# Transformation of banana peels into banana peel wood

Astrid de Laporte, Bernard Haye, Jérôme Charliac, Guillaume P Laurent, Patrick Le Griel, Pierre Carol, Ilan Raphael, Gervaise Mosser

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## To cite this version:

Astrid de Laporte, Bernard Haye, Jérôme Charliac, Guillaume P Laurent, Patrick Le Griel, et al.. Transformation of banana peels into banana peel wood. 2025. hal-05349065

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# Transformation of banana peels into banana peel wood

Astrid De Laporteª, Bernard Hayeª, Jérôme Charliacª, Guillaume P. Laurentª, Patrick Le Grielª<fnref n="1" />,
Pierre Carolᵇ, Ilan Raphaelᶜ & Gervaise Mosserª*.

ª Sorbonne Université, CNRS, Laboratoire de Chimie de la Matière Condensée de Paris, 75005, Paris, France.

ᵇ IEES - Institut d'écologie et des sciences de l'environnement de Paris, France.

ᶜ independent researcher, Clermont-Ferrand, France.

*Corresponding author: gervaise.mosser@sorbonne-universite.fr

astrid.paelinck@sorbonne-universite.fr

bernard.haye@sorbonne-universite.fr

jerome.charliac@sorbonne-universite.fr

guillaume.laurent@sorbonne-universite.fr

patricklegriel@gmail.com

pierre.carol@sorbonne-universite.fr

llan.raphael@gmail.com

## ABSTRACT

This study aims to establish a sustainable valorization pathway for banana peel, an abundant agro-industrial residue, by converting it into a high-performance, wood-like biocomposite material. Using a simple and scalable processing method and with water as the only additive, banana peels were transformed into a dense, brown, and hydrophobic biocomposite. The material was evaluated for its mechanical properties, water repellency, density, and compatibility with conventional woodworking techniques. The biocomposite exhibits a Young's modulus ranging from 0.8 to 3 GPa, and densities up to 1.2 g/cm³—values that are respectively comparable to those of light commercial woods and similar to that of ebony and a contact angle between 75° and 102°. It can be carved, shaped, and assembled with standard tools. Considering that banana production generates over 50 million tons of peel annually, this approach could yield up to 2 million tons of biocomposite each year. This work highlights the potential of agricultural waste as a renewable resource for producing wood alternatives. It supports the circular bioeconomy and offers a sustainable substitute for certain endangered tropical wood species.

Keywords: Banana peel valorization; Agro-industrial waste; Wood-like material; Sustainable materials; Bio-waste recycling, Endangered wood species

## Highlights:

<footnote n="1">¹ Presently retired</footnote>
* Scalable upcycling of banana peels into value-added materials

* Valorizing banana peels by transforming them into a dense, wood-like biocomposite

* Producing a workable material that can be sawn, carved, glued, or screwed like wood

* Achieving a bio-based material with mechanical properties and densities respectively close to balsa and ebony

* A sustainable alternative to endangered woods
# 1. INTRODUCTION

The global yearly production of bananas exceeds 135 million tons, making it one of the most widely consumed fruits worldwide. This popularity stems from its high energy and vitamin content, as well as the ease and variety of its preparation. Between 1961 and 2022, banana production rose spectacularly from 25,000 to 135 million tons, due to the selection and breeding of disease-tolerant cultivars and improved irrigation systems (Mohandas and Ravishankar, 2016). In many producing countries, beyond domestic consumption, banana cultivation and exportation play a major economic role [Web.Ref 1]. The global increase in population and growing awareness of the banana's nutritional benefits have further stimulated demand and intensified production efforts.

An average banana weighs about 125 g, with the peel representing 30 to 40% of the total weight (Pathak et al., 2017). This results in approximately 40 to 60 million tons of banana peel (BP) waste generated annually. BP is currently considered a form of green waste, but recent studies have explored its valorization (Hikal et al., 2022; Balda et al., 2021; Mirabella et al., 2014). Banana peels contain valuable constituents such as proteins (up to 9%), fibers (up to 30%), starch (up to 15%), and sugars (up to 30%), depending on the cultivar and ripeness. Their main structural components include cellulose, hemicellulose, and pectin (Pathak et al., 2017). BP contain chemicals and biomolecules such as ethanol, polyphenols, vitamins, antioxidants and antimicrobials. They also contain minerals such as calcium, phosphorus, iron, magnesium and sodium (Hikal et al., 2022). Thanks to these properties, BP has been studied as a feedstock for various animal species and as a source of functional components (Alkarkhi et al., 2011; Bakar et al., 2018; Schieber et al., 2012). Some studies highlight its poly-nutrient profile and medicinal potential (Asif et al., 2024). In material science, BP-derived bioplastics have been investigated (Zhang et al., 2024), and their physicochemical properties have been compared to other fruit peels (Pathak et al., 2017). Additionally, banana peel powder has shown potential as an adsorbent for cationic species, contributing to research on water desalting (Djilani et al., 2019) and decontamination—crucial issues in modern societies. For example, strontium(II) (Mahindrakar and Rathod, 2018), chromium (Elsaid, 2023), and other pollutants can be removed via BP adsorption, especially after specific activation treatments (Tolkou et al., 2024). BP can also be processed into biochar, combined with inorganic nanoparticles (Ma et al., 2017; Rong et al., 2019) or integrated with organic biomolecules to enhance functionality (Djilani et al., 2019). Despite these diverse valorization pathways, no reports have addressed the transformation of banana peels into a dense material comparable to natural wood. In this study, we present a novel approach to create such a wood-like material directly from whole banana peels—without converting them into powder or segregating by ripeness or variety. We refer to this new material as Banana Peel Wood (BPW).

