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Abstract Plant residues with larger carbon (C) to nitrogen (N) ratios can stimulate microbial growth and thereby protect soil nutrients from leaching. In poorly fertilized soil, excessive immobilization may limit nutrient availability and thus plant growth. Little is known about the impact of a shallow straw incorporation on soil microbial regulation of top-dressing fertilizer nutrients and spring crop establishment. We aimed to evaluate if wheat straw in combination with mineral fertilizer has more positive effects on plant performance than mineral fertilization alone and if this relates to changes of the extractable C:N:P ratio and microbial activity close to the roots. In order to conduct small-scale sampling with minimal disturbance during growth of spring barley (Hordeum vulgare L.), we developed rhizotrons with resealable ports. Rhizotrons were filled with loamy-sandy soil and fertilized with an equivalent of 150 kg N and 80 kg P ha−1. Half of the rhizotrons received the top dressing together with 4500 kg wheat straw-C ha−1. Throughout a 90-day greenhouse experiment, we analyzed soil C:N:P dynamics, and carbon dioxide (CO2) and nitrous oxide (N2O) emission, together with microbial biomass, selected bacterial genes (abundance), and transcripts (activity) in bulk and root-affected soil at multiple times. We focused on nitrifiers and denitrifiers and linked our data to barley growth. Interactions between straw and roots caused shifts towards larger C:P and C:N ratios in root-affected soil. These shifts were associated with increased 16S rRNA transcripts and denitrifier activities. Straw increased microbial biomass by 124% in the topsoil and at the same time increased root biomass by 125% and number of tillers by 80%. We concluded that microbial activation at the root-straw interface may positively feed back on soil nutrient regulation and plant performance. Further research has to evaluate if plant roots actively prime mining of previously immobilized nutrients in the straw detritusphere or if effects of pathogen suppression and growth promotion are dominating.

Background Plant root research can provide a way to attain stress-tolerant crops that produce greater yield in a diverse array of conditions. Phenotyping roots in soil is often challenging due to the roots being difficult to access and the use of time consuming manual methods. Rhizotrons allow visual inspection of root growth through transparent surfaces. Agronomists currently manually label photographs of roots obtained from rhizotrons using a line-intersect method to obtain root length density and rooting depth measurements which are essential for their experiments. We investigate the effectiveness of an automated image segmentation method based on the U-Net Convolutional Neural Network (CNN) architecture to enable such measurements. We design a data-set of 50 annotated chicory ( Cichorium intybus L.) root images which we use to train, validate and test the system and compare against a baseline built using the Frangi vesselness filter. We obtain metrics using manual annotations and line-intersect counts. Results Our results on the held out data show our proposed automated segmentation system to be a viable solution for detecting and quantifying roots. We evaluate our system using 867 images for which we have obtained line-intersect counts, attaining a Spearman rank correlation of 0.9748 and an r 2 of 0.9217. We also achieve an F 1 of 0.7 when comparing the automated segmentation to the manual annotations, with our automated segmentation system producing segmentations with higher quality than the manual annotations for large portions of the image. Conclusion We have demonstrated the feasibility of a U-Net based CNN system for segmenting images of roots in soil and for replacing the manual line-intersect method. The success of our approach is also a demonstration of the feasibility of deep learning in practice for small research groups needing to create their own custom labelled dataset from scratch.

Societal Impact Statement Infestation by the parasitic weed Striga is a major cause of cereal crop production losses on smallholder farms in Africa. Essential plant nutrients play an important indirect role in parasite seed germination, the first prerequisite for successful parasitism. Here, we demonstrate that increasing the nutrient availability for the host plant can also impede Striga development beyond its germination, independent of the resistance levels of the sorghum host. This insight provides additional support for crop protection recommendations to Striga‐affected farmers. Growing a resistant crop variety combined with adequate levels of fertilisers should be the backbone of defence against this parasitic weed. Summary Striga hermonthica is a widespread parasitic weed in sub‐Saharan Africa and an important biotic constraint to sorghum production. Resistant varieties and fertilisers are crucial components of integrated Striga management. N and P fertilisers reduce the production of host‐plant strigolactones, known as Striga germination stimulants, and thereby reduce infection. Whether essential plant nutrients affect the parasite–host interaction beyond Striga germination is unknown. We conducted mini‐rhizotron assays to investigate the effects of macronutrient and micronutrient availability on post‐germination Striga development. Four sorghum genotypes (Framida, IS10978, N13, IS9830) covering the complete array of known mechanisms of post‐attachment resistance were compared with susceptible genotype Ochuti. Plants were infected with pre‐germinated Striga seeds and subjected to four nutrient treatment levels: (1) 25% of the optimal concentration of Long Ashton solution for cereals; (2) 25% macronutrient and optimal micronutrient concentration; (3) optimal macronutrient and 25% micronutrient concentration; and (4) optimal macronutrient and micronutrient concentrations. Compared with the 25% base nutrient level, treatments supplemented with macronutrients reduced the number of viable vascular connections established by pre‐germinated Striga seedlings as well as the total parasite biomass on the sorghum root system. Macronutrient treatment effects were observed across sorghum genotypes, independent of the presence and type of post‐attachment resistance, but appeared to specifically improve mechanical resistance, hypersensitive and incompatibility responses before Striga reaches the host‐root xylem. This study demonstrates, for the first time, that nutrient availability drives Striga parasitism beyond the germination stages. Increased availability of nutrients, in particular macronutrients, enhances host‐plant resistance in post‐attachment stages, reinforcing the importance of current fertiliser recommendations. Infestation by the parasitic weed Striga is a major cause of cereal crop production losses on smallholder farms in Africa. Essential plant nutrients play an important indirect role in parasite seed germination, the first prerequisite for successful parasitism. Here, we demonstrate that increasing the nutrient availability for the host plant can also impede Striga development beyond its germination, independent of the resistance levels of the sorghum host. This insight provides additional support for crop protection recommendations for Striga‐affected farmers. Growing a resistant crop variety combined with adequate levels of fertilisers should be the backbone of defence against this parasitic weed.

