Utilization and re-use of solid and liquid waste generated from the natural indigo dye production process – A zero waste approach

Journal Pre-proofs Utilization and re-use of solid and liquid waste generated from the natural indigo dye production process- A zero waste approach Lopa Pattanaik, P. Duraivadivel, P. Hariprasad, Satya Narayan Naik PII: DOI: Reference:

S0960-8524(19)31950-9 https://doi.org/10.1016/j.biortech.2019.122721 BITE 122721

To appear in:

Bioresource Technology

Received Date: Revised Date: Accepted Date:

4 October 2019 24 December 2019 30 December 2019

Please cite this article as: Pattanaik, L., Duraivadivel, P., Hariprasad, P., Narayan Naik, S., Utilization and re-use of solid and liquid waste generated from the natural indigo dye production process- A zero waste approach, Bioresource Technology (2019), doi: https://doi.org/10.1016/j.biortech.2019.122721

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

© 2019 Published by Elsevier Ltd.

Utilization and re-use of solid and liquid waste generated from the natural indigo dye production process- A zero waste approach Lopa Pattanaik, Duraivadivel P., Hariprasad P., Satya Narayan Naik*, Centre for Rural Development & Technology, Indian Institute of Technology Delhi, New Delhi-110016, India *

E-mail: [email protected], [email protected]

Abstract The main aim of this work is focused towards possible reuse of both solid and liquid waste generated from the natural indigo dye production process. The solid waste (C/N: 15.01) was utilized to produce stable compost with possible re-use in Indigofera cultivation. Among seven compost combinations (C1-C7) using jeevamrutha (JA) and cow-dung (CD) as inoculum, C4 with 8% JA showed higher biomass degradation (51%) and plant growth potential (GI>125%). Whereas the undiluted liquid waste was treated using algal consortia, bacteria, and indigenous microbial population, achieved a maximum removal of 90% ammonia, 82% nitrate, and 88% phosphorus for its re-use in the dye production process. Hence, incorporation of suitable waste management strategies in natural indigo dye production could help to achieve a zero waste sustainable process. Keywords: Natural indigo dye; Solid and liquid waste; Waste utilization; Compost; Nutrient removal 1. Introduction With the emerging population and demand in fashion industries the production of garments are increasing day by day, which in turn increases the uses of various synthetic dyes. Among various dyes, indigo remains the most prized and irreplaceable dye in denim industries for more than a century due to its unique deep blue hue and vibrancy (Hsu et al., 2018). Over the past decades (2001-2011) the production of indigo dye has been reached more than twice (22,000 tons/year to 1

50,000 tons/year) due to its high demand in the global market (Hsu et al., 2018; Schrott, 2001). At present, this demand of indigo dye has been mostly fulfilled by the synthetic route, which is produced by the reaction of petroleum by-product (aniline) and toxic chemical (hydrogen cyanide) (Rebelo et al., 2014). However, due to serious health hazard (cancer, respiratory disease, skin and eye irritation, and toxic to aquatic life), persisting environmental pollution (water and soil pollution), and strict ecological and economical restrictions (bans on certain consumer goods containing synthetic azo dyes) there is an urge to replace the synthetic indigo over natural one in most of the textile industries, especially in denim industries (Pal et al., 2017; Shahid et al., 2013; Khan and Malik, 2014). In the present scenario, the only sustainable and feasible source for natural indigo dye is the plant-derived one (Shahid et al., 2013). Several R&D efforts have already been initiated by various developed and developing countries (United Kingdom, France, Italy, Japan, India, Vietnam, and Bangladesh, etc.) for production of natural indigo dye from several region specific indigo bearing plant sources (Bechtold and Mussak, 2009). Currently, the demand of natural indigo in the world market is mostly fulfilled by the Asian countries and India is one of the significant contributor in it, with an annual export of approximately 30-40 tons/year (Bechtold and Mussak, 2009; Chemexcil, 2018). In India, the natural indigo dye production has been carried out in a decentralized manner by various small-scale industries in the state of Tamil Nadu. The conventional indigo dye production is a water and biomass intensive process utilizing approximately 1 tonne of biomass and 10,000 L of water for 10 kg dye production. With only 1% dye productivity the remaining waste biomass or dye extracted solid waste (DSW) and spent liquid or dye extracted liquid waste (DLW) are discarded into the environment directly (Pattanaik et al., 2018). The DSW is

2

generally dumped into nearby vicinity of dye production units, which causes nuisance by releasing putrefying gases and leachate. The discharge of untreated DLW causes eutrophication in the water bodies and contamination of agricultural land due to nutrient over loading, which causes plant death. Further, due to increasing water scarcity and competition of land for open dumping of solid waste in India (Chinnasamy and Agoramoorthy, 2015; Manu et al., 2017), the survival of these dye production units are at great stake. In order to achieve a sustainable and cleaner dye production process proper management of these wastes is the need of the hour. The potential of DSW for different value added products has been explored by a detailed characterization of DSW as described previously by Pattanaik et al. (2018). From the detailed analysis, it was revealed that the DSW is a nitrogen (C/N ratio = 19.66) and mineral rich (P = 1513.47 and K = 5672.63 mg/L) organic waste and might be an excellent source of nutrient for plant growth if converted into compost, which could be reutilized for the cultivation of Indigofera tinctoria (Pattanaik et al., 2018). As like DSW, DLW is also a by-product released from indigo dye production process is believed to be rich in organic and nutrient matter. Like any other agricultural wastewater, DLW could be treated by various algal and bacterial species for nutrient removal (Choudhary et al., 2016; Pittman et al., 2011; Ji et al., 2019) and subsequently reutilized in the indigo dye production process by reducing the fresh water demand. Based on the above aspects, an integrated approach for management of waste generated from natural indigo dye production process towards resource recycle/re-use has been attempted for the very first time. In this study, composting of DSW has been assessed by inoculating mixed microbial consortia in the form of Jeevamrutha (JA) and cow dung (CD). Similarly, nutrient removal from DLW was also determined by mass multiplication of different microflora such as mixed

3

consortia of algae, soil beneficial aerobic bacteria, and indigenous microbial population (IMP). Hence, both DSW and DLW were utilized based on the concept of zero-waste approach could lead the natural indigo dye production a viable process. 2. Materials and Methods 2.1. Generation of DSW and DLW Indigofera tinctoria biomass was cultivated at Micromodel complex, IIT Delhi during the month of April-September 2017. The Indigofera seeds with 80% germination were collected from Indigo dye manufacturers, Villupuram district, India. The Indigofera seeds were sown in 200 square meter of agricultural land with a line spacing of nearly 50-60 cm in the Micromodel complex, IIT Delhi. After the onset of flowering, approximately 100 kg of fresh Indigofera biomass (including leaf and stem) was harvested and dipped in water at 1:10 (w:v) ratios in a 2000 L plastic tank. After 16 h of fermentation, the fermented biomass (DSW) was separated and chopped by mechanical chopper into small pieces (10-20 mm) and further processed for composting. The fermented water (FW) of around 20 L was collected and aerated by sparging (3 LPM for 1 h) for the oxidation of fermented broth and formation of indigo particles. The waterinsoluble indigo particles were separated from the liquid by centrifugation at 15,000 rpm (19,419 × g) for 15 min, and the spent liquid (DLW) was collected and further treated for nutrient removal. 2.2. Experimental procedures for composting of DSW Composting was carried out by mixing DSW with different proportions of JA and CD (Table 1a). Seven separate piles (including the control), each of 13 kg weight of chopped DSW was prepared for composting after mixing with a suitable amount of JA and CD, as a potential source for microbial inoculum. Fresh CD was collected from Kishangarh, Gosala, Delhi, and JA was

