How Does the Sound of Stream Water Affect the Growth of Cucumis sativus Plants Under Drought?
1Marcellino Melika, 2Shi Qi Huang, 3Theodora Boumakis
Francis Lewis High School, Queens, New York, USA

Abstract – This experiment investigated how the sound of stream water affects the growth of Cucumis sativus plants under drought stress. Plants can recognize vibrations (sounds). Additionally, plants limit their growth when they receive suboptimal amounts of water to preserve resources. The purpose of this study was to determine how the sound of stream water affects plants under drought stress, in order to determine if it will affect their growth. Four groups of 10 plants were germinated, with 3 experimental groups treated with the sound of stream water for different amounts of time (0.5, 2, or 3 hrs; control group had 0 hr). Once plants were germinated, drought stress began in all groups, but each group’s respective amount of treatment stayed the same (0, 0.5, 2, 3 hrs). During all stages of the experiment, the plants were watered during the period of sound treatment to develop a correlation. At the end of the experiment, it was found that growth significantly increased corresponding to increasing treatment time. Group 4 (3 hr) had the largest increase in growth compared to control, while group 2 (0.5 hr) had the least improvement over control. Subsequently, the sound of stream water treatment beneficially impacts plant growth, directly correlated to exposure.
Keywords: drought, suboptimal, vibrations, recognition, sound, bioacoustics

Introduction

Kirby Cucumber

Kirby Cucumbers, (or Cucumis sativus. L.), also known as pickling cucumbers, are a part of the Cucurbitaceae family and are a very important part to cuisine because of their prevalence in pickling and food. They are common fruits that originated from India and grow 6 inches or less. In addition, they are known for their thin, bumpy skin and are easy to digest by animals [1]. They also require a large amount of water to maintain proper soil moisture to grow since they are very sensitive to drought stress [2, 3]. Due to these factors, Kirby Cucumbers were determined to be an ideal candidate for testing the effects of the sound of stream water during drought conditions, to observe the possible positive effects it would have on the plant's overall plant growth.

Growing Crops in Areas Afflicted by Drought

People across the world are forced to grow crops to prevent hunger and starvation. These plants naturally receive water from common sources like lakes or streams but are unable to properly grow and survive due to the lack of water in dry areas heavily afflicted by drought. Droughts account for only 15% of natural disasters around the world but have caused approximately 650,000 deaths in the last 50 years, as well as losses of around USD 124 billion in the last 20 years alone [4]. The problem of growing crops in areas without a sufficient supply of water is a critical issue that requires attention to solve.

The Sound of Stream Water

The sound of stream water was chosen because of its prevalence, importance in nature, and frequency ranging from 500-900 Hz, providing ideal conditions [5]. The sound was played at 72.5 dB (decibels) in order to ensure that its effects would not be affected due to the background noise in the room that could mitigate or prevent the effect if played at a lower volume.

The sound of water (and in general noise/music) was thoroughly tested to see its effects on plants throughout several experiments. Several studies discovered that plants can “hear” sounds, are able to feel the vibrations from the sound waves and recognize different sounds. Furthermore, one study found that plants grow towards or away and have improved or mitigated growth when they are exposed to favorable or unfavorable sounds, respectively. After varying types of music were played (Vedic chants, rock music, western classical music, and Indian classical music) at the same volume, Rosa chinensis plants experienced improved growth from Vedic chants and Indian classical music, while rock music mitigated plant growth. Additionally, the plants grew towards the speakers in the case of Vedic chants and Indian classical music, but away from the speakers in the case of rock music [6]. In addition, another study found that plants use their roots to locate sounds, and subsequently, sources of water. Seedlings were placed in a maze containing a source of water and found that 8/10 of the seedlings were successful in locating the direction of the water source, and another group was equally successful despite only having access to the live sound of the water inside a pipe [7]. Similarly, one review discussed how, in general, it was found that plants can perceive and differentiate between different noises, from the sound of water to the sound of herbivore insects chewing [8]. When plants were pre-treated with the sounds/vibrations of caterpillar eating, they had increased levels of anthocyanin and glucosinolate (which help boost their defense systems) when they were subsequently fed to caterpillars compared to untreated plants [9].