Our method draws on techniques from earth-based construction and the food processing industry. It was progressively developed through 48 independent experimental trials, using simple and scalable steps. Here, we report detailed results from the final 12 experiments, for which we recorded comprehensive characterizations at each transformation stage.

This work aims to demonstrate the potential of banana peels as a feedstock for a bio-based, wood-like material, opening new perspectives in the circular economy, material substitution, and the sustainable management of agri-food waste.

# 2. MATERIALS AND METHODS
**2.1. Preparation**

**2.1.1. BP preparations**

BP were processed with the protocols reported hereby: a) directly used after collect and/or stored at 4°C, named FRESH, b) directly immersed in water for one day to three weeks, named HYDRATED, c) -20°C frozen until use, named FROZEN.

**2.1.2. BP blending**

The peels were blended in presence of water (300 ml per 1000 g of Hydrated BP, up to 400 ml per 1000g for Fresh and Frozen BP) in a Bartscher PRO XTRA 2.5L blender for two minutes at minimal speed (13000 rpm), and then one minute at the eighth graduation (~17600 rpm) to achieve fluid grinding.

**2.1.3. BP paste preparation**

The grind was put in 190 mm diameter and 90 mm height glass beaker and set in a vacuum chamber (J.P. SELECTA, 4000474) operated at room temperature to extract air bubbles until no longer bubbly. For some grinds, eruption started and increased over time. For those, air extraction was stopped before stability, to protect the equipment, and the grind was used. The grind was poured into 250 ml Nalgene bottles and centrifuged at 6000g for 30 min at 20 °C using a JA-14 rotor in an AVENTI J-26XP Beckman centrifuge. Pellets were collected, homogenized and finally compacted into a ball shape, wrapped in parafilm, put in a hermetic plastic bag with as little air as possible and stored at 4°C until use. Supernatant was discarded or used as plant fertilizer.

**2.1.4. BP Wood (BPW) preparation**

The paste was set and compressed by hand into different molds of varying size, geometry and material. Alternatively, the banana paste thickness was slowly lowered between two plastic sheets using a silicone rolling pin. The molded or rolled paste was then set in between metallic grids (mesh 900 µm) and put into a MEMMERT oven (UF75) controlled in temperature, humidity and ventilation to induce further dehydration and cooking. We classically used the following sequence: 5 days dehydration (25 °C, 100 % vent, 100 % opened air flap) and then increased temperature by 10 °C every 24 hours from 55 °C to 85 °C. Finally, BPWs were cut, sanded and polished for further characterization.

**2.2. Characterizations**

**2.2.1. Grind characterization**

Back extrusion was used to characterize the complex grind (Fig. SI_1). An INSTRON (34SC-05) compression bench equipped with a 50 N probe was used with a cylindrical compression platen (3.7 mm thickness, 25.0 mm diameter). Around 20 ml of the grind to be tested were poured into 27.65 mm inner diameter 68.2 mm height cylindrical transparent plastic tubes and fixed on the plateau of the vertical bench. The down speed of the probe was set at 0.5 mm/s (with a commutation preload of 0.10 N at a rate of 0.20 mm/min). The tests were carried out up to 80 % strain. Force and displacement were recorded on four different samples for each grind. Stress versus strain curves were analyzed as follows: the area under curve, which presents some relation to the energy necessary to press the probe into the grind was calculated on Microsoft Excel (version 16.78.3) table using the equation [1] :
$$ [1] \quad Area = \sum_{Min\%}^{79\%} \{ [A(n + 1) - A(n)] * [B(n + 1) + B(n)]/2 \} $$

Where A(n) are the values of strain and B(n) the values of stress recorded on the mechanical bench.

