Research article

Odd-order differential equations with deviating arguments: asymptomatic behavior and oscillation

  • Despite the growing interest in studying the oscillatory behavior of delay differential equations of even-order, odd-order equations have received less attention. In this work, we are interested in studying the oscillatory behavior of two classes of odd-order equations with deviating arguments. We get more than one criterion to check the oscillation in different methods. Our results are an extension and complement to some results published in the literature.

    Citation: A. Muhib, I. Dassios, D. Baleanu, S. S. Santra, O. Moaaz. Odd-order differential equations with deviating arguments: asymptomatic behavior and oscillation[J]. Mathematical Biosciences and Engineering, 2022, 19(2): 1411-1425. doi: 10.3934/mbe.2022065

    Related Papers:

    [1] Ana Paula Guedes Pinheiro, Augusto Bücker, Ana Cláudia Cortez, John Edward Hallsworth, João Vicente Braga de Souza, Érica Simplício de Souza . Vinegar production from Theobroma grandiflorum SCHUM (cupuassu). AIMS Bioengineering, 2021, 8(4): 257-266. doi: 10.3934/bioeng.2021022
    [2] Flávia da Silva Fernandes, Luan Reis Honorato da Silva, Érica Simplício de Souza, Lívia Melo Carneiro, João Paulo Alves Silva, Steven Zelski, João Vicente Braga de Souza, Jacqueline da Silva Batista . Isolation, genetic identification of Amazonian yeasts and analysis of thermotolerance and alcohol tolerance of Saccharomyces cerevisiae from Theobroma grandiflorum and Eugenia stipitata. AIMS Bioengineering, 2024, 11(1): 24-43. doi: 10.3934/bioeng.2024003
    [3] Kevyn Melo Lotas, Raissa Sayumy Kataki Fonseca, Joice Camila Martins da Costa, Ana Claudia Alves Cortez, Francisca das Chagas do Amaral Souza, Márcio Rodrigues Barreto, Lívia Melo Carneiro, João Paulo Alves Silva, Eveleise Samira Martins Canto, Flávia da Silva Fernandes, João Vicente Braga de Souza, Érica Simplício de Souza . Optimization of laccase production by Pleurotus ostreatus (Jacq.) P. Kumm. using agro-industrial residues: a comparative study on peels of tucumã (Astrocaryum aculeatum G. Mey.) and pupunha (Bactris gasipaes Kunth) fruits. AIMS Bioengineering, 2024, 11(4): 561-573. doi: 10.3934/bioeng.2024025
    [4] Zongyuan Zhu, Rachael Simister, Susannah Bird, Simon J. McQueen-Mason, Leonardo D. Gomez, Duncan J. Macquarrie . Microwave assisted acid and alkali pretreatment of Miscanthus biomass for biorefineries. AIMS Bioengineering, 2015, 2(4): 449-468. doi: 10.3934/bioeng.2015.4.449
    [5] Tutuka Dlume, Nonso E. Nnolim, Uchechukwu U. Nwodo . Exiguobacterium acetylicum transformed poultry feathers into amino acids through an extracellular secretion of keratinolytic enzymes. AIMS Bioengineering, 2024, 11(4): 489-505. doi: 10.3934/bioeng.2024022
    [6] Frank R. Bengelsdorf, Christina Gabris, Lisa Michel, Manuel Zak, Marian Kazda . Syntrophic microbial communities on straw as biofilm carrier increase the methane yield of a biowaste-digesting biogas reactor. AIMS Bioengineering, 2015, 2(3): 264-276. doi: 10.3934/bioeng.2015.3.264
    [7] Nikolaos Giormezis, Konstantinos Papakonstantinou, Fevronia Kolonitsiou, Eleanna Drougka, Antigoni Foka, Styliani Sarrou, Evangelos D. Anastassiou, Efthimia Petinaki, Iris Spiliopoulou . Biofilm synthesis and its relationship with genetic characteristics in clinical methicillin-resistant staphylococci. AIMS Bioengineering, 2015, 2(4): 375-386. doi: 10.3934/bioeng.2015.4.375
    [8] Clara Navarrete, José L. Martínez . Non-conventional yeasts as superior production platforms for sustainable fermentation based bio-manufacturing processes. AIMS Bioengineering, 2020, 7(4): 289-305. doi: 10.3934/bioeng.2020024
    [9] Urooj Ainuddin, Maria Waqas . Finite state machine and Markovian equivalents of the lac Operon in E. coli bacterium. AIMS Bioengineering, 2022, 9(4): 400-419. doi: 10.3934/bioeng.2022029
    [10] Olga M. Tsivileva, Inna M. Uchaeva, Nikolay A. Yurasov . Biotesting of technologically important carboxy containing acridones with solid-state fungal culture. AIMS Bioengineering, 2021, 8(1): 1-13. doi: 10.3934/bioeng.2021001
  • Despite the growing interest in studying the oscillatory behavior of delay differential equations of even-order, odd-order equations have received less attention. In this work, we are interested in studying the oscillatory behavior of two classes of odd-order equations with deviating arguments. We get more than one criterion to check the oscillation in different methods. Our results are an extension and complement to some results published in the literature.



