text:
Effect of Water Soluble Fertilizers on Yield, Oil Content and Economics of Groundnut

A field experiment was conducted at Main Agricultural Research Station (MARS), University of Agricultural Sciences, Dharwad, to know the effect of water soluble fertilizers on growth, yield and oil content of groundnut (Cv TAG 24). The experiment was conducted in a Vertisol with ten treatment combinations consisting of FYM and different doses of recommended NPK as basal soil application and foliar spray of water soluble fertilizers at 30, 45 and 60 days after sowing in a Randomized complete block design with three replications. Application of FYM + 100% RDF + foliar spray of fertilizers at 30, 45 and 60 DAS showed higher pod yield (5615 kg/ha) which was 22% higher over application of 100% RDF alone (4601 kg/ha). But the crop was equally responsive in increasing the pod yield, when RDF was reduced by 15% along with foliar application of water soluble grade fertilizer. The yield components, kernel yield (3892 kg/ha), haulm yield (8916 kg/ha), total number of pods plant (33.80), =sound mature kernels (88.67) and oil yield (1858 kg/ha) were highest in the treatment of FYM + 100% RDF + foliar spray of fertilizers over rest of the treatments. But the highest Original Research Article Manasa et al.; CJAST, 39(23): 89-96, 2020; Article no.CJAST.59614 90 Benefit cost ratio (4.40) was found in the treatment of FYM + 85% RDF + foliar application of fertilizers followed by the treatment of FYM + 100% RDF + foliar application of fertilizers (4.36) whereas the lowest B: C ratio (3.91) was observed in control.

INTRODUCTION
Groundnut (Arachis hypogaea L.) is the most important annual legume food crop in the world. Commercially, groundnut is the world's thirteenth most important food crop, fourth most important source of edible oil and third most important source of vegetable protein. About two thirds of world production is crushed for oil and one third is consumed as food [1]. Groundnut cake is a high protein animal feed. It contains about 50% oil, 25-30% protein, 20% carbohydrates and 5% fiber and ash having a substantial contribution to human nutrition [2].
In Karnataka, it is grown over an area of 0.67 million ha with a production of 0.42 million tonnes and a productivity of 629 kg ha -1 which is significantly lower compared to 1398 Kg/ha in India [3]. In Dharwad district, it is grown over an area of 17,403 ha with a production of 10,480 tons and a productivity of 644 kg ha -1 [4]. The low productivity of groundnut in Karnataka as well as Dharwad district might be due to several production constraints, which include growing crop on low fertility lands and imbalanced nutrition to the crop.
Groundnut is very exhaustive crop compared to other legumes because a very little portion of the plant residue is left in the soil after harvest [5]. Therefore, cultivation of groundnut depletes the soil fertility rapidly unless the crop is adequately fertilized. So, balanced fertilization is essential for enhancing the groundnut production. The nutrient requirement of groundnut is higher especially at pegging and pod development stages. The requirement at these stages cannot be fulfilled merely by soil application alone and need to be supplemented through foliar application. Futher more, foliar application enhances the efficiency of applied nutrients which otherwise subjected to leaching losses, precipitation and fixation losses.
Groundnut being a leguminous crop, fixes substantial quantity of atmospheric nitrogen. So, the application of full dose of nitrogen may not be required. Usually phosphorus requirement is higher at initial stages for root development. Since the experimental site is medium in available phosphorus and high in available potassium, dosage of fertilizer application may be reduced. Application of recommended dose of FYM also supply all essential nutrients in minute quantities besides improving the soil physical properties. Further, foliar application ensures the supply of nutrients as and when they are required by crop. Keeping all these points in view, there is a possibility for saving the costly fertilizer input without yield penalty which also lessens the environmental pollution. In the light of the above, an experiment was conducted with combination of FYM, doses of NPK and foliar application of water soluble fertilizers.

MATERIALS AND METHODS
A field experiment was conducted at Main Agricultural Research Station (MARS), University of Agricultural Sciences, Dharwad, India, during summer 2012. Dharwad is situated at 15 0 26  N latitude and 75 0 07  E longitude and at an altitude of 678 m above mean sea level. The mean annual rainfall during the experimental year from January 2012 to December 2012 was 540.11 mm. The highest mean monthly maximum temperature (35.8 0 C) and lowest mean monthly minimum temperature (12 0 C) were recorded in March 2012 and January 2012, respectively. Mean monthly maximum relative humidity was recorded during the month of July (84.6%).

Soil Chemical Properties and Adopted Methods
The soil was texturally clay, neutral in pH (7.24), non saline (0.61 dSm -1 ), medium in organic carbon (6.50 g kg -1 ), low in available nitrogen (237 kg N ha -1 ), medium in available phosphorus (34.6 kg P 2 O 5 ha -1 ) and rich in available potassium (470 kg K 2 O ha -1 ). The soil was sufficient in all available micro nutrients Viz., Fe (3.84 mg kg -1 ), Cu (0.51 mg kg -1 ), Mn (5.60 mg kg -1 ) except zinc (0.58 mg kg -1 ). Soil reaction, electrical conductivity and organic carbon were determined as described by Jackson [6]. Available nitrogen measured by modified alkaline permanganate method described by Sharawat and Burford [7], available phosphorus, potassium and sulfur were determined by following the procedures of Black [8], Available copper, zinc, iron and manganese were measured by following procedures given by Lindsay and Norwell [9].

Treatment Details
The experiment was laid with ten treatment combinations consisting of FYM and various levels of recommended NPK Viz., 100%, 85%, 60% NPK through soil application at the time of sowing and foliar spray of fertilizers at 30, 45 and 60 days after sowing (DAS) of groundnut. Foliar application included starter dose of water soluble grade fertilizer (11:36:24 + trace elements) @ 2% at 30 days after sowing followed by booster dose of water soluble grade fertilizer (8:16:39+ trace elements) @ 2% at 45 DAS and 60 DAS. Trace elements in the foliar mixture were Fe -800 ppm, Mn -400 ppm, Zn -200 ppm, Cu -50 ppm and Mo -50 ppm. Experiment was laid out in a randomised complete block design with three replications.

application of Fertilizers
The nitrogen, phosphorus and potassium were applied in the form of urea, SSP and muriate of potash, respectively. The entire quantity of fertilizer mixture containing nitrogen, phosphorus and potassium were applied as per the treatments to each plot at the time of sowing. FYM @ 7.5 t ha -1 was applied as per the treatment to each plot three weeks prior to sowing. Fertilizers were mixed thoroughly and covered with the soil. Foliar application of starter dose of water soluble grade fertilizer (11:36:24 + trace elements) @ 2% was applied at 30 days after sowing (DAS). Foliar application of booster dose of water soluble grade fertilizer (8:16:39 + trace elements) @ 2% were applied at 45 DAS and 60 DAS with knapsack sprayer in the morning hours as per the treatments. Eleven irrigations were given to the crop during entire growth period. One pre-sowing irrigation was given for land preparation.

Harvesting and plucking
The crop was harvested at physiological maturity. Immediately after uprooting, the plants were sun dried for one week. the pod yield and haulm yield plot -1 were recorded.

Oil content and oil yield
Dried kernels of each treatment were used for estimation of per cent oil content using Nuclear Magnetic Resonance (NMR). Oil yield was calculated by multiplying the oil per cent with kernel yield.

Statistical Analysis and Interpretation of Data
The analysis and interpretation of data were done using the Fischer's method of analysis of variance technique as described by Gomez and Gomez [10]. The level of significance used in 'F' and 't' test was P = 0.05. Critical difference values were calculated wherever the 'F' test was significant.

Correlation Studies
Simple correlation analysis was done to understand the interrelationships between nutrient uptake by the whole plant with yield attributes viz., dry pod yield, kernel yield, oil content and oil yield. Correlation coefficients (r) were calculated in SPSS package and tests of significance were applied as per the procedure outlined by Snedecor and Cochran [11].

Economic Analysis
Based on the prevailing price of inputs and produce, the net profit per hectare and benefit cost ratio were worked out by using the following formulae.