The number of peaks were calculated on Microsoft Excel (version 16.78.3) by first determining changes of tendencies in the set of stress values (increase/decrease) and allocating a value C of -1 or +1 in a third data column using the equation [2]:

$$ [2] \quad C(n) = SI(B(n) > B(n + 1); 1; -1) $$

Finally, the number of peaks was calculated with the equation [3] :

$$ [3] \quad Nbr.Peaks = \sum_{Min\%}^{79\%} ABS[D(n) - D(n + 1)] $$

At least four sampling per grind were analyzed, giving at least 4 values of each (area under curve and number of peaks) for each experiment. Those were used for statistical ANOVA exploitation and Pearson correlation matrices. Family means were used for the Radar plot.

### 2.2.2. Paste characterization

#### 2.2.2.1 DropBall test

Pastes were characterized using the DropBall test (Fig. SI_2A). Handmade balls of banana paste (4 to 6 per paste, 100 mg each) were placed in a reversed funnel connected to a vacuum pump and set at a 1-meter height from a transparent plexiglass plate put on ground and with respect to the ball and funnel contact. Each ball was gently sucked in the funnel and immediately released to allow its drop onto the transparent plexiglass. A caliper (Mitutoyo Digimatic Caliper) enabled measuring initial diameter of the ball before drop (Øl), the larger diameter after impact (Øl) and, after reversing the transparent plexiglass, the diameter of the paste at surface impact (Øs) (Fig. SI_2). (Øl-Øs) was used as characteristic of the paste. At least four paste balls per experiments were dropped and analyzed, giving at least 4 values by experiments that were used for statistical ANOVA exploitation and Pearson correlation matrices. The family means were used for the Radar plot. The cohesiveness of the paste, which corresponds to cracks seen on the dropped ball was difficult to quantify and was not assessed (Fig. SI_3).

#### 2.2.2.1 Fibers quantity

The quantity of fibers within the paste was evaluated on images of hand-broken pieces of paste. Images were eventually rotated, cropped and analyzed using Fiji (ImageJ2, version 2.14.0/1.54f). Cropped images were converted to 8-bits mode, and a threshold was set to clearly highlight as many as possible of the fibers visible on the untreated photos, while avoiding excessive overexposure of non-fibril texture. The percentage area of the highlighted fibers was then determined using the “Analyze Particles” function. Percentages from both faces of each fractured paste ball were summed. At least three different fractures were analyzed for each experiment, giving at least 3 values by experiment that were used for statistical ANOVA exploitation and Pearson correlation matrices. The family means were used for the Radar plot.
2.2.2.2 Fibers longest length

The longest fibers in the pastes were determined as follows: three sampling of 5 g each were taken from different part of the main paste ball and slowly disintegrated in water to extract all visible fibers. Photos were taken of the 15 to 30 longest fibers alongside a ruler for scale. The images were analyzed using Fiji by setting the scale based on the ruller. The segmented line tool was used to trace each fiber and measure its length. All measurements were recorded in a Microsoft Excel table (version 16.78.3). For statistical analysis, only the 15 longest fibers were considered in the ANOVA, and the 4 largest for the Pearson correlation matrices. Family means were used for the Radar plot.

2.2.3. Banana Peel Wood (BPW) characterization

2.2.3.1. Flexion Mechanical test

Flexion moduli: BPW were sawn into 8 mm wide, 40-100 mm long, and 3-4 mm thickness thin lamellae. An electro-mechanical INSTRON machine (5965) equipped with a 1 kN or a 50 N probe was used at a speed of 1 mm/min with a commutation preload of 1 mN at a rate of 0.50 mm/min. The span of the bending support was either 30 mm or 60 mm, depending on the length of the specimen lamellae. We extracted Young Modulus, maximum stress, energy and strain up to maximal stress. At least four different lamellae were tested for each sample, giving 4 values per experiment that were used for statistical ANOVA exploitation and Pearson correlation matrices. The family means were used for the Radar plot. Note that experiments were done in non-controlled atmospheric conditions with air moisture varying from 23 % to 63 % humidity. This has an impact on the values.

2.2.3.2. Hydrophilicity

Static contact angle test was performed using a Kruss DSA30 instrument with distilled water (DW) as liquid. Specifically, a drop of DW (~2 µL) was dropped onto the scaffold, and 5 images were taken 3 s after DW deposition. Right and left angles were measured from photos by the software from which means were calculated. Three different areas were tested for each sample, giving 15 values per sample that were used for statistical ANOVA exploitation and the four highest values for correlation matrices. The family means were used for the Radar plot.

