Due to its highly nutritive compounds, the demand for quinoa, a small grain originating from the Andean region of South America, increased rapidly over the last years. However, the main producing countries Bolivia and Peru cannot cover the growing demand. Therefore, the interest of European farmers in cultivating quinoa as a profitable source of income rose very fast. Thanks to a broad genetic diversity an adaption to various climatic conditions is possible. The objective of this study was to evaluate the stability of agronomic performance in two consecutive growing periods (2015 and 2016) of four European quinoa cultivars (Puno, Titicaca, Jessie, Zeno), originating from different genepools to identify a suitable cultivar to grow in southwestern Germany. Measurements included grain yield, thousand kernel weight (TKW), saponin content, protein content, crude fat content, amino acid profile and fatty acid profile. This study demonstrated the possibility of an economic production of quinoa under the environmental conditions in southwestern Germany, combining competitive yields (1.73–2.43 Mg ha⁻¹) with a high grain quality regarding protein content (11.9–16.1%), essential amino acid content (20.35–30.02 g 100 g⁻¹ crude protein), fat content (5.5–7.5%) and fatty acid profile (consists of 60% linoleic acid). Depending on cultivar, the investigated yield (TKW and protein content)-and quality ((semi-)essential amino acids)-traits varied more or less sensitive, which was attributed to lower precipitation and higher temperatures in 2015. Furthermore, best yield- and quality-characteristics were not combined in one cultivar, wherefore the selection of a specific quinoa cultivar has to be aligned with the production aim.

Cannabis is one of the oldest cultivated plants, but plant breeding and cultivation are restricted by country specific regulations. Plant growth, morphology and metabolism can be manipulated by changing light quality and intensity. Three morphologically different strains were grown under three different light spectra with three real light repetitions. Light dispersion was included into the statistical evaluation. The light spectra considered had an influence on the morphology of the plant, especially the height. Here, the shade avoidance induced by the lower R:FR ratio under the ceramic metal halide lamp (CHD) was of particular interest. The sugar leaves seemed to be of elementary importance in the last growth phase for yield composition. Furthermore, the last four weeks of flowering were crucial to influence the yield composition of Cannabis sativa L. through light spectra. The dry flower yield was significantly higher under both LED treatments compared to the conventional CHD light source. Our results indicate that the plant morphology can be artificially manipulated by the choice of light treatment to create shorter plants with more lateral branches which seem to be beneficial for yield development. Furthermore, the choice of cultivar has to be taken into account when interpreting results of light studies, as Cannabis sativa L. subspecies and thus bred strains highly differ in their phenotypic characteristics.

In recent years, the intra-annual yield variability of traditional food crops grown in Europe increased due to extreme weather events driven by climate change. The Andean crop quinoa (Chenopodium quinoa Willd.), being well adapted to drought, salinity, and frost, is considered to be a promising new crop for Europe to cope with unfavorable environmental conditions. However, cultivation guidelines and cropping experiences are missing on a long-term scale. The adaptation of a mechanistic crop growth model will support the long-term evaluation of quinoa if grown under the diverse environmental conditions of Europe. The objective of this study was to adapt the process-based cropping system model (CSM) CROPGRO, which is included in the Decision Support System for Agrotechnology Transfer (DSSAT). Therefore, species and genetic coefficients were calibrated using literature values and growth analysis data, including crop life cycle, leaf area index (LAI), specific leaf area (SLA), dry matter partitioning and nitrogen concentrations in different plant tissues, aboveground biomass, and yield components, of a sowing date experiment (covering two cultivars and four sowing dates) conducted in southwestern Germany in 2016. Model evaluation was performed on the crop life cycle, final aboveground biomass, and final grain yield for different sowing dates using an independent data set collected at the same site in 2017. The resulting base temperatures regarding photosynthetic, vegetative, and reproductive processes ranged between 1 and 10 °C, while the corresponding optimum temperatures were between 15 and 36 °C. On average, the crop life cycle was predicted with a root mean square error (RMSE) of 4.7 and 3.0 days in 2016 and 2017, respectively. In 2016, the mean predicted aboveground biomass during the growth cycle showed a d-index of 0.98 (RMSE = 858 kg ha⁻¹). Furthermore, the LAI, SLA, and leaf nitrogen concentrations were simulated with a high accuracy, showing a mean RMSE of 0.29 (d-index = 0.94), 25 cm² g⁻¹ (d-index = 0.88), and 0.51% (d-index = 0.95). Evaluations on the grain yield and aboveground biomass across four sowing dates in 2017 suggested a good robustness of the new quinoa model. The mean predicted aboveground biomass and grain yield at harvest maturity were 6479 kg ha⁻¹ (RMSE = 898.9 kg ha⁻¹) and 3843 kg ha⁻¹ (RMSE = 450.3 kg ha⁻¹), respectively. Thus, the CSM-CROPGRO model can be used to evaluate the long-term suitability, as well as different management strategies of quinoa under European conditions. However, further development on the simulation of small seed sizes and under water or nitrogen-limited environments are needed.

Empirical data on the effect of plant density (PD) and length of the vegetative phase (DVP) on plant growth, yield, and cannabinoid concentration of medicinal cannabis (Cannabis sativa L.) are still scarce, leading to a lack of specific cultivation recommendations. We conducted two greenhouse experiments to investigate the effect of PD in the range of 12–36 plants m^-2 (D-trial) and DVP in the range of 1–4 weeks (V-trial) on plant morphology, biomass growth of individual plant organs, and CBD concentration of individual inflorescence fractions. Empirical models for the relationships between the investigated plant traits and PD/DVP were created using linear regression analysis preceded by a lack-of-fit test. An increase in PD led to a linear decrease in inflorescence yield per plant (p = 0.02), whereas a positive linear relationship was found for inflorescence yield (p = 0.0001) and CBD yield (p = 0.0002) per m². Total area yields in the D-trial ranged from 119 to 247 g m^-2 from lowest to highest PD. DVP showed a positive linear relationship with inflorescence yield on an individual plant (p = 0.0001) and area basis (p < 0.0001) along with most other relevant agronomic traits such as CBD production, plant size and lateral shoot length. Total area yields in the V-trial ranged from 295 to 571 g m^-2 from lowest to highest DVP. The yield increase could be linked to the increased inflorescence number per plant rather than inflorescence size. In contrast to expectations, neither PD nor DVP had significant effects on the cannabinoid concentration gradient from upper to lower canopy layers. CBD concentrations in inflorescences from lower canopy layers were reduced by 23% in the V-trial and 46% in the D-trial. However, with increasing PD, the proportion of higher-concentrated inflorescence fractions from upper canopy layers increased from 46% to 68%, while an extension of DVP shifted this proportion only marginally from 45% to 50%. In the context of standardized production, we therefore advocate high-density production systems that increase the proportion of desired inflorescence fractions from upper canopy layers.