4

prepared in the laboratory by mixing 1 kg cow dung, 1 L cow urine, 200 g jaggery, 20 g flour, a handful of fertile soil, and 20 L water (Ukale et al., 2016). The JA mixture was prepared in a 50 L plastic bucket, covered with a cotton cloth on the top and stirred twice daily for 10-15 mins. The JA mixture was incubated at 35±2 ºC for 8 days to enhance the growth of the microbial population (Ukale et al., 2016) and on 9th day the sample was used for composting. After being appropriately mixed with CD or JA each pile was divided into quadruplicate, and feedstock mixture was put into earthen pots (size 30 cm × 40 cm) having the capacity of 3.25 kg with a hole at the bottom for leaching out of excess water. The composting process was conducted in a temperature controlled room (25±2 °C) for 42 days. Initially, the moisture content of the feedstock was maintained by the available moisture content of the biomass, and after the 10th day, moisture content (60-65%) was maintained by sprinkling water periodically to the feedstock mixture during turning of composting. The temperature was measured daily at the center of each compost pile using a hand held digital thermometer (multi-stem thermometer with external sensing probe). The physicochemical characteristics of the raw materials and the different combinations of feedstock materials used for the composting process are described in Table 1b. Quadruplicates composite samples of 25 g from each combination was collected periodically in every seven days. Nearly 500 mg of subsamples were used for microbial analysis, and remaining subsamples were air dried, powdered, and sieved by 0.2 mm sieve and stored for further physicochemical analysis. 2.3. Analysis of compost parameters The physicochemical parameter such as moisture content was determined by drying at 105 °C using hot air oven (ICT, India) for 24 h. Electrical conductivity (EC) and pH of aqueous extract of raw materials (DSW, CD, and JA) and periodically collected compost samples (waste to water

5

extract ratio of 1:10 w/v) were determined by pH & EC meter by Hanna instruments (model: HI 2550) following the method of Manu et al. (2017). The total carbon and nitrogen content was determined by Elementar CHN analyzer (model: vario EL III). The total organic matter (TOM) or volatile solid content and ash content was determined by loss of ignition method using muffle furnace (Multispan, India) at 550 ºC (Jain and Kalamdhad, 2019). The organic matter loss was calculated using the equation (Eq. 1) of Bustamante et al. (2012). 𝑂𝑀 𝑙𝑜𝑠𝑠 % = 100 ― 100

[

𝑋1 (100 ― 𝑋2) 𝑋2 (100 ― 𝑋1)

]………………………………………………………..(1)

where X1 and X2 are initial and final ash contents, respectively. The major elements or macronutrients (Al, Ca, Fe, K, Mg, Mn, Na, P, and S) and trace elements or micronutrients (B, Ba, Cd, Cr, Co, Cu, Li, Ni, Pb, Sr, and Zn) were determined using Inductively Coupled Plasma-Mass Spectrometry (ICP-MS, model: Agilent 7900) after digesting the samples in aqua-regia (Manu et al., 2017). The phytotoxic effect of compost samples was evaluated based on germination bioassay, using tomato seeds as described by Awasthi et al. (2014). Three replicates of each compost combination and control were maintained. The phytotoxicity test was evaluated by counting the number of germinated seeds (viable), and measuring the root and shoot length. Subsequently, the germination index (GI) and vigour index (VI) was calculated by using the following equations 2 and 3: 𝐺𝐼 =

(

𝑉𝐼 =

(

𝑁𝑜. 𝑜𝑓 𝑠𝑒𝑒𝑑 𝑔𝑒𝑟𝑚𝑖𝑛𝑎𝑡𝑒𝑑 𝑖𝑛 𝑡ℎ𝑒 𝑠𝑎𝑚𝑝𝑙𝑒 × 𝑚𝑒𝑎𝑛 𝑟𝑜𝑜𝑡 𝑙𝑒𝑛𝑔𝑡ℎ 𝑖𝑛 𝑡ℎ𝑒 𝑠𝑎𝑚𝑝𝑙𝑒 𝑁𝑜. 𝑜𝑓 𝑠𝑒𝑒𝑑 𝑔𝑒𝑟𝑚𝑖𝑛𝑎𝑡𝑒𝑑 𝑖𝑛 𝑡ℎ𝑒 𝑐𝑜𝑛𝑡𝑟𝑜𝑙 × 𝑚𝑒𝑎𝑛 𝑟𝑜𝑜𝑡 𝑙𝑒𝑛𝑔𝑡ℎ 𝑖𝑛 𝑐𝑜𝑛𝑡𝑟𝑜𝑙 𝑁𝑜. 𝑜𝑓 𝑠𝑒𝑒𝑑 𝑔𝑒𝑟𝑚𝑖𝑛𝑎𝑡𝑒𝑑 𝑖𝑛 𝑡ℎ𝑒 𝑠𝑎𝑚𝑝𝑙𝑒

𝑁𝑜. 𝑜𝑓 𝑠𝑒𝑒𝑑 𝑔𝑒𝑟𝑚𝑖𝑛𝑎𝑡𝑒𝑑 𝑖𝑛 𝑡ℎ𝑒 𝑐𝑜𝑛𝑡𝑟𝑜𝑙

) × 100 ……………...(2)

) × 100 × (𝑚𝑒𝑎𝑛 𝑟𝑜𝑜𝑡 𝑙𝑒𝑛𝑔𝑡ℎ + 𝑚𝑒𝑎𝑛 𝑠ℎ𝑜𝑜𝑡 𝑙𝑒𝑛𝑔𝑡ℎ)

……………………………………………………………………………(3)

2.4. Experimental procedures for the treatment of DLW 6

The treatment of DLW was carried out by two different soil beneficial bacteria i.e. Bacillus marisflavi (BM) and Bacillus licheniformis (BL), which were collected from Environmental Biotechnology Lab, IIT Delhi. The subculture condition for bacterial species and the batch experiment for treatment of DLW has been described in the supplementary file provided with this manuscript. Similarly, a mixed consortia of algae (AC) consisting of Scenedesmus sp. and Chlorella sp. were collected from SSP industries, Faridabad, India and further characterized morphologically (cell number, dimensions, and chloroplast shape) as per the method used by Bellinger and Sigee (2010). The probable genus of the algal consortia was found to be a mixer of Scenedesmus and Chlorella species, where Scenedesmus is found to be dominant in the consortia. The algal subculture condition followed by the batch experimental set-up for the treatment of DLW has been described in the supplementary file provided with this manuscript. 2.5. Analysis of DLW and algal biomass Total dissolved solids (TDS), chemical oxygen demand (COD), total ammonical nitrogen (TAN) or NH3-N, nitrate nitrogen (NO3-N), and total dissolved phosphorus (TDP) or PO4-P in the untreated and treated DLW were determined by following the standard methods (APHA, 2005). The Chl-a concentration of algal biomass was determined by spectrophotometer as described by Choudhary et al. (2016). 2.6. Microbiological analysis 2.6.1. Total microbial population study of the compost sample The total viable cells in the compost samples were determined by MTT (3-(4,5-dimethylthiazol2-yl)-2,5-diphenyl tetrazolium bromide) assay (Trafny et al., 2013). Microbial isolation from the compost sample and its quantification are described in detail in the supplementary material provided in this manuscript.

7

2.6.2. Isolation and characterization of IMP present in DLW Freshly collected, untreated, and unsterilized DLW (5 mL) samples were used for isolation of IMP. The methodology used for isolation and characterization of IMP has been described in detail in the supplementary material provided with this paper. 2.7. Statistical analysis The data corresponding to OM loss during the composting process was fitted to the first-order kinetic model, as it was explained that OM decomposition is a function of time follows firstorder kinetics (Eq. 4) (Bustamante et al., 2012): 𝑂𝑀 𝑙𝑜𝑠𝑠 % = 𝐴 (1 ― 𝑒 ―𝑘𝑡 )……………………………………………………………………(4) where, A is the maximum loss (%) of OM, k is the decomposition rate constant (1/d), and t is the composting time in days (d). The curves fittings were carried out, and the parameters (A, k) were determined by Microsoft excel 2010 solver program using nonlinear regression method (Padhi and Gokhale, 2017). Triplicate samples of each experiment were taken for analysis, and their mean with standard deviation values are reported. To determine the significant differences among the parameters analyzed for different combinations during the composting process, the data were further studied using one-way analysis of variance (ANOVA) and Tukey's test using SPSS 16 software. The least significant difference test at 5% probability was used to determine the significance of the difference in the mean values.

3. Results and discussion 3.1. Physico-chemical characteristics of DSW during composting

8

3.1.1. Temperature, pH and EC profiles Temperature is the real-time indicator of the composting process, which regulates the microbial population and metabolism. Temperature profiles of composts during composting with various combination of microbial inoculum are shown in Fig. 1a. From the figure, it is observed that mesophilic condition (<45 °C) was achieved in all the combinations. However, the maximum mesophilic temperature of 38.8 °C was observed in C4, in which the temperature started rising from the 2nd day of composting and reached the maximum value on the 5th day. On the other hand, in combination C5, C6 and C7, the maximum temperature noted are 35.9, 36.8, and 35.8 °C, respectively on the 6th day of composting. The rise in temperature during composting confirms exothermic degradation of organic materials, which in turn increases the microbial population and degradation of TOM. In combination C4, the optimum concentration of Jeevamrutha (8% w/w) and DSW (92% w/w) created favorable environmental conditions for growth and propagation of mesophilic microbial population. Whereas, in combinations C1, C2 and C3, the highest recorded temperature during composting was 30.0, 32.8, and 33.9 °C on 12th, 10th and 9th days, respectively. This reduction in temperature could be explained in terms of lesser microbial growth due to no or insufficient addition of microbial source (JA). A lower bulk volume could be another major reason behind the mesophilic temperature (<45 °C) during the composting (Rich et al., 2018; Tang et al., 2007). It has been reported that, thermophilic temperature (>45 °C) is an essential stage in composting due to rapid microbial growth, which shorten the total duration required for composting (Tang et al., 2007). However, Liang et al. (2003) found no significant influence of temperature (>43 °C) on microbial activity during composting of biosolids (wastewater sludge). Instead, a moisture percentage of 50-70% significantly influences the microbial activity of composting process. Similarly, a satisfactory

9

reduction in C/N ratio (26-21) and degradation of cellulose and hemicellulose at mesophilic temperature (30 °C) was reported by Paradelo et al. (2013) during composting of lignocellulosic winery waste. These findings justifies that mesophilic temperature can also be effective in the reduction of composting mass due to higher decomposition activity by microbial population. The pH is an excellent indicator to ascertain the degradation process and stability of compost. The initial pH values of the control was 7.1. Whereas, in all the compost combinations, the pH value was somewhat lower than 7.1, which could be due to slightly acidic nature of JA (pH: 5.0) and CD (pH: 6.2). However, the initial pH values for all combinations are suitable for composting as they are within the recommended neutral range (>6) (Wang et al., 2013). The pH trends in C1-C7 show an initial increasing phase followed by decreasing, and finally a stable phase towards the end of the process (Fig. 1b). Similar trend has also been reported by Wang et al. (2017) for composting of distilled grain waste at different initial pH values (4-6). The initial increase in pH during composting is due to the accumulation of ammonia in compost by ammonia volatilization (Yu et al., 2019). An initial rise in pH was observed in all combinations, while a significant increment noticed in case of C3 (7.0 to 7.9), C4 (7.0 to 8.0), C5 (6.9 to 7.9), and C6 (7.1 to 8.0). As the growth and propagation of nitrifying bacteria are inhibited in acidic pH, the suitable pH range for the nitrification process has been suggested in between 7.5-8.0 (Cáceres et al., 2018). Furthermore, temperature plays a major role in nitrification, and a mesophilic temperature (35 ºC) reported to be more suitable for nitrification compared to the thermophilic temperature (55 ºC). Because, higher temperature suppress ammonification, growth and activity of nitrifying bacteria, which was observed during composting of feces sample with saw dust (Li et al., 2013). Considering the above factors, it can be inferred that the combinations C4 and C6 might have provided a suitable environment for the growth of nitrifying bacteria from

10

the first week of composting as the pH values of these experimental runs have been already increased to 7.8 and 7.7 with a temperature of 38.8 ºC and 37.2 ºC, respectively. The increase in pH could be due to transformation of organic N into NH3 or NH4+ by ammonification. In the later phase, the acidification of composting material to neutral values (6.8-7.0) could be attributed to loss of NH3 (ammonia volatilization), oxidation of NH3 to NO3 (nitrification), and presence of low-molecular acids (Wong et al., 2017; Yu et al., 2019). A relatively stable pH value around neutral range (6.5-7.5) at the end of composting process considered to be an indicator of mature compost (Manu et al., 2017). From Fig. 1b, it has been observed that the final pH has been brought down to 7.3, 7.2, 7.2, 6.8, 7.2, 6.6, and 6.1 for C1, C2, C3, C4, C5, C6, and C7, respectively. However, the pH trend in C7 has not attained stability within the composting duration and is still decreasing. As the pH of the C7 combination is lower than the recommended limit as prescribed by FAI, 2007 (Indian Fertilizer Control Order, 1985) and SWM, 2016 (Solid Waste Management Rules), which cannot be considered as matured compost (Awasthi et al., 2014; Manu et al., 2017) (Table 2). Electrical conductivity (EC) reflecting the degree of salinity is an indirect indicator of composting. Compost with high EC (>4 mS/cm) releases excessive soluble products and affect adversely to the plant growth (low germination rate and withering) (Awasthi et al., 2014; Chan et al., 2016). During composting process, the EC value increases due to increment of soluble salts by decomposition of organic substances into nutrients and deposition of mineral salts such as phosphates, potassium, volatile fatty acids (VFAs), and ammonium ions (Awasthi et al., 2014; Sharma et al., 2018). The initial EC values increased from 1.01, 1.12, 1.1, 1.14, 1.12, 1.2, and 1.16 mS/cm to 1.52, 1.92, 2.01, 2.28, 2.07, 2.18, and 1.97 mS/cm in combinations C1, C2, C3,

11

C4, C5, C6, and C7, respectively (Fig. 1c). The final EC values of the matured compost are in the desirable range (<4 mS/cm) as prescribed by SWM, 2016 (Table 2). 3.1.2. Analysis of total carbon and nitrogen content The time profiles of TC or TOC for various experimental combinations are shown in Fig. 1d. A gradual decrease in TOC content was observed with an increase in composting duration. This decrease in TC content can be explained in terms of consumption of organic carbon by the microorganisms as energy source for their growth and propagation, with subsequent release of CO2 (Awasthi et al., 2016). The TC decrement followed an order of C4>C6>C7>C5>C3>C2>C1 (Fig. 1d). The microbial inoculation was observed to be effective for the degradation of organic matter (Sharma et al., 2018) and is supported by pH and EC data. The total nitrogen (TN) profiles for all compost combinations are presented in Fig. 1e. A variation in initial nitrogen content in all compost combinations was observed due to the addition of JA and CW. As per Wang et al. (2017), the initial nitrogen content of raw material is affected by the nitrogen content of amended material. As the initial nitrogen content of DSW biomass is higher than that of inoculum (JA and CW), the overall nitrogen content of all compost combinations decreased with the gradual increase in the concentration of inoculum. From Fig. 1e, it can be observed that the TN content decreased at the initial phase of composting, which is within the first week in case of C4, C5, C6, and C7. Whereas, in case of C1, C2, and C3, the decrease in TN content was observed in the second week of composting. This decrease in TN content could be due to a relatively lower temperature rise, which results in to slow degradation of biomass (Awasthi et al., 2016). The decrease in TN content in the process of composting is majorly due to the formation of NH3 by microbial degradation of biomass and its volatilization (Yu et al., 2019). However, the

12

increase in TN content in later phase is controlled by several factors, such as (i) net loss of dry biomass, (ii) microbial degradation of organic compounds and reduction of the weight of composting mass due to concentration effect, and (iii) nitrogen fixation by nitrogen-fixing bacteria, as explained by Wong et al. (2017). The total TN content increased and reached its maximum at the final stage of composting. The final TN content for C1 was maximum (3.24%) among all composting combinations (C1-C7), which could be due to the dilution effect (contains only biomass without inoculum) (Chan et al., 2016). 3.1.3. Total organic matter, ash content, and organic matter degradation kinetics of compost The TOM is considered as the total volatile solids content of different samples represented in Fig. 2a. The TOM helps in assessing the amount of biologically degradable and biologically inert (lignin) material present in the compost sample (Jain and Kalamdhad, 2018). Higher the degradation of organic matter considered better decomposition, but in the final compost, the organic matter should not be less than 30% (Table 2). The initial TOM of C1, C2, C3, C4, C5, C6, and C7 were reduced from 84.1, 83.67, 84.01, 83.30, 84.16, 83.50, and 83.66% to 80.54, 78.59, 76.58, 72.41, 77.47, 74.55, and 76.75%, respectively, during the composting. The maximum reduction in TOM was observed within 15 days of composting, and the highest reduction was observed in the first week, which is in correlation with the maximum temperature rise and microbial activity observed during the composting process. The highest TOM reduction of 10.89% was observed in combination C4, which is in close approximation with C6 (8.95%). Whereas, in combinations C1, C2, C3, C5, and C7, the percentage of TOM reductions were comparatively lower i.e. 3.56, 5.08, 7.43, 6.69, and 6.91%, respectively. Although, the TOM reduction obtained during composting of Indigofera is less, but still it is in close agreement with the TOM reduction observed for composting of

