Name: determining the contribution of the energy systems during exercise
Uploaded: 2012-03-20T12:00:00
Duration: 11 min 15 s
Description: Watch this Scientific Journal Video about Determining the Contribution of the Energy Systems During Exercise at JoVE.com

We thank to Fabiana Benatti for her kind cooperation in the video. We also thank FAPESP (#2007/51228-0) and CNPq (#300133/2008-1) for the support to our researches on this area.

Introduction
The energy necessary for sustaining a physical effort comes from two metabolic sources: aerobic and anaerobic metabolism. While the aerobic metabolism is more efficient than the anaerobic metabolism (i.e., it produces a higher amount of ATP per mol of substrate), producing energy through anaerobic metabolism can provide a high amount of energy in a very short time period. This may be decisive for any situation that requires extremely fast movements. 
Each sport has specific characteristics in terms of motor skills that confer unique physiologic and metabolic demands for that particular sport. The most important aspect of the metabolic demand is the relative contribution of the energy systems to the total energy required for the activity. To determine the specific demand of each sport is crucial for developing optimized training models, nutritional strategies and ergogenic aids that may maximize athletic performance.
Some sports are relatively easy to be reproduced in a laboratory setting, thus it is possible to create a controlled environment in which athletes can be evaluated. This is the case of running and cycling, for example. Predictable movements compose these sports and, therefore, they are easy to be studied. Using some simple equipment, it is possible to mimic quite exactly the same movements that athletes perform in real situations, such as training and competitions. Indeed, these sports have been more extensively studied by exercise scientists and benefited with a more complete and reliable scientific literature. 
On the other hand, a number of sports are much more difficult to be reproduced in laboratory. These sports are unpredictable and dependent on the actions of the partner(s) and opponent(s). This leads to an inability to accurately reproduce the competitive conditions in the lab and an inability to assess these athletes in field during either training or competition. Maybe because of these problems, they have received much less attention from the scientists. This is the case of the majority of team sports and many individual sports1.
Considering these aspects, we aimed to describe how to assess the differential contribution of the energy systems in sports that are difficult to reproduce in controlled laboratory conditions. Because judo is a very complex and unpredictable sport, we will use judo as an example. However, the concepts shown here can be adapted to a number of different sports.
1. Physiological Measurements at Rest
<ol>
 <li>Measure the athlete&#x2019;s body mass before he/she initiates exercising.</li>
 <li>Before initiating the exercise, collect a small resting blood sample from earlobe or fingertip and keep it on ice until the whole experimental procedure is finished.</li>
 <li>Following, place the calibrated portable gas analyser at the most convenient position, which depends on the movements that the athlete will perform, and record resting or baseline oxygen consumption for five minutes. During the baseline measurement, the athlete has to stay quiet standing on his/her feet (if the exercise will be performed in a standing position) or sat in the equipment that will be used (if the exercise will be performed in a cycloergometer or in any similar equipment).</li>
</ol>
2. Physiological Measurements during Exercise
<ol>
 <li>After collecting resting blood sample and resting oxygen consumption, you may ask the athlete to start the specific exercise that you are studying. The portable gas analyser has to be placed in a position that will no interfere with exercise and that exercise will not damage the equipment. Continue measuring oxygen consumption throughout the exercise period.</li>
</ol>
3. Physiological Measurements after Exercise
<ol>
 <li>After collecting exercise oxygen consumption data, keep recording oxygen consumption for ten minutes before shutting the equipment down. Always recalibrate the gas analyser if more than one athlete is being evaluated in the same day.</li>
 <li>In order to identify the peak plasma lactate after exercise, collect small blood samples immediately after exercise, three, five and seven minutes after exercise. Keep them on ice until analysis.</li>
</ol>
4. Blood Samples Processing and Peak Plasma Lactate Determination
<ol>
 <li>All blood samples must be placed in microtubes containing a similar volume of a 2% NaF solution (i.e., if you are collecting 25 &mu;L of blood, place it in 25 &mu;L of 2% NaF).</li>
 <li>When data collection is finished, separate plasma from erythrocytes by spinning the samples for 5 minutes at 2000 g at 4&deg;C.</li>
 <li>Plasma lactate can be determined through a variety of methods2,3. In our lab, we use the electrochemical method with the aid of an automatized lactate analyser (Yellow Springs 1500 Sport, Ohio).</li>
</ol>