    The policy of reducing gas emissions and the oil price are essential issues from the fuel industry. Besides, the world population is estimated to increase to 9.6 billion people by 2050, and ethanol production is projected to increase 3.4-fold by 2035. Therefore, the search for renewable sources of biomass will become increasingly essential [1],[2]. The USA and Brazil are the world's largest ethanol producers. Nowadays, bioethanol is the major source of renewable biofuel with about 29,000 (Mil. Gal.) produced in 2019 [3]. Brazil produces 33.8 billion liters of ethanol through sugarcane fermentation, 10.2 billion liters of anhydrous ethanol, and 23.6 billion liters of hydrous ethanol [4].

    Last decade studies have investigated the improvement of the sector producing ethanol from lignocellulosic biomass, especially agro-industrial waste [5][8]. Usually, conventional acid hydrolysis or/and enzymatic hydrolysis are the possible ways to be undertaken to achieve bioethanol production from biomass. [9] The acid hydrolysis processes require severe conditions such as high temperatures and low pH. The advantages of this process are that the acid can penetrate lignin without pretreatment, and the acid hydrolysis is faster and cheaper than enzyme hydrolysis [10],[11]. Therefore, the investigation of biomass for acid hydrolysis has been carried out worldwide. Acid hydrolysates with high fermentability were obtained with potato peel, wood chips, rice straw, maple wood, wood, sugar cane bagasse, and Paja brava [8],[12][19].

    Open markets from city of Manaus (Amazonas State- Brazil) produce 95.4 tons of vegetal waste per day. Carbohydrates, such as cellulose, starch and other polysaccharides can be found in fruits and processed waste in ethanol [20]. The present study was the first to screen vegetal wastes to produce acid hydrolysate suitable for ethanol fermentation. In addition, we investigated the influence of hydrolysis factors in the final concentration of fermentable sugars and furfural.

    The wastes investigated were a) peel from the fruit of Astrocaryum aculeatum Meyer, b) peel from the fruit of Bactris gasipaes Kunth, c) straw obtained from endocarp of the fruit of Euterpe oleracea Mart., d) peel from the fruit of Theobroma grandiflorum Schumann, and e) peel from the root of Manihot esculenta Crant. These wastes were obtained from open markets from the city of Manaus in January and April 2015. Wastes were washed with distillate water, grounded (< 3 mm) in a Skymsen Blender, 1.5 L, dried (80 °C for 6 h), and stored at −20 °C.

    Saccharomyces cerevisiae PE-2 (Strain 2) was provided by the Sugar Cane Technology Center, from the Junqueira factory (São Paulo, Brazil). This strain tolerates industrial conditions, such as ethanol tolerance and temperature changes [13],[14]. We maintained this strain in Sabouraud agar (dextrose 40 g/L, peptone 10 g/L, and agar 20 g/L).

    Acid hydrolysis was performed as described previously [21] with some modifications: the residue (5 g) and 50 mL of 3.7% w/w sulfuric acid were transferred to Erlenmeyer flasks (150 mL). The mixture was incubated in an autoclave (Autoclave Vertical Class B, FANEM, São Paulo, Brazil) with heating from room temperature 25 to 121 °C (9 min) and after reaching the 121 °C (15 psi) the hydrolysis was carried out for 15 min and we wait to the autoclave to reach room temperature (30 min). The hydrolysate neutralized (pH 7.0, NaOH) and filtrated 0.11 µm (Whatman® qualitative filter paper, grade 1, United States of America). The acid hydrolysates were characterized (sugars and furfural) before and after a detoxification step filtration through activated charcoal.

    The detoxification step was carried out by mixing the hydrolysate with 1% activated carbon (Merck KGaA, Darmstadt, Germany) followed by orbital agitation (100 rpm at 60 °C for 30 min). At the end of each, the resulting precipitate was removed by 11 µm filtration (Whatman® qualitative filter paper, grade 1, United States of America) to remove precipitate formed [22].

    Fermentation tests were carried out in 125 mL Erlenmeyer Flasks with airlock [9]. Hydrolysates without any nutrient correction (50 mL) were inoculated with Saccharomyces cerevisiae PE-2 at 1 × 107 cells/mL and incubated under orbital agitation (100 rpm) at room temperature (25 °C). Samples were taken after 0, 6, 12, 16, 24, 36, 48, 56, and 72 h and analyzed for cell biomass, reducing sugars, and ethanol. Acid hydrolysates were concentrated about five times (thermal oven at 80 °C) to kinetics studies on fermentation and again passed through the neutralization (NaOH, pH 7.0) and detoxification steps.

    The assays were carried out according to the experimental design 23 with 3 central points (Table 1) (de Barros Neto et al. 1995) evaluating the influence of the a) hydrolysis time (min); b) H2SO4-to-waste ratio (w/w) and c) solid-to-liquid ratio (w/v). The response variables were reducing sugars (g/L) and furans (g/L).

