Rice increases phosphorus uptake in strongly sorbing soils by intra-root facilitation

Benefits and limits of biological nitrification inhibitors for plant nitrogen uptake and the environment

Plant growth and high yields are secured by intensive use of nitrogen (N) fertilizer, which, however, pollutes the environment, especially when N is in the form of nitrate. Ammonium is oxidized to nitrate by nitrifiers, but roots can release biological nitrification inhibitors (BNIs). Under what conditions does root-exudation of BNIs facilitate nitrogen N uptake and reduce pollution by N loss to the environment? We modeled the spatial-temporal dynamics of nitrifiers, ammonium, nitrate, and BNIs around a root and simulated root N uptake and net rhizosphere N loss over the plant's life cycle. We determined the sensitivity of N uptake and loss to variations in the parameter values, testing a broad range of soil-plant-microbial conditions, including concentrations, diffusion, sorption, nitrification, population growth, and uptake kinetics. An increase in BNI exudation reduces net N loss and, under most conditions, increases plant N uptake. BNIs decrease uptake in the case of (1) low ammonium concentrations, (2) high ammonium adsorption to the soil, (3) rapid nitrate- or slow ammonium uptake by the plant, and (4) a slowly growing or (5) fast-declining nitrifier population. Bactericidal inhibitors facilitate uptake more than bacteriostatic ones. Some nitrification, however, is necessary to maximize uptake by both ammonium and nitrate transporter systems. An increase in BNI exudation should be co-selected with improved ammonium uptake. BNIs can reduce N uptake, which may explain why not all species exude BNIs but have a generally positive effect on the environment by increasing rhizosphere N retention.

Visualizing and quantifying 33P uptake and translocation by maize plants grown in soil

Phosphorus (P) availability severely limits plant growth due to its immobility and inaccessibility in soils. Yet, visualization and measurements of P uptake from different root types or regions in soil are methodologically challenging. Here, we explored the potential of phosphor imaging combined with local injection of radioactive 33P to quantitatively visualize P uptake and translocation along roots of maize grown in soils. Rhizoboxes (20 × 40 × 1 cm) were filled with sandy field soil or quartz sand, with one maize plant per box. Soil compartments were created using a gravel layer to restrict P transfer. After 2 weeks, a compartment with the tip region of a seminal root was labeled with a NaH2 33PO4 solution containing 12 MBq of 33P. Phosphor imaging captured root P distribution at 45 min, 90 min, 135 min, 180 min, and 24 h post-labeling. After harvest, 33P levels in roots and shoots were quantified. 33P uptake exhibited a 50% increase in quartz sand compared to sandy soil, likely attributed to higher P adsorption to the sandy soil matrix than to quartz sand. Notably, only 60% of the absorbed 33P was translocated to the shoot, with the remaining 40% directed to growing root tips of lateral or seminal roots. Phosphor imaging unveiled a continuous rise in 33P signal in the labeled seminal root from immediate post-labeling until 24 h after labeling. The highest 33P activities were concentrated just above the labeled compartment, diminishing in locations farther away. Emerging laterals from the labeled root served as strong sinks for 33P, while a portion was also transported to other seminal roots. Our study quantitatively visualized 33P uptake and translocation dynamics, facilitating future investigations into diverse root regions/types and varying plant growth conditions. This improves our understanding of the significance of different P sources for plant nutrition and potentially enhances models of plant P uptake.

Automatic Root Length Estimation from Images Acquired In Situ without Segmentation

Image-based root phenotyping technologies, including the minirhizotron (MR), have expanded our understanding of the in situ root responses to changing environmental conditions. The conventional manual methods used to analyze MR images are time-consuming, limiting their implementation. This study presents an adaptation of our previously developed convolutional neural network-based models to estimate the total (cumulative) root length (TRL) per MR image without requiring segmentation. Training data were derived from manual annotations in Rootfly, commonly used software for MR image analysis. We compared TRL estimation with 2 models, a regression-based model and a detection-based model that detects the annotated points along the roots. Notably, the detection-based model can assist in examining human annotations by providing a visual inspection of roots in MR images. The models were trained and tested with 4,015 images acquired using 2 MR system types (manual and automated) and from 4 crop species (corn, pepper, melon, and tomato) grown under various abiotic stresses. These datasets are made publicly available as part of this publication. The coefficients of determination (R2), between the measurements made using Rootfly and the suggested TRL estimation models were 0.929 to 0.986 for the main datasets, demonstrating that this tool is accurate and robust. Additional analyses were conducted to examine the effects of (a) the data acquisition system and thus the image quality on the models' performance, (b) automated differentiation between images with and without roots, and (c) the use of the transfer learning technique. These approaches can support precision agriculture by providing real-time root growth information.

