Synergistic sequential oxidative extraction for nanofibrillated cellulose isolated from oil palm empty fruit bunch.

This research presents a comprehensive study of sequential oxidative extraction (SOE) consisting of alkaline and acidic oxidation processes to extract nanocellulose from plant biomass. This proposed process is advantageous as its operation requires a minimum process with mild solvents, and yet successfully isolated high-quality nanofibrillated cellulose (NFC) from raw OPEFB. The SOE involved ammonium hydroxide (NH4OH, 2.6 M) and formic acid (HCOOH, 5.3 M) catalyzed by hydrogen peroxide (H2O2, 3.2 M). This approach was used to efficiently solubilize the lignin and hemicellulose from Oil Palm Empty Fruit Bunch (OPEFB) at the temperature of 100°C and 1 h extraction time, which managed to retain fibrous NFC. The extracted solid and liquor at each stage were studied extensively through physiochemical analysis. The finding indicated that approximately 75.3%dwb of hemicellulose, 68.9%dwb of lignin, and 42.0%dwb of extractive were solubilized in the first SOE cycle, while the second SOE cycle resulted in 92.3%dwb, 99.6%dwb and 99.8%dwb of solubilized hemicellulose, lignin, and extractive/ash, respectively. High-quality NFC (75.52%dwb) was obtained for the final extracted solid with 76.4% crystallinity, which is near the crystallinity of standard commercial NFC. The proposed process possesses an effective synergy in producing NFC from raw OPEFB with less cellulose degradation, and most of the degraded hemicellulose and lignin are solubilized in the liquor.

Correlation Study between the Organic Compounds and Ripening Stages of Oil Palm Fruitlets Based on the Raman Spectra.

The degree of maturity of oil palm fresh fruit bunches (FFB) at the time of harvest heavily affects oil production, which is expressed in the oil extraction rate (OER). Oil palm harvests must be harvested at their optimum maturity to maximize oil yield if a rapid, non-intrusive, and accurate method is available to determine their level of maturity. This study demonstrates the potential of implementing Raman spectroscopy for determining the maturity of oil palm fruitlets. A ripeness classification algorithm has been developed utilizing machine learning by classifying the components of organic compounds such as ß-carotene, amino acid, etc. as parameters to distinguish the ripeness of fruits. In this study, 47 oil palm fruitlets spectra from three different ripeness levels-under ripe, ripe, and over ripe-were examined. To classify the oil palm fruitlets into three maturity categories, the extracted features were put to the test using 31 machine learning models. It was discovered that the Medium, Weighted KNN, and Trilayered Neural Network classifier has a maximum overall accuracy of 90.9% by using four significant features extracted from the peaks as the predictors. To conclude, the Raman spectroscopy method may offer a precise and efficient means to evaluate the maturity level of oil palm fruitlets.

Oil Palm Fruits Ripeness Classification Based on the Characteristics of Protein, Lipid, Carotene, and Guanine/Cytosine from the Raman Spectra.

The capacity of palm oil production is directly affected by the ripeness of the fresh fruit bunches (FFB) upon harvesting. Conventional harvesting standards rely on rigid harvesting scheduling as well as the number of fruitlets that have loosened from the bunch. Harvesting is usually done every 10 to 14 days, and an FFB is deemed ready to be harvested if there are around 5 to 10 empty sockets on the fruit bunch. Technology aided by imaging techniques relies heavily on the color of the fruit bunch, which is highly dependent on the surrounding light intensities. In this study, Raman spectroscopy is used for ripeness classification of oil palm fruits, based on the molecular assignments extracted from the Raman bands between 1240 cm-1 and 1360 cm-1. The Raman spectra of 52 oil palm fruit samples which contain the fingerprints of different organic compounds were collected. Signal processing was applied to perform baseline correction and to reduce background noises. Characteristic data of the organic compounds were extracted through deconvolution and curve fitting processes. Subsequently, a correlation study between organic compounds was developed and eight hidden Raman peaks including protein, beta carotene, carotene, lipid, guanine/cytosine, chlorophyll-a, and tryptophan were successfully located. Through ANOVA statistical analysis, a total of six peak intensities from proteins through Amide III (ß-sheet), beta-carotene, carotene, lipid, guanine/cytosine, and carotene and one peak location from lipid were found to be significant. An automated oil palm fruit ripeness classification system deployed with artificial neural network (ANN) using the seven signification features showed an overall performance of 97.9% accuracy. An efficient and accurate ripeness classification model which uses seven significant Raman peak features from the correlation analysis between organic compounds was successfully developed.

Facile Synthesis of 3D Printed Tailored Electrode for 3-Monochloropropane-1,2-Diol (3-MCPD) Sensing.