RESULTS AND DISCUSSION
Yield and yield parameters were significantly influenced by foliar application of water soluble fertilizers (Table 1). Total number of pods per plant was increased with increasing level of fertilizers. The highest number of pods per plant was recorded with the treatment receiving FYM + 100% RDF + foliar spray of fertilizers (33.80). Roy [12] reported that the foliar grade water soluble fertilizers application to groundnut had the positive response to increase the pod yield either alone or in combination with recommended fertilizer dose. Further, Application of FYM might have provided balanced nutrients in readily available from throughout the growth period resulting in greater production of metabolites and their translocation to productive structures which could have helped in increased number of pods per plant and overall plant growth [13].
Shelling percentage and hundred kernel weight of groundnut did not differ significantly due to foliar application of water soluble fertilizer along with or without application of 100%, 85% or 60% RDF.
The maximum dry pod yield was observed in the treatment of FYM + 100% RDF + foliar spray of fertilizers (5615 kg/ha). However, the crop was equally responsive in increasing the pod yield, when RDF was reduced by 15% (85% of RDF) along with foliar application of water soluble fertilizer (5567 kg/ha). Even the treatment of FYM + 60% RDF + foliar spray of fertilizers produced higher dry pod yield (4956 kg/ha) compared to 100% RDF (4601 kg/ha) indicating the effective utilization of foliar applied nutrients (Table 1). This might also be due to groundnut being a leguminous crop, able to fix the atmospheric nitrogen so, basal application of nitrogenous fertilizer requirement is less. In addition foliar application of water soluble fertilizer could improve the nutrient uptake and utilization. Increased production of dry matter and its efficient translocation to the economic parts resulted in higher final pod yield as reported by Shete [14]. Similar observations were reported by Balerao [15] who observed that mean dry pod yield was increased by 5.6 -20% by foliar application of individual or combined trace elements, urea, phosphorus and plant growth regulators.
Kernel yield and haulm yields of groundnut were significantly influenced by soil and foliar application of fertilizers. The maximum kernel yield (3892 Kg/ha) and haulm yield (8916 Kg/ha) were observed in the treatment of FYM + 100% RDF + foliar spray of fertilizers (3892 kg/ha). However, the treatments T 8, T 4, T 5, T 7, and T 10 were on par with T 6 for kernel yield. Treatment of FYM + 60% RDF + foliar spray of fertilizers produced higher kernel yield (3377 kg/ha) on par with T 6 ( Table 1). In case of haulm yield all the treatments were found on par with T 6 except control. The growth of groundnut is intense from 30-70 Days after sowing [16]. Therefore, synchronization of nutrient supply at these stages through foliar application resulted in growth and higher yields. Efficient partitioning of metabolites, appropriate translocation and accumulation of photosynthates, vitamins, amino acids to developing reproductive structures through foliar application resulted in enhancement in yield attributing characters. Karthika and Ramanathan [17] found increased haulm yield of groundnut was mainly due to the higher production of dry matter, leaf area and all the yield attributing components of the crop. The improvement in the kernel yield might be due to the instant assimilation of nutrients supplied through the foliar application meeting the required nutrient demand of the crop during flowering period of groundnut. Improved pod weight under foliar treatments was mainly due to increased translocation of photosynthates from leaves and stem to developing pods resulting in sound mature kernels [18]. Foliar spray maintains the leaf area for longer duration which extends period of photosynthates translocation to developing pods resulting in bolder and wellshaped seeds [19].
The higher seed oil content (47.73%) and oil yield (1858 kg/ha) were observed in FYM + 100% RDF + foliar spray of fertilizers treatment. This might also be due to supply of iron with foliar spray which increased the oil content in kernels. The results of present investigation are in confirmity with the findings of Patil [20] and Krishnappa [21] in groundnut. Patil [20] observed that significant increase in protein and oil content of groundnut due to the foliar spray of ferrous sulphate at 30, 60 and 75 days after sowing. Moreover, Phosphorus is a major constituent of fatty acids, higher accumulation of phosphorus exhibited higher seed oil content. Higher kernel yield and higher oil content of the foliar sprayed treatments showed higher oil yields compared to their counter parts.

Economics
The acceptance of any generated technology is ultimately based on the cost of cultivation and net returns from it. In the present investigation, treatment with FYM + 100% RDF + foliar application of fertilizers showed highest gross income (Rs 213370.00 ha -1 ) as well as net income (Rs 173590.00 ha -1 ) followed by the treatment FYM + 85% RDF + foliar application of fertilizers (Rs 211546 and Rs 172351, gross income and net income, respectively). But the highest (4.40) benefit cost ratio was found in the treatment of FYM + 85% RDF + foliar application of fertilizers followed by the treatment (T 6 ) that received FYM + 100% RDF + foliar application of fertilizers (4.36) whereas the lowest B: C ratio (3.91) was observed in control (Table 2). Even though the gross and net returns were higher in the treatment of FYM + 100% RDF + foliar application of fertilizers but the B: C ratio was lower because of higher input cost compared to T 8 . Critical examination of the data revealed that all treatments with foliar spray of fertilizers recorded numerically higher B: C ratio compared to their corresponding treatments with water spray. Similar resulted were reported by Roy [12] who observed highest net return: cost ratio of 2.70 in the treatment FYM + 85% RDF + Foliar spray treatment.

Nutrient uptake by whole plant vs. yield and quality attributes
Yield attributes Viz., total number of pods, dry pod yield and kernel yield were positively and significantly influenced by leaf area, total dry matter production, number of nodules and chlorophyll content (Table 3). Both Major and micro nutrient uptake was positively correlated with dry pod yield, kernel yield, oil content and oil yield. Foliar application resulted in greater absorption, assimilation and translocation of  nutrients for increased photosynthesis. Therefore, better availability and uptake of nutrients could be assigned as the proper reason behind the significant increase in dry matter production and its accumulation ultimately reflected in yield parameters. Similar results were reported by Shivakumar [22] and Dalei [23]. Sulphur uptake was positively correlated with oil yield (0.96 **). Since sulphur is an integral part of oil, the increased availability of sulphur might have favorably influenced the synthesis of essential metabolism for higher oil content. Similar results were reported by Jat and ahlawat [24] and Yadav [25].

CONCLUSION
From the above study, it can be concluded that the application of inorganic fertilizers can be reduced upto 15% with application of foliar grade water soluble fertilizer starter dose of water soluble grade fertilizer (11:36:24 + trace elements) @ 2% at 30 days after sowing (DAS) + Foliar application of booster dose of water soluble grade fertilizer (8:16:39+ trace elements) @2% at 45 DAS and 60 DAS to achieve optimum yield, yield parameters as well as highest benefit: cost ratio. Thus, the practice of foliar nutrition as a supplement for standard soil fertilization was beneficial for summer groundnut.


extfieldsofstudy: Medicine Chemistry

provenance: AgriculturalAndFoodSciences,2019-2020-Agricultural And Food Sciences-2020.jsonl.gz.gz

text:
Pretreatment Affects Activated Carbon from Piassava

The specificity of activated carbon (AC) can be targeted by pretreatment of the precursors and/or activation conditions. Piassava (Leopoldinia piassaba and Attalea funifera Martius) are fibrous palms used to make brushes, and other products. Consolidated harvest and production residues provide economic feasibility for producing AC, a value-added product from forest and industrial residues. Corona electrical discharge and extraction pretreatments prior to AC activation were investigated to determine benefits from residue pretreatment. The resulting AC samples were characterized using elemental analyses and FTIR and tested for efficacy using methylene blue and phenol. All resulting AC had good adsorbent properties. Extraction as a pretreatment improved functionality in AC properties over Corona electrical discharge pretreatment. Due to higher lignin content, AC from L. piassaba had better properties than that from A. funifera.

Introduction
Activated carbons (ACs) are widely used in many environmental remediation processes because of their high adsorption capacity. ACs can remove a wide variety of pollutants in aqueous environments by having large surface presence of functional groups with affinities for various adsorbates [1]. The use of ACs in effluent purification improved the taste, smell, color, UV absorbance and oxidability of treated water [2]. Various raw materials, including wood, bone, coconut shells, coconut endocarp, sugarcane bagasse and fruit seeds [3,4] have been used to produce ACs with different characteristics. The choice of precursors and activation conditions make it possible to design ACs for specific applications [5]. All carbonaceous feedstock has the potential to be used for AC manufacture but not all are economically feasible mostly because of the expense of gathering and transporting the feedstock if left in the field. If the feedstock is already consolidated into a relatively small area, such as a lumber mill or processing plant, the feedstock may be readily gathered, transported and treated. Better still would be to have localized plants set up to do the treatment.

Elemental Analysis
Elements (CHNS) of AP and BP samples from all steps were determined in an elemental analyzer (Vario MacroCube, Elementar Americas, Inc., Ronkonkoma, NY, USA), following the protocol described by Paula et al. [14]. Samples milled to 270 mesh, as specified in the protocol, were analyzed. Oxygen content was calculated by difference according to Equation (1).
where O is oxygen, C is carbon, H is hydrogen, N is nitrogen and S is sulfur [13].

Infrared Spectroscopy (FTIR)
Specific functional groups of the 12 samples of Ch and ACs made from 270 mesh AP and BP were identified using Fourier transform infrared (FTIR) spectroscopy analysis (Digilab Excalibur FTS 3000, Bio-Rad, Hercules, CA, USA) in the spectral range of 400 to 4000 cm −1 and 4 cm −1 resolution.

Adsorption Tests and Modeling
The adsorption isotherms of methylene blue dye and phenol were obtained using 10 mg of AC adsorbent and 10 mL of adsorbate at varying concentrations (25,50, 100, 250, 500 and 1000 mg L −1 ). AC-adsorbate mixtures were stirred at 100 rpm for 24 h at room temperature (25 ± 2 • C). The equilibrium concentration was determined in a UV-visible spectrophotometer (AJX-3000PC, AJ Lab, AJ Micronal, Sao Paulo, Brazil) at of 665 nm and 270 nm for methylene blue and phenol, respectively. The Langmuir (Equation (2)) and Freundlich (Equation (3)) isotherm models [15] were used to analyze the data: q eq = (q m K L C eq )/(1 + K L C eq ) (2) where q eq is the equilibrium concentration of AC (mg g −1 ), C e is the equilibrium concentration in the solution (mg L −1 ), q m is the maximum capacity of adsorption of the AC (mg g −1 ) and K L is the Langmuir adsorption constant (L mg −1 ).
where K F is a constant that indicated the relative capacity of adsorption (mg g −1 ) (L g −1 ) −(1/n) and n is related to the intensity of adsorption of the AC.

Iodine Number (IN) and Surface Area with Methylene Blue-S MB
The iodine number, defined as the absorption of iodine in mg g −1 AC, was determined according to ASTM D4607-14 [16].
The surface area estimated with methylene blue (S MB ) was obtained as reported in Equation (4) [17]: where S MB • is the methylene blue surface area (1.93 m 2 mg −1 ) and q m is the maximum capacity of adsorption of the AC (mg g −1 ).

Estimation of the Brunauer, Emmett and Teller (BET) Surface Area
The micropore volume, total pore volume and AC surface areas were estimated from the IN and maximum adsorption of methylene blue (q m ). Structural Characterization of Activated Carbon (SCAC) software was used with the data to estimate the micropore volume, the total pore volume and the BET surface area of ACs [18].