5. Calculations
<ol>
 <li>Calculate the net energy generated by the aerobic metabolism by subtracting rest oxygen consumption from exercise oxygen consumption. Oxygen consumption at rest is obtained by multiplying the average of the last 30 seconds of baseline oxygen consumption by the total exercise duration time. Then, calculate the area under the curve of exercise oxygen consumption by using the trapezoidal method. Finally, subtract the resting oxygen consumption from exercise oxygen consumption.</li>
 <li>The contribution of the anaerobic alactic metabolism (i.e., the ATP-CP pathway) can be considered as the fast component of excess post-exercise oxygen consumption4-6, as illustrated in Figure 1. Calculate the energy produced by the alactic system by fitting the kinetics of post-exercise oxygen consumption to a bi- or a monoexponential curve. This can be done with the aid of mathematics' software (e.g. Microcal Origin version 7.0). Choose by the mono- or bi-exponential curve based on the model that best fits to your data set (i.e., the lowest residue). Then, use the terms provided by the fitted equation (Equation 1) to calculate alactic contribution according to Equation 2. 
 <img src="/files/ftp_upload/3413/3413fig1.jpg" alt="Fiugre 1" /> 
 Figure 1. Schematic illustration of a typical oxygen consumption curve obtained at rest, during, and after exercise. 
 Equation 1: 
 <img src="/files/ftp_upload/3413/3413eq1.jpg" alt="Equation 1" /> 
 Equation 2: 
 <img src="/files/ftp_upload/3413/3413eq2.jpg" alt="Equation 2" /> 
 where VO2(t) is oxygen uptake at time t, VO2baseline is oxygen uptake at baseline, A is the amplitude, &delta; is the time delay, &tau; is a time constant, and 1 and 2 denote the fast and slow components, respectively.</li>
 <li>To calculate the contribution of the lactic anaerobic system, it is assumed that 1 mM of lactate above the resting values corresponds to 3 mL of oxygen consumed per kilogram of body mass7. Thus, calculate delta peak plasma lactate (i.e., peak plasma lactate minus resting plasma lactate) and multiply it by 3 and by the athlete&#x2019;s body mass. The obtained value of oxygen in mL is then converted to L and to energy (kJ), assuming that each 1 L of O2 is equal to 20.92 kJ.</li>
 <li>Finally, the result obtained by each energy system is summed so you have the total energy expenditure during the activity and the relative contribution of each of system can be calculated.</li>
</ol>
6. Representative Results
Figure 2 depicts a representative curve of oxygen consumption at rest, during exercise and after exercise. In the example used here, athletes performed three different judo techniques (o-uchi-gari, harai-goshi and seoi-nage) for five minutes (one throw every 15 s)8. This is a typical response to intermittent exercise. After the calculations, we obtained the final results on the contribution of the energy systems during judo exercises (Table 1).
Additional representative results are displayed in Table 2. In this example, indoor rock climbers of different competitive levels (i.e., recreational vs. elite) were assessed during a low-difficulty climb route. Individual results for one elite athlete and one recreational athlete are shown (Table 2).
<table border="1">
 <tbody>
 <tr>
 <td rowspan="2">&nbsp;</td>
 <td colspan="2">Seoi-nague</td>
 <td colspan="2">Harai-goshi</td>
 <td colspan="2">O-uchi-gari</td>
 </tr>
 <tr>
 <td>kJ</td>
 <td>%</td>
 <td>kJ</td>
 <td>%</td>
 <td>kJ</td>
 <td>%</td>
 </tr>
 <tr>
 <td>Anaerobic alactic</td>
 <td>46 &plusmn; 20</td>
 <td>16.3 &plusmn; 2.8</td>
 <td>43 &plusmn; 21</td>
 <td>16.1 &plusmn; 2.7</td>
 <td>36 &plusmn; 22</td>
 <td>14.6 &plusmn; 2.8</td>
 </tr>
 <tr>
 <td>Aerobic</td>
 <td>223 &plusmn; 66</td>
 <td>82.2 &plusmn; 2.9</td>
 <td>211 &plusmn; 66</td>
 <td>82.3 &plusmn; 3.8</td>
 <td>196 &plusmn; 74</td>
 <td>84.0 &plusmn; 3.8</td>
 </tr>
 <tr>
 <td>Anaerobic lactic</td>
 <td>4 &plusmn; 2</td>
 <td>1.5 &plusmn; 0.7</td>
 <td>5 &plusmn; 5</td>
 <td>1.6 &plusmn; 1.4</td>
 <td>4 &plusmn; 4</td>
 <td>1.5 &plusmn; 1.1</td>
 </tr>
 <tr>
 <td>Total</td>
 <td>273 &plusmn; 86</td>
 <td> - </td>
 <td>259 &plusmn; 91</td>
 <td> - </td>
 <td>237 &plusmn; 99</td>
 <td> - </td>
 </tr>
 <tr>
 <td>Total (kJ/min)</td>
 <td>51.9 &plusmn; 8.7</td>
 <td> - </td>
 <td>49.4 &plusmn; 8.9</td>
 <td> - </td>
 <td>45.3 &plusmn; 19.6</td>
 <td> - </td>
 </tr>
 </tbody>
</table>
Table 1. Representative results of total energy expenditure and the contribution of the energy systems during three different judo exercises.
<table border="1">
 <tbody>
 <tr>
 <td>Competitive Level</td>
 <td>Aerobic (%)</td>
 <td>Anaerobic Lactic (%)</td>
 <td>Anaerobic Alactic (%)</td>
 <td>Total (kJ)</td>
 <td>Total (kJ/s)</td>
 </tr>
 <tr>
 <td>Elite</td>
 <td>40</td>
 <td>8</td>
 <td>52</td>
 <td>70.4</td>
 <td>1.00</td>
 </tr>
 <tr>
 <td>Recreational</td>
 <td>40</td>
 <td>15</td>
 <td>45</td>
 <td>96.1</td>
 <td>1.15</td>
 </tr>
 </tbody>
</table>
Table 2. Representative individual data of total energy expenditure and the contribution of the energy systems during a low-difficulty climb route.
<img src="/files/ftp_upload/3413/3413fig2.jpg" alt="Figure 2" /> 
Figure 2. Representative results obtained during a 5-minute judo exercise.