    Table 1.  Levels that were used to determine the influence of the concentrations of H2SO4-to-waste ratio (g/g), solid-to-liquid ratio (g/mL) and time (min) in acid hydrolysis according to 23 factorial design.
    Levels
    Factors −1 0 1
    H2SO4 to liquid ratio peel (g/g) 0.11 0.37 0.63
    Solid to liquid ratio (g/mL) 0.03 0.10 0.17
    Time (min) 4.4 15 25.6

     | Show Table
    DownLoad: CSV

    Acid hydrolysates were characterized for their monosaccharides by high-performance liquid chromatography (HPLC). The analysis was carried out on a Waters instrument, equipped with a refractive index detector and a BIO-RAD Aminex column HPX 87H (300 7.8 mm; Bio-Rad, Hercules, CA, USA), coupled to a refractive index detector (RID-6A). Sulfuric acid 0.005 mol/L was used as eluent at a flow rate of 0.6 mL/min, column temperature of 45◦C, and injected volume of 20 µL. The samples were previously filtered through a Sep-Pak C18 filter (Sigma Aldrich, USA). Concentrations of furfural and hydroxymethylfurfural (HMF) were also determined by High-Performance Liquid Chromatography Performance (HPLC) on a Waters machine with UV/Vis detector and HP-RP18 (200 × 4.6 mm), coupled to an ultraviolet detector SPD-10A UV–VIS in a wavelength of 276 nm, with eluent acetonitrile: water (1 : 9), and 1% of acetic acid. The used flow was 0.8 mL/min, the column temperature was 25 °C, and the volume injected was 20 µL.

    Sugars and furans of analytical standard were used for the construction of the quantitative standard curves used. Sugar concentration ranged from 0.02 g/L to 4.0 g/L. Furans concentration ranged from 1.0 mg/L to 150 mg/L.

    The concentration of reducing sugars (RS) was determined by the 3,5-Dinitrosalicylic acid dinitro method –DNS. Samples were centrifuged at 3,500 rpm for 5 min, diluted with distilled water, and added 1 mL of the DNS reagent, and we incubated the mixture in a boiling water bath for 5 min. After cooling to room temperature, we measured the absorbance of the supernatant at 540 nm (Spectrophotometer 600 plus, Fenton, São Paulo). The absorbance values for the substrate and enzyme blanks were subtracted from the absorbance value for the sampled sample. The observed absorbance was correlated to the concentration of reducing sugar using a standard glucose curve [23].

    The formation of inhibitory products mainly containing furfural and 5-hydroxymethyl furfural (HMF) after acid hydrolysis stage was monitored as total furans in mg/L as estimated by applying the methodology described by Martinez et al. [24]. Aliquots of the filtrates were previously centrifuged (15 min at 10,500 g); the pH adjusted to 7.0 with 0.1 M phosphate buffer, and absorbance (Spectrophotometer 600 plus, Fenton, São Paulo) was measure at 284 nm and 320 nm. The formula developed by Martinez et al. [24] was used to estimate the total furans in mg/L: Total Furans = (A284 − A320 − 0.056) / 0.127.

    S. cerevisiae cell growth was determined by measuring the optical density at 600 nm (Spectrophotometer 600 plus, Fenton, São Paulo) of the fermentation broth without centrifugation. Biomass (g/L) was determined using a calibration curve relating biomass (dry weight) to optical density.

    Fermented media samples were steam-distilled in a Tecnal model Te-012 micro still before ethanol concentration determination. Ethanol concentration was determined by spectrophotometer (Spectrophotometer 600 plus, Fenton, São Paulo) at 600 nm using the potassium dichromate method [25]. Ethanol yield was calculated as produced ethanol amount divided by the theoretical amount (calculated based on the quantity of sugar in the must) and expressed as a percentage w/w.

    All the experiments were carried out in triplicates and the data presented are the mean of the results and the standard deviation calculated for each analysis. The influence of the variables using the factorial design was performed using STATGRAPHICS PLUS software (version 4. 1).

    We carried out the hydrolysis of the wastes obtaining the hydrolysates. Then we submitted the hydrolysates to the analysis of the composition of their monomers and fermentation inhibitors by HPLC (Table 2). Among the wastes studied, hydrolysates of the peel of Bactris gasipaes and the peel of Manihot esculenta root had the highest concentrations of the monomers, with total monomers mass of 40.6 and 18.0 g/L, respectively.

    Table 2.  Concentration of carbohydrate monomers (glucose, xylose and arabinose) and furans (furfural and HMF) in hydrolysates obtained by acid hydrolysis of plant residues obtained from open markets in the city of Manaus (state of Amazonas, Brazil).
    Biomass Hydrolysates chemical constituents
    Glucose (g/L) Arabinose (g/L) Xylose (g/L) Furfural (mg/L) HMF (mg/L)
    Peel of Bactris gasipaes 33 ± 2 1.0 ± 0.1 7.1± 0.7 22 ± 1 189 ± 17
    Peel of Manihot esculenta 16.3 ± 0.07 0.32 ± 0.01 1.42 ± 0.04 9 ± 1 69 ± 3
    Peel of Theobroma grandiflorum 0.2 ± 0.1 0.2 ± 0.1 2.5 ± 0.3 37 ± 3 17 ± 6
    Peel of Astrocaryum aculeatum 1.04 ± 0.07 2.5 ± 0.2 5.5 ± 0.5 8 ± 2 19 ± 4
    Straw of Euterpe oleracea 0.45 ± 0.05 0.59 ± 0.07 11.1 ± 0.3 71 ± 7 32 ± 2

     | Show Table
    DownLoad: CSV

    We observed that the peels of Bactris gasipaes and Manihot esculenta were suitable to be converted into substrates rich in fermentable sugars. These two residues also had the highest concentration of starch [26],[27]. This result agrees with previous works that demonstrate the better potential of starchy products to produce acid hydrolysates rich in sugars [9].