2.2.3.3. Solid-state Nuclear Magnetic Resonance (NMR)

Wood samples were sanded with sandpaper 120. Around 250 mg of powder was packed in a 7 mm diameter rotor inserted in a broadband probe and spun at the magic angle (MAS) at 5 kHz. The spectrometer was a Bruker Avance III 7 T spectrometer, corresponding to a 13C Larmor frequency of 75 MHz. Three kinds of experiments were undertaken. DEPTH experiment allows probe background suppression(Robin Bendall and Gordon, 1983). A 30° pulse angle followed by two 180° pulses and a 10 s relaxation delay were used. 1H-13C Cross-Polarization (CP) was acquired with a 1 ms contact time. For 1H-13C refocused Insensitive Nuclei Enhanced by Polarization Transfer (INEPT), a scalar coupling constant J = 140 Hz was chosen. The evolution and refocalisation periods were 1/2J and 1/3J, respectively, to have CH, CH2, and CH3 peaks positive. For both CP and INEPT, a 1 s relaxation delay was used. All spectra were acquired with 1H SPINAL64 decoupling and processed with a line broadening of 30 Hz. Chemical shifts were calibrated using absolute referencing to the 1H frequency of TMS at 1 % in CDCl3 at 25°C, with the 13C adamantane peak difference as a secondary reference(Hoffman, 2022).
#### 2.2.3.4. Workability

The workability of the woods was tested through sawing, sculpturing, gluing and use in electrical guitar.

### 2.3. End of life

Black eye pea (*Vigna unguiculata*) seeds were germinated in plastic Pétri dishes on wet soft paper towel at 23°C, in 100% humidity with 16 hours of daylight. Once germination had occurred, the seedlings were put on top of small pots containing a mix of 100 g of potting soil (peat) and 300 g of sand. Plants were grown for 15 days at 26°C with 16 hours of daylight. Altogether 24 plants were cultivated, 16 of which were grown in presence of BPWs fragments coming from 4 different experiments (4 plants each), and 8 plants were grown as controls. Leaf chlorophyll content was evaluated using an optic clamp device (CCM 300 Opti-science, Hudson, NH, USA). After one week, chlorophyll content of the first emerging leaves (embryonic leaves) was measured. After two weeks, the chlorophyll content of the first (TF1) and second (TF2) trifoliate leaves were measured. After cultivation, plants were dehydrated for a week in a MEMMERT ventilated oven (UF75) operating 25°, 100 % vent, 100 % opened air flap. Dry weight of aerial and root parts were measured using a Sartorius (CP225D) precision scale.

### 2.4. Graphics

All graphics (statistics, correlation and radar) were generated via R (R 4.4.2 GUI 1.81 Sur ARM Build (8462) for MacOS X) using codes generated using ChatGPT.

Individual values as well as means with their standard deviations are represented on the violin graphs. For each of the three families (BP pretreatments), four independent experiments were done, and for each one of them, 4 to 15 independent measurements were made. Exception was for a few samples analysis of area covered by fibrils for which we only had three values. In those cases, the fourth value was the mean of the three others.

Differences between the families were analyzed using ANOVA followed by a Tukey post-hoc test (for 95% family-wise confidence level p < 0.05 was considered significant (0 ‘***’; 0.001 ‘**’; 0.01 ‘*’; < ‘ns’)). Pearson correlations were calculated using only four measurements per sample of each of the four experiments per family. The radar plot was generated with the means of each family, each axis being independent from the others.

## 3. RESULTS

### 3.1. Choosing an adequate process

Altogether, 48 independent experiments were run to set up and optimize the complete process and implement systematic characterizations at each stage of the transformation. Preliminary experiments highlighted both the potential of BP for wood making and the necessity of controlling the material behavior throughout the process, specifically to avoid irregular surface shrinkage creating surface splitting, or internal shrinkage resulting in hollow and/or porous wood. Cavitation forces occurring during blending caused entrapment of air bubbles, which revealed to be the primary factor leading to internal porosity and hollowness in the final bioproduct. A vacuum degassing step was thus introduced prior centrifugation to eliminate those air bubbles. We also observed bending and torsion of the material. To address these phenomena, we developed various molds: 3D printed plastic, aluminum or plaster molds and grids of different mesh. Furthermore, process parameters such as dehydration and
thermal treatment rates were varied along with paste thicknesses and applied compression weights from 1 to 6 kg. In parallel, dedicated characterizations protocols were introduced at each step of the transformation of the BP to identify stagewise predictive markers of the final product quality. The back idea was to eventually be able adjust the formulation as early as possible to enhance the properties of the resulting BPW.

The final process with the characterization workflow is schemed in Figure 1. The data presented in this article are derived from the final twelve experiments, for which standardized characterization datasets were collected (SI Table 1-4).