<ol>
	<li>Franchini, E., Del Vecchio, F. B., Matsushigue, K. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Physiological+profiles+of+elite+judo+athletes.">Physiological profiles of elite judo athletes.</a> Sports Med. 41, 147-166 (2011).</li><li>Bergmeyer, H. U., Bergmeyer, J., Grassl, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Methods of enzymatic analysis. , (1983).</li><li>Passonneau, J. V., Lowry, O. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Enzymatic+Analysis.">Enzymatic Analysis.</a> A Practical Guide. , (1993).</li><li>Beneke, R., Pollmann, C., Bleif, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=How+anaerobic+is+the+Wingate+Anaerobic+Test+for+humans.">How anaerobic is the Wingate Anaerobic Test for humans.</a> Eur. J. Appl. Physiol. 87, 388-392 (2002).</li><li>Beneke, R., Beyer, T., Jachner, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Energetics+of+karate+kumite.">Energetics of karate kumite.</a> Eur. J. Appl. Physiol. 92, 518-523 (2004).</li><li>Bertuzzi, R. C. D., Franchini, E., Kokubun, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Energy+system+contributions+in+indoor+rock+climbing.">Energy system contributions in indoor rock climbing.</a> Eur. J. Appl. Physiol. 101, 293-300 (2007).</li><li>di Prampero, P. E., Ferretti, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+energetics+of+anaerobic+muscle+metabolism:+a+reappraisal+of+older+and+recent+concepts.">The energetics of anaerobic muscle metabolism: a reappraisal of older and recent concepts.</a> Respir. Physiol. 118, 103-115 (1999).</li><li>Franchini, E., Bertuzzi, R. C. D., Degaki, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Energy+Expenditure+in+Different+Judo+Throwing+Techniques.+Proceedings+of+first+joint+international+pre-Olympic+conference+of+sports+science+and+sports+engineering,+vol+II.">Energy Expenditure in Different Judo Throwing Techniques. Proceedings of first joint international pre-Olympic conference of sports science and sports engineering, vol II.</a> Bio-mechanics and sports engineering. , 55-60 (2008).</li><li>Calmet, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Developing+ecological+research+in+judo.">Developing ecological research in judo.</a> Percept. Mot. Skills. 105, 646-648 (2007).</li><li>Mello, F. D., Bertuzzi, R. C., Grangeiro, P. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Energy+systems+contributions+in+2,000+m+race+simulation:+a+comparison+among+rowing+ergometers+and+water.">Energy systems contributions in 2,000 m race simulation: a comparison among rowing ergometers and water.</a> Eur. J. Appl. Physiol. 105, 615-619 (2009).</li><li>Bertuzzi, R. C., Franchini, E., Ugrinowitsch, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Predicting+MAOD+using+only+a+supramaximal+exhaustive+test.">Predicting MAOD using only a supramaximal exhaustive test.</a> Int. J. Sports Med. 31, 477-481 (2010).</li></ol>