13

Hydrilla verticillata (15%) (Jain and Kalamdhad, 2018) and pig manure (11.5%) (Wang et al., 2016). The result of TOM analysis indicated a significant difference exist between the various compost combinations (p<0.05). In contrast to TOM profile, the ash contents of different combinations were found to be increased with the incubation period. The final ash content for each combination was observed to be 19.46, 21.41, 23.42, 27.59, 22.53, 25.45, and 23.25% for C1, C2, C3, C4, C5, C6 and C7, respectively (Fig. 2b). A significant variation in ash content was observed between each combination of the experiment (p <0.05). An increase in ash content and decrease in TOM during composting signifies improved organic matter degradation by inoculation of JA and CD in comparison to the control sample (C1). The organic matter (OM) degradation profiles in terms of OM losses during composting for all combinations (C1-C7) are shown in Fig. 2c. As per previous literatures, the whole OM degradation profile can be divided into two phases: (i) initial phase of rapid degradation and (ii) later phase of slower degradation, which can be described by first-order kinetic model (Eq. 4) (Bustamante et al., 2012; Jain and Kalamdhad, 2019). The values of unknown parameters (A and k) were determined by fitting the experimental profiles to the model equation (Fig. 2c). The values of A, k, and RMSE are given in the supplementary material provided with this manuscript. The equations generated by using these parameters are found to be significant (P<0.05) for all compost combinations (C1-C7). The maximum degradation (A) for all combinations of compost are in the range of 29.76-51.51%, which are in close agreement to the results obtained during composting of different organic materials such as Hydrilla verticillata (25.4-47.4%) (Jain and Kalamdhad, 2019) and distilled grain waste (36.64-38.88%) (Wang et al., 2017). The slowest degradation rate with a k value of 0.0330 1/d was obtained for the control sample, followed by

14

0.044 and 0.052 1/d for C2 and C3, respectively. The highest rate of degradation (k = 0.073 1/d) was observed for C4 with a maximum degradation of 51.51%, followed by C6 (k = 0.068 1/d) and C7 (k = 0.061 1/d). A comparative degradation rate of 0.0234 1/d was observed during rotary drum composting of nitrogen rich Hydrilla verticillata mixed with carbon rich saw dust, cow dung, and grass clippings (Jain and Kalamdhad, 2019). In combinations C3 and C5, although the highest OM loss (42.94%) was observed in C3, the rate of degradation was higher for combination C5 (k = 0.059 1/d). By considering both k and A×k, a higher rate of decomposition was obtained for combination C5 in comparison to C3. Moreover, composting of DSW with JA that contains potential microbial population showed a better performance in terms of rate of OM degradation as compared to CD. 3.2. Microbial analysis of compost The total microbial population in terms of the number of viable cells in compost was estimated by MTT assay (Trafny et al., 2013). From the total viable cells distribution of different compost combinations provided in the supplementary material, it is observed that the viable cells count are higher at the initial level, which could be due to the inoculation of rich microbial sources (JA and CD) in Indigofera biomass at the beginning of composting process. During composting, the viable cells count increased from 0th day to 7th day, possibly due to biological activity in the utilization of initial organic and nitrogen source of the raw material, which enhances the growth and propagation of microorganism. This rapid growth of the microbial population releases heat to the surrounding to increase the temperature of compost (Paradelo et al., 2013). This result coincides with the temperature profile results obtained during the composting process. In the present experimental condition, the temperature change reached maximum up to mesophilic condition, indicates possible propagation of mesophilic microorganisms. However, during the

15

second week, a fall in optical density (OD) of viable cells has been observed, may be due to exhaustion of easily available nutrient sources (Paradelo et al., 2013). 3.3. Nutrient compositions of compost The macro and micronutrients content are the important parameters of the final compost in terms of nutrient value. The macronutrients such as K, P, Na, Ca, Mg, Mn and Fe in the final compost samples for all the combinations (C1-C7) varied in the range of 0.67-0.76, 0.22-0.41, 0.02-0.04, 0.13-0.23, 0.13-0.24, 0.47-1.0 and 0.60-1.25%, respectively (Table 2). Additionally, the essential micronutrients (Fe, Mn, Cu, Ni, and Zn) and heavy metals (Cd and Cr) contents in compost are found to be within the permissible limit as prescribed by FAI, 2007 and SWM, 2016 (Table 2). 3.4. Evaluation of compost maturity 3.4.1. Carbon to nitrogen (C/N) ratio C/N ratio has always been one of the critical factor deciding the optimal nutrient condition required for microbial growth and reproduction during composting and also plays an essential role in assessing compost maturity (Chan et al., 2016). The preferable initial C/N ratio of the composting raw material ranges between 25-35 (Wang et al., 2019). However, successful composting studies have been performed using substrate containing low initial C/N ratio than the desirable range. Awasthi et al. (2016) used gelatin industry sludge mixed with municipal solid waste, poultry waste, pig manure, and saw dust with an initial C/N ratio of 17.80 for composting (Awasthi et al., 2016). Similarly, Hydrilla verticillata mixed with cow dung and saw dust having an initial C/N ratio of 15 used by Jain and Kalamdhad (2018), and segregated vegetable waste mixed with water hyacinth, garden prune, sawdust, and cow dung with an initial C/N ratio of 22.01 used by Rich et al. (2018) for successful composting. In the present study, the initial C/N ratio of compost samples varies from 15 to 35, with the addition of various combinations of

16

inoculum in raw materials (Fig. 2d). As Indigofera is a leguminous plant, the initial C/N ratio of the control sample (C1) was quite low (14.97) due to high TN content of the plant biomass (2.98%). Although, CD and JA were reported to be the nitrogen-rich source (Wang et al., 2019; Ukale et al., 2016), but the observed TN content of CD (1.932) and JA (1.65) in this study was quite low as compared to TN content of DSW. As a result, with a gradual increment of JA and CD inoculum in DSW composting process, an increase in the C/N ratio was observed in different composting combinations as compared to control. As shown in Fig. 2d , the C/N ratios of all compost combinations (C1-C7) at the initial stage were slightly higher due to loss of nitrogen in the form of ammonia. In the later phase, the C/N ratios gradually decreased due to mineralization of organic matter, which in turn increased TN content and decreased in TC content, subsequently decreased the C/N ratio (Chan et al., 2016). Similar trends have also been reported for windrow composting of gelatin industry sludge by Awasthi et al. (2016) and composting of pig manure by Wang et al. (2016). The C/N ratio in the final compost for all compost combinations except C7 fall within the standard (<25) as described by Awasthi et al. (2016). However, the C/N ratio of combination C7 was found to be within the standard range (<20) as described by previous authors (Manu et al., 2017; Wang et al., 2016). 3.4.2. Germination index (GI) Germination index (GI) is a sensitive indicator to both phytotoxicity and maturity of the compost concerning germination of seeds and growth of the plant. Phytotoxicity in the compost is caused by the presence of heavy metals and low molecular weight compounds such as organic acids and ammonia produced during microbial decomposition of organic wastes. The presence of these

17

compounds in the compost might inhibit the germination of seeds and growth of the plant (Liu et al., 2011). The GI and VI values of all compost combinations after 60 days of composting are reported in Table 3. In several studies the recommended GI values for phytotoxic free compost varies from 50-90% (Wang et al., 2016; Rich et al., 2018). From Table 3, it is observed that the compost obtained for DSW composting process (C1-C7) exceeds all the recommended limit and can be considered as phytotoxic free. According to Rich et al. (2018), the GI value of 90% indicates the compost samples to be phytotoxic free, but not mature enough to help in germination or plant growth, which was observed in C1 (90%) and C7 (90%). However, in combinations C2 (97%), C3 (110%), C5 (114%), and C6 (96%), the GI values are close to or more than 100, indicate the maturity of the compost. The highest GI (129%) was observed in C4, which justifies the stability of compost and might help in enhancing the plant growth (Rawoteea et al., 2017). From the above observations, it could be inferred that the compost mixture containing JA could enhance the plant growth due to the presence of several plant-growth regulators i.e. nucleobases, vitamins, amino acids, sugars, and organic acids (Ukale et al., 2016). 3.5. Growth potential and nutrient removal efficiency of microorganisms in DLW Initial characterization of DLW revealed it is free from toxic contents, but rich in several nutrients (organic matter, nitrogen, and phosphorus), which is represented in the supplementary material provided with this manuscript. Hence, it is unsuitable for discharge into agricultural land or surface waters due to abundant nutrient content, but can be used as a rich source for microbial growth and propagation (Cai et al., 2013). Therefore, the primary reason behind the removal of nutrients from DLW is to reuse it either for irrigation in Indigofera biomass cultivation process or replacing the water use in Indigofera steeping process. Further, the quality