    The sugar content observed in the hydrolysates of Bactris gasipaes peel hydrolysate was satisfactory in comparison with results proposed in previous works reported in the literature [8],[13],[16],[28][30]. Oberoi et al. [31] obtained 50.8 g/L of sugar concentration in acid hydrolyzed orange peel. In another study, Chandel et al. [32] got maximum of the release of sugars of 30.29 g/L for acid hydrolysis of sugarcane bagasse.

    We did detoxification of the hydrolysate with activated coal. We have done this detoxification to remove fermentation inhibitors as Furfural and Hydroxymethylfurfural (HMF). These inhibitory compounds hinder the growth and metabolism of the microbes during the fermentation process and the severity of their effect on the cell increases with their concentration [33]. The detoxification treatment provided a complete furfural removal. In addition, the detoxification caused a reduction of 71% and 92% of HMF from Manihot esculenta and Bactris gasipaes, respectively. We also observed a reduction in the concentration of fermentable sugars (glucose, xylose, and arabinose), reaching losses between 17–30% (Table 3).

    Table 3.  Monomer concentration, furfural, and hydroxymethylfurfural Amazon waste after detoxification by activated carbon.
    Biomass Hydrolysates chemical constituents
    Glucose (g/L) Arabinose (g/L) Xylose (g/L) Furfural (mg/L) HMF (mg/L)
    Peel of Manihot esculenta 13.48 ± 0.07 0.27 ± 0.01 1.19 ± 0.05 - 20 ± 4
    Peel of Bactris gasipaes 24 ± 2 0.8 ± 0.1 5.5 ± 0.7 - 14.9 ± 0.2
    Peel of Theobroma grandiflorum 0.2 ± 0.1 0.2 ± 0.2 1.7 ± 0.2 - -
    Peel of Astrocaryum aculeatum 0.81 ± 0.08 1.9 ± 0.2 4.7 ± 0.5 - -
    Straw of Euterpe oleracea 0.30 ± 0.05 0.44 ± 0.08 8.2 ± 0.3 - -

    *Note: - Not detected by chromatography.

     | Show Table
    DownLoad: CSV

    We obtained concentrations of inhibitors lower than those described in the literature as impeding yeast fermentation. According to Ask et al. [34] the maximum concentrations of HMF and furfural that allow the growth of Saccharomyces cerevisiae strain VTT C-10883 is 1.30 g/L of HMF and 0.40 g/L of furfural. Thus, the concentrations (maximum of 30 mg/L of HMF and free of furfural) of furans present in the detoxified hydrolysates of this study can be considered low enough not to interfere with the production of ethanol. Similar results of detoxification with activated carbon were previous described. Arruda et al. [35] treatment with activated carbon reduced phenols in sugarcane bagasse hydrolysate to 88.5%. Sarawan [36] demonstrated a 98% and 88% removal efficiency for furfural and 5-hydroxymethylfurfural (HMF) respectively, with a 7% reducing sugar loss from acid-pretreated sorghum leaf (SL) wastes.

    To investigate the fermentability of the hydrolysates obtained after the detoxification, we concentrated and evaluated the conversion of sugars of the hydrolysates in ethanol in a fermentation assay with Saccharomyces cerevisiae. In the assays, the initial sugar concentration in the hydrolysates of Manihot esculenta and Bactris gasipaes peels were 65.75 g/L and 96.68 g/L, respectively. Sugars were consumed during de fermentation with high fermentability (Figure 1). The yeast produced 29 g/L (2.9% w/w), and 44 g/L (4.4% w/w), of ethanol in 72 h for the cultures conducted in Manihot esculenta and Bactris gasipaes hydrolysates, respectively (Figure 1). As for the concentration of ethanol achieved, Oberoi et al. [31] report a 1.2% (w/w) of ethanol from acid hydrolyzed orange peel. In another study, Manikandan et al. [37] obtained ethanol production of 9.8% (w/w) from banana peel acid hydrolysate after 120 h fermentation with mutant strains of Saccharomyces cerevisiae.

    Figure 1.  The concentration of reducing sugars (g/L), ethanol yield (g/L), and cell (dry weight, g/L) during alcoholic fermentation of the acid hydrolysate of the peel of Bactris gasipaes (A) and peel of the root of Manihot esculenta (B).

    The peel of Bactris gasipaes due to the high content of fermentable sugars in the hydrolysates was selected to investigate the influence of hydrolysis factors in the variables reducing sugars and furans, we carried out hydrolysis experiments according to a factorial design 23 investigating the influence of time, H2SO4 to waste ratio and liquid to solid ratio. The peel of Bactris gasipaes was the residue selected for these experiments. Table 4 shows the levels of factors used and the results of the response variables. The reducing sugar concentration ranged from 1.6 to 48.9 g/L, demonstrating the high effect of the factors investigated.

    Table 4.  Influence of the factors H2SO4-to-residue ratio (g/g), solid-to-liquid ratio (g/mL), and time (min) in the response variables reducing sugars and total furans experiments performed according to a factorial design 23 + midpoints.
    Exp. Variables (real values) Responses
    H2SO4-to-residue ratio (g/g) Solid-to-liquid ratio (g/mL) Time (min) Reducing Sugars (g/L) Furans (mg/L)
    1 0.37 0.10 15.0 25.9 8.8
    2 0.63 0.17 4.4 48.9 21.6
    3 0.11 0.17 25.6 16.6 12.0
    4 0.63 0.03 4.4 6.4 10.0
    5 0.11 0.17 4.4 21.7 4.4
    6 0.63 0.17 25.6 37.1 22.0
    7 0.11 0.03 4.4 1.6 0.6
    8 0.63 0.03 25.6 6.1 4.2
    9 0.37 0.10 15.0 27.1 6.5
    10 0.37 0.10 15.0 23.5 7.4
    11 0.11 0.03 25.6 3.0 0.7

     | Show Table
    DownLoad: CSV

    The main effects and their interactions calculated from the data in Table 4 are presented in Table 5.