The authors declare they have no conflict of interest regarding this study.

The method we have shown hare can be used for both continuous and intermittent exercise. The great advantage of the method is that it can be adapted to exercises and sports that are difficult to be mimicked in controlled laboratory settings. Furthermore, this is the only available method capable of distinguishing the contribution of three different energy systems. Thus, the method allows the study of sports with great similarity to real situations, providing desirable ecological validity to the study9. For example, a recent study by Mello et al.10 showed that the glycolytic contribution in a 2000 m on water rowing race is of only 7%, which means that rowing performance is mainly dependent on the aerobic metabolism. Similarly, a study by Beneke et al.4 confirmed that the main source of energy during one of the most used anaerobic tests, the Wingate Anaerobic Test, is the anaerobic metabolism (20% aerobic; 30% alactic and 50% glycolytic). Recent studies by our group have also characterized the energy contributions of indoor climbing6 and judo8, as reported in this example. Indeed, the knowledge on the energetic contribution is critical for the development of ergogenic strategies, training organization or even for validating a test.
This method has some limitations. First, the cost of the equipment is somewhat high, and specialized trained personnel are required. Second, although most sports can be mimicked with this technique, it is not any type of exercise that can be studied using the portable gas analyzer. Finally, as plasma lactate does not exactly represent the total lactate produced by skeletal muscle during activity, the results obtained by this procedure can be considered as an estimative of the metabolic demand during exercise, rather than a precise quantification of the energetic contribution. Nonetheless, this is the only validated method available11 capable of distinguishing the contribution of the three different energy systems.

<table border="1">
	<tbody>
		<tr>
			<th>Name of the reagent</th>
			<th>Company</th>
			<th>Comments</th>
		</tr>
		<tr>
			<td>YSI 1500 Sport</td>
			<td>Yellow Springs</td>
			<td>This equipment allows a quick and easy plasma lactate determination</td>
		</tr>
		<tr>
			<td>K4 b2</td>
			<td>Cosmed</td>
			<td>This equipment is essential for measuring oxygen consumption throughout the exercise</td>
		</tr>
		<tr>
			<td>Software Microcal 6.0</td>
			<td>Origin</td>
			<td>This software (or any other with similar capabilities) will be useful for the calculations</td>
		</tr>
	</tbody>
</table>