Chemical Composition of Fibers
The chemical compositions of the untreated AP and BP used in AC preparation are described in Table 1. AP and BP have low ash and high lignin contents which are important characteristics in producing AC with optimal properties. High lignin contents provide high yields thereby contributing to the fixed carbon content at the end of carbonization and activation processes. Lignin biochar was shown to have a much higher yield than cellulose or pine wood [19] probably due to the higher decomposition temperature of lignin. Decomposition of hemicellulose, cellulose and lignin occur in the range of 200-260, 240-350 and 280-500 • C, respectively [20]. Lignin decomposes at higher temperatures and over a much wider temperature range than do hemicellulose or cellulose; the aromatic rings of lignin make it much less susceptible to degradation and require high temperatures. AC derived from AP had higher lignin and extractives and lower cellulose, hemicelluloses and ash than AC derived from BP. The results found in this work, for the chemical composition of BP-Un, agree with those obtained by Schuchardt et al. [21], who found values of 0.8, 0.7, 45.0, 28.6 and 25.8 for ash, extractives, lignin (Klason), cellulose and hemicellulose, respectively.

Elemental Composition
Elemental composition of the piassava fibers, charcoal and activated carbon are shown in Table 2. AP had higher lignin (Table 1) and N (Table 2) contents that BP. However, after the pretreatments by Corona discharge or extraction, the two samples had similar values.
AP-Un-Ch had higher C than BP-Un-Ch. The comparative increase in C and the resulting decrease in H and O during thermal conversion are shown in Table 2. High heat treatment volatilizes H-, Oand N-containing compounds [22] and results in high C contents. Pretreatments mostly affected the elemental composition of Ch (AP-Un-Ch, AP-Co-Ch, AP-Ex-Ch, BP-Un-Ch, BP-Co-Ch and BP-Ex-Ch).
In addition to the elements reported here, silica is also found in both AP and BP and was found to be 52% in A. funifera in the form of SiO 2 [23] and occurred as bodies with protrusions of about 20 µm in diameter taking up most of the space in a single cell [24,25]. Energy dispersive X-ray analysis showed that the bodies were mostly of silica [26].

Infrared Spectroscopy (FTIR)
FTIR was used to identify specific functional groups in AP-Un and BP-Un and compare the results with the pretreated samples and with the charcoal and activated carbons obtained from the piassava fibers ( Figure 1).
The FTIR spectra between 2000 and 500 cm −1 best describes functional groups in the samples. However, countless peaks in this region due the stretching and deformational vibrations of functional groups belonging to lignin and carbohydrates create overlapping peaks that make interpretation difficult. Close inspection reveals that AP-Un and BP-Un spectra ( Figure 1a) have peaks at 1715 cm −1 characterizing C=O (unconjugated ketone, conjugated carboxylic acids groups and ester groups of carbohydrates), 1600 cm −1 representative of C=C (aromatic ring of lignin) plus C=O, 1510 cm −1 attributed to lignin backbone, 1270 cm −1 as lignin guaiacyl ring plus C=O and 1055 cm −1 assigned to C-O(H) of carbohydrates [27][28][29].
In BP-Un and AP-Un ( Figure 1a) the peaks at 1270 and 1055 cm −1 have about the same intensity, however, the lignin peaks, notably the peak at 1510 cm −1 , are more intense in AP-Un ( Figure 1a) than in BP-Un. The greater intensity of the lignin peaks confirms that AP-Un contains more lignin than BP-Un (Table 1).
According to Sadeghnejad et al. [30], corona treatment induces changes in material surface properties mostly due to reactions between covalent bonds in atmospheric oxygen and carbons on the sample surface. However, such change is not obvious in the spectra (Figure 1b) perhaps because corona treatment occurs on material surfaces, therefore, once the material has been ground for measurement by FTIR, the differences are no longer apparent in the resulting spectra.
A peak at 1560 cm −1 , attributed to C=C of the aromatic skeleton may be seen in charcoal spectra in both AP-Un-Ch and BP-Un-Ch ( Figure 1d). The 1560 cm −1 may be due to an increase in carbonization that results in dehydrogenation and the formation of double bonds that indicated aromatization of the material [27,28]. Table 2  Un. The greater intensity of the lignin peaks confirms that AP-Un contains more lignin than BP-Un (Table  1).
According to Sadeghnejad et al. [30], corona treatment induces changes in material surface properties mostly due to reactions between covalent bonds in atmospheric oxygen and carbons on the sample surface. However, such change is not obvious in the spectra (Figure 1b) perhaps because corona treatment occurs on material surfaces, therefore, once the material has been ground for measurement by FTIR, the differences are no longer apparent in the resulting spectra. . Note that BP-Un and AP-Un (a) have the same intensity at peaks 1270 and 1055 cm −1 . The peak at higher intensity at the peak 1510 cm −1 in AP-Un compared to BP-Un is indicative of higher lignin in AP-Un than in BP-Un. The peaks at 1560 cm −1 , attributed to C=C of the aromatic skeleton, indicates dehydrogenation, the formation of double bonds and aromatization of the material in AP-Un-Ch and BP-Un-Ch). The 1050 cm −1 peak has disappeared (d,e), suggesting carbohydrate degradation. The peak at 1190 cm −1 shows the change of aromatic structure of the lignin due to the carbonization. The pretreatments had no significant effect on either charcoal or activated carbons (d-i). AP, L. piassaba (Amazon piassava); the peaks at 2339 correspond to CO 2 stretching (a-i). BP, A. funifera (Bahia piassava); Ch, charcoal; AC, activated carbon; Un, untreated (no pretreatment); Co, Corona electrical discharge pretreatment; Ex, solvent extraction pretreatment. Figures 2 and 3 show the isotherms that can be classified as type I (Langmuir type). According to the International Union of Pure and Applied Chemistry (IUPAC) classification, the Langmuir type of isotherm indicates high affinity between adsorbate and adsorbent. The adsorption isotherm is an important tool that reveals the specific relationship between the adsorbate molecules and the carbonaceous adsorbents [31]. The Langmuir and Freundlich parameters, for methylene blue and phenol (Table 3) show that the piassava ACs adsorbed higher quantities of methylene blue than phenol and that there was an influence from the pretreatments in the adsorption processes of the two compounds. The Langmuir model assumes a monolayer coverage of dyes over a homogenous adsorbent surface without further adsorption occurring in the occupied sites. In comparison, a heterogeneous adsorption was described by the Freundlich isotherm. The Freundlich model showed a continued increase in the concentration of dye on the adsorbent surface [32] and did not assume homogenous site energies or limited adsorption.AP-AC have higher adsorption capacity for methylene blue than BP-AC. AC produced from extracted AP and BP (AP-Ex-AC and BP-Ex-AC) had higher adsorption capacity than other pretreatments tested. The Langmuir model showed a better fit to the isotherm data than the Freundlich model as indicated by the R 2 (Qe vs. Ce) values. The better fit Langmuir model indicated that adsorption occurred on a homogeneous surface [33].   Piassava AC in this study was shown to have greater capacity to adsorb methylene blue (223-424 mg g −1 ) compared to other ACs found in literature [1,6,32,[39][40][41][42]. AC adsorption for phenol in this study (125-226 mg g −1 ) were similar to reported values in the literature (145-278 mg g −1 ) [1,6,43,44].

Adsorption Tests
Avelar et al. [1] showed that activated carbons produced from piassava fibers have high adsorption capacity for specific compounds, most often better than commercial AC used for comparison in the study of these authors.
Castro et al.
[6] reported a qm of 388 for adsorption of methylene blue (Corona pretreatment), whereas, in the present work, a lower qm value of 385 is reported. The pretreatments for the two studies were slightly  The R 2 (Qe vs. Ce) values for adsorption of phenol by AP-AC fit well to the Langmuir model. BP-Un-AC fit well to the Freundlich model whereas BP-Co-AC and BP-Ex-AC fit well to the Langmuir model. AP-Un-AC and BP-Un-AC had the highest adsorption capacity values for phenol compared to other ACs. ACs produced with Corona pretreated fibers (AP-Co-AC and BP-Co-AC) had decreased adsorption compared to other ACs. The adsorption capacity is also influenced by surface chemistry probably due to the presence of superficial functional groups and heteroatoms in the ACs. Chemical composition may be an additional factor affecting the surface chemistry of the ACs. Several factors may contribute to the adsorption capacity of phenol in addition to the best fit model that is provided to explain its adsorption. The effective adsorbent capacity is determined by the initial concentration of the adsorbent, ionic strength, temperature and pH, all of which significantly affect phenol removal efficiency [34,35]. Xiong et al. [36] showed that phenol was removed more efficiently at an alkaline pH during the initial 25 min of reaction time and leveled off thereafter. Beker, et al. state that surface pH of adsorbents decreases with increasing degree of activation and that with increasing alkalinity, a reduction in adsorption capacity results. The optimal pH of 6.5 was found for adsorption of phenol. However, pH affects the type and ionic state of surface functional groups [37], so adsorbance capacity depends on the functional groups on the activated carbon. In this study, pH was not determined, however, FTIR results indicate a slightly acidic pH of AC due to the presence a strong peak at about 2339 cm −1 (Figure 1) indicative of stretching of CO 2 [38].
Avelar et al. [1] showed that activated carbons produced from piassava fibers have high adsorption capacity for specific compounds, most often better than commercial AC used for comparison in the study of these authors.
Castro et al.
[6] reported a q m of 388 for adsorption of methylene blue (Corona pretreatment), whereas, in the present work, a lower q m value of 385 is reported. The pretreatments for the two studies were slightly different which is perhaps the reason for the numerical differences in adsorption of methylene blue. In Castro et al. [6], the fibers were Corona pretreated whole whereas, in this study, the fibers were ground prior to Corona pretreatment. Perhaps in the previous work, the application of Corona pretreatment on whole fibers was more homogeneous than grinding the fibers prior to pretreatment.