Additive manufacturing (AM) has allowed enormous advancement in technology and material development; thus, it requires attention in developing functionalized printed materials. AM can assist in efficiently manufacturing complex tailored electrodes for electrochemical sensing in the food industry. Herein, we used a commercial fused deposition modeling (FDM) filament of acrylonitrile butadiene styrene (ABS) for FDM 3D printing of a self-designed electrode with minimal time and cost compared to a commercial electrode. A graphene-based ABS conductive filament (ABS-G) was used to fabricate the conductive electrode in a dual-nozzle FDM 3D printer. The electrochemically conductive 3D printed electrode was characterized using cyclic voltammetry and tested against standard 3-monochloropropane-1,2-diol (3-MCPD) with known concentrations using an amperometric detection method. Results showed a basis for promising application to detect and quantify 3-MCPD, a food contaminant known for its carcinogenic potential. The fabrication of functionalized 3D printed polymer electrodes paves way for the development of complete 3D printable electrochemical sensors. Under optimal conditions, this newly synthesized electrochemical sensor exhibited sensitivity with a linear response range from 6.61 × 10-4 to 2.30 × 10-3 µg/mL with an estimated limit of detection of 3.30 × 10-4 µg/mL against 3-MCPD.

Production of Rigid Polyurethane Foams Using Polyol from Liquefied Oil Palm Biomass: Variation of Isocyanate Indexes.

Development of polyurethane foam (PUF) containing bio-based components is a complex process that requires extensive studies. This work reports on the production of rigid PUFs from polyol obtained via liquefaction of oil palm empty fruit bunch (EFB) biomass with different isocyanate (NCO) indexes. The effect of the NCO index on the physical, chemical and compressive properties of the liquefied EFB-based PUF (EFBPUF) was evaluated. The EFBPUFs showed a unique set of properties at each NCO index. Foaming properties had affected the apparent density and cellular morphology of the EFBPUFs. Increasing NCO index had increased the crosslink density and dimensional stability of the EFBPUFs via formation of isocyanurates, which had also increased their thermal stability. Combination of both foaming properties and crosslink density of the EFBPUFs had influenced their respective compressive properties. The EFBPUF produced at the NCO index of 120 showed the optimum compressive strength and released the least toxic hydrogen cyanide (HCN) gas under thermal degradation. The normalized compressive strength of the EFBPUF at the NCO index of 120 is also comparable with the strength of the PUF produced using petrochemical polyol.

A Revisit to the Formation and Mitigation of 3-Chloropropane-1,2-Diol in Palm Oil Production.

Process-based contaminants in food-particularly in vegetable oils-have been a topic of interest due to their potential health risk on humans. Oral consumption above the tolerable daily intake might result in health risks. Therefore, it is critical to correctly address the food contaminant issues with a proper mitigation plan, in order to reduce and subsequently remove the occurrence of the contaminant. 3-monochloropropane-1,3-diol (3-MCPD), an organic chemical compound, is one of the heat- and process-induced food contaminants, belonging to a group called chloropropanols. This review paper discusses the occurrence of the 3-MCPD food contaminant in different types of vegetable oils, possible 3-MCPD formation routes, and also methods of reduction or removal of 3-MCPD in its free and bound esterified forms in vegetable oils, mostly in palm oil due to its highest 3-MCPD content.

Superabsorbent hydrogel from oil palm empty fruit bunch cellulose and sodium carboxymethylcellulose.

A green regenerated superabsorbent hydrogel was fabricated with mixtures of dissolved oil palm empty fruit bunch (EFB) cellulose and sodium carboxymethylcellulose (NaCMC) in NaOH/urea system. The formation of hydrogel was aided with epichlorohydrin (ECH) as a crosslinker. The resultant regenerated hydrogel was able to swell >80,000% depending on the NaCMC concentrations. The hydrogel absorbed water rapidly upon exposure to water up to 48 h and gradually declined after 72 h. The crosslinked of covalent bond of COC between dissolved EFB cellulose (EFBC) with NaCMC was confirmed with Attenuated total reflectance Fourier transform infrared (ATR-FT-IR) spectroscopy. Crystallinity and thermal stability of the hydrogel samples were depended on the concentrations of NaCMC, crosslinking, and swelling process. The strength and stability of crosslinked network was studied by examining the gel fraction of hydrogel. This study explored the swelling ability and probable influenced factors towards physical and chemical properties of hydrogel.

Cationic and anionic modifications of oil palm empty fruit bunch fibers for the removal of dyes from aqueous solutions.

Oil palm empty fruit bunch (EFB) fibers were employed to remove dyes from aqueous solutions via adsorption approaches. The EFB fibers were modified using citric acid (CA) and polyethylenimine (PEI) to produce anionic and cationic adsorbents, respectively. The CA modified EFB fibers (CA-EFB) and PEI-modified EFB fibers (PEI-EFB) were used to study the efficiency in removing cationic methylene blue (MB) and anionic phenol red (PR) from aqueous solutions, respectively, at different pHs, temperatures and initial dye concentrations. The adsorption data for MB on the CA-EFB fitted the Langmuir isotherm, while the adsorption of PR on the PEI-EFB fitted the Freundlich isotherm, suggesting a monolayer and heterogeneous adsorption behavior of the adsorption processes, respectively. Both modified fibers can be regenerated up to seven adsorption/desorption cycles while still providing as least 70% of the initial adsorption capacity.