ALBERT

Description: The current demand for safflower florets (Carthamus tinctorius L.) in the food-coloring industry, especially in Europe, is rising. The present production, mainly located in China, is not sufficient. Unlike for the production of seeds, there are currently no recommendations for the cultivation of safflower for floret production in Germany. Therefore, field experiments were conducted at the experimental station Ihinger Hof, Southwestern Germany, in 2017 and 2018. The aim was to evaluate yield and yield parameters, such as number of capitula, floret yield, and carthamidin content for (i) two cultivars grown with (ii) two row spacing (12 and 33 cm) using (iii) two sowing densities (40 and 75 plants m−2), and (iv) five harvest dates. Results showed that lower sowing densities resulted in a significantly larger number of branches and capitula per plant and higher yields of florets and carthamidin. Harvesting two to three weeks after flowering resulted in the significantly highest floret and carthamidin yields. More capitula per plant, higher carthamidin contents, and higher floret and carthamidin yields were obtained with the Chinese cultivar. In general, yields of flowering florets (2.30–468.96 kg ha−1), carthamidin contents (2.53–8.29%), and carthamidin yields (0.04–37.86 kg ha−1) were comparable to or higher than in other studies. In conclusion, this study showed that safflower has great potential for the production of florets in Southwest Germany, for the food-color industry.

Description: Intercropping systems of cereals and legumes have the potential to produce high yields in a more sustainable way compared to sole cropping systems. Their agronomic optimization remains a challenging task given the numerous management options and the complexity of interactions between the crops. Efficient methods for analyzing the influence of different management options are needed. The canopy cover of each crop in the intercropping system is a good determinant for light competition, thus influencing crop growth and weed suppression. Therefore, this study evaluated the feasibility to estimate canopy cover within an intercropping system of pea and oat based on semantic segmentation using a convolutional neural network. The network was trained with images from three datasets during early growth stages comprising canopy covers between 4% and 52%. Only images of sole crops were used for training and then applied to images of the intercropping system. The results showed that the networks trained on a single growth stage performed best for their corresponding dataset. Combining the data from all three growth stages increased the robustness of the overall detection, but decreased the accuracy of some of the single dataset result. The accuracy of the estimated canopy cover of intercropped species was similar to sole crops and satisfying to analyze light competition. Further research is needed to address different growth stages of plants to decrease the effort for retraining the networks.

Description: The Decision Support System for Agrotechnology Transfer (DSSAT) currently provides a safflower model based on CROPGRO. The model was calibrated with the field data of one cultivar grown in New Mexico in 2013 and 2014. As it is rather new and has not yet been tested with other field data, it is important to evaluate the model in different environments. This study evaluated the CROPGRO safflower model for two different cultivars grown under field conditions in southwestern Germany. In addition, a new approach was added, enabling it to predict the yield of florets, which is of special interest, as these are used as a food colorant in Europe. The default model was evaluated with data from 2017 and 2018, obtained in a field trial in southwestern Germany with two cultivars, with row spacing of 12 and 33 cm and sowing densities of 40 and 75 plants m−2. As the default model was not well adapted to European conditions, model modifications were implemented in the species, ecotype, and cultivar files. With these modifications, observed variables such as leaf appearance over time were well predicted (RMSE: 4.76; d-index: 0.88), and simulations of the specific leaf area and leaf area index were greatly improved (RMSE: 24.14 and 0.82; d-index: 0.78 and 0.73). Simulations of the original New Mexico data set were also improved. The newly-added approach to predict floret yield was successfully integrated into the model. Over two years and two cultivars, floret yield was simulated with a RMSE of 97.24 and a d-index of 0.79. Overall, the extended model proved to be useful for simulating growth, floret yield, and yield of safflower in southwestern Germany.

Description: In agroforestry systems (AFS), trees shade the understory crop to a certain extent. Potato is considered a shade-tolerant crop and was thus tested under the given total solar irradiance and climatic conditions of Southwestern Germany for its potential suitability in an AFS. To gain a better understanding of the effects of shade on growth, yield and quality; a three-year field experiment with different artificial shading levels (12%, 26% and 50%) was established. Significant changes in growth occurred at 50% shading. While plant emergence was not affected by shade, flowering was slightly delayed by about three days. Days until senescence also showed a delay under 50% shade. The number of tubers per plant and tuber mass per plant were reduced by about 53% and 69% under 50% shade. Depending on the year, tuber dry matter yield showed a decrease of 19–44% at 50% shade, while starch content showed no significant differences under shade compared to unshaded treatment. The number of stems per plant, plant height and foliage mass per plant as well as tuber fraction, black spot bruise and macronutrient content were unaffected. Overall, potato seems to tolerate shading and can therefore be integrated in an AFS, and can cope with a reduced total irradiance up to 26%.