1. Fine roots play a key role in carbon (C) and nutrient cycling, since fine root life span drives soil organic input and, thus, nitrogen (N) availability. The two main fungal symbioses found in temperate forest trees, ectomycorrhizae (ECM) and arbuscular mycorrhizae (AM), induce different root morphological changes upon infection, but the consequences for root life span are not clear. 2. We explored differences in fine root life span between four AM and four ECM tree species using mini-rhizotrons in a factorial drought experiment in large mesocosms. 3. Median root life span of young AM and ECM trees differed fundamentally in its response to soil moisture and season of root birth; ECM root life span was reduced from 176 to 81 days in dry soil compared to moist soil, independent of season. By contrast, AM root life span was less responsive to drought, but decreased from 185 to 127 days when comparing roots produced early in the growing season versus mid-season. In both mycorrhizal types, root life span was positively related to root diameter and negatively to the portion of lower order roots. 4. Synthesis. While our results indicate morphological and architectural traits that predict root life span across tree species, they also indicate fundamental differences in the environmental response of root life span in young AM and ECM trees. This knowledge helps to improve global predictions of root life span.

We studied the drought response of eight commercial hybrid maize lines with contrasting drought sensitivity together with the reference inbred line B73 using a non-invasive platform for root and shoot phenotyping and a kinematics approach to quantify cell level responses in the leaf. Drought treatments strongly reduced leaf growth parameters including projected leaf area, elongation rate, final length and width of the fourth and fifth leaf. Physiological measurements including water use efficiency, chlorophyll fluorescence and photosynthesis were also significantly affected. By performing a kinematic analysis, we show that leaf growth reduction in response to drought is mainly due to a decrease in cell division rate, whereas a marked reduction in cell expansion rate is compensated by increased duration of cell expansion. Detailed analysis of root growth in rhizotrons under drought conditions revealed a strong reduction in total root length as well as rooting depth and width. This was reflected by corresponding decreases in fresh and dry weight of the root system. We show that phenotypic differences between lines differing in geographic origin (African vs. European) and in drought tolerance under field conditions can already be identified at the seedling stage by measurements of total root length and shoot dry weight of the plants. Moreover, we propose a list of candidate traits that could potentially serve as traits for future screening strategies.

Accurate segmentation of fine roots in field rhizotron imagery is essential for high-throughput root system analysis but remains challenging due to limitations of traditional methods. Traditional methods for root quantification (e.g., soil coring, manual counting) are labor-intensive, subjective, and low-throughput. These limitations are exacerbated in in situ rhizotron imaging, where variable field conditions introduce noise and complex soil backgrounds. To address these challenges, this study develops an advanced deep learning framework for automated segmentation. We propose an improved U-shaped Convolutional Neural Network (U-Net) architecture optimized for segmenting larch (Larix olgensis) fine roots under heterogeneous field conditions, integrating both in situ rhizotron imagery and open-source multi-species minirhizotron datasets. Our approach integrates (1) a Convolutional Block Attention Module (CBAM) to enhance feature representation for fine-root detection; (2) an additive feature fusion strategy (UpAdd) during decoding to preserve morphological details, particularly in low-contrast regions; and (3) a transfer learning protocol to enable robust cross-species generalization. Our model achieves state-of-the-art performance with a mean intersection over union (mIoU) of 70.18%, mean Recall of 86.72%, and mean Precision of 75.89%—significantly outperforming PSPNet, SegNet, and DeepLabV3+ by 13.61%, 13.96%, and 13.27% in mIoU, respectively. Transfer learning further elevates root-specific metrics, yielding absolute gains of +0.47% IoU, +0.59% Precision, and +0.35% F1-score. The improved U-Net segmentation demonstrated strong agreement with the manual method for quantifying fine-root length, particularly for third-order roots, though optimization of lower-order root identification is required to enhance overall accuracy. This work provides a scalable approach for advancing automated root phenotyping and belowground ecological research.

