Summary Functional root traits are becoming a key measure in plant ecology, and root length measurements are needed for the calculation of root traits. Several methods are used to estimate the total root length (TRL) of washed root samples [e.g. modified line intersect (LI) method, WinRHIZOTM and IJ_Rhizo], but no standardized comparison of methods exists. We used a set of digital images of unstained root samples to compare measurements given by the LI method and automated methods provided by WinRHIZOTM and IJ_Rhizo. Linear regression models were used to detect bias. Both linear regression models and the Bland‐Altman`s method of differences were used to evaluate the accuracy of eight methods (1 manual, 2 semi‐automated and 5 automated) in comparison with a reference method that avoided root detection errors. Length measurements were highly correlated, but did not exactly agree with each other in 11 of 12 method comparisons. All tested methods tended to underestimate the TRL of unstained root samples. The accuracy of WinRHIZOTM was influenced by the thresholding method and the root length density (RLD) in the pictures. For the other methods, no linear relationship was found between accuracy and RLD. With WinRHIZOTM (global thresholding + pixel reclassification; RLD = 1 cm cm−2), the Regent's method and the Tennant's method underestimated the TRL by 7·0 ± 6·2% and 4·7 ± 7·9%, respectively. The LI method gave satisfactory results on average (underestimation: 4·2 ± 6·0%), but our results suggest that it can lead to inaccurate estimations for single images. In IJ_Rhizo, the Kimura method was the best and underestimated the TRL by 5·4 ± 6·1%. Our results showed that care must be taken when comparing measurements acquired with different methods because they can lead to different results. When acquiring root images, we advise to (i) increase the contrast between fine roots and background by staining the roots, and (ii) avoid overlapping roots by not exceeding a RLD of 1 cm cm−2. Under these conditions, good length estimates can be obtained with WinRHIZOTM (global thresholding + pixel reclassification). The Kimura method in IJ_Rhizo can be an alternative to WinRHIZOTM.

No abstract

No abstract

Industrial Symbiosis (IS) is a collaborative cross-sectoral approach to connect the resource supply and demand of various industries in order to optimize the resource use through exchange of materials, energy, water and human resources across different companies, while generating ecological, technical, social and economic benefits. One of the main goals of IS is the set-up of advanced circular/cascading systems, in which the energy and material flows are prolonged for multiple utilization within industrial systems in order to increase resource productivity and efficiency, while reducing the environmental load. Many Information Communication Technology (ICT) tools have been developed to facilitate IS, but they predominantly focus on the as-is analysis of the IS system, and do not consider the development of a common desired target vision or corresponding possible future scenarios as well as conceivable transformation paths from the actual to the defined (sustainability) target state. This gap shall be addressed in this paper, presenting the software requirements engineering results for a holistic IT-supported IS tool covering system analysis, transformation simulation and goal-setting. This new approach goes beyond system analysis and includes the use of expert systems, system dynamics and Artificial Intelligence (AI) techniques, which turn the IT-supported IS tool to be developed into a comprehensive and holistic instrument with which future scenarios and transformation paths can be simulated.