Microwave Assisted Natural Dye Extraction from Amaltas ( Cassia fistula ) for Cotton Dyeing: Process Optimization Using Modern Statistical and Machine Learning Algorithms

Abstract

Background

The current study explored the use of amaltas (Cassia fistula) extract, which contains tannin as a natural dye, for dyeing cotton fabric.

Method

Microwave assisted extraction (MAE) was employed to extract the colorant in a suitable medium. The dyeing factors were optimized using innovative response surface design (RSD). To investigate the predictive ability of the models, artificial neural network (ANN) in addition to response surface methodology (RSM) was used.

Results

After selecting the levels of dyeing variables sustainable, eco-salts (including Al, Fe, and tartaric acid) and bio-extracts (including pomegranate and madder) were considered to develop the desired shades. Color fast shades for dyeing of irradiated cotton were obtained at optimum points when employed before and after mordanting with eco-salts and bio-extracts. The colorfastness of the selected mordanted fabric was assessed according to ISO standards and good to excellent fastness ratings were observed.

Conclusion

The proposed RSD helped to obtain the efficient experimental data. Furthermore, ANN model has proved to enhance the prediction capacity of the model comparatively. Validity of the optimization procedures and prediction capability of the models were assessed by using mean square error and coefficient of determination (R²).

Keywords

design of experiment optimization green extraction amaltas microwave assisted extraction sustainability

Introduction

Dyes and pigments are now a days important part of our lives because everywhere the colorful objects we see are glorifying the global village.^1,2 They are commonly used in industries such as textiles, fashion, cosmetics, and printing.³ The pollutant from industrial wastewater has increased researchers attention because their effluents disturb water quality parameters, soil fertility, the environment, and community health.⁴ Due to these harmful effects, although different methods have been developed to reduce the effect of pollutants before releasing to the environment, such as biological processes and chemical oxidation yet, their lethal effect is continuously destroying global beauty.⁵ Biodegradable, have low toxicity and do not generate any allergic reactions are the key potentials of natural dyes.^6-8

Natural dyes are sourced from organic materials, including plants, animals, and minerals.⁹ Investigating new plant species can significantly expand the range of natural dyes available for textile coloration globally.^10,11 To ensure sustainability and cost-effectiveness, it is crucial to develop efficient extraction methods that are eco-friendly, energy-efficient, rapid, and yield high-quality colorants.^12,13 One such modern technique, microwave-assisted extraction (MAE), offers superior color yield in larger quantities while minimizing time, energy, and solvent use.¹⁴ For getting colorant shades, chemical mordants such as Cr ⁺ ³, Cu ⁺ ³, Fe ⁺ ², Al ⁺ ³, Co ⁺ ² etc, are used, but some of these salts (Cr ⁺ ³, Co ⁺ ³, N_i²⁺) are carcinogenic and need replacement with a green anchor.^15,16 These products are made from sustainable and renewable bio-resources and have little effect on the environment.¹⁷ These colors are utilized in cosmetics, pharmaceuticals, solar cells, food, flavors, and other products.^18,19 Additionally, neither carcinogenic nor hazardous compounds are present in the effluents of these dyes.²⁰ These colors are less harmful, polluting, and poisonous.^21,22

There are numerous ways to separate bio matter (colorant) from plants, but the microwave aided strategy (MAS) for extracting the natural colors from plants is more efficient.^23,24 Microwave treatment (MT) is the most effective contemporary technique for heating to get a useful yield from unprocessed plant powder.^25,26 In many cases, mordants produce various colors, improve color fastness, and even impart an affinity to fabric for the dye.^27,28 Due to the non-toxicity and biocompatibility, as well as their provision of color fastness and suitable antibacterial characteristics, bio-mordants have been suggested for the use in the natural dyeing of fabrics.²⁹ Organic mordants are used to enhance shade quality by overdyeing of fabrics.^30,31 These mordants include pomegranate and madder. There are many plants that yield bio-colorants but Amaltas (Cassia fistula) is the versatile plant.³² Its bark, pods, flowers, roots, leaves also have potential to produce color. It is traditionally used to treat skin conditions, as well as laxative, anti-fungal, anti-inflammatory, anti-bacterial, and anti-diabetic effects.^33,34 Anthraquinone which imparts a reddish-brown hue to the matrix, is the primary colorant utilized in Cassia fistula ripped pods.³⁵