Finally, one gap observed in the research on sound and its biological effects on plants mentioned above is the investigation into the effect of the sound of stream water on plant growth under drought conditions. When plants undergo drought, they limit their growth in order to conserve water to survive. This experiment tested if the sound of water would prevent the plants from limiting their growth as much in response to drought, believing a water source to be available, to see if it will improve plant growth and yield because of the plant's ability to recognize the sound of water. As a result, this can benefit life by helping farmers in dry areas increase crop production and yield so that they will be able to feed more people and increase profits. It can also add knowledge to previous studies by possibly identifying an effective and practical treatment to mitigate drought’s effect on yield and growth.

Materials and Methods

Growth of Cucumber Seedlings

10 pots each were placed onto 4 trays (separated by group) and a 2 cm deep hole was carefully made in the middle of the soil, then 1 seed was planted into each pot. The hole was then covered with the soil, and this process was repeated for all pots. Each pot was labeled according to “HMB-(group number in roman numerals)-(pot number in numbers)”, like HMB-III-7. The seeds were planted and watered with 15 mL 4 days a week until they were all germinated, (which was determined to be the presence of a shoot above the soil) while being treated with the sound of water for their respective times (0, 0.5, 2, or 3 hrs. depending on group). Plants were then watered a total of 4 days a week, coinciding with the sound of water 4 days a week. Once the seeds germinated, drought treatment began a week after the day the sound of water started. Each group was watered with 15 mL of water two days a week. The sound of stream water was played for groups 2, 3, and 4 for 0.5, 2, and 3 hours respectively, and all groups were watered within this time. The speaker was approximately 16 cm away from all groups, and when a group reached their required time of treatment, they were moved into the quiet opposite corner of the room with the control group to ensure that no sound could be intercepted until it was time for their sound treatment again.

Preparation of the Sound of Stream Water

A calm stream water recording (https://www.youtube.com/watch?v=UJZxtO9XNno) was playing on a speaker connected to a computer, set at an average volume of 72.5 dB and frequency ranging from 500-900 Hz. The video was selected because of its invariability (constant flow of noise) as well as its long run length of 12 hours.

Measurement

Several variables were measured throughout all trials. Firstly, the average shoot length was recorded. This was done by measuring the length of all 40 plants (10 in each group). The length was considered as the distance from the bottom of the shoot outside of the soil to the highest point of the shoot. Then, the collected data were averaged by each group to obtain a mean value for each group. Additionally, the average leaf length was collected. All 40 plants’ leaves were measured. Leaf length was considered as the distance from the tip of the leaf to the base of the leaf connected to the stem. Only leaves that were above 2 cm were considered in order to not drag down data due to measuring newly formed leaves. These lengths were added and then divided by the total number of measured leaves of the plant, which was then averaged by each group to obtain a mean value for each group. Continuing, the average amount of leaves was observed. This was done by counting the number of leaves of all plants, and then averaging by each group to obtain a mean value for each group (in this case, newly formed leaves were also counted). Finally, average dry/wet mass as well as average water retention was collected. At the end of the experiment, the plants were removed from the soil and weighed on a precise scale, then averaged among each group to receive a mean value for each group (wet mass). Then, the plants were baked at 87℃ for 18 hours until all water was removed, and re-measured and averaged by each group to receive another mean value for each group (dry mass). Finally, the mean values for wet and dry mass were subtracted from each other to determine the average plant water retention for each group. All data was collected and calculated 4 days a week (except for average wet/dry mass and average plant water retention), excluding a few days where data could not be collected (like for example weekends or holidays).
Data Analysis