18

of DLW after treatment should meet the dischargeable criteria for irrigation in land or inland surface water. The initial nutrient and metal concentrations in DLW (provided in the supplementary material of this manuscript) are comparable with the nutrient characteristics of other wastewaters derived from various agro-industries and municipal wastewater treatment plant (Cai et al., 2013; Hongyang et al., 2011; Li et al., 2011; Pittman et al., 2011). Nutrient removal using microorganisms (bacteria and algae) is the most efficient and cost-effective approach, extensively used in the wastewater treatment process (Qu et al., 2015). Among various bacterial strains, Bacillus strains have been reported for efficient nutrient removal from wastewater (Rout et al., 2017; Zhang et al., 2012). Similarly, widely used algal strains i.e. Scenedesmus and Chlorella species have been popularly used for nutrient removal from wastewater due to its higher N and P removal efficiency (Pittman et al., 2011). Based on the above findings, two Bacillus strains namely BM and BL, and algal consortia consisting of Scenedesmus and Chlorella species have been considered for nutrient removal from DLW in this study. The nutrient removal efficiency of these strains have been assessed, and the results are compared with the efficiency of IMP present in DLW. 3.5.1. Nutrient removal efficiency of bacterial strains Before assessing the nutrient removal efficiency of various bacterial species, the growth profile of these strains were studied in undiluted DLW medium. From the growth profile provided in the supplementary material, it was observed that two bacterial strains (BM and BL) showed growth pattern similar to IMP. From the growth curve, it was observed that the lag phase of all bacterial strains lasts for 6 h, followed by exponential phase and finally entered the stationary phase after 20, 33, and 23 h for BM, BL, and IMP strains, respectively. The removal efficiency of nutrients by bacterial strains including IMP are given in Table 4. The total COD removal by BM, BL, and

19

IMP were 83.44, 80.13, and 78.81%, respectively. The reduction in COD implies growth of the bacteria in heterotrophic mode by utilizing the organic carbon source. The decrease in nitrogen content like TAN was observed to be 87.01, 90.31, and 86.23% and NO3-N was 79.31, 80.73, and 82.32% by BM, BL, and IMP, respectively. The removal of both TAN and NO3- N could be due to heterotrophic nitrification and aerobic denitrification potential of the microbial species such as Bacillus sp., Pseudomonas sp., and Aeromonas sp. (Li et al., 2015; Rout et al., 2017; Zhang et al., 2012). As like COD and nitrogen, a higher phosphorus removal of 87.64, 86.58, and 85.95 % was also observed by BM, BL, and IMP, respectively. The reason might be due to the possibility of microorganism became polyphosphate accumulator, which helped in simultaneous removal of nitrogen and phosphorus by utilizing external carbon source (Rout et al., 2017). The above reported nitrogen and phosphorous removal by bacteria and IMP species can be comparable to the previous investigation of Li et al. (2015). A removal efficiencies of 88.13, 70.83, and 51.21% for NH3-N, NO3-N and PO4-P were obtained by Pseudomonas stutzeri in 50 h for approximately 10 times lower strength wastewater (COD: 156.20 mg/L, NH3-N: 33.95 mg/L, NO3-N: 0.62 mg/L, PO4-P: 2.28 mg/L) than the undiluted DLW (COD: 1887.5 mg/L, NH3-N:117.36 mg/L; NO3-N: 18.22 mg/L; PO4-P: 99.70 mg/L) in this study (Table 4). Although, in the present study the specific mechanism behind the nutrients removal by the microbes are unclear, but due to high nutrient removal efficiency, these microbes are of further research interest to understand their mechanism. 3.5.2. Nutrient removal using algal strains The algal consortia were grown in the DLW, and the growth potential was measured by estimating the Chl-a content as shown in growth profile of algae, provided in the supplementary material of this manuscript. The exponential increase in Chl-a content was observed between 3-

20

10 days, followed by a stationary phase starting from the 15th day (Chl-a content: 6.14 µg/mL). The nutrient removal on 15th day by algal consortia in terms of reduction in COD, TAN, NO3- N, and TDP were achieved up to 60.26, 63.74, 5.10, and 60.48%, respectively. Whereas, in the control sample containing IMP, the reduction was achieved by 47.01, 39.14, 32.76, and 49.44% for COD, TAN, NO3- N, and TDP, respectively. The reduction of COD and increase in Chl-a content implies that the algal consortia might have a mixotrophic (both autotrophic and heterotrophic) mode of growth (Hongyang et al., 2011). However, a relative reduction of COD was also observed in the control sample, which implies that the IMP might have a heterotrophic mode of growth as like bacteria in DLW. Although, both algal consortia and the IMP reduced the COD efficiently, but the treated DLW could not meet up to the discharge limits (COD: 250 mg/L for inland surface water and COD: 500 mg/L for irrigation land) as described by Choudhary et al. (2016) (Table 4). Again, due to comparatively less removal of TAN and NO3-N using algal consortia after 15 days of treatment lead the experiment to keep operational for an additional 15 days. On the 30th day of growth of algal consortia, removal of TAN (84.10%) remained higher as compared to NO3-N (40.72%). The possible reason could be due to the preference of TAN over NO3-N in case of algal nitrogen assimilation (Cai et al., 2013). The other reason for higher TAN reduction could be due to ammonia stripping by volatilization of ammonia at higher pH (>8) (Luo et al., 2016). The phosphorus removal showed a slight improvement as compared to the 15th day with a removal efficiency of 82.54 and 70.21% in both algal consortia and control sample, respectively. The reasons for high reduction of phosphorus from DLW could be due to metabolic uptake by microbial cell (bacteria and algae), phosphorus precipitation at higher pH (>8) and presence of polyphosphate accumulating organisms (Li et al., 2011; Rout et al., 2017).

21

The nutrient removal by algae (TAN: 84.10%, NO3-N: 40.72%, PO4-P: 82.54%) reported in this study can be compared with the nutrient removal efficiency of Cholerella species for treatment of piggery wastewater (filtrated and 80% diluted with distilled water) (Ji et al., 2013). The diluted piggery wastewater of nutrient strength (COD: 168 mg/L; NH3-N: 53.6 mg/L; NO3N: 0.34 mg/L; PO4-P: 11.4 mg/L) was treated in batch mode for 30 days and achieved a removal efficiency of 47% total nitrogen and 82% total phosphorous (Ji et al., 2013). Although the nutrients removal in DLW by both algal and IMP reached up to the dischargeable limit except the COD. Whereas, significant nutrients removal from DLW was observed using bacteria (BL and BM), which is comparatively similar to the results of IMP. Therefore, it can be inferred that IMP could be a best alternative for treatment of DLW. However, on the basis of nutrient removal efficiency of IMP in both algal culture condition (temperature: 25 ± 2 °C, rpm: 120, light intensity: 50–60 mol/m2 s, and dark-light cycle of 12:12 h) and bacterial culture condition (time: 48 h, temperature: 35±2 °C and rpm: 120), the IMP showed effective removal in the later stage. Therefore, similar environmental condition can be maintained on large scale to achieve a higher removal of nutrient from DLW by IMP 3.5.3. Identification of indigenous microbial population The indigenous microorganisms, which efficiently removed the nutrients, were isolated and identified as LP1/Aeromicrobium sp. (KY558737.1) with 94.58% similarity, LP2/Nocardiopsis sp. (MH540129.1) with 99.9% similarity, LP3/Aneurinibacillus aneurinilyticus (AB680012.1) with 99.79% similarity, and LP4/ Brevibacillus borstelensis (MK088265.1) with 99.40% similarity. The partial 16S rRNA sequences of each strain were submitted to GenBank nucleotide sequence databases under the accession number of MK418769, MK418770, MK418771, and MK418772 for LP1, LP2, LP3, and LP4, respectively.