Surface Area of the ACs
The iodine number, methylene blue adsorption and BET (Est-S BET ) surface area estimations of AC are shown in Table 4. The iodine number and the methylene blue number are important and can be used to estimate of the surface area, of the micropore volume and of the total pore volume of activated carbon samples through multiple regression, thus, the two parameters are important since the materials possess different pore sizes which can be accessed by the different molecules according to the pore geometry [18]. IN is the capacity of the adsorbent (AC) to decolorize a compound and indicates adsorbent microporosity [45] and degree of activation [39]. Methylene blue adsorption studies are widely used to evaluate adsorbents. Due the dimensions of the methylene blue molecule, the dye serves as a visible marker and an indicator of mesoporosity and, to a lesser extent, microporosity. The iodine molecule is relatively small and is, therefore, an indicator of microporosity [18]. The development of pore structure in the AC during activation followed three main steps: (1) opening of unreachable pores, (2) creation of new pores and (3) enlargement of existing pores [31].
Pretreatment of AP and BP resulted in changes to the surface areas and pore volumes. In general, the AC produced from extracted pretreatment (AP-Ex-AC, BP-Ex-AC) had the largest surface areas of all ACs. During the extraction process, soluble phenolic and carbohydrate components were removed, eliminating pore obstruction by those components during the carbonization and activation processes.
Corona electrical discharge pretreatment also showed potential to alter and improve the qualities of the resulting pretreated ACs. The differences between AP-AC and BP-AC seems to be associated with the chemical composition of the untreated raw materials ( Table 2) which influences the pore formation and surface areas of the resulting ACs. AP has higher lignin content than BP. Based on the findings of [46], one would expect a decrease in surface area with an increase in lignin content since their conclusion is that due to the large numbers of oxygen-containing functional groups in cellulose and hemicellulose, the small molecules (H 2 O, CO 2 and CO) would volatilize during heat treatment and be replaced by micropores. They state that since lignin has aromatic units that are chemically inert, a nonporous AC would be produced. However, Deng et al. [46] used chemical activation and treated at 400 • C, at which temperature lignin would not decompose. In this study, activation was with CO 2 at 800 • C, above the temperature that lignin would start to decompose. Delignification of Elmwood was used to release sugars of hemicellulose for production of value-added products, a high-lignin fraction resulted from the process and was converted into an additional high-value microporous AC of high surface area (1220 m 2 g −1 ) [47].
The estimated surface areas (Est-S BET ) of ACs in the present study were lower than those reported in the literature that used chemical activation [1,[31][32][33]39]. Chemical activation typically yields AC with higher surfaces area than physical activation. Values of the same magnitude were found when compared with studies that performed physical activation [1,6,45]. Maneerung et al. [45] reported SBET values of 737 m 2 g −1 from woody biomass after steam or CO 2 activation at 800 • C with corresponding yields of 55% and 39%, respectively. The starting material was residual charcoal from mesquite (Prosopis spp.) chips which had been processed for syngas. Thus, the feedstock precursor was very different in the Maneerung et al. [45] study than that in this study in that there was probably little or no volatile compounds remaining associated with the charcoal that could get redeposited on the carbon [6] effectively clogging or reducing the pore diameters or numbers. The conditions for activation were for 3 h at a gas flow rate of 90 mL min −1 in Maneerung et al. [45] vs. 2 h at a flow rate of 150 mL min −1 in this study. Activation at elevated temperatures for long duration, generally results in a reduction in AC yield. According to Maneerung et al. [45], AC surface area increases with increasing process temperature and with the amount of activating agent.
In AP-AC and BP-AC, the chemical differences between the piassavas and the two pretreatments (Corona electrical discharge and extraction) influenced the final AC properties. However, the AP-AC and BP-AC had properties similar to those found in the literature. The ACs of this work were physically activated, which is an advantage, since there is no need for extra washing or the use of expensive reagents.

Conclusions
ACs prepared from Amazon and Bahia piassava fibers, with and without pretreatment, by physical activation with CO 2 have potential for use as adsorbent. The pretreatments applied to the fibers influenced the properties of the ACs.
The initial chemical compositions of Amazon and Bahia piassavas affect the physical-chemical characteristics of the resulting AC due to the higher lignin content in AP compared to BP. The ACs had higher adsorption capacity of methylene blue than phenol, according to adsorption isotherms and Langmuir and Freundlich parameters. Extraction as a pretreatment improved AC properties over Corona electrical discharge pretreatment. All of the ACs in this work had good adsorbent properties, employing extraction as a pretreatment was an improvement over values reported in the literature and AP-AC had better properties than BP-AC.
This study provides relevant information on the characteristics of the ACs produced from untreated and pretreated piassava fibers and verifies previously reported research.

Conflicts of Interest:
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
Disclaimer: Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture.
EEO Statement: The U.S. Department of Agriculture prohibits discrimination in all its programs and activities on the basis of race, color, national origin, age, disability, and where applicable, sex, marital status, familial status, parental status, religion, sexual orientation, genetic information, political beliefs, reprisal, or because all or part of an individual's income is derived from any public assistance program. (Not all prohibited bases apply to all programs.) Persons with disabilities who require alternative means for communication of program information (Braille, large print, audiotape, etc.) should contact USDA's TARGET Center at (202) 720-2600 (voice and TDD). To file a complaint of discrimination, write to USDA, Director, Office of Civil Rights, 1400 Independence Avenue, S.W., Washington, D.C. 20250-9410, or call (800) 795-3272 (voice) or (202) 720-6382 (TDD). USDA is an equal opportunity provider and employer.


extfieldsofstudy:
Physics
Materials Science

text:
Review: A Comparison of Conditions for The Extraction of Vegetable and Essential Oils Via Microwave-Assisted Extraction

Microwave Assisted Extraction (MAE) has been utilized in extracting a myriad of phytochemicals, lipids, carbohydrates, and proteins. This extraction method essentially takes advantage of water present inside cells by exciting the molecules hence increasing the internal temperature and pressure till the cells bursts. MAE is studied extensively due to its advantages over other typical extraction methods; especially in essential oil extraction. However, there is not many researches on using MAE to extract vegetable oil. Essential and vegetable oils are both derived from plants, but the characteristics of both oils differs. Therefore, the proper conditions for MAE extraction of the oils are different. This paper reviews the MAE conditions such as extraction time, power of microwave, solvent to feed ratio, and the set-up of microwave equipment. This paper attempts to show the differences between the MAE conditions between vegetable and essential oil extraction. The challenges faced by MAE is also discussed briefly with suggestions to overcome them. The Internet of Things is also discussed for its implementation in a scaled up MAE reactor.

Introduction
Microwave-assisted extraction (MAE) has been utilised in extracting both essential oil (EO) and vegetable oil (VO). However, due to the different characteristics of EO and VO, the parameters of the extraction between the two are different. VO is defined as fats extracted from either the seeds of a fruit or a vegetable or from other parts of plants [1]. EO is defined as volatile substances which is extracted via hydrodistillation or mechanical method that is mainly made up of terpenoid which is responsible for the scent, odour, or smell in plants [2] [3]. Some important parameters that need to be considered for which are the solvent, solvent volume, extraction time, and microwave power [4]. Therefore, these parameters are discussed in this paper.

Composition of VO and EO
Generally, the major composition of vegetable oils are fats whereas the composition of essential oils are terpene/terpenoids [2]. VO is mainly comprised of glycerides with 97 % triacylglycerides [1]. The different type of fatty acids that are attached to the triacylglycerides generally determines the properties of the VO [1]. VO liquid state in room temperature is attributed to the high density of unsaturated fatty acids [1]. A lower melting point VO would usually contain C6-C12 fatty acids [1]. For example, coconut oil extracted from coconut meat contains saturated fatty acids which are made up of mostly medium chain fatty acid [5]. A large portion of it is made up of lauric acid, a 12 carbon long fatty acid [5]. EO on the other hand, comprised of mainly the phytochemical terpenoid with only 1-10 wt% of the composition identified to be non-volatile substances [2]. The composition of EO includes terpenes derivatives, alcohols, esters, and ketones [2]. Interestingly, essential oil could be extracted from different parts of a plant like the extraction of flavonoids and tannins from coconut leaves [6]. For example, orange oil, an EO deriving from the peels of oranges, has a composition dominated by limonene; a terpene [7].

Volatility and viscosity
Volatility is affected by the vapour pressure of the liquid where a high vapour pressure is an indication of high volatility [8] Vapour pressure is determined by the intermolecular force (IMF) of the liquid and also its molecular mass [8] Liquids with large IMF and molecular mass tend to have low vapour pressure hence lower volatility [8]. Essential oils are also known as volatile oils [9]. This is due to the fact that terpenoids or terpene derivates, the majority of the constituents of EO, is volatile [2]. Vegetable oils like olive, coconut, and palm oil are also known as non-volatile oil as those oils do not evaporate at room temperature and stay in liquid form due to IMF between fatty acids [1] [10]. If the oil is non-volatile, more often than not, it is viscous. For example, palm oil, a type of non-volatile oil, has a viscosity of 0.46 x10-1 Pa.s at 30 ℃ [11] 2. Comparison of parameters in MAE 3.1 Extraction time Table 1 shows the data for the extraction of several EO and Table 2 shows the data for the extraction of several VO done by several studies. Unless stated, the unit of the yield from the studies as shown in equation 1.
Most of the studies of essential oil extraction via MAE are more than 30 minutes and VO extraction, less than 30 minutes. The long time for EO extraction via MAE is may be due the extraction is kept on going until the volume of EO extracted was constant [12] [13] [14].

