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.

Recognition of Orobanche cumana Below-Ground Parasitism Through Physiological and Hyper Spectral Measurements in Sunflower (Helianthus annuus L.).

Broomrape (Orobanche and Phelipanche spp.) parasitism is a severe problem in many crops worldwide, including in the Mediterranean basin. Most of the damage occurs during the sub-soil developmental stage of the parasite, by the time the parasite emerges from the ground, damage to the crop has already been done. One feasible method for sensing early, below-ground parasitism is through physiological measurements, which provide preliminary indications of slight changes in plant vitality and productivity. However, a complete physiological field survey is slow, costly and requires skilled manpower. In recent decades, visible to-shortwave infrared (VIS-SWIR) hyperspectral tools have exhibited great potential for faster, cheaper, simpler and non-destructive tracking of physiological changes. The advantage of VIS-SWIR is even greater when narrow-band signatures are analyzed with an advanced statistical technique, like a partial least squares regression (PLS-R). The technique can pinpoint the most physiologically sensitive wavebands across an entire spectrum, even in the presence of high levels of noise and collinearity. The current study evaluated a method for early detection of Orobanche cumana parasitism in sunflower that combines plant physiology, hyperspectral readings and PLS-R. Seeds of susceptible and resistant O. cumana sunflower varieties were planted in infested (15 mg kg-1 seeds) and non-infested soil. The plants were examined weekly to detect any physiological or structural changes; the examinations were accompanied by hyperspectral readings. During the early stage of the parasitism, significant differences between infected and non-infected sunflower plants were found in the reflectance of near and shortwave infrared areas. Physiological measurements revealed no differences between treatments until O. cumana inflorescences emerged. However, levels of several macro- and microelements tended to decrease during the early stage of O. cumana parasitism. Analysis of leaf cross-sections revealed differences in range and in mesophyll structure as a result of different levels of nutrients in sunflower plants, manifesting the presence of O. cumana infections. The findings of an advanced PLS-R analysis emphasized the correlation between specific reflectance changes in the SWIR range and levels of various nutrients in sunflower plants. This work demonstrates potential for the early detection of O. cumana parasitism on sunflower roots using hyperspectral tools.

Ancestral QTL Alleles from Wild Emmer Wheat Enhance Root Development under Drought in Modern Wheat.

A near-isogenic line (NIL-7A-B-2), introgressed with a quantitative trait locus (QTL) on chromosome 7AS from wild emmer wheat (Triticum turgidum ssp. dicoccoides) into the background of bread wheat (T. aestivum L.) cv. BarNir, was recently developed and studied in our lab. NIL-7A-B-2 exhibited better productivity and photosynthetic capacity than its recurrent parent across a range of environments. Here we tested the hypothesis that root-system modifications play a major role in NIL-7A-B-2's agronomical superiority. Root-system architecture (dry matter and projected surface area) and shoot parameters of NIL-7A-B-2 and 'BarNir' were evaluated at 40, 62, and 82 days after planting (DAP) in a sand-tube experiment, and root tip number was assessed in a 'cigar-roll' seedling experiment, both under well-watered and water-limited (WL) treatments. At 82 DAP, under WL treatment, NIL-7A-B-2 presented greater investment in deep roots (depth 40-100 cm) than 'BarNir,' with the most pronounced effect recorded in the 60-80 cm soil depth (60 and 40% increase for root dry matter and surface area, respectively). NIL-7A-B-2 had significantly higher root-tip numbers (∼48%) per plant than 'BarNir' under both treatments. These results suggest that the introgression of 7AS QTL from wild emmer wheat induced a deeper root system under progressive water stress, which may enhance abiotic stress resistance and productivity of domesticated wheat.

Phenotypic plasticity and water flux rates of Citrus root orders under salinity.

Knowledge about the root system structure and the uptake efficiency of root orders is critical to understand the adaptive plasticity of plants towards salt stress. Thus, this study describes the phenological and physiological plasticity of Citrus volkameriana rootstocks under severe NaCl stress on the level of root orders. Phenotypic root traits known to influence uptake processes, for example frequency of root orders, specific root area, cortical thickness, and xylem traits, did not change homogeneously throughout the root system, but changes after 6 months under 90 mM NaCl stress were root order specific. Chloride accumulation significantly increased with decreasing root order, and the Cl(-) concentration in lower root orders exceeded those in leaves. Water flux densities of first-order roots decreased to <20% under salinity and did not recover after stress release. The water flux densities of higher root orders changed marginally under salinity and increased 2- to 6-fold in second and third root orders after short-term stress release. Changes in root order frequency, morphology, and anatomy indicate rapid and major modification of C. volkameriana root systems under salt stress. Reduced water uptake under salinity was related to changes of water flux densities among root orders and to reduced root surface areas. The importance of root orders for water uptake changed under salinity from root tips towards higher root orders. The root order-specific changes reflect differences in vulnerability (indicated by the salt accumulation) and ontogenetic status, and point to functional differences among root orders under high salinity.

A root is a root is a root? Water uptake rates of Citrus root orders.

Knowledge about the physiological function of root orders is scant. In this study, a system to monitor the water flux among root orders was developed using miniaturized chambers. Different root orders of 4-year-old Citrus volkameriana trees were analysed with respect to root morphology and water flux. The eight root orders showed a broad overlap in diameter, but differences in tissue densities and specific root area (SRA) were clearly distinguishable. Thirty per cent of the root branch biomass but 50% of the surface area (SA) was possessed by the first root order, while the fifth accounted for 5% of the SA (20% biomass). The root order was identified as a determinant of water flux. First-order roots showed a significantly higher rate of water uptake than the second and third root orders, whereas the fourth and fifth root orders showed water excess. The water excess suggested the occurrence of hydraulic redistribution (HR) as a result of differences in osmotic potentials. We suggest that plants may utilize hydraulic redistribution to prevent coarse root desiccation and/or to increase nutrient acquisition. Our study showed that the novel 'miniature depletion chamber' method enabled direct measurement of water fluxes per root order and can be a major tool for future studies on root order traits.