    Table 5.  Effect of variables H2SO4 to residue ratio (A), solid to liquid ratio (B), and their second order interactions (AB; AC; BC) on to produce reducing sugars and furans calculated from the data presented in Table 4.
    Effect estimated Reducing sugars (g/L) Furans (mg/L)
    Average 19.80 ± 0.55* 8.92 ± 0.35*
    A: H2SO4-to-residue ratio (g/g) 13.92 ± 1.30* 10.02 ± 0.82*
    B: solid-to-liquid ratio (g/mL) 26.82 ± 1.30* 11.12 ± 0.82*
    C: Time (min) −3.93 ± 1.30 0.57 ± 0.82
    AB 9.94 ± 1.30* 3.57 ± 0.82
    AC −2.09 ± 1.30 −3.27 ± 0.82
    BC −4.47 ± 1.30 3.42 ± 0.82

    *Note: Standard errors in a pure error with 2 degrees of freedom, *: Effects statistically significant at 95% confidence.

     | Show Table
    DownLoad: CSV

    In the statistical analysis, the significant effects in reducing sugars (p < 0.05) were: H2SO4 to residue ratio (A), solid to liquid ratio (B), and their interaction (AB). The significant factors in furans were: H2SO4 to residue ratio (A), solid to liquid ratio (B).

    Based on the significant effects, models predicted the sugar and furans content in the hydrolysate as a function of the hydrolysis condition. (Equations 1 and 2).

    Reducing sugars (g/L)=0.94+0.27*A+90.23*B+268.92*A*B

    Furans (mg/L)=0.94+0.27*A+90.23*B+268.92*A*B

    The analysis of variance (ANOVA) of the mathematical models described by Equations 1 and 2 are presented in Tables 6 and 7, respectively. Both models were significant at 95% confidence, no lack of adjustment, and reaching determination coefficients higher than 80%. Thus, both models were considered suitable for representation as response surfaces.

    Table 6.  Analysis of variance of the response reducing sugars in the hydrolysates of Bactris gasipaes peel under different ratios of H2SO4-to-residue ratio (g/g) and solid-to-liquid ratio (g/mL).
    Source Sum of squares DF Mean Square F-Value p-value
    Model 2025.3 3 675.1 21.2 0.0007
    A: H2SO4-to-residue (g/g) 388.0 1 388.0 12.2 0.0102
    B: solid-to-liquid ratio (g/mL) 1439.4 1 1439.4 45.1 0.0003
    AB 197.9 1 197.9 6.2 0.0415
    Residual 223.2 7 31.9
    Lack of Fit 216.5 5 43.3 12.8 0.0739
    Pure error 6.8 2 3.4
    Total 2248.5 10
    Coefficient of determination (R2) 90.1%
    Adjusted coefficient of determination (Adj-R2) 85.8%

    *Note: *Significant at 95% confidence: p < 0.05.

     | Show Table
    DownLoad: CSV
    Table 7.  Analysis of variance of the response “total furans” in the hydrolysates of Bactris gasipaes peels under different ratios of H2SO4-to-residue ratio (g/g) and solid-to-liquid ratio (g/mL).
    Source Sum of squares DF Mean Square F-Value p-value
    Model 448.5 2 224.3 22.0 0.0006
    A: H2SO4-to-residue (g/g) 201.0 1 201.0 19.7 0.0022
    B: solid-to-liquid ratio (g/mL) 247.5 1 247.5 24.2 0.0012
    Residual 81.7 8 10.2
    Lack of Fit 79.0 6 13.2 9.8 0.0955
    Pure Error 2.7 2 1.3
    Total 530.2 10
    Coefficient of determination (R2) 84.6%
    Adjusted coefficient of determination (Adj-2) 80.7%

    *Note: **Significant at 95% confidence: p < 0.05.

     | Show Table
    DownLoad: CSV

    Response surfaces (Figures 2 and 3) describe the behavior of total sugar and furan concentrations as a function of hydrolysis conditions, as predicted by the models (Equations 1 and 2). The responses surface graphs showed that the increase in the H2SO4 to waste ratio (g/g) and solid to liquid ratio (g/L) favored the release of sugars in the hydrolysate and the formation of furans (Figures 2 and 3).

    Figure 2.  Response surface demonstrating the effect of the ratio solid-to-liquid ratio (g/g) and H2SO4-to-waste ratio (g/mL) in the concentration of reducing sugars (g/mL) in the acid hydrolysate of the peel of Bactris gasipaes.
    Figure 3.  Response surface demonstrating the effect of the solid-to-liquid ratio (g/g) and H2SO4-to-waste ratio (g/mL) in the concentration of Furans (mg/L) in the acid hydrolysate of the peel of Bactris gasipaes.