<figure><img src="image_3.png" /><figcaption>Figure 1: The different steps of the process finally adopted to produce wood out of banana peels (BPW). The effect of three pretreatments of the peels were analyzed to identify eventual differences of wood properties. The stages at which analysis were made are indicated in blue.</figcaption></figure>

## 3.2. Analyzing grinds and pastes

The protocol starts with three alternative pretreatments of the BP denominated: *Fresh*, that were immediately used after consumption of the fruit or after storage at 4°C, *Hydrated* that were stored immersed into tap water from one day to three weeks and *Frozen* that were stored at -20°C before processing. The pretreated peels were blended to obtain the grind from which air bubbles were subsequently extracted under vacuum. Generally Frozen grinds were found easier to degas while Fresh grinds were more difficult. We did not observe specific rule for Hydrated grinds. Four sampling of the grind were then checked for their physical properties by back-extrusion (Fig. SI_1). As schemed in Figure SI_1, profiles of the back-extrusion tests were analyzed for the quantity of events and the energy necessary to back-extrude the grind. We found that Fresh and Hydrated grinds were not significantly different from one another but were significantly lower than Frozen ones in terms of energy (Fig. 2A). Reversely Frozen and Hydrated samples revealed non-significantly different one from another but were significantly lower than Fresh one in terms of events.

Once water excess eliminated by centrifugation, the paste was evaluated. The dropball test did not reveal any significative differences between the three families (Fig. 2B).

## 3.3. Analyzing Banana Peel Wood

### 3.3.1. *Mechanical testing*

Dehydration and cooking transformed paste into BPW that were characterized for their mechanical resistance in flexion, hydrophobicity and density (Fig. 2C). Fresh BPW presents the
lowest flexible parameters although statistical analysis shows no significant differences with
Frozen ones. Their mean values are respectively around 1.4 GPa and 1.9 GPa for Young moduli,
17 and 24 MPa for maximum stress and 169 and 198 kJ.m⁻³ for the energy at maximum stress.
On the contrary, Hydrated samples show significantly higher flexion Young moduli (mean value
of 2.3 GPa), maximum stress (mean value of 32 MPa) and highest flexion energy (mean value
of 280 kJ.m⁻³).

3.3.2. *Hydrophobicity*

Contact angle measurements showed that the highest angles were found for Hydrated woods (Fig. 2C). The means are significantly different from one family to another with the highest at 90° for Hydrated, then 81° and 77° respectively for Fresh and Frozen samples. That makes Hydrated samples potentially the most hydrophobic.

<figure><img src="image_4.png" /></figure>

Figure 2: Statistical analysis at different stages of the process. A: Liquid grind characterized by back-extrusion, B: Paste characterized by ball dropping and fiber content and fiber length, C: Banana Peel Wood characterized by mechanical testing in flexion and contact angle. Differences between the families were analyzed using ANOVA followed by Tukey post-hoc test (for 95% family-wise confidence level p < 0.05 was considered significant (0 ‘***’; 0.001 ‘**’; 0.01 ‘*’; < ‘ns’). We analyzed the samples at each step of the process to see eventual differences. Except for the test of the ball drop we always found significant differences for at least two families of samples. The pairing varies depending on the analysis.

3.3.3. *Densities*

We checked mean densities of BPW of highest and lowest Young modulus for each family. For Fresh samples, we found the same density of 1.1 g.cm⁻³ both for low and high Young moduli (0.95 and 2.21 GPa) indicating zero difference in density for a difference of 1.26 GPa. For Hydrated and Frozen samples, we find respectively differences in density of 0.2 and 0.3 g.cm⁻³ for differences of 1.64 and 1.98 GPa between low and high Young moduli<fnref n="2" />.

<footnote n="2">² Samples of lowest values of Young moduli 1.4 and 0.9 GPa for 1.0 and 0.8 g.cm⁻³, and samples of highest values of Young moduli 3.03 and 2.92 GPa for 1.2 and 1.1 g.cm⁻³ respectively for Hydrated and Frozen samples.</footnote>
### 3.3.4. Solid-state NMR

sNMR measurements were used to probe the different phases present in the samples (Fig. 3A). To check the synthesis variability, CP and INEPT experiments, were performed on three different Hydrated samples (Fig. 3B-D). Spectra show locally some significant changes (peaks at 73 and 99 ppm with CP, or the peak at 30 ppm with INEPT). We also checked for any substantial differences between BPW of the three different pretreatments. Unfortunately, the differences were in the same range as for the Hydrated family. Similarly, we could not see any significant differences between the BPW having the highest and lowest flexion Young modulus.