22

4. Conclusion This study provides suitable routes for the management of both DSW and DLW with the prospect of the current need of the natural indigo industry. The compost developed in this study can reduce the fertilizer need of the Indigofera biomass cultivation. Further, the reuse of treated liquid waste in the existing indigo dye production process would be recommended to sustain the large water demand of this process. This approach of recycling the waste would help in attaining zero waste goal and also benefit both farmers and dye producers by reducing the process cost. Conflict of interest There is no conflict of interest declared by the authors. Acknowledgment Authors are thankful to Dr. Susant Kumar Padhi and Dr. Pritam Kumar Dikshit for their valuable contribution for this research. Appendix A. Supplementary data Supplementary data associated with this article can be found in the online version References 1. American Public Health Association-APHA, 2005. Standard methods for examination of water and wastewater, 21st ed. American Public Health Association, Washington. 2. Awasthi, M.K., Pandey, A.K., Bundela, P.S., Wong, J.W.C., Li, R., Zhang, Z., 2016. Cocomposting of gelatin industry sludge combined with organic fraction of municipal solid waste and poultry waste employing zeolite mixed with enriched nitrifying bacterial consortium. Bioresour. Technol. 213, 181–189. 3. Awasthi, M.K., Pandey, A.K., Khan, J., Bundela, P.S., Wong, J.W.C., Selvam, A., 2014. Evaluation of thermophilic fungal consortium for organic municipal solid waste

23

composting. Bioresour. Technol. 168, 214–221. 4. Bechtold, T., Mussak, R., 2009. Handbook of natural colorants. John Wiley & Sons. 5. Bustamante, M.A., Alburquerque, J.A., Restrepo, A.P., la Fuente, C., Paredes, C., Moral, R., Bernal, M.P., 2012. Co-composting of the solid fraction of anaerobic digestates, to obtain added-value materials for use in agriculture. Biomass Bioenerg. 43, 26–35. 6. Cáceres, R., Malińska, K., Marfà, O., 2018. Nitrification within composting: a review. Waste Manag. 72, 119–137. 7. Cai, T., Park, S.Y., Li, Y., 2013. Nutrient recovery from wastewater streams by microalgae: status and prospects. Renew. Sustain. Energy Rev. 19, 360–369. 8. Chan, M.T., Selvam, A., Wong, J.W.C., 2016. Reducing nitrogen loss and salinity during 'struvite' food waste composting by zeolite amendment. Bioresour. Technol. 200, 838– 844. 9. CHEMEXCIL, 2018. Basic Chemicals, Cosmetics & Dyes Export Promotion Council. https://chemexcil.in. Accessed October 2018. 10. Chinnasamy, P., Agoramoorthy, G., 2015. Groundwater storage and depletion trends in Tamil Nadu State, India. Water Resour. Manag. 29, 2139–2152. 11. Choudhary, P., Prajapati, S.K., Malik, A., 2016. Screening native microalgal consortia for biomass production and nutrient removal from rural wastewaters for bioenergy applications. Ecol. Eng. 91, 221–230. 12. Hongyang, S., Yalei, Z., Chunmin, Z., Xuefei, Z., Jinpeng, L., 2011. Cultivation of Chlorella pyrenoidosa in soybean processing wastewater. Bioresour. Technol. 102, 9884–9890. 13. Hsu, T.M., Welner, D.H., Russ, Z.N., Cervantes, B., Prathuri, R.L., Adams, P.D., Dueber,

24

J.E., 2018. Employing a biochemical protecting group for a sustainable indigo dyeing strategy. Nat. Chem. Biol. 14, 256. 14. Jain, M.S., Kalamdhad, A.S., 2018. Efficacy of batch mode rotary drum composter for management of aquatic weed (Hydrilla verticillata (Lf) Royle). J. Environ. Manage. 221, 20–27. 15. Jain, M.S., Kalamdhad, A.S., 2019. Drum composting of nitrogen-rich Hydrilla Verticillata with carbon-rich agents: Effects on composting physics and kinetics. J. Environ. Manage. 231, 770-779. 16. Ji, M.K., Kim, H.C., Sapireddy, V.R., Yun, H.S., Abou-Shanab, R.A., Choi, J., Lee, W., Timmes, T.C., Inamuddin., Jeon, B.H., 2013. Simultaneous nutrient removal and lipid production from pretreated piggery wastewater by Chlorella vulgaris YSW-04. Appl. Microbiol Biotechnol. 97, 2701-2710. 17. Ji, X., Li, H., Zhang, J., Saiyin, H., Zheng, Z., 2019. The collaborative effect of Chlorella vulgaris-Bacillus licheniformis consortia on the treatment of municipal water. J. Hazard. Mater. 365, 483–493. 18. Khan, S., Malik, A., 2014. Environmental and health effects of textile industry wastewater, in: Malik, A., Grohamann, E., Akhtar, R. (Eds.), Environmental Deterioration and Human health, Springer, Dordrecht, pp. 55-71. 19. Li, C., Yang, J., Wang, X., Wang, E., Li, B., He, R., Yuan, H., 2015. Removal of nitrogen by heterotrophic nitrification-aerobic denitrification of a phosphate accumulating bacterium Pseudomonas stutzeri YG-24. Bioresour. Technol. 182, 18–25. 20. Li, Q., Wang, X.C., Zhang, H.H., Shi, H.L., Hu, T., Ngo, H.H., 2013. Characteristics of nitrogen transformation and microbial community in an aerobic composting reactor under

25

two typical temperatures. Bioresour. Technol. 137, 270-277. 21. Li, Y., Chen, Y.-F., Chen, P., Min, M., Zhou, W., Martinez, B., Zhu, J., Ruan, R., 2011. Characterization of a microalga Chlorella sp. well adapted to highly concentrated municipal wastewater for nutrient removal and biodiesel production. Bioresour. Technol. 102, 5138–5144. 22. Liang, C., Das, K.C., McClendon, R.W., 2003. The influence of temperature and moisture contents regimes on the aerobic microbial activity of a biosolids composting blend. Bioresour. Technol. 86, 131–137. 23. Liu, D., Zhang, R., Wu, H., Xu, D., Tang, Z., Yu, G., Xu, Z., Shen, Q., 2011. Changes in biochemical and microbiological parameters during the period of rapid composting of dairy manure with rice chaff. Bioresour. Technol. 102, 9040–9049. 24. Luo, L., He, H., Yang, C., Wen, S., Zeng, G., Wu, M., Zhou, Z., Lou, W., 2016. Nutrient removal and lipid production by Coelastrella sp. in anaerobically and aerobically treated swine wastewater. Bioresour. Technol. 216, 135-141. 25. Manu, M.K., Kumar, R., Garg, A., 2017. Performance assessment of improved composting system for food waste with varying aeration and use of microbial inoculum. Bioresour. Technol. 234, 167–177. 26. Padhi, S.K., Gokhale, S., 2017. Benzene biodegradation by indigenous mixed microbial culture: kinetic modeling and process optimization. Int. Biodeterior. Biodegradation 119, 511–519. 27. Pal, H., Chatterjee, K.N., Sharma, D., 2017. Water footprint of denim industry, in: Sustainability in Denim. Elsevier, pp. 111–123. 28. Paradelo, R., Moldes, A.B., Barral, M.T., 2013. Evolution of organic matter during the

26

mesophilic composting of lignocellulosic winery wastes. J. Environ. Manage. 116, 18– 26. 29. Pattanaik, L., Naik, S.N., Hariprasad, P., 2018. Valorization of waste Indigofera tinctoria L. biomass generated from indigo dye extraction process potential towards biofuels and compost. Biomass Convers. Bior. 1–13. 30. Pittman, J.K., Dean, A.P., Osundeko, O., 2011. The potential of sustainable algal biofuel production using wastewater resources. Bioresour. Technol. 102, 17–25. 31. Qu, D., Wang, C., Wang, Y., Zhou, R., Ren, H., 2015. Heterotrophic nitrification and aerobic denitrification by a novel groundwater origin cold-adapted bacterium at low temperatures. Rsc Adv. 5, 5149–5157. 32. Rawoteea, S.A., Mudhoo, A., Kumar, S., 2017. Co-composting of vegetable wastes and carton: Effect of carton composition and parameter variations. Bioresour. Technol. 227, 171–178. 33. Rebelo, S.L.H., Linhares, M., Simões, M.M.Q., Silva, A.M.S., Neves, M.G.P.M.S., Cavaleiro, J.A.S., Freire, C., 2014. Indigo dye production by enzymatic mimicking based on an iron (III) porphyrin. J. Catal. 315, 33–40. 34. Rich, N., Bharti, A., Kumar, S., 2018. Effect of bulking agents and cow dung as inoculant on vegetable waste compost quality. Bioresour. Technol. 252, 83–90. 35. Rout, P.R., Bhunia, P., Dash, R.R., 2017. Simultaneous removal of nitrogen and phosphorous from domestic wastewater using Bacillus cereus GS-5 strain exhibiting heterotrophic nitrification, aerobic denitrification and denitrifying phosphorous removal. Bioresour. Technol. 244, 484–495. 36. Schrott, W., 2001. Denim wieder im Blickpunkt der Textilindustrie. Melliand Textilber