Novel QTL for Lateral Root Density and Length Improve Phosphorus Uptake in Rice (Oryza sativa L.)

The rice root system consists of two types of lateral roots, indeterminate larger L-types capable of further branching, and determinate, short, unbranched S-types. L-type laterals correspond to the typical lateral roots of cereals whereas S-type laterals are unique to rice. Both types contribute to nutrient and water uptake and genotypic variation for density and length of these laterals could be exploited in rice improvement to enhance adaptations to nutrient and water-limited environments. Our objectives were to determine how best to screen for lateral root density and length and to identify markers linked to genotypic variation for these traits. Using different growing media showed that screening in nutrient solution exposed genotypic variation for S-type and L-type density, but only the lateral roots of soil-grown plants varied for their lengths. A QTL mapping population developed from parents contrasting for lateral root traits was grown in a low-P field, roots were sampled, scanned and density and length of lateral roots measured. One QTL each was detected for L-type density (LDC), S-type density on crown root (SDC), S-type density on L-type (SDL), S-type length on L-type (SLL), and crown root number (RNO). The QTL for LDC on chromosome 5 had a major effect, accounting for 46% of the phenotypic variation. This strong positive effect was confirmed in additional field experiments, showing that lines with the donor parent allele at qLDC5 had 50% higher LDC. Investigating the contribution of lateral root traits to P uptake using stepwise regressions indicated LDC and RNO were most influential, followed by SDL. Simulating effects of root trait differences conferred by the main QTL in a P uptake model confirmed that qLDC5 was most effective in improving P uptake followed by qRNO9 for RNO and qSDL9 for S-type lateral density on L-type laterals. Pyramiding qLDC5 with qRNO9 and qSDL9 would be possible given that trade-offs between traits were not detected. Phenotypic selection for the RNO trait during variety development would be feasible, however, the costs of doing so reliably for lateral root density traits is prohibitive and markers identified here therefore provide the first opportunity to incorporate such traits into a breeding program.

Phenotypes and Molecular Mechanisms Underlying the Root Response to Phosphate Deprivation in Plants

Phosphorus (P) is an essential macronutrient for plant growth. The roots are the main organ for nutrient and water absorption in plants, and they adapt to low-P soils by altering their architecture for enhancing absorption of inorganic phosphate (Pi). This review summarizes the physiological and molecular mechanisms underlying the developmental responses of roots to Pi starvation, including the primary root, lateral root, root hair, and root growth angle, in the dicot model plant Arabidopsis thaliana and the monocot model plant rice (Oryza sativa). The importance of different root traits and genes for breeding P-efficient roots in rice varieties for Pi-deficient soils are also discussed, which we hope will benefit the genetic improvement of Pi uptake, Pi-use efficiency, and crop yields.

Harnessing belowground processes for sustainable intensification of agricultural systems

Increasing food demand coupled with climate change pose a great challenge to agricultural systems. In this review we summarize recent advances in our knowledge of how plants, together with their associated microbiota, shape rhizosphere processes. We address (molecular) mechanisms operating at the plant-microbe-soil interface and aim to link this knowledge with actual and potential avenues for intensifying agricultural systems, while at the same time reducing irrigation water, fertilizer inputs and pesticide use. Combining in-depth knowledge about above and belowground plant traits will not only significantly advance our mechanistic understanding of involved processes but also allow for more informed decisions regarding agricultural practices and plant breeding. Including belowground plant-soil-microbe interactions in our breeding efforts will help to select crops resilient to abiotic and biotic environmental stresses and ultimately enable us to produce sufficient food in a more sustainable agriculture in the upcoming decades.