<figure><img src="image_5.png" /><figcaption>Figure 3: 13C solid-state NMR spectra. A: Comparison of INEPT, CP, and DEPTH of a typical BPW; 3600 scans and 35 kHz 1H decoupling. B: CP spectra of three hydrated BPW; 2048 scans, 70 kHz 1H decoupling, normalization on the peak at 105 ppm. C-D: alkene and alkane regions of INEPT spectra of three hydrated BPW; 1024 scans, 70 kHz 1H decoupling, normalization on the peak at 32 ppm. Stars denote spinning side bands.</figcaption></figure>

### 3.3.5. Analytical analysis

The correlation matrices show that correlations are the most informative for Fresh samples. We can see that back-extrusion energy will predict rather well the negative impact on Young modulus; the higher the energy will be the lower the mechanical properties in flexion. We see that we could tentatively predict the hydrophobic behavior when evaluating the quantity of the fiber present in the paste. We also see that the longest the fibers will be, the most likely the wood will be resistant to flexion. For Hydrated samples, back-extrusion energy gives us some good indication on the length of fiber present and some pretty good indication on its hydrophobicity but only poor indication on the resistance of the final wood to be obtained. For Frozen samples, we see that back extrusion energy will give us good indication on the impact on the mechanical properties of the wood and no indication on its hydrophobicity. If we consider the results obtained with the data from the three families put together, we see no predictive indication.
<figure><img src="image_6.png" /><figcaption>Figure 4: Pearson correlation Matrices. The highest correlations between the different analysis within each family is the highest for the Fresh banana peels. Right from the beginning of the process, right after the blending, we can predict how the BPW would behave. If we can make some tentative guess for Frozen samples, it is not possible for Hydrated. As seen all together, it is pretty hard to determine the issues.</figcaption></figure>

Differences between the three families are synthetized in the radar plot constructed with families mean values (Fig. 5). It shows that means of Fresh samples have the worst flexion mechanical resistance while it has the highest number of peaks. Frozen means show highest back extrusion energy together with highest content of fibers and longest fibers with intermediate mechanical properties. Finally, Hydrated samples present highest density, mechanical values and best hydrophobicity while lowest values for all fibers length and quantity.

<figure><img src="image_7.png" /><figcaption>Figure 5: Radar plot the three families. Fresh, Hydrated and Frozen represented respectively in green, orange and red. The axes are independent from one another with means by family obtained for each type of characterization.</figcaption></figure>
## 3.4. End of Life

In order to assess the end of life of BPW in compost, we tested the impact of small fragments of BPW on the development of plants using black-eye-pea (*Vigna unguiculata*) plants as model (Zegaoui et al., 2017). We observed that plant aerial growth and development were affected when BPW was added to the soil (Fig. 6). Both total aerial dry weight and leaf chlorophyll content were significantly lower. Although roots grew the closest to the BPW in the soil, roots weight was not significantly different in control and BPW samples, suggesting that roots are not affected. When seeds were germinated directly on humidified BPWs, plants developed but remained yellowish and rickety. However, if put back on proper soil they rapidly regained a normal green color (Fig. SI_4) and pursue proper development.

<figure><img src="image_8.png" /></figure>

Figure 6: Test for end of life of Banana Peel Wood in the environment. We observe an impact of the BPW on *Vigna unguiculata* plant development. The presence of BPW slows down aerial plant growth, with lower chlorophyll accumulation. Left, germinated *Vigna unguiculata* seedlings before planting on soil. Center, *Vigna unguiculata* plants at one day (J1), seven days (J7) and fifteen days (J15) of growth on soil. Rows A, B, D, E, F are plants cultivated with six BPW cubes. Row C, are control plants. Right, top, dry weight of aerial and root parts of plants, bottom, chlorophyll content of embryonic leaves (E) and trifoliated leaves (TF). Significant difference between control plants and plants grown on PBW were analyzed using ANOVA followed by Tukey post-hoc test (for 95% family-wise confidence level p < 0.05 was considered significant (0 ‘***’; 0.001 ‘**’; 0.01 ‘*’; < ‘ns’)).

## 3.5. Workability

The present BPW, has the density of Eboni wood with the mechanical properties of balsa. They can be sawn, screwed, glued and sculptured (Fig. 7). BPW can be used as decorative wood, marquetry, or to make useful objects. Currently, T. Bouhier is manufacturing equipment for an electric guitar machining the BPW to test its strength and handling in this context.
<figure><img src="image_9.png" /><figcaption>Figure 7: Workability of the BPW. Proof of concept in A: Sculpture (8 cm diameter, made by G.M.), B: Gluing, C: Sawing down to 647 µm thickness, D: Use in electrical guitar equipment top and side views of: (top) 2 potentiometer, buttons (bottom) humbucker pickup contour (Fabrication & Photos: T. Bouhier).</figcaption></figure>