Another important aspect is the statistical optimization of dyeing parameters. Researchers have successfully utilized both of these models to enhance optimization outcomes by selecting the most optimal input factors for improving the response yield ie (K/S).³⁶ In laboratory experiments with small data sets and additional hidden nodes, a larger number of data points are necessary to accurately estimate the model parameters. Failure to account for this can lead to over fitting, causing the model to memorize data rather than generalize results.

Following considerations make the current study novel:

Extract colorant from Amaltas using sustainable medium at selected radiation time.

Observe significance of selected dyeing parameters using RSM and ANN.

Structural simplification to avoid over-fitting in ANN.

Employ carefully chemical and bio-anchors to develop color fast shades.

Asses fastness ratings as per ISO standardization.

Study the whole dyeing process as per sustainable developed goal (SDG) i-e. Sustainable practice.

Methodology

Material Used

Dried reddish-brown pods of Amaltas (Cassia fistula) as anthraquinone dye has been selected, cleaned, and crushed finely into powder form. Red sumac, Anar (Punica granatum) and Rubia (Rubia cordifolia) to serve as bio-mordants have been purchased, cleaned, and processed for additional testing. For extraction, dyeing, and mordanting, inorganic mordants such as Aluminum salt, Fe-salt, and tartaric acid were employed.

Extraction and Irradiation Process

In extraction process, on boiling 4g of finely crude powder with 100 mL of aqueous medium, the crude stud was filtered and filtrate was used for coloring cotton. The same process was carried out in acidic medium. These extracts were subjected to MW treatment at high power for up to 2–10 min in a laboratory-based household oven. By maintaining an extract to fabric ratio of 25:1, Extracts before and after MW-treatment were used to dye cotton 80°C for 45 min.

Statistical Modeling and Machine Learning Techniques for Dyeing Parameters Assessment

In response surface methodology (RSM) quadratic models are most commonly being employed to investigate the relationship between response and predictors. For the optimization of dyeing parameters a new design structure was employed, motivated by the concept provided.by Gilmour and Ahmad.^37,38 The structure of the proposed design (½ S₄^IV + ½ S₃^III + 8 S₀) is presented in Table 1. This design has provided optimum values of the color parameters, considering limited number of design trials by using the given experimental ranges. To enhance the model prediction capacity, artificial neural network (ANN) model structured as; four inputs, three hidden and one output node was considered. The same description has been given in our previous work done by Aftab.³⁹ The activation function used is the Rectified Linear Unit (ReLU), while the optimizer employed is Stochastic Gradient Descent (SGD). The weights were initialized using a normal distribution.

Table 1.

Subsets of Proposed Design (½ S₄^IV + ½ S₃^III + 8 S₀).

½ S₄^IV				½ (S₃)^III				8S₀
−1	−1	−1	−1	−1	−1	1	0	0	0	0	0
1	−1	−1	1	1	−1	−1	0	0	0	0	0
−1	1	−1	1	−1	1	−1	0	0	0	0	0
1	1	−1	−1	1	1	1	0	0	0	0	0
−1	−1	1	1	−1	−1	0	1	0	0	0	0
1	−1	1	−1	1	−1	0	−1	0	0	0	0
−1	1	1	−1	−1	1	0	−1	0	0	0	0
1	1	1	1	1	1	0	1	0	0	0	0
				−1	0	−1	1
				1	0	−1	−1
				−1	0	1	−1
				1	0	1	1
				0	−1	−1	1
				0	1	−1	−1
				0	−1	1	−1
				0	1	1	1

