aid tools to better manage supply chain risks and deliver more consistent quality produce. Key project activities included:
- Monitoring export handling conditions to identify opportunities for improving practice
- Developing decision aid tools to inform handling strategies for increasing product consistency
- Increasing exporter awareness and adoption of monitoring and decision aid tools and services
The monitoring of > 200 export shipments identified that poor airfreight temperature management and extended seafreight duration of up to five weeks were major supply chain risks to consistently delivering high quality produce. While new wireless remote monitoring technologies were embraced by exporters for their real-time reporting of consignment temperature and location, data interpretation was a time-consuming process for advanced users seeking comparison of multiple shipments and loggers. The development of customisable, intuitive dashboards that streamed data from multiple logger brands improved the efficiency of data analysis and associated decision making.
Parallel export simulation trials were completed to quantify the impacts of different handling scenarios on fruit quality. This helped the exporters to prioritise interventions to reduce instances of temperature breaches that otherwise compromised quality and reduced returns. The co-investing mango exporter shared the monitoring data with their chain partners to encourage improved cool-chain practice. As a result, average mango airfreight consignment temperatures to Asia reduced from 17°C to 13°C from year one to year four and was associated with a 2.4-day increase in shelf life.
Time x temperature storage trials established the suitability of different cultivars to tolerate seafreight or airfreight supply chains and still arrive with sufficient shelf life. Models for predicting the remaining shelf life of four mango and six stone fruit cultivars were developed. The models were based on monitored conditions from harvest to the importer and were validated in commercial supply chains had an accuracy of ± 1-4 days at a 90 per cent prediction interval. The co-investing stone fruit exporter relied on these decision aid tools to guide the selection of cultivars suited to air and seafreight. They are intending to implement delayed or step-wise cooling after packing into their export handling protocol after it was shown to reduce the incidence of internal fruit disorders in susceptible stone fruit cultivars.
Monitoring handling procedures prior to export also revealed variation in practice that reduced the consistency of product quality arriving in-market. The co-investing citrus exporter identified the need to standardise and improve lemon degreening and pre-cooling treatments to successfully reduce the risk of chilling injury developing during seafreight. Models for predicting the risk of rot development on table grape berries were further refined.
The benefits of monitoring have been promoted through case studies and other media and forums, leading to greater awareness and adoption. Through their association with the project team, 33 leading exporters, who account for at least 69 per cent of all mangos and more than 10 per cent of total stone fruit export volume, have adopted wireless reporting monitoring technology as a standard practice in the past two to four years. Additional businesses beyond this project have co-invested in several other supply chain improvement projects where there is a monitoring and predictive tools component.
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