Several variables were analyzed throughout the experiment’s trials, beginning with the overall shoot and leaf length. This was done by averaging results by group to determine the average lengths for each group. Furthermore, the average amount of leaves for each plant were calculated, alongside the average leaf width. This was done by averaging data by group to determine the average number of leaves per plant in each group. Average leaf width was determined by adding up all the collected data and then dividing by the total number of leaves in the group. Finally, the average final wet and dry mass was calculated. The average final wet mass was calculated by averaging data among each group to determine the final average wet mass. The final average dry mass was found by averaging data among each group, to determine the average final dry mass per plant in each group. In addition to these variables, online softwares were also used throughout data collection. One of these softwares was a Google Sheets spreadsheet to store all the data and track/discover trends. This will allow all the information and data to be more organized, accessible, and readily available. Furthermore, the patterns and trends were also transferred into graphs to help signify the relationships between pieces of data. These specific graphs were splatter-plot line graphs to show growth over time, like for shoot length, leaf length, and leaf amount. Additionally, bar graphs were used to show singular pieces of data (like dry/wet mass and water retention). Lastly, the ANOVA (analysis of variation) software system, as well as Tukey HSD (honest significant difference), will also be used to help keep track of the variance between variables and quantities (https://www.socscistatistics.com/tests/anova/default2.aspx). The Tukey HSD test expounds the ANOVA values between multiple group values, and the ANOVA software is important in order to determine and calculate the variance between data points.

Results

Draft Melika 548370994-image1.png

Figure 1. Average shoot/leaf length over time-Trial 1. Each line or bar represents a different amount of treatment of the sound of stream water. There were 10 plants per group. Error bars represent the standard deviation. Generally, increased treatment led to increased growth, even through the later phases of drought stress where withering occurs. ANOVA followed by Tukey HSD was conducted to determine the significant difference *p<0.05, **p<0.01 compared with the control group.

Draft Melika 548370994-image2.png

Figure 2. Average shoot/leaf length over time-Trial 2. Each line or bar represents a different amount of treatment of the sound of stream water. There were 10 plants per group. Error bars represent the standard deviation. Generally, increased treatment led to increased growth (except in the case of the 2 hr group), even through the later phases of drought stress where withering occurs. ANOVA followed by Tukey HSD was conducted to determine the significant difference *p<0.05, **p<0.01 compared with the control group.

Draft Melika 548370994-image3.png

Figure 3. Comparison of final plant conditions among groups-Trial 2. Each line or bar represents a different amount of treatment of the sound of stream water. There were 10 plants per group. Error bars represent the standard deviation. Generally, increased treatment led to increased growth (except in the case of the 2 hr group), even through the later phases of drought stress where withering occurs. ANOVA followed by Tukey HSD was conducted to determine the significant difference *p<0.05, **p<0.01 compared with the control group.

Figure 1 demonstrates that the control group had significantly less average shoot length compared to 0.5, 2, and 3-hour treatments, implying that the exposure to the sound of stream water improved growth, compared to without it. In figure 2, there was a significant improvement in the average leaf length in the group with the 3-hour treatment, compared to all the other groups. Additionally, the group with the most amount of treatment (3 hours) exhibited the most overall growth compared to all other control and experimental groups, showing that extended exposure further improves growth, compared to little exposure. It was also shown in figures 3 and 4 that group 3 had the highest overall wet and dry mass in comparison to the rest of the groups. Some observations made throughout the experiment was that group 1 and 2 had a slow germination rate and the plants in group 3 and 4 were growing at an increasing rate. Group 1 shows signs of wilting at an early stage of growth while groups 2, 3, and 4 all had strong stems that hold the plants up.

Discussions and Conclusions

The hypothesis created for the experiment was that cucumber plants treated with the sound of stream water would exhibit signs of improved shoot length, leaf width, and amount, as well as dry and wet mass. Based on the data that was collected throughout 2 trials, the sound of stream water had beneficial effects on growth, which was (in general) magnified by greater amounts of exposure. The sound of stream water improved shoot length at all tested exposures (0.5, 2, and 3 hours) (Figures 1A, 1B, 2A, and 2B), which supports the findings from past studies that concluded that the sound of water improved the growth of plants though not under drought stress [6]. For the shoot growth shown in the first trial, the experimental groups all had significantly more growth compared to the control, with the 3-hour treatment having the most and the 2-hour group having less than the 0.5-hour group in the early stages of the experiment while in trial 2 such significant results were only exhibited in 0.5 and 3-hour treatments, with 0.5-hour treatment having significantly better results than 3-hour treatment, and the group exposed with 2-hour treatment only having a slight improvement (1.1 cm) compared to control at the end of the experiment, overall implying that any level of exposure to treatment, even with differing circumstances, can significantly improve shoot growth.

The average leaf width in Trial 1 followed similar patterns to the shoot growth, with all experimental groups having significantly improved leaf width, this time with the group exposed to 2-hour treatment having the most improvement compared to the control, even though the 3-hour treatment group was leading for the majority of the experiment (Figures 1C and 1D), while again for Trial 2 the 3-hour group had massively improved growth, and the 2-hour group was only slightly better than control and worse than the 0.5-hour group (Figures 2C and 2D) Additionally, throughout all trials signs of withering leaves were only exhibited near the end of the experiment in the experimental groups, while in the control groups signs of withering were observed early within the commencement of drought stress, implying that the sound of stream water treatment also delayed the effects of withering.

When looking at the average amount of leaves each plant had, the 3-hour group had over double the average amount of leaves in the control group, while the 2 and 0.5-hour groups had similar amounts of leaves (Figure 3A). Overall, the results shown through Trial 2 imply that the sound of stream water can also further accelerate the growth of cucumber plants, allowing them to grow significantly more leaves on average compared to groups without sound treatment.

In addition to growth measurements, the average final wet and dry mass was also recorded. In Trial 2, the 3-hour group had very significantly more mass in both wet and dry forms compared to all other groups, and while the 2-hour group only showed a slight increase in wet and dry mass compared to the control, the 0.5-hour group also had significantly more wet and dry mass when compared to control (Figures 3B and 3D).

The experiment had a few sources of error. There were a few days when the experimenters were unable to rotate or measure the plants to ensure proper sunlight distribution between the cucumber plants of all groups. In such cases, some plants might have had a more favorable position to grow in compared to others as they received slightly more sunlight. Constant visits would be performed for future trials to rotate and measure all plants on time. Another error was that some plants could not be counted towards the data collected due to errors that occurred during the setup of the experiment, causing lowered sample sizes for some groups. For the rest of the groups, the data also only had 10 seeds in each group per trial, causing our data to be susceptible to errors. To discourage this from happening again, all future trials should include larger sample sizes to get more reliable results and data.

In the future, this experiment could be altered to determine the extent of sound recognition in plants. This would consist of determining the effect of other natural sounds that naturally affect plants on plant growth and stress levels, like the sound of thunder to see if the plants prepare to receive as much water as possible or for more vulnerable plants to try to protect themselves from heavy rain. Additionally, this experiment could be altered to see if plants could be able to correlate any sound (naturally or not naturally heard by plants) to incoming stress and preparation, like thunder. In addition, these experiments could be performed on other plants not belonging to the Cucurbitaceae family to provide more authentic and widespread conclusions about the effects of the sound of stream water on plants under drought stress.

Acknowledgements

Thank you to Dr. D. Marmor​, Mrs. N. Jaipershad​, Dr. L. Wang, Ms. J. Zhu, Ms. A. Khemlani, Dr. J. Cohen​, Dr. X. Lin​, Mr. Z. Liang, Ms. R. DePietro, and the FLHS Science Department for funding.

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Volume 6, 2024
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