Colorfast Shade Formation Using Additives

The extracts from red sumac (Rhus typhina), anar (Punica granatum), and rubia (Rubia cordifolia) were prepared for use as bio-mordants. After boiling, each mordant was filtered, and the resulting filtrate was utilized in the subsequent extraction process. The cellulosic fabric, with was pre- and post-mordanted using 0.5–2.5 g/100 mL of aluminum salt, iron salt, and tartaric acid (TAA), at 70 °C for 45 min, using a 25:1 ratio of bio-mordant to fabric.

Evaluation of Dyed Fabric

For color analysis, using the Kubelka Munk equation calculated in the colorimeter spectrometer and shade affecting variables have been examined. The dyed samples were exposed to the ISO standard for light fastness, wash fastness and rubbing fastness before and after chemical and eco- mordanting at given conditions.

Results and Discussion

Selection of Dyeing and Radiation Level

The application of MW radiation after isolation results in a high yield in terms of K/S, which is a promising facilitation of the interaction between the powder and the medium. Using an acidic medium, the results indicate that while the yield was poor prior to radiation, it improved following radiation till 10 min (Figure 1a and b). Using a relatively simple water extract (NRE), the colour amount onto simple non treated fabric (NRF) was low, but after treatment (RF) up till 4 min, the good yield was obtained by treated extract (RE) on application for dyeing. Microwave rays influence the bio-coloration of fabrics dyed with plant-based dyes.⁴⁰ Due to its properties, cotton fabric, where modified surface by these potential rays, is capable of absorbing colorants to the extreme extent.⁴¹ An additional benefit of using these rays is that these waves do not change the chemical composition of the fibers; rather, they merely increase the surface sorption capacity physically to enhance colour strength. Furthermore, microwave rays have the advantage for not affecting the chemical nature of the fibers, focusing solely on physically optimizing the surface for maximum dye absorption.^42,43 Hence MW-rays have promising potential to improve the sorption behavior of fabric for colorant without altering its chemistry, which is an important advantage for its utilization in textiles.

Figure 1.

Dyeing of Cotton with Aqueous (a) and Acidic Extracts (b) of Amaltas Extracts Before and After MW Exposure.

Statistical Analysis of Dyeing Variables

Table 2 presents the analysis of variance (ANOVA), which highlights the statistical contribution of the color parameters. It shows that quadratic model fit is ideal in the present study, moreover factors such as the salt (p-value = .008) and the temperature (p-value = .002) are playing significant role for the response i-e. K/S. At the same time all interaction terms of the color parameters were found significant (p < .01) except pH*salt and contributing significantly for the response. The quadratic model is found to be most suitable for the current study because of insignificant value of the lack of fit (0.606 which is more than 0.05). The low value of standard deviation (0.1084) indicates the high precision and more reliability of the conducted experiments and lab data.

Table 2.

Assessment of Significance of Selected Dyeing Valuable Using Analysis of Variance.

Source	DF	Adj. SS	Adj. MS	F-value	p-value
Model	14	2.95312	0.210937	17.92	.000*
Linear	4	0.27345	0.068363	5.81	.006*
pH	1	0.00531	0.005310	0.45	.513
Salt	1	0.05993	0.059931	5.076	.008*
Temperature	1	0.16169	0.161688	13.74	.002*
Time	1	0.00569	0.005694	0.48	.498
Square	4	1.81765	0.454412	38.61	.000*
pH*pH	1	0.97870	0.978705	83.16	.000*
Salt*salt	1	0.04204	0.042037	3.57	.080
Temperature*temperature	1	0.15056	0.150558	12.79	.003
Time*time	1	0.03264	0.032639	2.77	.118
2-Way Interaction	6	0.95649	0.159415	13.55	.000*
pH*salt	1	0.00617	0.006172	0.52	.481
pH*temperature	1	0.07413	0.074127	6.30	.025*
pH*time	1	0.06439	0.064386	5.47	.035*
Salt*temperature	1	0.28361	0.283610	24.10	.000*
Salt*time	1	0.08981	0.089810	7.63	.015*
Temperature*time	1	0.14330	0.143295	12.18	.004*
Error	14	0.16476	0.011769
Lack-of-Fit	8	0.08670	0.010838	0.83	.606
Pure Error	6	0.07806	0.013010
Total	28	3.11788
Model Summary:	S.D. = 0.1084,		R²= 0.9472	R² (Adj.) = 0.8943