4. DISCUSSION

The removal of air bubbles subsequently to grinding revealed critical for the quality of the final wood. The efficiency of their elimination depended strongly on the grind. Highly viscous and cohesive grinds, for which air removal up to stabilization was not achieved, led to more or less split, porous or hollow wood, suggesting migration and fusion of air bubbles during the drying and cooking process, with exclusion of the biocomponents. Back-extrusion showed that Fresh grind samples presented generally more fibers and/or air-bubbles than Frozen ones and needed a lower energy to back extrude, while Hydrated samples needed similar energy than Fresh ones while having smaller number of residual fibers and/or air-bubbles. The key role of fibers in modulating the final mechanical qualities of the BPW, could thus be clearly identified.

The fact that the dropball test did not reveal any significative differences between the three families was surprising since the grind already showed differences. Besides, Frozen samples generally revealed a lot of fibers and long one compared to Fresh and even more to Hydrated ones. We therefore expected to see a significative difference in dropball results at least between Frozen and the two other types. Apparently, another factor such as the degree of residual water within the paste and/or cohesiveness forces hindered the effect of fibers. An alternative test exist in which the material to be tested is set as a flat thick surface at the bottom and a defined solid ball is dropped on (Chalernwong and Srikunwong, 2014; Hernandez et al., 2015). This test, probably more acurate, required more matter, and was not selected here.

Mechanical test flexion reveals that the strongest wood is obtained with Hydrated BP. It is rather counterintuitive as one would expect a reinforcing effect of fibers. The mean densities,
which are slightly higher for Hydrated (1.15 ± 0.12 g.cm⁻³) than for Fresh and Frozen (1.05 ± 0.04 g.cm⁻³), are similar to woods such as Asian Eboni (SI_Table 5). Contact angle measurements showed that Hydrated samples are potentially the most hydrophobic. Solid state NMR revealed similar variations within each family than in between or between highest and lowest flexion Young modulus. Those variations reveal the differences in mobility and composition within each BPW (SI_sNMR). This indicates alternatively or concomitantly that: 1) NMR was not adequate to reveal potential differences, 2) the degree of ripeness of the peels before pretreatment is predominant, or 3) the cooking neutralized chemical differences. Pearson correlation matrices were calculated to identify potential steps in the process that could predict the final properties of BPW. If so, parameters or formulation could be modified to improve the wood before reaching the final step of dehydration and cooking.

The results presented above show that BPW can vary in quality depending on the pretreatment applied to the peels before processing. However, as seen on the violin graphs the variation of the values within each family can be significant, the pretreatment is therefore not the only source of differences. Variations could be due to the degree of ripeness of peels before pretreatments, to the origin of the banana, whether they were organic or not, or because for instance, we used varying ratios of peels immersed from one day to three weeks. Nevertheless, it remains that the BPW obtained by peels immersed into water generally present higher mechanical properties and higher hydrophobicity than the two other families. The correlation matrices reveal that the most predictable behavior is when working with Fresh peels but they generally give lower quality BPW.

The result of the end-of-life test suggest that either BPW retains an essential nutriment from the water or soil, preventing an adequate plant growth or it exudes a mild toxic component. This result contrast with that obtain with BP fertilizer (Hariyono et al., 2021; Soleh et al., 2023). We can conclude that nutriments favorable for plant development present in the BP are either lost or no more assimilable by the plants due to the fabrication process of BPW. Noticeably, BP biochar obtained by thermal pyrolysis had positive effects on soil properties and lowered greenhouse gases emissions compared to BP (Sial et al., 2019). BPW could thus be an intermediate status of BP before thermal pyrolysis into biochar for use as soil amendment or catalysts (Soares Dias et al., 2024).

We compared our BPW to different natural woods, which characteristics are published on the CIRAD-Tropix 7 (SI_Table 5) (Gérard et al., 2011). We see that mean data of BPW woods compare best to balsa wood. However, considering best values, we see that we can achieve maximal stress values near that of Scots pine, while Young modulus would be higher. We point out here that the values given in CIRAD Tropix 7 were monitored at 12% humidity while our experimental conditions varied from 22% to 28% for the twelve last experiments considered here. It was shown that increased humidity decreased the mechanical properties of wood (Gerhards, n.d.; Tiemann, 1906). Using data given in Tieman H.D [1906] (Tiemann, 1906), we have made the graphic in Figure SI_5. We see for instance that for Eastern Spruce the relation between bending stress at rupture and moisture is defined by the equation:

$$[4] \qquad y = 227x^{-0.502}$$

When applied to spruce, this relation gives values of 65, 48 and 43 MPa respectively for 12, 23 and 28% moisture. Thus to calculate the theoretical value of the Young modulus at different moisture percentage, we can use the relation:
$$[5] \qquad y_1 = y_2 \left[ \frac{x_1}{x_2} \right]^{-0.502}$$

We find that Young modulus drops from 11.9 GPa at 12% moisture to 8.8 and 5.7 GPa respectively at 22 and 28% moisture. Even though, BPW presents lower Young moduli than natural wood except for “soft” wood such as balsa. Comparing our results with those found in the review of Jakob et al. 2022 (Jakob et al., 2022) we see values of elastic modulus from 2 to 7 times higher for natural woods than for BPW. This indicates that the micro-structure of the BPW is less favorable to mechanical resistance but not dramatically. It might be possible to gain in mechanical resistance by applying similar densifying processes as those described in (Jakob et al., 2022). Noticeably, densities of BPW are comparable to that of Asian Black Eboni (1.1 g.cm⁻³, SI_Table 5).

Considering the energy cost, with the equipment used here, we consumed around 550 kWh for transforming 5000 g of banana peels into 300 g of BPW. The drying step is the most demanding in energy and we do not know whether we could have processed more paste in a same run. This is equivalent to 2.7 kg CO₂ for electricity produced by nuclear energy (270 kg CO₂ for fossil). Outdoors drying and solar cooking or equipment similar to that of glass production line could be advantageous alternatives.

To conclude we can say that at the present stage of development, using only pure banana peels, with no special rules in their collect and without any additional compounds or post treatments, we can reach BPW that have high density (up to 1.2 g.cm⁻³), flexion Young modulus and maximal stress of 3 GPa and 45 MPa respectively. The yield of the BPW manufacturing process at a laboratory scale is around one tenth of the initial weight in banana peels used.

Finally, and most interestingly, BPW was obtained solely using banana peels and water. This indicates that all the chemical elements necessary to create this biocomposite were already present into the peels. No additional chemicals were needed. Besides, from an industrial perspective, it can be assumed that banana peels would arrive in large batches at a relatively uniform stage of maturity, facilitating the homogeneity and reproducibility of the resulting woods.

## 5. CONCLUSION

Among others, trees like ebony or balsa are endangered due to different factors, the common one being the increasing demand. For ebony, this is combined with the slow growth of the trees, the limited systematic reforestation, which would ensure the preservation of species, and illegal harvesting (Deblauwe, 2021; Jahanbanifard et al., 2019). For balsa, it is on the contrary its fast growth and the difficulty of harvesting it. The demand for ebony is mainly emanating from luxury, musical instrument manufacturing and high-end craftsmanship. Balsa, due to its lightness, is mainly used in aeronautics, wind energy, shipbuilding, model making, and sound insulation. The world market of those woods represents around 150 of million of dollars per year for balsa [web.ref. 3] and, officially, a few tens of million dollars for ebony [web.ref. 4 & 5].

Our new wood-like material looks and feels like wood. It combines properties of ebony by its high density (1.2 g.cm⁻³) with that of balsa by its mechanical resistance to flexion (Young modulus ranging from 0.93 to 3.03 GPa). Besides, this new material presents a good
hydrophobicity with a contact angle ranging from 75° to 102°. Moreover, we have shown that BPW can be sawn, carved and assembled. For all those reasons, we believe that BPW could fit wonderfully into the timber market even at its present state of development. None the least BPW is produced via a clean process without any additional chemicals but water.

**CRediT authorship contribution statement**

**Astrid de Laporte**: investigation, writing – review & editing, **Bernard Haye**: codes development, review & editing, **Jérôme Charliac**: investigation, experimental set up, review & editing, **Guillaume Laurent**: investigation, Formal analysis, writing – review & editing, **Patrick Le Griel**: experimental set up, review, **Pierre Carol**: formal analysis, writing – review & editing, **Ilan Raphael**: formal analysis, writing – review & editing, **Gervaise Mosser**: conceptualization, resources, methodology, investigation, codes development, formal analysis, validation, visualization, writing original draft, review & editing.

**Declaration of competing interest**

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

**Data availability**

Data will be made available on request.

**Acknowledgements**

For the collection of banana peels, the authors thank: members of the Laboratoire de Chimie de la Matière Condensée de Paris (LCMCP), the children N. & W. Abdul-Aribi from the Charles Somasco School (Creil, France), the CROUS of Sorbonne-University, F. & D. Baras-Lesaffre and the GM family members. The authors thank P. Dumont and S. Agys from the greenhouse of Sorbonne-Université for taking care of plantation. GM thanks T. Bouhier for discussions and suggestions concerning the development of molds as well as for testing the handling of the BPW in the context of instrumental manufacturing. The authors thank the Group MATBIO of LCMCP for financial support.

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