Microwave power
Generally, the higher the power, the larger the yield of oil [15]. Some studies utilised irradiation power that are not optimised like the maximum power was used to extract lemon essential oil [16]; which is unnecessary even if the objective of the study was to compare the heat and mass transfer of different MAE mode of operations. Whereas, optimised conditions like that was done, the studies showed that high power is not needed and the extraction duration is lower than conventional extraction duration [17] [18] [13]. A high microwave power would incur solvent losses the longer the extraction due to solvent boiling [19].

Solvent and solvent to feed ratio (SF)
There is a glaring difference between the solvent used in VO and EO MAE extraction where EO extraction utilised only water as solvent and some studies do not even use solvents for the extraction [20] [21]. This method is known as Solvent Free MAE (SFME). From the Table 1, it can be observed that EO extraction usually uses a lot of solvent when compared to VO extraction. It is true that the more solvent used, the greater the mass transfer of oil to solvent hence increasing yield. However, if the feed or samples are fully immersed and there is sufficient contact between the feed and solvent, the volume would be adequate [15]. Other than that, a higher amount of solvent would also be economically inefficient due to a higher energy requirement to heat up, cool down, and separating the solvent from the extracted compound [22]. Thus, optimisation of SF ratio is important as the amount of solvent to be used and its recovery is a limitation in terms of cost [23].
It can be observed that there is a difference between the utilised solvents between EO and VO. VO extraction via microwave used organic or non-polar solvents whereas EO essentially used only either water or steam. So, it is clear that EO extraction is much safer, cheaper, and environmentally friendlier than VO extraction. It is interesting to note that EO, like VO, is also non-polar; i.e. it will not dissolve in water. EO's composition is made up of terpenoid which is volatile and therefore contributes to EO's volatility [24]. Due to this, and also the fact that terpenoids are also thermolabile, hydrodisillation is used in most of EO's extraction methods which would preserve the components of EO that would otherwise decompose at high temperatures [4].

Microwave setup
The setup of the extraction equipment is an important factor for the effectiveness of MAE. Many setups have been devised such as gravity MAE, solvent free MAE, and steam diffusion MAE [25]. Commercial MAE equipment serve advantages in controlling other parameters that may be effective in increasing yield like RotoSYNTH's rotating vessel, higher power (Mars 6, CEM), and controlling pressure (Discover SP).
It can be seen from the table EO MAE are ex-situ extraction where EO is extracted outside the vessel in which the feed or material was in. Figure 1 shows the typical setup of MAE for EO where sometimes the collector would be replaced by a clavenger apparatus. A modification of this set up was done where the setup was in an inverted position where instead of the water vapour and EO going up, the extraction was assisted by gravity and went down [25]. This is known as the gravity assisted MAE. It is also possible for EO extraction to not include solvents where this setup is known as solvent free MAE [26] [20] [27]. Modifications play a part in yield. This was proved by extracting orange essential oil by 4 different MAE methods where it was found out that 92% of the total oil could be extracted by using the gravity assisted Other method had lowered yield due to excessive heating and also the increased solubility of EO in water [25].
On the other hand, VO MAE are in-situ where VO extracted stays in the vessel in which the feed or material was in. All VO extraction from the table are in-situ with the exception of hazelnut oil extraction where the oil was obtained by pressing after microwave treatment [28]. As for the other studies, the solvent would then be evaporated usually by rotary evaporator [29]. It would be unlikely for VO extraction MAE setup to mirror the setup for EO unless it is to extract the EO present in VO. This is due to the volatility of the oil. At room temperature, it can be observed that a typical VO like coconut oil, soybean oil, and olive oil would not evaporate as opposed to EO like lavender oil or lemongrass oil where these two would evaporate. Therefore, the setup of the MAE should be taken into account and prior to that, what type of oil is to be extracted. A good setup would be one that would aid in the dispersal of solvent and microwave throughout the feed. In-situ (condenser on top connected to vessel inside the modified microwave)

Reference
In-situ (modified with mechanical stirrer) Microwave set up

Problems faced by MAE
Some of the problems faced by this type of extraction are (1) solvent must be able to absorb microwave [34]. One should mix non-polar solvent with polar solvents to increase the effectivity of the solvents to absorb microwave [33]. (2) Thermolabile substances extraction [34]. Interestingly, it was suggested that transparent solvents are recommended for the extraction of thermolabile substances, which would explain why most studies for EO extraction via MAE used water [4]. (3) Other solvents other than water may be hazardous although there are studies from the table which used solvents such as n-hexane without any problems [35]. (4) Overpressure and leakage [4]. There are commercial microwaves that can control pressure and detect leakage [4]. However, modifying household microwaves do not have this luxury unless they are fitted with pressure and leak sensors. Other sensors that could be fitted are thermocouples (to monitor the temperature of the microwave) and thermographic camera (to observe heat distribution). (5) Non-polar solvents are unable to absorb microwave effectively [19]. This is akin to running the microwave empty; if the vessel used to contain the solvent does not absorb the microwave effectively [36]. This would damage the magnetron beyond repair and would cause arcing in the cavity or along the waveguide [35]. To detect a weak magnetron, household microwave manufacturers would provide a benchmark on how long would it take for water to boil. This method however, is painstakingly slow [37]. Another way to detect failing magnetron is via connecting it to an ohm meter between the terminals of a magnetron where a good magnetron would read less than 1 Ω when the ohm meter is set to the lowest resistance [37]. Other than that, by connecting a magnetron's terminal and metal casing to an ohm meter at the highest resistance scale, a reading of infinity would indicate a good magnetron [37]. (6) arcing. To prevent arcing, the lining of the cavity and the waveguide must be shielded. This should also be applied to sensors that are exposed directly to the microwave [38]. Recommended metals to prevent arcing are such as molybdenum, stainless steel, and  [38]. Problems 4 and 5 may not be so important in a lab scale setup, but to scale MAE up and for it to be viable for the industry, these problems are important to be addressed.

Advanced analytics and Internet of Things as a solution
Previously, it was mentioned that many sensors are needed to maintain a setup of a scaled up MAE. Studies of MAE pilot scale [39] [40]. The MAE reactor used by [39] was equipped with a rotatable drum which the feed is inserted in, a sensor that sense microwave and sends signals to adjust the microwave power if the power is too low, a resistance temperature detector, and an interlock to prevent accidental openings. The MAE reactor used by [40] was a continuous process (fitted with a pump) instead of a batch. At the end of the reactor, a thermocouple was fitted unto and at the start of the reactor, an infrared probe was added [40]. For safety, a vent was added in the case of over-boiling and a release valve was added in the case of blockage [40]. Other than the sensor installed in the reactor by [39] to adjust the microwave power, there is no mention of both reactors being automated and there are no sensors that monitor the electrical part of the reactor which would make maintenance a difficult task.
Internet of Things (IoT) is the utilisation of the internet to control and monitor devices remotely by having the devices send and receive data [41]. Advanced analytics is used in IoT by gathering data from sensors to be utilised for predictive analytics [42]. The implementation of predictive analytics would aid in automation and the implementation of new hardware [42]. This would also make predictive maintenance possible which helps in the optimisation of maintenance whether it be predicting when a part is going to malfunction, optimal time for maintenance, process optimisation, and to design new facilities [43]. By implementing IoT with predictive analytics in scaled up MAE reactors, it would be possible to optimise the process effectively with less time consumed and monitor the parts of the MAE reactors for any loss of performance; without being overwhelmed by large amounts of data.


extfieldsofstudy: Medicine Biology

s2fieldsofstudy:
Agricultural And Food Sciences
Biology

text:
Rapid Gut Adaptation to Preterm Birth Involves Feeding-Related DNA Methylation Reprogramming of Intestinal Genes in Pigs.

Following preterm birth, the immature gut function and immunology must rapidly adapt to cope with bacterial colonization and enteral milk feeding. We hypothesized that intestinal epigenetic changes are involved in the gut response to preterm birth and the first feeding. Using piglets as models for infants, preterm, and term pigs were fed total parenteral nutrition (TPN) or partial enteral feeding for 5 days, followed by exclusive enteral feeding with bovine milk until day 26 (weaning age). Intestinal structure, function, microbiome, DNA methylome, and gene expressions were compared between preterm and term pigs on days 0, 5, and 26 (n = 8 in each group). At birth, the intestine of preterm pigs showed villus atrophy and global hypermethylation, affecting genes related to the Wnt signaling pathway. Hypermethylation-associated lowered expression of lipopolysaccharide-binding protein and genes related to the Toll-like receptor 4 pathway were evident during the first 5 days of life, but most early methylation differences disappeared by day 26. Regardless, sucrase and maltase activities (adult-type brush border enzymes) remained reduced, and the gut microbiota altered (fewer Akkermansia, more Lachnoclostridia and Lactobacilli) until day 26 in preterm pigs. During the 0- to 5-day period, many new preterm-term methylation differences appeared, but mainly when no enteral feed was provided (TPN feeding). These methylation differences affected intestinal genes related to cell metabolism, including increased GCK (glucokinase) expression via promoter hypomethylation. In conclusion, the immature intestine has a remarkable capacity to adapt its gene methylation and expression after preterm birth, and only few preterm-related defects persisted until weaning. Early enteral feeding may be important to stimulate the methylation reprogramming of intestinal genes, allowing rapid intestinal adaptation to preterm birth.

