A selection of raw materials
Resource management The quest towards responsibly sourced growing media AHDB project code: CP138 Transition to responsibly sourced growing media use within UK horticulture Term: January 2015 to December 2020 Project leader: Barry Mulholland, ADAS In response to both customer pressure and government policy developments over the last 10 years, there has been a slow move away from peat as the only main constituent of growing media. Many ornamentals businesses have adopted peat-reduced media, but there is now a need to take the next step and move to peat-free media. Four key raw materials have emerged with potential for use: coir, bark, wood fibre and green compost. However, the creation and testing of new blends is currently a relatively slow process, relying on various plant species or crop types as indicators of potential performance. Furthermore, industry needs more confidence and understanding of their use before large-scale adoption and use in commercial production can commence to any great extent. 28 Resource management
The project This project set out to create a model which can objectively and quantifiably predict the performance of a raw material or blend based on a number of physical characteristics which can be measured. The model doesn’t negate the need for trials, but the number of screening trials can be significantly reduced as a result. A series of trials across all of horticulture were established to help populate the model, confirm predictions, provide confidence in the use of new media blends and ascertain the cultural adaptions required for their successful adoption.
Results Predicting blend performance The understanding and selection of growing media based on physical properties is important, because of the vast number of commercially available material types that constitute coir, bark, wood fibre and green compost. Based on three key physical parameters – air-filled porosity, available water and bulk density – the model, developed as part of the project, can identify blends which possess key, high-performing attributes, independently of plant response. Such attributes can now be determined for different raw materials and blends in a consistent way for the end user. A user-friendly interface has been generated for the model, which will be developed into a commercial testing service offered to industry.