Prediction Performance Comparison of RSM and ANN Modeling

Figure 2 illustrates a graphical comparison of predictions made by RSM and ANN models. The standard order of experimentation is depicted on the X-axis, while the observed K/S values are represented on the Y-axis. There is very close agreement between the observed values of K/S and ANN fitted values. This suggests that model is accurately fitted. The R² for training and testing data set is 0.97 and 0.9041 respectively. Similarly the MSE value for training and testing data is 0.0076 and 0.0289 respectively. Overall R² is 0.998 which is high and desired. It is evident that the predicted data points from the ANN model are generally closer to the observed values compared to those from the RSM model. Consequently, the ANN model demonstrates superior predictive performance relative to the RSM.

Figure 2.

Performance Evaluation of Observed Response K/S (Cassia fistula) and Fitted Responses.

Mordant Selection for Stable Shade Formation

Mordanting either makes the shade brighter or darker depending upon metal used. Coordinate covalent bond depending on the type of fabric, extract, and metal employed determines the strength of natural dye complex. The developed natural dye complex gives stable and firm hues onto fabrics. Since many years ago, mordanting has been the state-of-the-art method for changing the color and tone or the depth of the shade with stable fastness. For the purpose of obtaining colorfast hues, cotton was dyed with Amaltas and then treated with salts of aluminum & iron and tartaric acid. As an alternative for comparative studies, bio molecules from herbal based plant waste have also been introduced. These biomolecules have phenolic sites which utilized their –OH from binding with colorant and fabric through special H- bounding to give dark stable shades. The results in Figure 3a and b show that 2.5% of Fe salt as pre and 2% of Fe salt as post treatment has given high yield. Comparatively before and after dyeing 2.5% mL of Fe salt is recommend to get shade of high strength. It has been observed that utilizing bio-mordants 0.5% madder produces a good yield (Figure 4a and b). Consequently, it is advisable to use 0.5% iron as a pre-chemical mordant and 0.5% madder as a pre-bio-mordant. The tonal variation of selected mordanted fabrics before and after dyeing with Amaltas has shown variable trends (Tables 3 and 4). Iron salt (2.5%) before dyeing has produced vibrant shades (K/S = 1.93) with a dark level trend (L* = 62.42) with reddish-yellow tone (a* = 5.63, b* = 9.95). Therefore, for achieving the desired results, iron (Fe) salt is recommended for use before dyeing (Table 3). Similarly, among bio-mordants used, 0.5% of madder before dyeing has given excellent results (Table 4). Overall in comparison among eco-chemical mordants iron salt has been considered and substantive for cotton to obtain colorfast shades and among bio-mordants used, madder has been found wonderful source to develop colorfast tint.

Figure 3.

Dyeing of Cotton with Amaltas Extract Before (a) and After (b) Coating with Chemical-Mordants.

Figure 4.

Dyeing of Cotton with Amaltas Extract Before (a) and After (b) Coating with Organic-mordants.

Table 3.

Tonal Variation of Selected Dyed and Chemical Mordanted Cotton with Amaltas Extract.

Table 4.

Tonal Variation of Selected Dyed and Organic Mordanted Cotton with Amaltas Extract.