determining the contribution of the energy systems during exercise

One of the most important aspects of the metabolic demand is the relative contribution of the energy systems to the total energy required for a given physical activity. Although some sports are relatively easy to be reproduced in a laboratory (e.g., running and cycling), a number of sports are much more difficult to be reproduced and studied in controlled situations. This method presents how to assess the differential contribution of the energy systems in sports that are difficult to mimic in controlled laboratory conditions. The concepts shown here can be adapted to virtually any sport.
The following physiologic variables will be needed: rest oxygen consumption, exercise oxygen consumption, post-exercise oxygen consumption, rest plasma lactate concentration and post-exercise plasma peak lactate. To calculate the contribution of the aerobic metabolism, you will need the oxygen consumption at rest and during the exercise. By using the trapezoidal method, calculate the area under the curve of oxygen consumption during exercise, subtracting the area corresponding to the rest oxygen consumption. To calculate the contribution of the alactic anaerobic metabolism, the post-exercise oxygen consumption curve has to be adjusted to a mono or a bi-exponential model (chosen by the one that best fits). Then, use the terms of the fitted equation to calculate anaerobic alactic metabolism, as follows: ATP-CP metabolism = A1 (mL . s-1) x t1 (s). Finally, to calculate the contribution of the lactic anaerobic system, multiply peak plasma lactate by 3 and by the athlete&#x2019;s body mass (the result in mL is then converted to L and into kJ).
The method can be used for both continuous and intermittent exercise. This is a very interesting approach as it can be adapted to exercises and sports that are difficult to be mimicked in controlled environments. Also, this is the only available method capable of distinguishing the contribution of three different energy systems. Thus, the method allows the study of sports with great similarity to real situations, providing desirable ecological validity to the study.

Watch this Scientific Journal Video about Determining the Contribution of the Energy Systems During Exercise at JoVE.com

Determining the Contribution of the Energy Systems During Exercise

This protocol allows researchers focused on exercise and sports sciences to determine the relative contribution of three different energy systems to the total energy expenditure during a large variety of exercises.

One of the most important aspects of the metabolic demand is the relative contribution of the energy systems to the total energy required for a given ...

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Dysfunctional skeletal muscle mitochondria play a role in altered metabolism observed with aging, obesity and Type II diabetes. Mitochondrial ...

Environmental Screening of Aeromonas hydrophila, Mycobacterium spp., and Pseudocapillaria tomentosa in Zebrafish Systems

Health monitoring systems are developed and used in zebrafish research facilities because pathogens of Danio rerio such as Aeromonas hydrophila, Mycobacterium spp., and Pseudocapillaria tomentosa have the potential to impair animal welfare and research. The fish are typically analyzed post mortem to detect microbes. The use of sentinels is a suggested way to improve the sensitivity of the surveillance and to reduce the number of animals to sample. The setting of a pre-filtration sentinel tank out of a recirculating system is described. The technique is developed to prevent water pollution and to represent the fish population by a careful selection of age, gender, and strains. In order to use the minimum number of animals, techniques to screen the environment are also detailed. Polymerase Chain Reaction (PCR) on surface sump swabs is used to significantly improve the detection of some prevalent and pathogenic mycobacterial species such as Mycobacterium fortuitum, Mycobacterium haemophilum, and Mycobacterium chelonae. Another environmental method consists of processing the sludge at the bottom of a holding tank or sump to look for P. tomentosa eggs. This is a cheap and fast technique that can be applied in quarantine where a breeding device is submerged into the holding tank of imported animals. Finally, PCR is applied to the sludge sample and A. hydrophila is detected at the sump&#39;s bottom and surface. Generally, these environmental screening techniques applied to these specific pathogens have led to an increased sensitivity compared to the testing of pre-filtration sentinels.

Environmental Screening of Aeromonas hydrophila, Mycobacterium spp., and Pseudocapillaria tomentosa in Zebrafish Systems

This protocol describes the use of sump swabs and sludge analysis of zebrafish systems, which leads to increased detection compared to the sole use of sentinels to detect pathogens such as Aeromonas hydrophila, Mycobacterium spp., and Pseudocapillaria tomentosa. A system to monitor P. tomentosa eggs in quarantine is also proposed.