Aims The flow of electric current in the root-soil system relates to the pathways of water and solutes, its characterization provides information on the root architecture and functioning. We developed a current source density approach with the goal of non-invasively image the current pathways in the root-soil system. Methods A current flow is applied from the plant stem to the soil, the proposed geoelectrical approach images the resulting distribution and intensity of the electric current in the root-soil system. The numerical inversion procedure underlying the approach was tested in numerical simulations and laboratory experiments with artificial metallic roots. We validated the method using rhizotron laboratory experiments on maize and cotton plants. Results Results from numerical and laboratory tests showed that our inversion approach was capable of imaging root-like distributions of the current source. In maize and cotton, roots acted as “leaky conductors”, resulting in successful imaging of the root crowns and negligible contribution of distal roots to the current flow. In contrast, the electrical insulating behavior of the cotton stems in dry soil supports the hypothesis that suberin layers can affect the mobility of ions and water. Conclusions The proposed approach with rhizotrons studies provides the first direct and concurrent characterization of the root-soil current pathways and their relationship with root functioning and architecture. This approach fills a major gap toward non-destructive imaging of roots in their natural soil environment.

Aims Root system architecture (RSA) plays a crucial role in determining the efficiency of absorbing water in the different soil layers. Studies on the RSA, however, are limited partly because plant roots are found underground and difficult to observe them during plant development. This study aimed to assess the variation in the RSA traits of sorghum landraces at the seedling stage. Methods A set of one hundred sixty diverse sorghum genotypes were grown in soil-based rhizotrons and data on nodal root angles (NRA), days to nodal root emergence (DNRE), number of nodal roots (NNR), nodal root length (NRL), fresh root weight (RFW), dry root weight (DRW), root-to-shoot ratio (RSR), fresh shoot weight (FSW), dry shoot weight (DSW), leaf area (LA) were collected. Results The analysis of variance revealed the presence of high variation among genotypes for all the studied traits. Repeatability of the RSA traits ranged from 44.8% for RSR to 85.2% for NNR. The wide variation ranging from 16.3° to 53.0° and heritability (63.1%) of the nodal root angles allow the selection of desirable genotypes adapted to drought environments. Several diverse sorghum genotypes with narrow and wide nodal root angles were identified. Genotypes with narrow nodal root angles such as G141, G100, and G63 could be prioritized for use in developing cultivars suitable for dry areas. Conclusions This study illustrates the presence of promising sorghum genotypes in terms of RSA traits, which should be utilized for the development of novel cultivars that match cultivation environments differing in water availability.

The terminal branch orders of plant root systems have been proposed as short-lived ‘ephemeral’ modules specialized for resource absorption. The occurrence of ephemeral root modules has so far only been reported for a temperate tree species and it is unclear if the concept also applies to other woody (shrub, tree) and herb species. Fine roots of 12 perennial dicotyledonous herb, shrub and tree species were monitored for two growing seasons using a branch-order classification, sequential sampling and rhizotrons in the Taklamakan desert. Two root modules existed in all three plant functional groups. Among the first five branch orders, the first two (perennial herbs, shrubs) or three (trees) root orders were ephemeral and had a primary anatomical structure, high nitrogen (N) concentrations, high respiration rates and very short life spans of 1–4 months, whereas the last two branch orders in all functional groups were perennial, with thicker diameters, no or collapsed cortex, distinct secondary growth, low N concentrations, low respiration rates, but much longer life spans. Ephemeral, short-lived root modules and long-lived, persistent root modules seem to be a general feature across many plant functional groups and could represent a basic root system design.

Giant reed (Arundo donax L.) is a deep-rooted crop that can survive prolonged dry periods probably as a result of its capacity to uptake water from below ground, but specific information on the functioning of deep/shallow roots is missing. The objective of this study was to understand the dynamic interrelationships of root water acquisition, canopy water conservation and abscisic acid (ABA) signals from both shallow and deep roots. In transparent split top-bottom rhizotron systems (1-m-high columns), where hydraulically isolated and independently watered layers were created with the aid of calibrated soil moisture sensors, water uptake trends were monitored. Rooting patterns were traced on the walls of the rhizotrons. Leaf gas exchange was determined using a portable infrared gas analyser. Leaf and root ABA concentrations were monitored. Under well-watered conditions, water uptake from both upper and deeper soil layers was similar. Water uptake from deeper soil layers increased gradually by up to 2.2-fold when drought stress was imposed to upper layers compared to the control conditions. Despite the significant increase in water uptake from deeper layers, surface root length density of drought-treated plants remained unchanged, suggesting increased root water uptake efficiency by these roots. However, these adjustments were not sufficient to sustain photosynthesis and therefore biomass accumulation, which was reduced by 42 %. The ABA content in shallower drought-treated roots increased 2.6-fold. This increase closely and positively correlated with foliar ABA concentration, increased intrinsic water use efficiency and leaf water potential (LWP). Giant reed is able to change its water sources depending on water availability and to maximize water uptake efficiency to satisfy canopy evapotranspirative demands. The regulation of deep root functioning and distribution, adjustment of canopy size, and root/foliar synthesized ABA play a central role in controlling LWP and leaf transpiration efficiency.