INTRODUCTION
Preterm birth accounts for ∼10% of all live births and remains a major global health problem (1). For survival after preterm birth, the structure and function of the immature gut must rapidly adapt to the new nutritional and microbial environment. This adaptation may fail, or take some time to develop, as indicated by a high sensitivity to feeding intolerance, gut inflammation, and necrotizing enterocolitis (NEC) in preterm infants during the first weeks after birth (2,3). Later, children born preterm may show elevated risks of neurologic and metabolic disorders (4)(5)(6)(7), whereas persistent gut complications are less often reported. Both short-and long-term gut complications may result from a combination of three critical factors, shortened gestational age at birth, premature transition to enteral feeding, and inappropriate bacterial colonization. Thus, the optimal dietary strategy (e.g., timing, volume, and type of diet) and most appropriate bacterial colonization of the immature gut remain unknown. A better understanding of how the immature gut interacts with environmental factors, such as nutrition and microbes, is required to define how early feeding strategies can best secure optimal adaptation of the preterm infant to postnatal life.
Adequate nutrient supply is critical for growth and organ development in preterm infants, but mother's milk is often insufficient or delayed in supply during the first weeks after preterm birth. Partial or total parenteral nutrition (TPN) is often used to support nutritional intake during the first 1-2 weeks, and this helps to combat the high sensitivity to feeding intolerance and NEC (8). On the other hand, lack of milkderived immunomodulatory and trophic factors during TPN may compromise intestinal maturation (9,10) and lead to more systemic infections and metabolic disorders (11). Preterm pigs, an animal model of preterm birth with a full range of prematurity signs (e.g., high sensitivity to NEC, sepsis, respiratory distress, neurological impairment, metabolic disorders) (12), respond to fast increases in enteral feeding (e.g., >120 mL/kg per day within few days) with marked intestine-trophic responses, but also with a high NEC sensitivity, especially when the diet is infant formula vs. more protective milk diets, such as sow's or cow's colostrum (12)(13)(14). The NEC risk is much less when enteral feeding is advanced slowly, in parallel with parenteral nutrition (15), similar to the situation for most preterm infants. There are differences in transfer of passive immunity between pigs and infants (e.g., immunoglobulin transferred postnatally via the gut in piglets vs. transplacental transport before birth in infants), but these differences do not appear to explain differences in NEC sensitivity (16). Even small volumes of formula may be detrimental in both preterm infants and pigs, and gradual feeding with natural milk or colostrum products may benefit intestinal maturation (15,17,18). Early enteral feeding (ENT) with small volumes is therefore recommended for preterm infants (10) despite that its diet dependency and the benefits vs. risks remain debated. It is therefore important to investigate the intestinal molecular functions affected by early TPN and early supplemental ENT feeding to understand the biological pathways and mechanisms of gut adaptation in preterm neonates. In an ongoing clinical trial in very preterm infants (ClinicalTrials.gov identifier NCT03085277), ENT with small volumes of bovine colostrum is being investigated.
As one of the important epigenetic mechanisms of tissue adaptation, DNA methylation plays a key role in sensing environmental exposures, thereby regulating transcription and cellular function during development (19). Because of the shortened gestation, intestines of preterm neonates may be subject to an accelerated adaptation after birth to adjust cellular functions, together with distinct DNA methylation profiles that reflect developmental immaturity at birth and postnatal exposure to enteral milk and microbes. We previously showed that formula feeding and bacterial colonization have marked shortterm effects on intestinal DNA methylation in preterm pigs (18,20), but it is not known if such changes are stable more long-term and ENT-dependent. Preterm-term comparisons of the intestinal methylome with advancing postnatal age help to elucidate if the phenotypic and molecular differences observed at birth may have long-term consequences for gut development in preterm neonates.
We hypothesized that the intestine of preterm neonates has a distinct epigenetic signature at birth and that DNA methylation changes in the postnatal period depending on the presence of ENT stimulation, to help adapt the immature intestine to postnatal life. Cesarean-delivered preterm or term pigs were euthanized for tissue collection shortly after birth or fed TPN or gradually increasing amounts of enteral nutrition (ENT) using bovine colostrum for 5 days, followed by transition to the same milk diet until day 26 (weaning age). The two feeding regimen, both of which minimize NEC risk (15), allowed us to examine how the immature intestine responded to the presence of enteral nutrition without confounded by NEC. Intestinal phenotypes (including morphology, digestive and absorptive function, microbiota composition), genome-wide DNA methylation, and targeted gene expression were compared between preterm and matched term pigs.

Animal Experimental Procedure
All animal procedures were approved by the Danish National Committee on Animal Experimentation. One hundred sixtyeight piglets from eight sows (Danish Landrace × Large White × Duroc) were delivered by cesarean section at full term (day 118 or 100% gestation, n = 56 pigs from three sows) or preterm (day 106, 90% of gestation, n = 112 pigs from five sows) (21,22). Based on immaturities in the intestine and other organs (e.g., lungs, liver, kidney, immunity), preterm 90% gestation pigs can be considered a relevant model for corresponding aspects in human infants delivered at ∼70% gestation (12). Immediately after cesarean section, all pigs were transferred to our piglet neonatal intensive care unit and reared in individual incubators. Within 3 h of delivery, all pigs were fitted with orogastric and umbilical arterial catheters. Preterm and term pigs were randomly assigned to be euthanized immediately after birth (n = 8, sodium pentobarbital, 200 mg/kg, intraarterial) or to receive total parental nutrition (TPN) or parenteral nutrition plus supplemental enteral nutrition (ENT) for 5 days. Total parenteral nutrition-treated pigs were given parenteral nutrition with gradually increasing volume (from 96 mL/kg per day on day 1-114 mL/kg per day on day 5). Enteral feeding-treated pigs were given bovine colostrum with gradually increasing volume (from 16 mL/kg per day on day 1-64 mL/kg per day on day 5), accompanied by a reduction in parental nutrition, such that the two dietary regimens both provided similar fluid volumes and were isoenergetic. In this setting, parental nutrition was infused continuously, while bovine colostrum was given every 3 h using the orogastric catheter. Importantly, the volume progression (16-64 mL/kg per day) was relatively slow, representing a careful approach to advance enteral nutrition.
On day 5, TPN and ENT pigs were randomly assigned to be euthanized for tissue collection or transitioned to full enteral nutrition with cow's milk, a gut-protective diet for preterm pigs (23), until euthanasia on day 26. For the latter ones, parental nutrition was discontinued on day 5, and pigs started to receive full enteral nutrition via a trough until the end of the study (8-10 feedings per day). During the period when pigs learned drinking milk from the trough (2-3 days), any remaining milk left in the trough was given to the pigs via the orogastric catheter. Therefore, during transition from TPN or partial ENT to full ENT, all pigs received the preplanned milk amount. All animals were reared individually throughout the study. Incubators with controlled ventilation and heating (from 0 to 5 days), larger home boxes (from 5 to 12 days), and even larger home cages (from 12 to 26 days) were used. All details of animal procedures were described previously (21,22).
Consequently, intestinal tissues were collected on days 0, 5, and 26, from a total of 10 groups of pigs. Eight pigs from each group were randomly selected for this study (Figure 1A, total n = 80). Shortly before euthanasia, intestinal permeability was measured by the lactulose-mannitol technique, glucose absorptive capacity by performing a galactose absorption test, plasma levels of glucose-dependent insulinotropic polypeptide (GIP) by radioimmunoassay, and diarrhea was evaluated by a diarrhea score, as described previously (22). Immediately after euthanasia, two 1-cm pieces of the middle of small intestine (jejunum, 50% along the length) were collected, snap frozen in liquid nitrogen, and kept at −80 • C for subsequent analysis of enzyme activities, DNA methylome, and gene expression. Considering our aim to characterize the overall intestinal methylation differences, involving all interacting cell populations, we decided to analyze full-thickness intestine. Two additional full-thickness 1-cm sections of the middle intestine were fixed in 4% paraformaldehyde for later histological analysis. Luminal content from colon was collected for later microbiota analysis.

Intestinal Morphology and Enzyme Activity Analyses
To evaluate the mucosal morphology, two paraformaldehydefixed jejunum samples were embedded in paraffin, sectioned, mounted on slides, and stained with hematoxylin and eosin before measuring villus height and crypt depth as described previously (23). For each pig, villus height and crypt depth were measured from 10 representative well-oriented villus-crypt axes by ImageJ software, National Institutes of Health, USA. The mean of 10 villus heights and crypt depths were used as representative value for one pig. To estimate the proportion of epithelial cells in the middle small intestine, immunohistochemistry (IHC) using the epithelial cell marker (cytokeratin) was performed, and the proportion of the positive staining for cytokeratin in crosssectional areas was calculated by the IHC toolbox in ImageJ. Finally, activities of brush border enzymes (lactase, maltase, and sucrase) were analyzed in homogenates of the middle intestinal tissues by spectrophotometry and were expressed as units per gram of wet tissue, as described previously (20,22).

Reduced Representation Bisulfite Sequencing
Genomic DNA from the middle intestinal tissues was extracted using DNeasy Blood & Tissue Kit (Qiagen, Hilden, Germany) and was subjected to reduced representation bisulfite sequencing (RRBS), as previously described (24). Raw sequencing data were processed by the Illumina base-calling pipeline. Low-quality reads that contained more than 30% N's or >10% of the sequence with low-quality value (quality value <20) per read were omitted from the data analysis. Bisulfite sequence mapping program was used for sequence alignment to the Ensembl pig reference genome (Sscrofa10.2). Methylation level of individual cytosine was calculated as the ratio of sequenced depth of methylated cytosine to the total sequenced depth of the individual cytosine. One of 80 samples failed in RRBS and was excluded in DNA methylation analysis.

Gene Expression Analysis
Gene expression was analyzed as previously described (25). Briefly, total RNA was isolated from middle intestinal tissues (n = 8 in each group), using the RNeasy Mini Kit (Qiagen), and cDNA was synthesized using 2 µg total RNA by High-Capacity cDNA Reverse Transcription Kit (ThermoFisher, Waltham, MA, USA) according to the manufacturer's instructions. Primers for real-time quantitative polymerase chain reaction (RT-qPCR) were designed using Primer-BLAST. Real-time qPCR analysis was performed using QuantiTect SYBR Green PCR Kit (Qiagen) on LightCycler 480 (Roche, Basel, Switzerland), and results were analyzed according to double delta Ct method. Relative quantification of target genes was normalized to the housekeeping gene HPRT1 and was presented as mean values ± SEM.