27

82, 331–337. 37. Shahid, I., Shahid, M., Mohammad, F., 2013. Perspectives for natural product based agents derived from industrial plants in textile applications–a review. J. Clean. Prod., 57, 2-18. 38. Sharma, D., Yadav, K.D., Kumar, S., 2018. Role of sawdust and cow dung on compost maturity during rotary drum composting of flower waste. Bioresour. Technol. 264, 285– 289. 39. Solid Waste Management (SWM) Rules, 2016. http://www.moef.gov.in/sites/default/files/SWM%202016.pdf. Accessed May 2019 40. Tang, J.C., Shibata, A., Zhou, Q., Katayama, A., 2007. Effect of temperature on reaction rate and microbial community in composting of cattle manure with rice straw. J. Biosci. Bioeng. 104, 321–328. 41. Trafny, E.A., Lewandowski, R., Zawistowska-Marciniak, I., Stępińska, M., 2013. Use of MTT assay for determination of the biofilm formation capacity of microorganisms in metalworking fluids. World J. Microbiol. Biotechnol. 29, 1635–1643. 42. Ukale, D.U., Bhagwat, R. V, Upadhyay, S.K., Cukkemane, N., Cukkemane, A.A., 2016. Metabolic analysis of liquid formulations of organic manures and its influence on growth and yield of Solanum lycopersicum L.(tomato) crop in field. Biocatal. Agric. Biotechnol. 8, 50–54. 43. Wang, Q., Awasthi, M. K., Zhang, Z., Wong, J. W., 2019. Sustainable composting and its environmental implications, in: Taherzadeh, M. J., Bolton, K.,Wong, J., Pandey, A. (Eds.), Sustainable Resource Recovery and Zero Waste Approaches, Elsevier. pp. 115132.

28

44. Wang, Q., Li, R., Cai, H., Awasthi, M.K., Zhang, Z., Wang, J.J., Ali, A., Amanullah, M., 2016. Improving pig manure composting efficiency employing Ca-bentonite. Ecol. Eng. 87, 157–161. 45. Wang, S.P., Zhong, X.Z., Wang, T.T., Sun, Z.Y., Tang, Y.Q., Kida, K., 2017. Aerobic composting of distilled grain waste eluted from a Chinese spirit-making process: The effects of initial pH adjustment. Bioresour. Technol. 245, 778–785. 46. Wang, X., Selvam, A., Chan, M., Wong, J.W.C., 2013. Nitrogen conservation and acidity control during food wastes composting through struvite formation. Bioresour. Technol. 147, 17–22. 47. Wong, J. W. C., Wang, X., Selvam, A., 2017. Improving compost quality by controlling nitrogen loss during composting, in: Wong, J.W.C., Tyagi, R. D., Pandey, A. (Eds.), Current Developments in Biotechnology and Bioengineering, Elsevier, pp. 59-82. 48. Yu, H., Xie, B., Khan, R., Shen, G., 2019. The changes in carbon, nitrogen components and humic substances during organic-inorganic aerobic co-composting. Bioresour. Technol. 271, 228–235. 49. Zhang, Q.L., Liu, Y., Ai, G.M., Miao, L.L., Zheng, H.Y., Liu, Z.P., 2012. The characteristics of a novel heterotrophic nitrification-aerobic denitrification bacterium, Bacillus methylotrophicus strain L7. Bioresour. Technol. 108, 35–44.

Figures Caption

29

Fig. 1. Changes in temperature (a), pH (b), electrical conductivity (c), total carbon (TC) (d), and total nitrogen (TN) (e) of different composting combinations during Indigofera biomass composting process Fig. 2. Changes in total organic matter (TOM) (a), ash content (b), organic matter degradation kinetics (c), and C/N ratio (d) of different composting combinations during Indigofera biomass composting

Tables Caption Table 1a. Combinations of raw materials used for composting Table 1b. Major physico-chemical characteristics of raw materials used for composting Table 2. Comparison of physicochemical characteristics of matured compost sample with the prescribed standards; significance difference (P<0.05) among different compost combinations are indicated by different lower case letters Table 3. Phytotoxicity test of all combinations of compost samples; significance difference (P<0.05) in plant germination index among various compost combinations are indicated by different lowercase letters Table 4. Nutrient removal from DLW by algae, bacteria, and indigenous microbial population with respect to the permissible discharge standards

30

(b) 8.2

C1

8.0

C2

C3

C4

C5

C6

C7

7.8 7.6 7.4 7.2

pH

7.0 6.8 6.6 6.4 6.2 6.0 5.8 0

5

10

15

20

25

30

35

40

45

Time of composting (days)

(c)

2.6

C1

C2

C3

C4

C5

C6

(d) 46

C7

C1

C2

C3

C4

C5

C6

30

35

C7

45

2.2

44

Total organic carbon (%)

Electrical conductivity (mS/cm)

2.4

2.0 1.8 1.6 1.4 1.2 1.0

43 42 41 40 39 38

0.8 0

5

10

15

20

25

30

35

40

37

45

0

5

10

Time of composting (Days)

15

20

25

40

45

Time of composting (days)

(e) 3.5

C1

C2

C3

C4

C5

C6

C7

3.0

Total nitrogen (%)

2.5

2.0

1.5

1.0

0.5

0.0 0

5

10

15

20

25

30

35

40

45

Time of composting (days)

Fig. 1. Changes in temperature (a), pH (b), electrical conductivity (c), total carbon (TC) (d), and total nitrogen (TN) (e) of different composting combinations during Indigofera biomass composting process

31

C1

C2

C3

C4

C5

C6

(b)

C7

30

84

28

82

26

80

24

Ash content (%)

Total organic matter (%)

(a) 86

78 76

C2

C4

C5

C6

C7

20 18

72

16 14 0

5

10

15

20

25

30

35

40

45

0

5

10

Time of composting (days)

(c) 55

C1 C4

50

C1 C5

C2 C5

C2 C6

C3 C6

C3 C7

15

20

25

30

35

40

45

Time of composting (days)

(d) 45

C4 C7

C1

C2

C3

C4

C5

C6

30

35

C7

40

45

35

40 35

C/N ratio

Organic matter losses (initial value in %)

C3

22

74

70

C1

30 25

30

25

20

20

15 10

15

5

10

0 0

5

10

15

20

25

30

35

40

45

0

5

10

15

20

25

40

45

Time of composting (days)

Time of composting (days)

Fig. 2. Changes in total organic matter (TOM) (a), ash content (b), organic matter degradation kinetics (c), and C/N ratio (d) of different composting combinations during Indigofera biomass composting

Table 1a. Combinations of raw materials used for composting

32

Combinations C1 C2 C3 C4 C5 C6 C7

Unit % % % % % % %

DSW 100 98 96 92 84 90 80

Jeevamrutha 2 4 8 12 -

Cow dung 10 20

Table 1b. Major physicochemical characteristics of raw materials used for

composting Parameters pH EC Total carbon Total nitrogen C/N Total organic matter

Unit mS/cm % % %

DSW 6.33±0.2 1.06±0.08 44.73±1.44 2.98±0.14 15.01±0.63 84.1±0.59

Jeevamrutha 4.5±0.05 4.9±0.05 37.82±1.25 1.93±0.08 19.53±0.52 67.93+2.56

33

Cow dung 6.19±0.08 3.29±0.02 42.12±1.32 1.65±0.0.05 25.38±0.23 71.32±2.27

Table 2. Comparison of physicochemical characteristics of matured compost sample with the prescribed standards; significance difference (P<0.05) among different compost combinations are indicated by different lower case letters