    The maximum sugar content, approximately 49 g/L of total reducing sugars, was, obtained in hydrolysis using 0.17 solid to liquid ratio (g/mL) and 0.63 H2SO4 to waste ratio (g/g) and 4.4-minute reaction times. The total amount of sugars achieved in Bactris gasipaes peel hydrolysis, about 49 g/L, was high compared to the literature in studies reporting hydrolysates from various lignocellulosic materials, which generally reached values between 6.9 and 36.5 g/L of total sugars (Table 8). This result shows the great potential of Bactris gasipaes peel, as a residue to produce high content of monosaccharide hydrolysates, which can be used as a substrate in bioprocesses such as ethanol production.

    Table 8.  Optimal parameters for obtaining hydrolysates from various agro-industrial wastes, determined by previous works.
    Waste Concentration of H2SO4 w/v (%) Temperature (°C) Duration (min) Total sugar (g/L) References
    Bactris gasipaes 7.4 121 4.4 48.9 Present study
    Sugar cane bagasse 7.0 121 45 6.9 Morais and Broetto et al.[38]
    Brewery waste 2.0 121 15 26.3 Carvalheiro et al.[39]
    Spent coffee grounds 1.0 162 45 33.5 Mussatto et al.[40]
    Corn Stover 1.5 120 15 17.8 Kabir et al.[19]
    Rice Straw 1.5 120 20 15.4 Kabir et al.[19]
    Wheat Straw 1.5 120 20 20.6 Kabir et al.[19]

     | Show Table
    DownLoad: CSV

    This study is important since we are presenting the literature wastes from the Amazon biomass able to be used in ethanol production. Open markets from the city of Manaus produce about 35 tons of vegetal residue daily including tons of the peel from the fruit of Bactris gasipaes and peel of Manihot esculenta root. Instead of their abundance, few studies investigated these vegetal wastes as substrates for biotechnological uses [41]. The results obtained in the present study are auspicious, and this residue of Bactris gasipaes of Amazon regional agriculture presents potential as a substrate for acid hydrolysis and ethanol fermentation.

    Waste management is a huge field and improving methods of collecting, distributing, reusing, transforming, and disposing of wastes is an important work to help protect the interests of the environment and sustain our growing population. Among the wastes studied, hydrolysates of the peel of Bactris gasipaes had the highest concentrations of the monomers. After the detoxification treatment provided a complete furfural removal. The reducing sugars generated by the acid hydrolysis of cassava and peach palm peel could be fermented by ethanol. We produced information about the influence of acid/residue ratio, the ratio of solid/liquid, and time in the hydrolysate of the peel of Bactris gasipaes. The maximum sugar content, approximately 49 g/L of total reducing sugars, was, obtained in hydrolysis using 0.17 solid to liquid ratio (g/mL) and 0.63 H2SO4 to waste ratio (g/g) and 4.4-minute reaction times. This is the first study to submit residues from the Amazon Forest to acid hydrolysis, resulting in important information for discussion of the second-generation biofuel.