Colorfastness for Developed Shades

The results of colorfastness suggest that minimizing the use of mordants in shade development has successfully tackled the issue of low-quality shades. By utilizing microwave treatment for colorant extraction, along with surface coating of cellulose fabric with eco-mordanting, has shown promising outcomes. This approach has developed the stable dye complex onto fabric which upon analysis through standard procedures has shown resistance to fade from heat, light, and washing. Furthermore, incorporating plant materials as a dual source for both dyeing and mordanting has also played a role in producing colorfast shades. The fastness results displayed in Table 5 demonstrate that clove can be effectively employed for dyeing natural fabrics.

Table 5.

Colorfast Results of Selected Mordanted Dyed Fabrics Using Amaltas Extracts.

Mordants	Mordants Conc.	Light Fastness	Wash Fastness	Rubbing Fastness
Mordants	Mordants Conc.	Light Fastness	Wash Fastness	Dry Rub Fastness	Wet Rub Fastness
Fe-salt	2.5% pre	5	4/5	4	4/5
Fe-salt	2% post	4/5	4/5	4/5	4/5
Al-salt	2.5% pre	5	4/5	4/5	4/5
Al-salt	1% post	5	4/5	4/5	4/5
Tartaric acid (TAA)	2.5% pre	5	4/5	4/5	4/5
Tartaric acid (TAA)	1% post	5	4/5	4/5	4/5
Pomegranate	1% pre	4/5	4/5	5	4/5
Pomegranate	1% post	5	4/5	5	4/5
Madder	0.5% pre	5	4/5	5	4/5
Madder	2% post	4/5	4/5	5	4/5
Red sumac	1.5% pre	5	4/5	4/5	4/5
Red sumac	2% post	5	4/5	4/5	4/5

Conclusion

The increasing desire for green products has prompted researchers to seek out new sources, such as amaltas, which is well known for its antiviral, antibacterial, and antioxidant properties. This plant, with its remarkable medicinal benefits, has been investigated for its potential in dyeing of cotton. Additionally, microwave rays have been used for extraction, and eco-labeled chemicals and eco-mordants have been utilized for colorfast stable shading. A new RSD was used to find the optimal design points with various possibilities to explore the conditions of the dyeing parameters. To analyze the functional behavior of amaltas under specific dyeing conditions, RSM and ANN with simplest possible structure were utilized. The ANN model has shown comparatively better model adequacy evaluated by high coefficient of determination (R²) values. Hence the combination of RSM and ANN modeling can effectively be used to optimize the response function. The obtained results have shown that if extract and fabric both are radiated, good yield is observed. In nut shell, new plants should be explored for textile by employing ANN along with RSM modeling to better understand cost, energy effect and nature of processing.

Highlights

This is newly introduced work on natural dye extraction by using amaltas for isolation of environmental friendly colorants for cotton.

Literature reports that no one has did such a comprehensive research on exploration of this novel and green medical source of colorant for textiles.

this work will guide new comers of textile and green chemistry researchers to use modern statistical approaches for making coloration process more suitable and viable for cotton industry.

For the first time innovative response surface design has been employed for the optimization of dyeing parameter.

Suitable structure of artificial neural network modeling for small data set have been utilized to avoid over-fitting problem for the first time in literature for the prediction purpose. If suitable structure of artificial neural network is not being utilized then the model never generalizes the unknown data well which is mostly happened in the past.

The present study is the complementary application of both modern statistical and machine learning algorithm and proves that none of these techniques is the replacement to the other, which is mostly being claimed by the researchers.

Bio mordants and chemical mordants have been used to enhance the performance of the eco-friendly process. Also greener extracts of medical plants have been used to develop new colorfast shades to produce soothing and eye catching effects.

Footnotes

Acknowledgment

The work is the part of PhD Studies done by Mr Muhammad Aftab, Department of Statistics, Government College University Faisalabad, Faisalabad 38000, Pakistan.

ORCID iD

Shahid Adeel

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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