Microbiota Analysis
Total DNA was extracted, and the v3-v4 hypervariable regions of the 16S rRNA sequence were amplified through PCR. The resultant amplicons were sequenced using the Illumina MiSeq system (Illumina, San Diego, CA, USA), producing pairedend reads. The raw data set containing pair-ended reads was merged, trimmed, filtered from chimeric reads, and subjected to operational taxonomic units (OTUs) clustering using the UPARSE pipeline. Representative sequences were aligned to the SILVA reference alignment (version: SILVA123). The OTU annotation results were employed to determine the microbiota composition in the colon region of each pig.

Statistical Analysis
Comparisons of phenotypic variables (villus height, crypt depth, brush border enzyme activities, gene expressions) were made using Student t-test, and a two-tailed p < 0.05 was considered as statistically significant. Comparison of epithelial proportion was made using Mann-Whitney U-test, and a two-tailed p < 0.05 was considered as statistically significant. Differentially methylated regions (DMRs) were identified as previously described (20). Briefly, the methylation levels between the two groups were tested using the Mann-Whitney U-test, and false discovery rate (FDR) of DMRs was controlled at level 0.05 with the Benjamini-Hochberg procedure. For microbiome analysis, Shannon diversity differences were tested using Mann-Whitney U-test, and a two-tailed p < 0.05 was considered statistically significant. Comparisons of relative abundance were made using Mann-Whitney U-test, and all p-values were adjusted for multiple comparisons with FDR correction.

The Intestinal DNA Methylome Is Hypermethylated at Birth in Preterm Pigs
A total of 39.7 mio reads per sample were generated from RRBS (mean across samples). Among the reads passing QC (∼33.8 mio/sample), 67.7% could be mapped to the Ensembl pig reference genome (Sscrofa10.2, Table S1). DNA methylation mainly occurred on CpG cytosines (mean methylation level, m = 60.4%), rather than CHG (m = 0.7%) or CHH cytosines (m = 0.6%). Thus, only CpG cytosines were analyzed thereafter. To avoid the potentially confounding influence of X chromosome inactivation on DNA methylation patterns between male and female pigs, only autosomal data were used. A total of 1,772,546 CpG cytosines detected in 10 groups of pigs were used for analysis.
Based on the individual cytosines, principal component analysis (PCA) showed that intestinal DNA methylomes were distinct for each age group. Moreover, the preterm and term groups remained separated postnatally (Figure 2A). Next, we started with a comprehensive genome-wide characterization of the intestinal CpG methylation in preterm and term pigs at birth (before any feeding). Similar to other mammalian DNA methylation landscape (26), the overall DNA methylation level of the gene body, that is, the genomic region from transcription start site (TSS) of a gene to its transcription end site (TES), was higher than that of adjacent intergenic regions (72.5 vs. 41.8%, p < 0.0001), and there was a marked hypomethylation (7.4%) around the TSS (Figure 2B, Table S2). The preterm intestines showed global hypermethylation compared to the term group (64.3 vs. 63.6%, paired Mann-Whitney U-test p < 0.0001; Figure 2B). A total of 103 genomic regions were identified as significantly DMRs between preterm and term pigs ( Figure 2C, Table S3). There were more hypermethylated DMRs (n = 82) than hypomethylated DMRs (n = 21). These DMRs included 941 CpG cytosines, equivalent to 0.05% of all the cytosines analyzed. In preterm pigs, 76% of these cytosines showed relative hypermethylation, and 37% was highly methylated (methylation level >75%).
Among the total 103 DMRs, 59 overlapped with genic regions, particularly in introns. Fifty-five genes contained at least one DMR in either their putative promoters or the gene bodies. Genes that contained DMR in their putative promoter included BHLHA9, SLC5A10, COX17, lipopolysaccharidebinding protein (LBP), STK11, CPTP, RD3L, FGFR3, C4orf46, NAP1L5, and ZPBP. Gene ontology enrichment analysis on all the 55 genes resulted in multiple biological processes, including steroid hormone receptor activity and canonical Wnt signaling pathway (Table S4). STK11 (also called LKB1) was involved in canonical Wnt signaling pathway that is important for epithelium development (27) and possessed a DMR in the putative promoter where methylation level was higher in preterm vs. term newborns (74 vs. 50%). Consistent with that promoter methylation may suppress gene expression, the mRNA expression of STK11 was down-regulated in the preterm newborns (0.7-fold, p < 0.001; Figure 2D). Similar to that the villus height and crypt depth differed between preterm and term pigs only at birth, differential methylation and gene expression of STK11 were detected at birth, but not on day 5 or 26.

Persistent Abnormal Methylation and Expression of Intestinal Genes Related to Innate Immunity
To investigate whether the observed differences of intestinal methylation between preterm and term newborns persist into the postnatal period, DMRs in 5-and 26-day-old pigs, fed either TPN or ENT during the first 5 days, were identified and compared with the 103 DMRs detected at birth. Only 6 and 28 of the 103 newborn DMRs persisted until day 5 in ENT-or TPN-feeding groups, respectively. On day 26, just before weaning, all the DMRs detected at birth were no longer different between preterm and term pigs ( Figure 2E). The 34 DMRs that lasted until day 5 in preterm pigs were associated with 13 genes, of which four genes (LBP, LHPP, NR3C1, WHSC1) were identified both in the ENT and TPN groups. The remaining nine intestinal genes with preterm-term gene methylation differences that lasted until day 5 were found only among TPN-fed pigs.
Among the above four common genes containing persistent DMRs until day 5, only LBP (lipopolysaccharide binding protein) contained a DMR within its putative promoter region, showing Values in barplots are presented as mean ± SEM. # P < 0.1, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. hypermethylation in preterm pigs (89 vs. 64% at birth and 84 vs. 57% by day 5; Figure 2F). The mRNA expression of LBP was negatively correlated with its promoter methylation level (Spearman ρ = −0.54, p < 0.0001) and was less expressed in preterm vs. term pigs at birth (0.1-fold, p < 0.001) and day 5 (0.3-fold for ENT, 0.5-fold for TPN, both p < 0.1; Figure 2F). Lipopolysaccharide-binding protein is important for initiating Toll-like receptor 4 (TLR4) signaling, which is essential for neonatal intestinal immune tolerance (28) and was proposed to impact the risk of NEC in preterm infants (29). Thus, expression of genes involved in TLR4 signaling was also examined. Similar to LBP, both TLR4 and the accessory protein CD14 tended to be less expressed in 5-day-old preterm vs. term pigs (both 0.3fold, p < 0.1). MYD88, which mediates signal transduction for TLR4, was comparable between preterm and term pigs or even up-regulated in TPN-fed 5-day-old preterm pigs (1.6-fold, p < 0.05; Figure 2F). Moreover, microRNA-146a and interleukin 10 (IL-10), representative for intestinal anti-inflammation, were less expressed in 5-day-old preterm pig, especially those fed TPN (0.05-and 0.06-fold, respectively, both p < 0.05), whereas proinflammatory cytokine IL-8 was less expressed in preterm pigs at birth (0.4 fold, p < 0.01) and increased to a similar level to that in term pigs on day 5 ( Figure 2F). C3 that is involved in complement cascade, another component of the innate immune response, showed persistent overexpression in preterm vs. term pigs from birth (1.2-fold) to day 5 (1.8-fold for ENT, 2.3-fold for TPN, all p < 0.05; Figure 2F).
Another DMR was located within a CpG island in the gene body region of NR3C1 encoding for the glucocorticoid receptor (GR), which may interfere with TLR4 signaling. This DMR showed hypermethylation in preterm vs. term pigs (89 vs. 69% at birth and 90 vs. 70% on day 5), but the DNA methylation level was not correlated with gene expression (Spearman ρ = 0.15, p > 0.05). Except that C3 was up-regulated by ENT vs. TPN during the first week regardless of gestation (1.6-fold for preterm, 2.1fold for term, both p < 0.05), no differences in DNA methylation or mRNA expression in the above genes were detected between the ENT-and TPN-treated pigs.