Parameters pH

C1 7.3 ±0.06d

EC 1.52±0.03a (mS/cm ) TOM (%) 80.54±0.30d TOC (%) 43.35±0.84d TN (%) 3.24±0.05d C/N ratio 13.12±0.08a Macro nutrients (%) K 0.76±0.1a P 0.27±0.03ab Na 0.02±0.002a Ca 0.23±0.05a Mg 0.23±0.07a Mn 1.00±0.05b Fe 1.25±0.03d Micro nutrients (mg/kg) Cu 19.53±0.15c Ni 9.62±0.45bc Zn 55.29±1.63c Cd 0.08±0.001b Cr 1.81±0.04b

FAI (2007)

SWM (2016)

C2 7.2±0.01d

C3 7.2±0.01d

C4 6.8±0.05c

C5 7.2±0.01d

C6 6.6±0.06b

C7 6.1 ±0.02a

6.5–8.5

6.5-7.5

1.92±0.06b

2.01±0.03bc

2.28±0.06d

2.07±0.07bc

2.18±0.07bc

1.97±0.05b

2-6

≤4

78.59±0.024cd 41.49±0.36cd 2.90±0.004cd 14.30±0.11a

76.58±0.59bc 41.01±0.31bc 2.58±0.19c 15.90±0.73b

72.41±0.74a 38.28±0.16a 2.71±0.22cd 14.13±0.5a

77.47±0.55c 40.51±0.11c 2.42±0.01bc 16.72±0.20b

74.55±0.22b 39.22±0.21ab 1.98±0.0.02ab 19.80±0.21c

76.75±0.50bc 39.45±0.45ab 1.71±0.035a 23.07±0.02d

>30 ≥16 1-3 <25

≥12 ≥0.8 ≤20

0.69±0.01a 0.34±0.04ab 0.03±0.005a 0.19±0.01a 0.18±0.02a 0.71±0.01a 0.76±0.01b

0.72±0.25a 0.22±0.02a 0.03±0.005a 0.14±0.004a 0.17±0.001a 0.70±0.01a 0.62±0.02a

0.67±0.18a 0.41±0.01b 0.02±0.001a 0.18±0.06a 0.17±0.04a 0.66±0.02a 0.60±0.02a

0.71±0.04a 0.38±0.005b 0.02±0.004a 0.14±0.07a 0.13±0.07a 0.47±0.08a 0.62±0.008a

0.74±0.02a 0.34±0.04ab 0.04±0.003a 0.20±0.08a 0.24±0.03a 1.0±0.02b 0.89±0.03c

0.74±0.19a 0.22±0.02a 0.02±0.002a 0.13±0.09a 0.18±0.06a 0.73±0.09a 0.68±0.02ab

0.6-1.7 0.4-1.1 -

≥0.4 ≥0.4 -

16.41±0.56b 11.44±0.45c 52.70±0.89bc 0.07±0.001ab 2.51±0.04c

11.56±0.48a 15.18±0.87d 41.48±0.68a 0.06±0.003a 3.43±0.05d

30.24±0.78d 8.4±0.2bc 90.08±2.7e 0.10±0.004d 1.71±0.06b

40.67±0.65e 4.2±0.21a 46.39±0.23ab 0.06±0.002a 1.01±0.02a

17.043±0.25b 8.13±0.45b 75.51±1.4d 0.13±0.005e 1.65±0.01b

12.16±0.24a 15.86±1.2d 43.76±2.1a 0.07±0.002ab 3.6±0.02d

≤300 ≤50 ≤1000 ≤5 ≤50

300 50 1000 5 50

34

Table 3. Phytotoxicity test of all combinations of compost samples; significance difference (P<0.05) in plant germination index among various compost combinations are indicated by different lowercase letters Compost samples

Mean Seed germinated

Mean shoot length (cm)

Mean root length (cm)

GI (%)

Control

15

3.14±0.58

3.1±0.80

100±7.70

C1

13.5

3.88±0.96

3.17±0.61

90.06±7.00

C2

14

5.16±0.73

3.68±0.56

97.42±5.27

C3

14

4.82±0.72

3.79±0.65

109.92±3.50

C4

15

5.00±0.91

3.58±0.82

129.03±4.40

C5

14

4.88±0.83

3.54±0.94

113.76±2.16

C6

14.5

5.04±0.75

3.03±0.53

96.19±4.16

C7

14

4.77±0.23

3.0±0.77

90.32±3.51

35

VI

ab

a

624.29±139 a

a

615.86±136

ab bc d c

a a

c

783.33±121

cd

806.51±132

e

900.00±173

cd

801.17±163

c

785.54±187

b

725.45±187

Table 4. Nutrient removal from DLW by algae, bacteria, and indigenous microbial population with respect to the permissible discharge standards Parameters COD (mg/L) NO3-N (mg/L) TAN (mg/L)

Untreated DLW

Algal treated DLW

Control/IMP 1887.5±88.39 700±52.23 18.22±0.23 6.35±0.23 117.36±0.64 20.4±2.39

Algae 537.5±53.0. 10.80±0.01 18.65±1.18

Bacterial treated DLW Control/IMP 400 ± 70.71 3.22 ± 0.27 16.15 ± 0.32

BM 312.5 ± 17.67 3.77 ± 0.37 15.24 ± 0.32

TDP (mg/L) 99.70±7.68 29.7±1.9 17.4±0.7 14.2 ± 0.19 12.32 ± 0.19 pH 7.2±0.18 8.67±0.09 9.65±0.07 8.59 ± 0.20 8.3 ± 0.07 TDS (mg/L) 2800±78 1300±58 1220±38 1450 ± 89 1300 ± 72 All values are expressed in mg/L except pH. DRSI: Discharge and reuse standards for irrigation DRSIS: Discharge and reuse standards Inland surface waters a,c a Choudhary et al. (2016) b According to General Standards for Discharge of Environmental Pollutants for inland surface water, The Environment (Protection) Rules, 1986 given by Central Pollution Control Board, India. c According to Jordanian Standard (JS: 893/2002) for effluent reuse for agricultural irrigation 1 and 2, adopted from “A compendium of standards for wastewater reuse inthe Eastern Mediterranean Region” World Health Organization (WHO-EM/CEH/142/E). d According to treated wastewater criteria for reuse in Kuwait, adopted from “A compendium of standards for wastewater reuse in the Eastern Mediterranean Region” World Health Organization (WHO-EM/CEH/142/E). e Source: Schedule-I: Standards for Emission or Discharge of Environmental Pollutants from various Industries (Common Effluent Treatment Plants), The Environment (Protection) Rules, 1986 given by Central Pollution Control Board, India.

BL 375±35.35 3.51±0.40 11.37±1.29

13.37±0.32 8.14±0.07 1300±68

Credit author statement

The contribution of individual authors has been described below: Lopa Pattanaik (First Author): Conducting research and investigation, specifically performing the experiments, data collection, and preparation of manuscript

36

Duraivadivel P.: Specifically performing the experiments of isolation of pure culture bacteria and studying their nutrient removal efficiency Dr. Hariprasad P.: Ideas, formulation or evolution of overarching research goals and aims, development of methodology for experiment *Dr. S.N Naik, Professor (Corresponding Author): Ideas, formulation or evolution of overarching research goals and aims

Declaration of Interest Statement Manuscript title: Utilization and re-use of solid and liquid waste generated from the natural indigo dye production process- A zero waste approach The authors whose names are listed immediately below certify that they have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript. We (authors) hereby declare the followings: (1) the

information in the manuscripts is true, correct and we do not have any conflict of interest, (2) all

authors mutually agree that the manuscript is submitted to BITE, and (3) this work has not been published/submitted or being submitted to another journal.

Author names:

37

Lopa Pattanaik, Center for Rural Development Technology (CRDT), Indian Institute of Technology-Delhi (IIT-D), Hauz Khas, New Delhi Duraivadivel P., Center for Rural Development Technology (CRDT), Indian Institute of Technology-Delhi (IIT-D), Hauz Khas, New Delhi Dr. Hariprasad P., Center for Rural Development Technology (CRDT), Indian Institute of Technology-Delhi (IIT-D), Hauz Khas, New Delhi Dr. S.N Naik, Professor, Center for Rural Development Technology (CRDT), Indian Institute of Technology-Delhi (IIT-D) Hauz Khas, New Delhi -110016, India, Email: [email protected], [email protected], Phone: +91-9818294067

Graphical Abstract

38



Conversion of solid waste to compost for its re-use in Indigofera cultivation.



Enhancement of compost quality by using Jeevamrutha as inoculum.



Treatment of liquid waste by diverse micro-flora for nutrient removal and water reuse.



Nutrient removal was significant using bacteria and indigenous microbes over algae.

39