Miriam Athmann

A six-year field study was conducted at Château Lafite Rothschild in Bordeaux, France, to investigate the effects of biodynamic (BD) preparations on soil microbiological and chemical properties. Basal respiration (B-Resp), microbial biomass carbon (MBC), total carbon (C-total), and soil organic carbon (SOC) were analyzed in soils from organically managed vineyards, comparing those without (BD −) and with BD preparations (BD +). Accordingly, two treatments were arranged in a randomized block design with four replicates. Soil microbial activity was assessed using the multi-substrate-induced respiration (multi-SIR) method, which measured the catabolic response to 17 low molecular weight organic substances (LMWOS). The results indicated that BD + plots exhibited significantly higher B-Resp (+ 40.0%) and MBC (+ 33.7%) compared to BD − plots, suggesting enhanced microbial metabolic activity. An upward trend in SOC (+ 17.4%) and C-total (+ 16.7%) was observed in BD + soils, indicating improved carbon sequestration potential. The multi-SIR analysis revealed a significant increase in respiratory responses to D-glucose and D-fructose in BD + plots, and an increasing trend of respiratory response for 13 other LMWOS. A higher respiratory response suggests a lower anabolic demand for specific substrates. Principal component analysis distinctively separated BD + from BD − treatments, underscoring the microbial functional profile changed by BD preparations. The significant increases observed in BD + treatments, particularly in B-Resp, MBC, and the catabolic use of D-glucose and D-fructose, demonstrate that integrating BD preparations into organic vineyard systems enhances the biological activity of microbial communities in soils. In the ongoing experiment further research will allow us to understand better longer-term impacts of BD on soil properties.

With climate change, prolonged droughts are expected, requiring agronomic strategies to ensure stable wheat yields. Intercropping presents a promising approach, yet knowledge on non‐legume intercrops remains limited. Thus, this study investigated the effects of strip intercropping spring wheat ( Triticum aestivum ‘Quintus’) with taprooted coriander ( Coriandrum sativum ‘Jantar’) on growth, grain quality of wheat, and the water‐use efficiency (WUE) of both cropping systems under two irrigation regimes: well‐watered (ww, 60% of soil maximum water‐holding capacity) and reduced irrigation (dw, 40%). Experiments were conducted in 120 L containers filled with sandy loam. Under reduced irrigation, when wheat was intercropped with coriander (WCO), wheat grain yield remained comparable to that of sole wheat (WHE), even though the intercropped pots contained only half as many wheat plants. WUE, calculated as total wheat grain yield per pot per liter of applied water, was significantly higher in the intercropping system compared to the system where wheat was growing alone under the same water regime. Moreover, wheat crude protein content was higher under reduced irrigation in both the intercropped and the stand‐alone system when being compared to well‐watered conditions. Coriander seed yield was not significantly affected by irrigation. These results indicate that wheat–coriander intercropping enhances WUE compared to the sole wheat system, stabilizing wheat yield under water‐limited conditions.

Different methods have been proposed for in situ root-length density (RLD) measurement. One widely employed is the time-consuming sampling of soil cores or monoliths (MO). The profile wall (PW) method is a less precise, but faster and less laborious alternative. However, depth-differentiated functions to convert PW RLD estimates to MO RLD measurements have not yet been reported. In this study, we perform a regression analysis to relate PW results to MO results and determine whether calibration is possible for distinct crop groups (grasses, brassicas and legumes) consisting of pure and mixed stands, and whether soil depth affects this calibration. The methods were applied over two years to all crop groups and their absolute and cumulative RLD were compared using a linear (LR) and multiple linear (MLR) regression. PW RLD was found to highly underestimate MO RLD in absolute values and in highly rooted areas. However, a close agreement between both methods was found for cumulative root-length (RL) when applying MLR, highlighting the influence of soil depth. The level of agreement between methods varied strongly with depth. Therefore, the application of PW as the main RLD estimation method can provide reliable estimates of cumulative root distribution traits of cover crops.