Reprogramming of the Intestinal DNA Methylome in Preterm Neonates Is Feeding-Dependent
Although most of the DNA methylation differences observed at birth disappeared by day 5 and especially day 26, PCA showed persistent separation between the preterm and term groups in postnatal period (Figure 2A). A detailed look into the four postnatal groups of DMRs, that is, 5d-ENT, 5d-TPN, 26d-ENT, and 26d-TPN pigs, revealed a number of new postnatal DMRs that did not overlap with the DMRs detected at birth. On day 5, there were more new DMRs in the TPN group (n = 800) than in the ENT group (n = 60; Figure 3A, Tables S5, S6). The 800 new DMRs in the TPN group consisted of 6,767 CpG cytosines, equivalent to 0.38% of all the cytosines analyzed. Approximately 89% of the involved cytosines showed hypermethylation in the preterm group. These 800 TPN-specific DMRs overlapped with putative promoters of 54 genes and gene bodies of 255 genes.
Pathway enrichment analysis based on all the genes containing the TPN-specific DMRs revealed nine KEGG pathways being significantly enriched (Figure 3B, Table S7), including multiple metabolic pathways (e.g., galactose metabolism, amino sugar, and nucleotide sugar metabolism). Among the 20 genes involved in the above nine KEGG pathways, one gene (GCK, encoding glucokinase) was involved in multiple pathways and had a DMR located within its putative promoter region, where methylation level was correlated with gene expression (Spearman ρ = −0.54, p < 0.01). Glucokinase showed promoter hypomethylation (51 vs. 75%) and increased gene expression in 5-day-old TPN-fed preterm vs. term pigs (1.7-fold, p < 0.05; Figure 3C). This GCK expression also correlated negatively with the plasma level of GIP, a sensor for luminal glucose (30) (p < 0.0001, r = −0.52; Figure 3D). To explore additional effects of the gene methylation-regulated intestinal GCK, a protein-protein interaction analysis with the remaining 19 genes involved in the enriched pathways was performed. Result showed that GCK was directly or indirectly related to seven genes (GMPPA, GMDS, GALE, GALK1, PPARA, PPARD, and FABP1).
Next, to examine whether the new postnatal preterm-term methylation difference persisted until weaning, we searched for overlapped DMRs in 5-and 26-day groups. The result revealed only two genes (ZIP4 and DTX4), which showed no methylation difference at birth. However, hypermethylation of these two genes occurred after 5 days of TPN (but not ENT) feeding (55 vs. 31% for ZIP4, 59 vs. 34% for DTX4), and hypermethylation persisted until 26 days (56 vs. 39% for ZIP4, 61 vs. 39% for DTX4), although all pigs received full ENT from 5 to 26 days ( Figure 3E). Subsequent analysis of mRNA expression of these two genes showed hypermethylation-associated down-regulation in TPN-fed preterm pigs on day 5 (0.1-fold for ZIP4, 0.2-fold for DTX4, both p < 0.05), but not day 26 ( Figure 3E).
On day 26, the number of new DMRs in the TPN group (n = 31) was similar to that in the ENT group (n = 39), and these were associated with a similar number of genes (14 and 15 for TPN and ENT, respectively, Tables S8, S9). In both ENT and TPN groups, DMRs associated with CAMK2G, BRD3, and BAHCC1 were detected. Methylation level of DMRs in these three genes was higher (79 vs. 53% for CAMK2G, 81 vs. 53% for BRD3, and 69 vs. 40% for BAHCC1) in preterm vs. term pigs on day 26. As sucrase activity differed between preterm and term pigs only on day 26, correlation between sucrase activity and the methylation of these three genes was analyzed using all pigs. Significant negative correlation was found (all Spearman ρ < −0.6, p < 0.0001). In summary, the above results described a feeding-dependent DNA methylation reprogramming pattern in the neonatal intestine following preterm birth.

DISCUSSION
Perinatal intestinal maturation is determined by intrinsic genetic mechanisms (a predetermined "biological clock"), as well as external stimuli, including the birth process, nutrition, and microbes. When born preterm, the intestine needs to rapidly adapt to tolerate the transition from parenteral to enteral nutrition while avoiding NEC. Total parenteral nutrition or parenteral nutrition together with small volume of natural milk or colostrum is NEC-protective in preterm infants (31) and preterm pigs (15). It is critical to understand the molecular mechanisms that make the preterm intestine adapt, or fail to adapt, and characterize the subclinical differences between these two feeding regimen. Considering that DNA methylation can be affected by nutrition and plays a key role in regulating gene expression, our study provides new knowledge on feedingdependent intestinal adaptation in preterm neonates. We show that reduced gestational age at birth (independent of other birthrelated factors) is associated with a marked hypermethylation of intestinal genes that largely disappears by weaning. The two NEC-protective feeding regimens used in this study for the first 5 days (TPN, ENT) modulated the immune response in similar ways, but differed in their effects on specific genes related to intestinal metabolism. Preterm birth and the early diet differences may not have major long-lasting effects on intestinal functions, as indicated by the limited number of persistent gene methylation changes. However, it cannot be excluded that a more NEC-provocative early feeding regimen, using fast advancement of infant formula, would have more lasting effects on gene expressions and its regulation by gene methylation differences.
The global intestinal hypermethylation at preterm birth included a key gene, STK11/LKB1, which is a tumor suppressor gene in the Wnt/β-catenin pathway to regulate intestinal epithelial cells apoptosis and control cell proliferation (32). Here we showed that at preterm birth the immature intestine had shorter villus height and crypt depth, together with less expression of STK11 via promoter hypermethylation. The down-regulation of STK11 in the immature intestine may facilitate intestinal epithelial cell growth after preterm birth, and consistently, difference in the villus height and crypt depth disappeared within the first week of life. Thus, our results suggest that DNA methylation plays an important role in helping the immature intestine to adapt to postnatal life, both when fed enterally and parenterally during the first day after birth.
Intestinal hypermethylation in preterm neonates included another key gene related to innate immunity, LBP, and hypermethylation of its promoter-reduced LBP mRNA expression within the first week in preterm vs. term newborns. Lipopolysaccharide-binding protein presents LPS to host cells through TLR4 (33), and we previously showed that the expression of LBP is positively correlated with bacterial adherence to the intestinal epithelium in preterm pigs (18). Reduced neonatal LBP expression following preterm birth may indicate for an immature gut immunity in preterm pigs, also reflected by reduced expression of genes in the TLR4 signaling pathway. In mice pups, the newborn intestine develops tolerance to LPS stimulation by expressing TLR4-dependent microRNA-146a, which represses the TLR4 signaling molecule IRAK1 and prevents nuclear factor κB (NF-κB) translocation (28). Correspondingly, we found that TLR4 and its accessory protein CD14 as well as microRNA-146a, but not MYD88, were downregulated in the preterm intestine by day 5, probably leading to impaired LPS tolerance in an MYD88-independent manner. Consistently, the anti-inflammatory cytokine IL-10, which could be induced by microRNA-146a (34), was also less expressed in the preterm intestine by day 5. The proinflammatory cytokine IL-8 (a NF-κB target gene) was less expressed in the preterm intestine at birth but increased to a level comparable to that in term pigs already by day 5. In addition, C3, which is central for activation of the complement system, was persistently higher expressed in the preterm vs. term intestine during the first week. These results suggest that preterm birth is a risk factor for the immature intestine via an immature TLR4 signaling pathway, regardless of the initial feeding regimen (TPN or ENT) and at least partly regulated by epigenetic changes. It is important to note that both feeding regimens in the current study were NECprotective (TPN or ENT with bovine colostrum). Only when fed infant formula, LBP expression increases more markedly in response to bacterial contact and results in much lower microRNA-146a, as well as much higher C3 levels, as shown previously (18). This helps to explain the well-known difference in NEC risk among TPN-, colostrum-, and formula-fed preterm newborn pigs and infants.
Unlike in the case of LBP, hypermethylation of NR3C1, encoding GR, was observed in the gene body with no difference in mRNA expression between newborn preterm and term pigs. Hypermethylation of NR3C1 in the preterm intestine may be associated with lack of cortisol stimulation before preterm birth, because methylation of this gene is sensitive to cortisol and stress responses (35). In both pigs and humans, circulating glucocorticoid levels increase markedly prior to term (36) to regulate final maturation of many organ functions, including the intestine (37,38). A better understanding of the potential regulatory role of methylation in NR3C1 gene body is required.
While most newborn intestinal methylation defects in preterm pigs disappeared rapidly postnatally, novel pretermterm differences were identified, especially in relation to metabolic pathways in 5-day-old pigs fed TPN. These TPNspecific methylation changes covered 0.38% genome-wide cytosines, which were much more than that detected at birth (0.05%). Pathway enrichment analysis identified one gene, GCK (glucokinase), whose promotor hypomethylation likely upregulated the corresponding GCK transcription in TPNtreated preterm pigs. This may reflect a specific adaptation of the preterm TPN-fed intestine to facilitate glucose metabolism (relative to fat and amino acid metabolism). The inverse correlation with circulating GIP levels, an important sensor to luminal glucose (30), supports this hypothesis. In addition, protein-protein interaction analysis indicated that GCK might interact with PPARA (peroxisome proliferator-activated receptor α) and FABP1 (fatty acid binding protein 1), both of which are major regulators of fatty acid metabolism (39)(40)(41) and showed aberrant DNA methylation in TPN-fed preterm pigs. Thus, gene methylation of GCK may help to adapt intestinal nutrient metabolism in preterm neonates during the important transition from parenteral to enteral nutrition. Despite the marked feedingdependent DNA methylation reprogramming in the first week of life, the intestinal DNA methylation in preterm neonates converges toward the pattern observed in term counterparts, with advancing postnatal age and transition to full ENT.
The present study used whole intestinal tissue samples, not isolated cell types (e.g., enterocytes) for DNA methylation analysis. This approach likely better represents the in vivo state of the intestine with many different cell types interacting during development and in response to feeding and diseases. On the other hand, this approach limited our ability to identify cell type-specific methylation changes associated with preterm birth and early feeding regimens. As DNA methylation is known to vary across cell types (42), changes in the intestinal cell composition may also contribute to DNA methylation changes in the intestinal tissue. However, as we did not observe any difference in the proportion of epithelial cells between preterm and term pigs along development, the reported DNA methylation differences are unlikely to be due to major changes in relative cell compositions.
In conclusion, the preterm intestine has a remarkable capacity to adapt to postnatal life, and this may involve highly dynamic gene methylation changes. At preterm birth, the intestinal epigenetic patterns may reflect incomplete fetal programming associated with immature morphology, digestive capacity and elevated risk of inflammation. The immature intestine has a high reprogramming capacity, involving both immunological and metabolic plasticity. The first week after preterm birth is an important window of opportunity, and early and gradual introduction of protective milk diets (e.g., mother's own milk or colostrum) may be important to facilitate optimal adaptation.

DATA AVAILABILITY STATEMENT
The data sets generated for this study can be found in the NCBI Gene Expression Omnibus (GEO) with accession GSE108284.

ETHICS STATEMENT
The animal study was reviewed and approved by the Danish National Committee on Animal Experimentation.

AUTHOR CONTRIBUTIONS
XP and FG analyzed and interpreted the data. XP, FG, and PS were major contributors in writing the manuscript. TT took part in the main study design. All authors read and approved the final manuscript.