    [1] R. P. Agarwal, C. Zhang, T. Li, Some remarks on oscillation of second order neutral differential equations, Appl. Math. Comput., 274 (2016), 178–181. doi: 10.1016/j.amc.2015.10.089. doi: 10.1016/j.amc.2015.10.089
    [2] M. Bohner, S. R. Grace, I. Jadlovska, Oscillation criteria for second-order neutral delay differential equations, Electron. J. Qual. Theo. Differ. Equ., 60 (2017), 1–12. doi: 10.14232/ejqtde.2017.1.60. doi: 10.14232/ejqtde.2017.1.60
    [3] A. Muhib, On oscillation of second-order noncanonical neutral differential equations, J. Inequal. Appl., 2021 (2021), 1–11. doi: 10.1186/s13660-021-02595-x. doi: 10.1186/s13660-021-02595-x
    [4] J. Dzurina, S. R. Grace, I. Jadlovska, T. Li, Oscillation criteria for second-order Emden–Fowler delay differential equations with a sublinear neutral term, Math. Nachr., 293 (2020), 910–922. doi: 10.1002/mana.201800196. doi: 10.1002/mana.201800196
    [5] G. E. Chatzarakis, O. Moaaz, T. Li, B. Qaraad, Some oscillation theorems for nonlinear second-order differential equations with an advanced argument, Adva. Differ. Eq., 2020 (2020), 1–17. doi: 10.1186/s13662-020-02626-9. doi: 10.1186/s13662-020-02626-9
    [6] O. Moaaz, E. M. Elabbasy, B. Qaraad, An improved approach for studying oscillation of generalized Emden–Fowler neutral differential equation, J. Ineq. Appl., 2020 (2020), 1–18. doi: 10.1186/s13660-020-02332-w. doi: 10.1186/s13660-020-02332-w
    [7] O. Moaaz, M. Anis, D. Baleanu, A. Muhib, More effective criteria for oscillation of second-order differential equations with neutral arguments, Mathematics, 8 (2020), 986. doi: 10.3390/math806098. doi: 10.3390/math806098
    [8] S. S. Santra, R. A. El-Nabulsi, Kh. M. Khedher, Oscillation of Second-Order Differential Equations With Multiple and Mixed Delays under a Canonical Operator, Mathematics, 9 (2021), 1323. doi: 10.3390/math9121323. doi: 10.3390/math9121323
    [9] S. S. Santra, Kh. M. Khedher, O. Moaaz, A. Muhib, S-W Yao, Second-order impulsive delay differential systems: necessary and sufficient conditions for oscillatory or asymptotic behavior, Symmetry, 13 (2021), 722. doi: 10.3390/sym13040722. doi: 10.3390/sym13040722
    [10] S. S. Santra, A. K. Sethi, O. Moaaz, Kh. M. Khedher, S-W. Yao, New oscillation theorems for second-order differential equations with canonical and non canonical operator via Riccati transformation, Mathematics, 9 (2021), 1111. doi: 10.3390/math9101111. doi: 10.3390/math9101111
    [11] A. Alghamdi, C. Cesarano, B. Almarri, O. Bazighifan, Symmetry and its importance in the oscillation of solutions of differential equations, Symmetry, 13 (2021), 650. doi: 10.3390/sym13040650. doi: 10.3390/sym13040650
    [12] O. Moaaz, Ch. Park, A. Muhib, O. Bazighifan, Oscillation criteria for a class of even-order neutral delay differential equations, J. Appl. Math. Comput., 63 (2020), 607–617. doi: 10.1007/s12190-020-01331-w. doi: 10.1007/s12190-020-01331-w
    [13] O. Moaaz, C. Cesarano, A. Muhib, Some new oscillation results for fourth-order neutral differential equations, Eur. J. Pure Appl. Math., 13 (2020), 185–199. doi: 10.29020/nybg.ejpam.v13i2.36. doi: 10.29020/nybg.ejpam.v13i2.36
    [14] O. Bazighifan, T. Abdeljawad, Q. M. Al-Mdallal, Differential equations of even-order with p-Laplacian like operators: qualitative properties of the solutions, Adv. Differ. Equ., 2021 (2021), 96. doi: 10.1186/s13662-021-03254-7. doi: 10.1186/s13662-021-03254-7
    [15] O. Bazighifan, F. Minhos, O. Moaaz, Sufficient conditions for oscillation of fourth-order neutral differential equations with distributed deviating arguments, Axioms, 9 (2020), 39. doi: 10.3390/axioms9020039. doi: 10.3390/axioms9020039
    [16] O. Moaaz, S. Furuichi, A. Muhib, New comparison theorems for the nth order neutral differential equations with delay inequalities, Mathematics, 8 (2020), 454. doi: 10.3390/math8030454. doi: 10.3390/math8030454
    [17] O. Moaaz, R. A. El-Nabulsi, O. Bazighifan, Oscillatory behavior of fourth-order differential equations with neutral delay, Symmetry, 12 (2020), 371. doi: 10.3390/sym12030371. doi: 10.3390/sym12030371
    [18] C. Park, O. Moaaz, O. Bazighifan, Oscillation results for higher order differential equations, Axioms, 9 (2020), 14. doi: 10.3390/axioms9010014. doi: 10.3390/axioms9010014
    [19] M. Aktas, A. Tiryaki, A. Zafer, Oscillation criteria for third-order nonlinear functional differential equations, Appl. Math. Lett., 23 (2010), 756–762. doi: 10.1016/j.aml.2010.03.003. doi: 10.1016/j.aml.2010.03.003
    [20] B. Baculikova, E. M. Elabbasy, S. H. Saker, J. Dzurina, Oscillation criteria for third-order nonlinear differential equations, Math. Slovaca, 58 (2008), 201–220. doi: 10.2478/s12175-008-0068-1. doi: 10.2478/s12175-008-0068-1
    [21] O. Moaaz, J. Awrejcewicz, A. Muhib, Establishing new criteria for oscillation of odd-order nonlinear differential equations, Mathematics, 8 (2020), 607–617. doi: 10.3390/math8060937. doi: 10.3390/math8060937
    [22] O. Moaaz, I. Dassios, W. Muhsin, A. Muhib, Oscillation Theory for Non-Linear Neutral Delay Differential Equations of Third Order, Appl. Sci., 10 (2020), 4855. doi: 10.3390/app10144855. doi: 10.3390/app10144855
    [23] O. Moaaz, E. M. Elabbasy, E. Shaaban, Oscillation criteria for a class of third order damped differential equations, Arab J. Math. Sci., 24 (2018), 16–30. doi: 10.1016/j.ajmsc.2017.07.001. doi: 10.1016/j.ajmsc.2017.07.001
    [24] O. Moaaz, D. Baleanu, A. Muhib, New aspects for non-existence of kneser solutions of neutral differential equations with odd-order, Mathematics, 8 (2020), 494. doi: 10.3390/math8040494. doi: 10.3390/math8040494
    [25] S. H. Saker, J. Dzurina, On the oscillation of certain class of third-order nonlinear delay differential equations, Math. Bohem., 135 (2010), 225–237.
    [26] R. P. Agarwal, M. Bohner, T. Li, C. Zhang, Oscillation of third-order nonlinear delay differential equations, Taiwanese J. Math., 17 (2013), 545–558. doi: 10.11650/tjm.17.2013.2095. doi: 10.11650/tjm.17.2013.2095
    [27] T. Li, Yu. V. Rogovchenko, On asymptotic behavior of solutions to higher-order sublinear Emden-Fowler delay differential equations, Appl. Math. Lett., 67 (2017), 53–59. doi: 10.1016/j.aml.2016.11.007. doi: 10.1016/j.aml.2016.11.007
    [28] C. Zhang, R. P. Agarwal, T. Li, Oscillation and asymptotic behavior of higher-order delay differential equations with fanxiexian_myfhpfanxiexian_myfh-Laplacian like operators, J. Math. Anal. Appl., 409 (2014), 1093–1106. doi: 10.1016/j.jmaa.2013.07.066. doi: 10.1016/j.jmaa.2013.07.066
    [29] C. Zhang, T. Li, B. Sun, E. Thandapani, On the oscillation of higher-order half-linear delay differential equations, Appl. Math. Lett., 24 (2011), 1618–1621. doi: 10.1016/j.aml.2011.04.015. doi: 10.1016/j.aml.2011.04.015
    [30] B. Baculikova, J. Dzurina, Oscillation of third-order neutral differential equations, Math. Comput. Mode., 52 (2010), 215–226. doi: 10.1016/j.mcm.2010.02.011. doi: 10.1016/j.mcm.2010.02.011
    [31] T. Li, Y. V. Rogovchenko, On the asymptotic behavior of solutions to a class of third-order nonlinear neutral differential equations, Appl. Math. Lett., (2020), 106293. doi: 10.1016/j.aml.2020.106293. doi: 10.1016/j.aml.2020.106293
    [32] D. Lackova, The asymptotic properties of the solutions of the n-th order functional neutral differential equations, Comput. Appl. Math., 146 (2003), 385–392. doi: 10.1016/S0096-3003(02)00590-8. doi: 10.1016/S0096-3003(02)00590-8
    [33] M. Bohner, T. S. Hassan, T. Li, Fite-Hille-Wintner-type oscillation criteria for second-order half-linear dynamic equations with deviating arguments, Indag. Math. (N.S.), 29 (2018), 548–560. doi: 10.1016/j.indag.2017.10.006. doi: 10.1016/j.indag.2017.10.006
    [34] T. Li, N. Pintus, G. Viglialoro, Properties of solutions to porous medium problems with different sources and boundary conditions, Z. Angew. Math. Phys., 70 (2019), 1–18. doi: 10.1007/s00033-019-1130-2. doi: 10.1007/s00033-019-1130-2
    [35] T. Li, G. Viglialoro, Boundedness for a nonlocal reaction chemotaxis model even in the attraction-dominated regime, Differ. Integral Equ., 34 (2021), 315–336.
    [36] B. Baculikova, J. Dzurina, On the oscillation of odd order advanced differential equations, Bound. Value Probl., 214 (2014), 214. doi: 10.1186/s13661-014-0214-3. doi: 10.1186/s13661-014-0214-3
    [37] R. P. Agarwal, S. R. Grace, D. O'Regan, Oscillation Theory for difference and functional differential equations, Marcel Dekker, Kluwer Academic, Dordrecht, 2000. doi: 10.1007/978-94-015-9401-1.
  • This article has been cited by:

    1. Flávia da Silva Fernandes, Érica Simplício de Souza, Lívia Melo Carneiro, João Paulo Alves Silva, João Vicente Braga de Souza, Jacqueline da Silva Batista, Clemencia Chaves Lopez, Current Ethanol Production Requirements for the Yeast Saccharomyces cerevisiae, 2022, 2022, 1687-9198, 1, 10.1155/2022/7878830
    2. Nancy González-Jaramillo, Natalia Bailon-Moscoso, Rodrigo Duarte-Casar, Juan Carlos Romero-Benavides, Peach Palm (Bactris gasipaes Kunth.): Ancestral Tropical Staple with Future Potential, 2022, 11, 2223-7747, 3134, 10.3390/plants11223134
    3. Ajinath Dukare, Mahesh Kumar Samota, Bhushan Bibwe, Sandeep Dawange, Using convective hot air drying to stabilize mango peel (Cv-Chausa): evaluating effect on bioactive compounds, physicochemical attributes, mineral profile, recovery of fermentable sugar, and microbial safety, 2022, 16, 2193-4126, 3897, 10.1007/s11694-022-01496-x
    4. Ajinath Dukare, Bhushan Bibwe, Mahesh Kumar Samota, Sandeep Dawange, Manoj Kumar, José M. Lorenzo, Assessment of Bioactive Compounds, Physicochemical Properties, and Microbial Attributes of Hot Air–Dried Mango Seed Kernel Powder: an Approach for Quality and Safety Evaluation of Hot Air–Dried Mango Seed Kernel Powder, 2022, 15, 1936-9751, 2675, 10.1007/s12161-022-02318-y
    5. Asma Chaudhary, Ali Hussain, Qurat-ul-Ain Ahmad, Tooba Ahmad, Qandeel Minahal, Shuichi Karita, Balakrishnan Deepanraj, Watermelon peel hydrolysate production optimization and ethanologenesis employing yeast isolates, 2022, 2190-6815, 10.1007/s13399-022-02923-1
    6. Rodrigo Duarte-Casar, Nancy González-Jaramillo, Natalia Bailon-Moscoso, Marlene Rojas-Le-Fort, Juan Carlos Romero-Benavides, Five Underutilized Ecuadorian Fruits and Their Bioactive Potential as Functional Foods and in Metabolic Syndrome: A Review, 2024, 29, 1420-3049, 2904, 10.3390/molecules29122904
    7. Julkipli Julkipli, Sandhya Babel, Optimizing dilute sulfuric acid thermohydrolysis of dried food waste using the desirability function to produce a fermentation-friendly hydrolysate for biohydrogen production, 2025, 199, 09619534, 107922, 10.1016/j.biombioe.2025.107922
  • Reader Comments
  • © 2022 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(2624) PDF downloads(98) Cited by(6)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog