Monitoring Escape and Feeding Behaviours of Cruiser Fish by Inertial and Magnetic Sensors

A method was developed and applied for monitoring two types of fast-start locomotion (feeding and escape) of a cruiser fish, Japanese amberjacks Seriola quinqueradiata. A data logger, which incorporated a 3-axis gyroscope, a 3-axis accelerometer and a 3-axis magnetometer, was attached to the five fish. The escape, feeding and routine movements of the fish, which were triggered in tank experiments, were then recorded by the data logger and video cameras. The locomotor variables, calculated based on the high resolution measurements by the data logger (500 Hz), were investigated to accurately detect and classify the types of fast-track behaviour. The results show that fast-start locomotion can be detected with a high precision (0.97) and recall rate (0.96) from the routine movements. Two types of fast-start movements were classified with high accuracy (0.84). Accuracy was greater if the data were obtained from the data logger, which combined an accelerometer, a gyroscope and a magnetometer, than if only an accelerometer (0.80) or a gyroscope (0.66) was used.     

Identification of Behaviour in Freely Moving Dogs (Canis familiaris) Using Inertial Sensors

Monitoring and describing the physical movements and body postures of animals is one of the most fundamental tasks of ethology. The more precise the observations are the more sophisticated the interpretations can be about the biology of a certain individual or species. Animal-borne data loggers have recently contributed much to the collection of motion-data from individuals, however, the problem of translating these measurements to distinct behavioural categories to create an ethogram is not overcome yet. The objective of the present study was to develop a “behaviour tracker”: a system composed of a multiple sensor data-logger device (with a tri-axial accelerometer and a tri-axial gyroscope) and a supervised learning algorithm as means of automated identification of the behaviour of freely moving dogs. We collected parallel sensor measurements and video recordings of each of our subjects (Belgian Malinois, N=12; Labrador Retrievers, N=12) that were guided through a predetermined series of standard activities. Seven behavioural categories (lay, sit, stand, walk, trot, gallop, canter) were pre-defined and each video recording was tagged accordingly. Evaluation of the measurements was performed by support vector machine (SVM) classification. During the analysis we used different combinations of independent measurements for training and validation (belonging to the same or different individuals or using different training data size) to determine the robustness of the application. We reached an overall accuracy of above 90% perfect identification of all the defined seven categories of behaviour when both training and validation data belonged to the same individual, and over 80% perfect recognition rate using a generalized training data set of multiple subjects. Our results indicate that the present method provides a good model for an easily applicable, fast, automatic behaviour classification system that can be trained with arbitrary motion patterns and potentially be applied to a wide range of species and situations.     

Multi-day Longitudinal Assessment of Physical Activity and Sleep Behavior Among Healthy Young and Older Adults Using Wearable Sensors

ObjectivesThe number of elderly people is growing rapidly and aging is found to affect activities of daily living. Older adults are found to perform less physical activity when compared to younger ones. In the perspective of movement behavior, it is not well understood how are elderly different from younger ones. It is not known whether they produce only low frequency movement accelerations or the overall number of movements produced are reduced in elderly. It is also not known how elderly and younger ones perform movement transitions throughout the duration of a day and during night-time sleep.Material and methodsIn this study, 10 healthy young and 10 healthy old participants wore inertial measurement unit at their lower back for 3-days. The 24 hours of day were divided into four 6 hour time zones and transitions made by young and elderly were investigated. All participants performed their regular daily activities unhindered and longitudinal multi-day signals for acceleration and angular velocity were analyzed. Time-frequency analysis was performed using wavelet transform and frequency content of each movement performed was computed.ResultsWe found that both young and older adults performed significantly more low amplitude movements than medium and high amplitude movements. Healthy young adults produced significantly more movements at 1.1 Hz than older adults. Healthy young adults were also found to have produced significantly smaller number of transitions in the mid-phases of sleep. They were also found to produce significantly larger accelerations during night-time sleep transitions than their older counterparts.ConclusionThe advantages of collecting longitudinal data about human movement and sleep transition data can lead us to important clinical diagnosis. The information from longitudinal assessment can help develop lifestyle interventions for disease prevention, monitoring of chronic diseases to prevent or slow disease progression among elderly people.     

Contact Patterns in a High School: A Comparison between Data Collected Using Wearable Sensors,Contact Diaries and Friendship Surveys

Given their importance in shaping social networks and determining how information or transmissible diseases propagate in a population, interactions between individuals are the subject of many data collection efforts. To this aim, different methods are commonly used, ranging from diaries and surveys to decentralised infrastructures based on wearable sensors. These methods have each advantages and limitations but are rarely compared in a given setting. Moreover, as surveys targeting friendship relations might suffer less from memory biases than contact diaries, it is interesting to explore how actual contact patterns occurring in day-to-day life compare with friendship relations and with online social links. Here we make progresses in these directions by leveraging data collected in a French high school and concerning (i) face-to-face contacts measured by two concurrent methods, namely wearable sensors and contact diaries, (ii) self-reported friendship surveys, and (iii) online social links. We compare the resulting data sets and find that most short contacts are not reported in diaries while long contacts have a large reporting probability, and that the durations of contacts tend to be overestimated in the diaries. Moreover, measured contacts corresponding to reported friendship can have durations of any length but all long contacts do correspond to a reported friendship. On the contrary, online links that are not also reported in the friendship survey correspond to short face-to-face contacts, highlighting the difference of nature between reported friendships and online links. Diaries and surveys suffer moreover from a low sampling rate, as many students did not fill them, showing that the sensor-based platform had a higher acceptability. We also show that, despite the biases of diaries and surveys, the overall structure of the contact network, as quantified by the mixing patterns between classes, is correctly captured by both networks of self-reported contacts and of friendships, and we investigate the correlations between the number of neighbors of individuals in the three networks. Overall, diaries and surveys tend to yield a correct picture of the global structural organization of the contact network, albeit with much less links, and give access to a sort of backbone of the contact network corresponding to the strongest links, i.e., the contacts of longest cumulative durations.     

Nonlinear Analysis of Stride Interval Time Series in Gait Maturation Using Distribution Entropy

ObjectivesThis study aimed to investigate whether DistEn was capable of identifying complexity or irregularity for gait data and whether having low parameter-dependency sensitivity by comparing with the Approximate Entropy (ApEn) and Sample Entropy (SampEn).Material and methodsThe data were divided into three groups according to gait maturation. Firstly, the mean amplitude histogram, standard deviation (SD), and the power spectrum were calculated for each group. Secondly, ApEn, SampEn, and DistEn algorithms were calculated. Statistical analyses were then performed to compare groups.ResultsFor m=3 with M= 256 and M=512 parameters, DistEn showed a statistically significant difference between in pairwise comparisons between all groups (P_a, P_b, and P_c < 0.05). DistEn consistently decreased from Group1, to Group2, and to Group 3. For m=2 with r=0.30 values, SampEn showed a statistically significant difference only in pairwise comparisons between Group1 and Group3 (P_b < 0.05). For with m=3 and r=0.30 parameters, SampEn also showed a statistically significant difference in pairwise comparisons between Group1 and Group3 (P_c < 0.05) as well as Group2 and Group3 (P_c < 0.05) SampEn increased from Group1 to Group3 and from Group2 to Group3. There was not any statistically significant difference in pairwise comparisons of groups for ApEn. Furthermore, DistEn showed less parameter consistency than ApEn and SampEn.ConclusionDistEn showed the best performance in capture the complexity changes in gain patterns with growth.     

Spatiotemporal and Kinematic Parameters Relating to Oriented Gait and Turn Performance in Patients with Chronic Stroke

Background

The timed up and go test (TUG) is a functional test which is increasingly used to evaluate patients with stroke. The outcome measured is usually global TUG performance-time. Assessment of spatiotemporal and kinematic parameters during the Oriented gait and Turn sub-tasks of the TUG would provide a better understanding of the mechanisms underlying patients’ performance and therefore may help to guide rehabilitation. The aim of this study was thus to determine the spatiotemporal and kinematic parameters which were most related to the walking and turning sub-tasks of TUG performance in stroke patients.

Methods

29 stroke patients carried out the TUG test which was recorded using an optoelectronic system in two conditions: spontaneous and standardized condition (standardized foot position and instructed to turn towards the paretic side). They also underwent a clinical assessment. Stepwise regression was used to determine the parameters most related to Oriented gait and Turn sub-tasks. Relationships between explanatory parameters of Oriented gait and Turn performance and clinical scales were evaluated using Spearman correlations.

Results

Step length and cadence explained 82% to 95% of the variance for the walking sub-tasks in both conditions. Percentage single support phase and contralateral swing phase (depending on the condition) respectively explained 27% and 56% of the variance during the turning sub-task in the spontaneous and standardized conditions.

Discussion and Conclusion

Step length, cadence, percentage of paretic single support phase and non-paretic swing phase, as well as dynamic stability were the main parameters related to TUG performance and they should be targeted in rehabilitation.     

Intralimb Coordination Patterns in Absent,Mild, and Severe Stages of Diabetic Neuropathy: Looking Beyond Kinematic Analysis of Gait Cycle

Aim

Diabetes Mellitus progressively leads to impairments in stability and joint motion and might affect coordination patterns, mainly due to neuropathy. This study aims to describe changes in intralimb joint coordination in healthy individuals and patients with absent, mild and, severe stages of neuropathy.

Methods

Forty-seven diabetic patients were classified into three groups of neuropathic severity by a fuzzy model: 18 without neuropathy (DIAB), 7 with mild neuropathy (MILD), and 22 with moderate to severe neuropathy (SVRE). Thirteen healthy subjects were included as controls (CTRL). Continuous relative phase (CRP) was calculated at each instant of the gait cycle for each pair of lower limb joints. Analysis of Variance compared each frame of the CRP time series and its standard deviation among groups (α = 5%).

Results

For the ankle-hip CRP, the SVRE group presented increased variability at the propulsion phase and a distinct pattern at the propulsion and initial swing phases compared to the DIAB and CTRL groups. For the ankle-knee CRP, the 3 diabetic groups presented more anti-phase ratios than the CTRL group at the midstance, propulsion, and terminal swing phases, with decreased variability at the early stance phase. For the knee-hip CRP, the MILD group showed more in-phase ratio at the early stance and terminal swing phases and lower variability compared to all other groups. All diabetic groups were more in-phase at early the midstance phase (with lower variability) than the control group.

Conclusion

The low variability and coordination differences of the MILD group showed that gait coordination might be altered not only when frank evidence of neuropathy is present, but also when neuropathy is still incipient. The ankle-knee CRP at the initial swing phase showed distinct patterns for groups from all degrees of neuropathic severity and CTRLs. The ankle-hip CRP pattern distinguished the SVRE patients from other diabetic groups, particularly in the transitional phase from stance to swing.     

Diaphragm Postural Function Analysis Using Magnetic Resonance Imaging

We present a postural analysis of diaphragm function using magnetic resonance imaging (MRI). The main aim of the study was to identify changes in diaphragm motion and shape when postural demands on the body were increased (loading applied to a distal part of the extended lower extremities against the flexion of the hips was used). Sixteen healthy subjects were compared with 17 subjects suffering from chronic low back pain and in whom structural spine disorders had been identified. Two sets of features were calculated from MRI recordings: dynamic parameters reflecting diaphragm action, and static parameters reflecting diaphragm anatomic characteristics. A statistical analysis showed that the diaphragm respiratory and postural changes were significantly slower, bigger in size and better balanced in the control group. When a load was applied to the lower limbs, the pathological subjects were mostly not able to maintain the respiratory diaphragm function, which was lowered significantly. Subjects from the control group showed more stable parameters of both respiratory and postural function. Our findings consistently affirmed worse muscle cooperation in the low back pain population subgroup. A clear relation with spinal findings and with low back pain remains undecided, but various findings in the literature were confirmed. The most important finding is the need to further address various mechanisms used by patients to compensate deep muscle insufficiency.     

Evolutionary Robotic Approaches in Primate Gait Analysis

Understanding how primates move is particularly challenging because many of the experimentation techniques that would normally be available are unsuitable for ethical and conservation reasons. We therefore need to develop techniques that can maximize the data available from minimally intrusive experimentation. One approach for achieving this is to use evolutionary robotic techniques to build a musculoskeletal simulation and generate movement patterns that optimize some global parameter such as economy or performance, or to match existing kinematic data. If the simulation has a sufficiently high biofidelity and can match experimentally measured performance criteria then we can use it to predict aspects of locomotor mechanics that would otherwise be impossible to measure. This approach is particularly valuable when studying fossil primates because it can be based entirely on morphology and can generate movements spontaneously. A major question in human evolution is the origin of bipedal running and the role of elastic energy storage. By using an evolutionary robotics model of humanoid running we can show that elastic storage is required for efficient, high-performance running. Elasticity allows both energy recovery to minimize total energy cost and also power amplification to allow high performance. The most important elastic energy store on the human hind limb is the Achilles tendon: a feature that is at best weakly expressed among the African great apes. By running simulations both with and without this structure we can demonstrate its importance, and we suggest that identification of the presence or otherwise of this tendon—perhaps by calcaneal morphology or Sharpey’s fibers—is essential for identifying when and where in the fossil record human style running originated.     

Design and Kinematic Analysis of a Novel Humanoid Robot Eye Using Pneumatic Artificial Muscles

This paper proposed a novel humanoid robot eye, which is driven by six Pneumatic Artificial Muscles （PAMs） and rotates with 3 Degree of Freedom （DOF）. The design of the mechanism and motion type of the robot eye are inspired by that of human eyes. The model of humanoid robot eye is established as a parallel mechanism, and the inverse-kinematic problem of this flexible tendons driving parallel system is solved by the analytical geometry method. As an extension, the simulation result for saccadic movement is presented under three conditions. The design and kinematic analysis of the prototype could be a sig- nificant step towards the goal of building an autonomous humanoid robot eye with the movement and especially the visual functions similar to that of human.     

Removing of Disinfection By-Product Precursors from Surface Water by Using Magnetic Graphene Oxide

The magnetic graphene oxide (MGO) was successfully synthesised by the in situ chemical co-precipitation method with Fe³⁺, Fe²⁺ and graphene oxide (GO) in laboratory and, was used as an adsorbent for disinfection by-product (DBP) precursors removing from four natural surface water samples. The results indicate that various DBPs formation significantly decreased by 7–19% to 78–98% for the four samples after MGO treatment and, the treatment process was rapidly reached equilibrium within 20 minutes. The DBP precursors removal efficiency decreased with the increasing pH value from 4 to 10. Hydrophobic compounds (humic acid and fulvic acid) are more sensitive to MGO, whereas hydrophilic and nitrogenous compounds (aromatic proteins) are more insensitive. MGO could be regenerated by using 20% (v/v) ethanol and, the DBP precursors removal efficiency can stay stable after five cycles. These results indicate that MGO can be utilized as a promising adsorbent for the removal of DBP precursors from natural surface water.     

Cross-Talk Correction Method for Knee Kinematics in Gait Analysis Using Principal Component Analysis (PCA): A New Proposal

Background

In 3D gait analysis, the knee joint is usually described by the Eulerian way. It consists in breaking down the motion between the articulating bones of the knee into three rotations around three axes: flexion/extension, abduction/adduction and internal/external rotation. However, the definition of these axes is prone to error, such as the “cross-talk” effect, due to difficult positioning of anatomical landmarks. This paper proposes a correction method, principal component analysis (PCA), based on an objective kinematic criterion for standardization, in order to improve knee joint kinematic analysis.

Methods

The method was applied to the 3D gait data of two different groups (twenty healthy subjects and four with knee osteoarthritis). Then, this method was evaluated with respect to three main criteria: (1) the deletion of knee joint angle cross-talk (2) the reduction of variance in the varus/valgus kinematic profile (3) the posture trial varus/valgus deformation matching the X-ray value for patients with knee osteoarthritis. The effect of the correction method was tested statistically on variabilities and cross-talk during gait.

Results

Cross-talk was lower (p<0.05) after correction (the correlation between the flexion-extension and varus-valgus kinematic profiles being annihilated). Additionally, the variance in the kinematic profile for knee varus/valgus and knee flexion/extension was found to be lower and higher (p<0.05), respectively, after correction for both the left and right side. Moreover, after correction, the posture trial varus/valgus angles were much closer to x-ray grading.

Conclusion

The results show that the PCA correction applied to the knee joint eliminates the cross-talk effect, and does not alter the radiological varus/valgus deformation for patients with knee osteoarthritis. These findings suggest that the proposed correction method produces new rotational axes that better fit true knee motion.     

Using Fiberless,Wearable fNIRS to Monitor Brain Activity in Real-world Cognitive Tasks

Functional Near Infrared Spectroscopy (fNIRS) is a neuroimaging technique that uses near-infrared light to monitor brain activity. Based on neurovascular coupling, fNIRS is able to measure the haemoglobin concentration changes secondary to neuronal activity. Compared to other neuroimaging techniques, fNIRS represents a good compromise in terms of spatial and temporal resolution. Moreover, it is portable, lightweight, less sensitive to motion artifacts and does not impose significant physical restraints. It is therefore appropriate to monitor a wide range of cognitive tasks (e.g., auditory, gait analysis, social interaction) and different age populations (e.g., new-borns, adults, elderly people). The recent development of fiberless fNIRS devices has opened the way to new applications in neuroscience research. This represents a unique opportunity to study functional activity during real-world tests, which can be more sensitive and accurate in assessing cognitive function and dysfunction than lab-based tests. This study explored the use of fiberless fNIRS to monitor brain activity during a real-world prospective memory task. This protocol is performed outside the lab and brain haemoglobin concentration changes are continuously measured over the prefrontal cortex while the subject walks around in order to accomplish several different tasks.     

Quantitative Gait Analysis Using a Motorized Treadmill System Sensitively Detects Motor Abnormalities in Mice Expressing ATPase Defective Spastin

The hereditary spastic paraplegias (HSPs) are genetic conditions in which there is progressive axonal degeneration in the corticospinal tract. Autosomal dominant mutations, including nonsense, frameshift and missense changes, in the gene encoding the microtubule severing ATPase spastin are the most common cause of HSP in North America and northern Europe. In this study we report quantitative gait analysis using a motorized treadmill system, carried out on mice knocked-in for a disease-associated mutation affecting a critical residue in the Walker A motif of the spastin ATPase domain. At 4 months and at one year of age homozygous mutant mice had a number of abnormal gait parameters, including in stride length and stride duration, compared to heterozygous and wild-type littermates. Gait parameters in heterozygous animals did not differ from wild-type littermates. We conclude that quantitative gait analysis using the DigiGait system sensitively detects motor abnormalities in a hereditary spastic paraplegia model, and would be a useful method for analyzing the effects of pharmacological treatments for HSP.     

Change Trend of Water Resources Using Matter Analysis

Many countries currently face pressures and risks associated with scarce water resources. By using grey correlation analysis, we can choose physical factors with close relationships to water resources. In this article, we used physical factors as possible predictors and thus endowed matter analysis with a forecast function, which represents a novel application. By repeatedly adjusting grade division values (classical domain and joint domain) of each factor, it is possible to determine the maximum fit between the calculated grade and the actual grade of annual runoff. Results presented here indicate that this method is suitable for forecasting changing annual runoff trends in drainage basins. By focusing on forecasts of changing trends relating to water resources, we have set up a preliminary calculation system based on matter analysis. It is expected that this application will become more sensitive, resulting in improved performance in terms of trend forecasts of water resources using matter analysis.     

Variations in Kinematics during Clinical Gait Analysis in Stroke Patients

In addition to changes in spatio-temporal and kinematic parameters, patients with stroke exhibit fear of falling as well as fatigability during gait. These changes could compromise interpretation of data from gait analysis. The aim of this study was to determine if the gait of hemiplegic patients changes significantly over successive gait trials. Forty two stroke patients and twenty healthy subjects performed 9 gait trials during a gait analysis session. The mean and variability of spatio-temporal and kinematic joint parameters were analyzed during 3 groups of consecutive gait trials (1–3, 4–6 and 7–9). Principal component analysis was used to reduce the number of variables from the joint kinematic waveforms and to identify the parts of the gait cycle which changed during the gait analysis session. The results showed that i) spontaneous gait velocity and the other spatio-temporal parameters significantly increased, and ii) gait variability decreased, over the last 6 gait trials compared to the first 3, for hemiplegic patients but not healthy subjects. Principal component analysis revealed changes in the sagittal waveforms of the hip, knee and ankle for hemiplegic patients after the first 3 gait trials. These results suggest that at the beginning of the gait analysis session, stroke patients exhibited phase of adaptation,characterized by a “cautious gait” but no fatigue was observed.     

Quantitative 3D Analysis of Plant Roots Growing in Soil Using Magnetic Resonance Imaging

Precise measurements of root system architecture traits are an important requirement for plant phenotyping. Most of the current methods for analyzing root growth require either artificial growing conditions (e.g. hydroponics), are severely restricted in the fraction of roots detectable (e.g. rhizotrons), or are destructive (e.g. soil coring). On the other hand, modalities such as magnetic resonance imaging (MRI) are noninvasive and allow high-quality three-dimensional imaging of roots in soil. Here, we present a plant root imaging and analysis pipeline using MRI together with an advanced image visualization and analysis software toolbox named NMRooting. Pots up to 117 mm in diameter and 800 mm in height can be measured with the 4.7 T MRI instrument used here. For 1.5 l pots (81 mm diameter, 300 mm high), a fully automated system was developed enabling measurement of up to 18 pots per day. The most important root traits that can be nondestructively monitored over time are root mass, length, diameter, tip number, and growth angles (in two-dimensional polar coordinates) and spatial distribution. Various validation measurements for these traits were performed, showing that roots down to a diameter range between 200 μm and 300 μm can be quantitatively measured. Root fresh weight correlates linearly with root mass determined by MRI. We demonstrate the capabilities of MRI and the dedicated imaging pipeline in experimental series performed on soil-grown maize (Zea mays) and barley (Hordeum vulgare) plants.The root system is of critical importance for the survival, development, and performance of higher plants, because it is the major organ for anchorage, acquisition of water and nutrients, and carbon storage. Therefore, there is a long-standing interest in the scientific community regarding the structure, function, and development of root systems. Rising concerns about the environmental impact and increasing cost of fertilizers have initiated breeding programs for more resource-efficient cultivars and the development of methods for phenotyping root systems. The opaque nature of soils generally demands destructive methods such as root excavation for subsequent optical assessment (Lynch, 2007; Trachsel et al., 2011). Although efficient for screening large numbers of plants for a limited set of clearly discernible traits, this approach does not allow detailed monitoring of root development over time. Other approaches, such as rhizotrons or mini-rhizotron tubes, where root growth is observed along transparent windows (Nagel et al., 2009), monitor only a fraction of the roots. Methods in which the whole root system is visible are typically based on artificial media such as paper pouches (Chen et al., 2011; Le Marié et al., 2014), three-dimensional (3D) gels (Iyer-Pascuzzi et al., 2010), and hydro- or aeroponics (Herdel et al., 2001). Results may thus not be directly transferable to plants grown in natural 3D soil environments (Gregory et al., 2003). For example, roots are known to grow faster and thinner when the penetration resistance is low (Bengough et al., 2011; Chimungu et al., 2015). Computed tomography (CT; both x-ray and neutron) has been proposed to overcome the mentioned difficulties with studying roots in natural soil. CT has been successfully used to obtain high-resolution images of roots (Moradi et al., 2009; Flavel et al., 2012; Mooney et al., 2012). High resolution is necessary for segmenting roots due to a poor contrast between roots and soil (Jassogne et al., 2009; Mairhofer et al., 2012; Mairhofer et al., 2013). A first direct comparison (to our knowledge) of magnetic resonance imaging (MRI) and x-ray CT for 3D root imaging has recently been published (Metzner et al., 2015), showing that the two modalities pose different opportunities and limitations for root imaging.MRI is based on the magnetic moment of atomic nuclei like ¹H (protons), which are highly abundant in living tissues, mainly in water molecules. The magnetic moment can be manipulated using strong magnetic and radio frequency fields that have no known impact on plant development to produce 3D datasets of samples. MRI offers several contrast parameters that can be manipulated for discriminating different structures such as roots from soil background (Rogers and Bottomley, 1987; Jahnke et al., 2009). The basic principles of MRI are described in detail in several textbooks (Callaghan, 1993; Haacke et al., 1999) or review articles (Köckenberger et al., 2004; Blümler et al., 2009; van As et al., 2009; Borisjuk et al., 2012). Research applications to plant roots range from phytopathology (Hillnhütter et al., 2012), across storage root internal structures (Metzner et al., 2014) and water uptake modeling (Stingaciu et al., 2013), to coregistration with positron emission tomography for investigating structure-function relations (Jahnke et al., 2009). Water mobility in roots and soil has also been shown to be detectable with MRI (MacFall and Johnson, 2012; Gruwel, 2014). In particular for imaging roots with MRI, these studies generally explored the applicability of MRI but largely lacked validation of the data against conventional techniques of root visualization after harvest. Our goal was to develop MRI protocols to image roots of plants growing in soil to obtain global root parameters such as root length, mass, or root diameters; gather root growth angles and number of root tips; get spatial information on the distribution of root system architecture (RSA) parameters such as root length densities; and, wherever possible, verify these parameters against harvest data.