Description: Agroforestry, as an improved cropping system, offers some advantages in terms of yield, biodiversity, erosion protection or habitats for beneficial insects. It can fulfill the actual sustainability requirements for bioenergy production like food supply, nature conservation, stop of deforestation. However, competition between intercropped species for water, nutrients and light availability has to be carefully considered. A field trial with shading nets was conducted in Southwest Germany to evaluate the influence of different shading levels (−12, −26, and −50% of full sunlight) on biomass growth, dry matter yield and biogas quality parameters of maize (Zea mays L., cv. ‘Corioli CS’). Shading the plants causes a delayed development, a reduction in height and leaf area index and a slower senescence. Dry matter yields were reduced about 18%, 19%, and 44% compared to 21.05 Mg ha−1 year−1 at full sunlight. Biogas and methane yields were also significantly reduced, the 50% shading treatment showed a reduction of 45% for both parameters. Further, shading led to higher crude protein and crude ash contents. If silage maize is grown under shade, the yields of dry matter, biogas, and methane are nearly halved under 50% shade. Cultivation up to 26% shading could be possible.

Description: 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.

Description: 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.

Description: In soybean production, the shade avoidance response can affect yield negatively in both mono- and inter-cropping systems due to increased heterogeneity of the crop and lodging. This is mainly regulated by photoreceptors responding to the ratio between red and far-red light (R:FR) and photosynthetic photon flux density (PPFD). In this study, three soybean cultivars were grown under different R:FR and PPFD in a light emitting diode (LED) climate chamber to disentangle the effect of each on morphology and dry matter. Results showed that plant organs were influenced differently and indicated an interaction with the increase in assimilates at high PPFD. Internode elongation was mainly influenced by low PPFD with an additive effect from low R:FR, whereas petiole elongation responded strongly under low R:FR. Hence, petiole elongation can be seen as the main response to the threat of shade (high PPFD and low R:FR) and both petiole and internode elongation as a response to true shade (low PPFD and low R:FR). Interactions between cultivar and light treatment were found for internode length and diameter and leaf mass ratio, which may be unique properties for specific cropping systems.

Description: Low photosynthetic photon flux density (PPFD) under shade is associated with low blue photon flux density (BPFD), which independent from PPFD can induce shade responses, e.g., elongation growth. In this study, the response of soybean to six levels of BPFD under constant PPFD from LED lighting was investigated with regard to morphology, biomass and photosynthesis to increase the knowledge for optimizing the intensity of BPFD for a speed breeding system. The results showed that low BPFD increased plant height, leaf area and biomass and decreased leaf mass ratio. Photosynthetic rate and internode diameter were not influenced. A functional structural plant model of soybean was calibrated with the experimental data. A response function for internode length to the perceived BPFD by the internodes was derived from simulations and integrated into the model. With the aim to optimize lighting for a speed breeding system, simulations with alternative lighting scenarios indicated that decreasing BPFD during the growth period and using different chamber material with a higher reflectance could reduce energy consumption by 7% compared to the experimental setup, while inducing short soybean plants.

Description: The search for approaches to a holistic sustainable agriculture requires the development of new cropping systems that provide additional ecosystem services beyond biomass supply for food, feed, material, and energy use. The reduction of chemical synthetic plant protection products is a key instrument to protect vulnerable natural resources such as groundwater and biodiversity. Together with an optimal use of mineral fertilizer, agroecological practices, and precision agriculture technologies, a complete elimination of chemical synthetic plant protection in mineral-ecological cropping systems (MECSs) may not only improve the environmental performance of agroecosystems, but also ensure their yield performance. Therefore, the development of MECSs aims to improve the overall ecosystem services of agricultural landscapes by (i) improving the provision of regulating ecosystem services compared to conventional cropping systems and (ii) improving the supply of provisioning ecosystem services compared to organic cropping systems. In the present review, all relevant research levels and aspects of this new farming concept are outlined and discussed based on a comprehensive literature review and the ongoing research project “Agriculture 4.0 without Chemical-Synthetic Plant Protection”.