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The circular economy in agriculture aims to reduce waste while also making best use of residues by using economically viable processes and procedures to increase their value. In this study a two-level cascade cultivation system was set up under greenhouse conditions. The research was focused on the identification of crop species as secondary crops and the development/iterative optimization of cultivation practices. For this purpose, different crop-combinations with a primary and different secondary crops were investigated using different system-layouts. Measurements were carried out during two cultivation periods. During the 1st Period a combination of cucumber (Cucumis sativus) as primary crop, with rosemary (Rosmarinus officinalis), basil (Ocimum basilicum), and peppermint (Mentha piperita) as secondary crops, was evaluated. In the 2nd Period the drainage of tomato (Solanum lycopersicum) plants was re-used to irrigate spearmint (Mentha spicata), dill (Anethum graveolens), celery (Apium graveolens) and parsley (Petroselinum crispum) plants. In both periods, different fertigation management strategies based on the drainage solution of the primary crop were employed. The use of the cascade hydroponic system improved both crop water and nutrient use efficiency. Notably, the NO3 disposal was about 40% less as compared to a monoculture. Average fresh water consumption of secondary crop plants irrigated with diluted drainage solution was reduced by 30% in comparison to plants irrigated with fresh water. [ABSTRACT FROM AUTHOR]

Background Light curtain arrays (LC), a recently introduced phenotyping method, yield a binary data matrix from which a shoot silhouette is reconstructed. We addressed the accuracy and applicability of LC in assessing leaf area and maximum height (base to the highest leaf tip) in a phenotyping platform. LC were integrated to an automated routine for positioning, allowing in situ measurements. Two dicotyledonous (rapeseed, tomato) and two monocotyledonous (maize, barley) species with contrasting shoot architecture were investigated. To evaluate if averaging multiple view angles helps in resolving self-overlaps, we acquired a data set by rotating plants every 10° for 170°. To test how rapid these measurements can be without loss of information, we evaluated nine scanning speeds. Leaf area of overlapping plants was also estimated to assess the possibility to scale this method for plant stands. Results The relation between measured and calculated maximum height was linear and nearly the same for all species. Linear relations were also found between plant leaf area and calculated pixel area. However, the regression slope was different between monocotyledonous and dicotyledonous species. Increasing the scanning speed stepwise from 0.9 to 23.4 m s-1 did not affect the estimation of maximum height. Instead, the calculated pixel area was inversely proportional to scanning speed. The estimation of plant leaf area by means of calculated pixel area became more accurate by averaging consecutive silhouettes and/or increasing the angle between them. Simulations showed that decreasing plant distance gradually from 20 to 0 cm, led to underestimation of plant leaf area owing to overlaps. This underestimation was more important for large plants of dicotyledonous species and for small plants of monocotyledonous ones. Conclusions LC offer an accurate estimation of plant leaf area and maximum height, while the number of consecutive silhouettes that needs to be averaged is species-dependent. A constant scanning speed is important for leaf area estimations by using LC. Simulations of the effect of varying plant spacing gave promising results for method application in sets of partly overlapping plants, which applies also to field conditions during and after canopy closure for crops sown in rows. [ABSTRACT FROM AUTHOR]