In the image forming methods, copper chloride crystallization (CCCryst), capillary dynamolysis (CapDyn), and circular chromatography (CChrom), characteristic patterns emerge in response to different food extracts. These patterns reflect the resistance to decomposition as an aspect of resilience and are therefore used in product quality assessment complementary to chemical analyses. In the presented study, rocket lettuce from a field trial with different radiation intensities, nitrogen supply, biodynamic, organic and mineral fertilization, and with or without horn silica application was investigated with all three image forming methods. The main objective was to compare two different evaluation approaches, differing in the type of image forming method leading the evaluation, the amount of factors analyzed, and the deployed perceptual strategy: Firstly, image evaluation of samples from all four experimental factors simultaneously by two individual evaluators was based mainly on analyzing structural features in CapDyn (analytical perception). Secondly, a panel of eight evaluators applied a Gestalt evaluation imbued with a kinesthetic engagement of CCCryst patterns from either fertilization treatments or horn silica treatments, followed by a confirmatory analysis of individual structural features. With the analytical approach, samples from different radiation intensities and N supply levels were identified correctly in two out of two sample sets with groups of five samples per treatment each (Cohen’s kappa, p = 0.0079), and the two organic fertilizer treatments were differentiated from the mineral fertilizer treatment in eight out of eight sample sets with groups of three manure and two minerally fertilized samples each (Cohen’s kappa, p = 0.0048). With the panel approach based on Gestalt evaluation, biodynamic fertilization was differentiated from organic and mineral fertilization in two out of two exams with 16 comparisons each (Friedman test, p < 0.001), and samples with horn silica application were successfully identified in two out of two exams with 32 comparisons each (Friedman test, p < 0.001). Further research will show which properties of the food decisive for resistance to decomposition are reflected by analytical and Gestalt criteria, respectively, in CCCryst and CapDyn images.

The scale of root quantification in research is often limited by the time required for sampling, measurement, and processing samples. Recent developments in convolutional neural networks (CNNs) have made faster and more accurate plant image analysis possible, which may significantly reduce the time required for root measurement, but challenges remain in making these methods accessible to researchers without an in-depth knowledge of machine learning. We analyzed root images acquired from three destructive root samplings using the RootPainter CNN software that features an interface for corrective annotation for easier use. Root scans with and without non-root debris were used to test if training a model (i.e. learning from labeled examples) can effectively exclude the debris by comparing the end results with measurements from clean images. Root images acquired from soil profile walls and the cross-section of soil cores were also used for training, and the derived measurements were compared with manual measurements. After 200 min of training on each dataset, significant relationships between manual measurements and RootPainter-derived data were noted for monolith (R²=0.99), profile wall (R²=0.76), and core-break (R²=0.57). The rooting density derived from images with debris was not significantly different from that derived from clean images after processing with RootPainter. Rooting density was also successfully calculated from both profile wall and soil core images, and in each case the gradient of root density with depth was not significantly different from manual counts. Differences in root-length density (RLD) between crops with contrasting root systems were captured using automatic segmentation at soil profiles with high RLD (1–5 cm cm^–3) as well with low RLD (0.1–0.3 cm cm^–3). Our results demonstrate that the proposed approach using CNN can lead to substantial reductions in root sample processing workloads, increasing the potential scale of future root investigations.

In low input agriculture, a thorough understanding of the plant-nutrient interactions plays a central role. This study aims to investigate the effects of nitrogen (N), phosphorus (P), and potassium (K) and liming omission on shoot growth as well as on topsoil root biomass, growth and morphology (tuber and fibrous roots) of sugar beet grown under field conditions at the Dikopshof long-term fertilizer experiment (Germany). Classical shoot observation methods were combined with root morphology and link measurements using an image analysis program. Omission of the nutrients N, P and K as well as of liming led to a significant decrease in shoot growth. Tuber yield was lowest for the unfertilized and the K omission treatment. The root shoot ratio was highest in the N deficient treatment. In the K omission treatment, a strategic change from a less herringbone root type (early stage) to a more herringbone root type (late stage), which is more efficient for the acquisition of mobile nutrients, was observed. By contrast, a change from a more herringbone (early stage) to a less herringbone root type (late stage) which is less expensive to produce and maintain was observed in the unfertilized treatment. We conclude that sugar beet alters its root morphology as a nutrient acquisition strategy.

Biopores provide nutrients from root debris and earthworm casts. Inside large biopores, root function is limited due to the lack of root–soil contact. However, the immediate surroundings of biopores may hold a key function as “hotspots” for root growth in the subsoil. To date, sufficient quantitative information on the distribution of roots and nutrients around biopores is missing. In this field study, the biopore sheath was sampled at distances of 0–2, 2–4, 4–8, and 8–12 mm from the surface of the pore wall. The results show a laterally decreasing gradient from the pore towards 8–12 mm distance in root length density (RLD) of spring barley (Hordeum vulgare L.) and faba bean (Vicia faba L.), as well as in total nitrogen (N_t)- and total carbon (C_t)-content. In the biopore sheath (2–12 mm), the share of roots with a diameter of less than 0.4 mm was 92% for barley and 89% for faba bean. The findings support the view that roots can utilize biopores to gain access to deeper soil layers and may use the sheath for nutrient uptake and entrance through to the bulk soil. However, especially for barley, the inner layer of the biopore sheath appeared to be more important for root growth than the sheath of farer distance.