Health monitoring systems are developed and used in zebrafish research facilities because pathogens of Danio rerio such as Aeromonas hydrophila, ...

Establishment of an Extracellular Acidic pH Culture System

Conditions of the tumor microenvironment, such as hypoxia or nutrient starvation, play critical roles in cancer progression and malignancy. However, the role of acidic extracellular pH in tumor aggressiveness and its underlying mechanism has not been extensively studied compared to hypoxic or nutrient starvation conditions. In addition, a well-defined culture method to mimic the acidic extracellular tumor microenvironment has not been fully reported.
Here we present a simple in vitro culture method to maintain acidic extracellular pH using reduced bicarbonate and increased lactate or HCl concentrations in the culture medium. The medium pH was sustained for at least 24 h and gradually decreased by 72 h following culture of PANC-1 and AsPC-1 pancreatic cancer cells. Three distinct acidic media conditions in this study highly upregulated pH-responsive genes such as MSMO1, INSIG1, and IDI1 compared to hypoxia or nutrient starvation. The upregulation of these genes can be used as a marker of acidic pH. These simple techniques are beneficial to elucidate underlying mechanisms of tumor malignancy under acidic tumor microenvironment. Therefore, our extracellular acidic pH culture system enables discovery of cellular acidic pH responses not only in cancer cells but also in primary cells, such as renal tubular cells, in relation to the other acidic disorders including, diabetic ketoacidosis, lactic acidosis, renal tubular acidosis, and respiratory acidosis.

The acidic tumor microenvironment plays critical roles in tumor progression. To assess the effects of acidic extracellular pH on cancer cells in vitro, we established simple acidic culture systems.

Conditions of the tumor microenvironment, such as hypoxia or nutrient starvation, play critical roles in cancer progression and malignancy. However, the ...

A Labor-saving and Repeatable Touch-force Signaling Mutant Screen Protocol for the Study of Thigmomorphogenesis of a Model Plant Arabidopsis thaliana

Plants responding to both intracellular and extracellular mechanical stimulations (or force signals) and develop special morphological changes, a called thigmomorphogenesis. In past decades, several signaling components have been identified and reported for being involved in the mechanotransduction (e.g., calcium ion binding proteins and jasmonic acid biosynthesis enzymes). However, the relatively slow pace of research in the study of force signaling or thigmomorphogenesis is largely attributed to two reasons: the requirement for laborious human hand-manipulated touch induction of thigmomorphogenesis and the force strength errors associated with people&#8217;s hand-touch. To enhance the efficiency of external force loading on a plant organism, an automatic touch-force loading machine was built. This robotic arm-driven hair brush touches provide a labor-saving and easily repeatable touch-force simulation, unlimited rounds of touch repetition and adjustable touch strength. This hair touch-force loading machine can be used for both large scale screening of touch-force signaling mutants and the phenomics study of plant thigmomorphogenesis. In addition, touch materials such as human hair, can be replaced with other natural materials like animal hair, silk threads and cotton fibers. The automated moving arms on the machine may be equipped with water sprinkling nozzles and air blowers to mimic the natural forces of rain drops and wind, respectively. By using this automatic hair touch-force loading machine in combination with the hand-performed cotton swab touching, we have investigated the touch response of two force signaling mutants, MAP KINASE KINASE 1 (MKK1) and MKK2 plants. The phenomes of the touch-force loaded wild type plants and two mutants were evaluated statistically. They have exhibited significant differences in touch response.

A Labor-saving and Repeatable Touch-force Signaling Mutant Screen Protocol for the Study of Thigmomorphogenesis of a Model Plant Arabidopsis thaliana

A gentle touch-force loading machine is built from human hair brushes, robotic arms and a controller. The hair brushes are driven by robotic arms installed on the machine and move periodically to apply touch-force on plants. The strength of machine-driven hair touches is comparable to that of manually applied touches.

Plants responding to both intracellular and extracellular mechanical stimulations (or force signals) and develop special morphological changes, a called ...