extfieldsofstudy: Mathematics Medicine

s2fieldsofstudy:
Agricultural And Food Sciences
Biology

text:
A strategy for qualitative and quantitative profiling of glycyrrhiza extract and discovery of potential markers by fingerprint-activity relationship modeling

This study was to evaluate the quality consistency of glycyrrhiza extract and to explore the possible anti-oxidant components in combination with chromatographic fingerprint and bioactivity evaluation. Characteristic fingerprints of glycyrrhiza extract samples from different sources were generated by high performance liquid chromatography with diode array detector (HPLC-DAD) and evaluated using hierarchical clustering and similarity analysis. Compared with the conventional qualitative similarity evaluation method, the averagely linear quantified fingerprint method had an important quantitative similarity parameter supported by quantitative analysis, which was recommended in the fingerprint evaluation. Antioxidant activities of the glycyrrhiza extract samples were determined by DPPH (2, 2-diphenyl-1-picryldrazyl) radical scavenging assays. In addition, the fingerprint-efficacy relationship was investigated by the chemical fingerprints and the anti-oxidant activities utilizing partial least squares model, which was capable of exploring and discovering the bioactive components of glycyrrhiza extracts. Therefore, the present study provided a powerful strategy to evaluate the holistic quality consistency of medicinal plant.

Chromatographic separation was measured with an Agilent series 1100 system equipped with quaternary gradient pump, thermostatic column compartment, DAD, autosampler and a CAPCELL PAK C18 MG column (250 × 4.6 mm, 5.0 μm, shiseido, Japan). The mobile phase consisted of aqueous solution containing 0.1% (v/v) phosphoric acid and 5 mM sodium 1-heptanesulfonate (A) and acetonitrile containing 10% (v/v) anhydrous ethyl alcohol and aqueous solution and 2.4% (v/v) phosphoric acid (B). Separation was achieved using the following linear gradient program: 6-18% B at 0-10 min, 18-33% B at 10-20 min, 33-46% B at 20-32 min, 46-60% B at 32-45 min, 60-78% B at 45-60 min, 78-80% B at 60-65 min. The column temperature was maintained at 35 °C. A 10 μL aliquot of each sample was injected into the HPLC-DAD system. The flow rate was set at 1.0 mL/min. The detection wavelengths were set at 344 nm, 280 nm, 250 nm, 220 nm and 203 nm. Similarity analysis. ALQFM is a mathematical data processing method based on fingerprint vector, which contains the quality and quantity analysis of fingerprints. Meanwhile, the quality level of evaluation criteria can be applied to read the evaluation results more intuitively and easily. The visualization analysis process for ALQFM was shown in Fig. 2A. , where x i and y i are the ith peak area, serve as sample and reference fingerprint vector, respectively. Average linear qualitative similarity (S L , Eq. 1) can clearly reflect the degree of similarity in the chemical compositions of the sample fingerprint and reference fingerprint in terms of distribution ratio. To describe apparent and calculated similarity, slope of linear equation (b, Eq. 2) and apparent content similarity (R%, Eq. 3) are calculated after weight-corrected by m S (the weight of each GE sample) and m R (the average weight of 30 GE samples). The closer R% and b are to 1, the more similar the sample fingerprint vector is to the reference fingerprint vector. Fingerprint variation coefficient (α, Eq. 4), a statistical error, is calculated using R% and b, which can reflect the accuracy of the model. Average linear quantitative similarity (P L , Eq. 5), an important quantitative parameter, is employed to monitor the overall content of all fingerprint components in the sample fingerprint. Accordingly, α, S L and P L are combined in the averagely linear quantified fingerprint method (ALQFM) to evaluate the quality of TCM (8 grades listed in Supporting Information Table S1). Generally, samples with the grade ≤ 5 were recommended as the qualified ones.

Results and Discussion
Methodology validation of HPLC analysis. The calibration curve, including linear ranges as well as the limit of quantity (LOQ) and limit of detection (LOD), regression equation and correlation coefficient (R 2 ) were showed in Supporting Information Table S2. All the analytes showed excellent linearity (R 2 ≥ 0.9999) over the tested concentration ranges. The LOQ and LOD, which were determined in the range of 0.500-5.000 μg/mL and 0.025-0.125 μg/mL, respectively. The accuracy of the HPLC method was evaluated by using the standard addition method and the average percent recoveries for six investigated compounds ranged from 97.65% to 100.71%, with relative standard deviation (RSD) value less than 1.92%. RSD values of each co-possessing fingerprint peak area were, respectively, less than 3.40%, 1.65% and 2.78% for the stability, precision and repeatability tests. Considering these results, the method was accurate and valid enough.
Compounds content analysis. The content of active ingredient contents in 30 GE samples was simultaneously determined using the established calibration curves (Supporting Information Table S2). Based on quantitative results (Table 1) Fig. S1), respectively, corresponding to the flavonoids and triterpene saponins 29 . In order to perform quality control of HM, it is necessary to establish a chromatogram with comprehensive composition information. However, for the complexity of HM compositions, it is difficult to accomplish this at a single wavelength. Therefore, fusion fingerprint 43 capable of synthesizing enhancing signal response and rich fingerprint information was absolutely necessary. As shown in Fig. 3, typical fusion HPLC fingerprints of 30 GE samples had similar chemical profiles with some common chemical compositions. Next, GE sample fingerprints and the reference fingerprint (RFP constructed by taking the average of the GE sample chromatograms) were imported to an in-house software "Digitized Evaluation System for Super-Information Characteristics of TCM Chromatographic Fingerprints 4.0" (Software certificated NO. 0407573, China) to calculate the quality evaluation results as presented in Table 2. Table 2 showed that except S6 (grade 5), the fusion fingerprint grades exhibited some fluctuations compared with the results at each wavelength. The resulting fluctuations may be caused by differences in response intensity and number of fingerprints at each wavelength. Consequently, the fusion fingerprint evaluation strategy is comprehensive and indispensable for avoiding potential deviations from single wavelength. Furthermore, except S18, the remaining 29 GE samples had α < 0.30 and all of the 30 GE samples had S L > 0.80, indicating that the samples were similar in the distribution and number of chemical compositions. Based on the qualitative parameters S L and α, the quality grades of 29 samples should be within 1-5. In fact, at 203 nm, S9 and S13 were judged to be outliers (8 and 6 respectively) combined with quantitative parameters (48.3% and 139.2%, respectively). For fingerprint analysis, a qualitative assessment (an acceptable α < 0.30 and S L > 0.70) should be performed firstly, followed by a further quantitative evaluation (acceptable 70.0% ≤ ≤ 130.0%). Eventually, in this study, the fusion qualities of 30 GE samples were successfully evaluated in terms of the criteria (shown in Table 2). The quality grade of S16, S17, S25, S26, S30 were best (Grade 1), those of S8, S19-S21, S23 and S27 were better (Grade 2), and those of S4, S5, S7, S11, S14, S22, S24, S28 and S29 were good (Grade 3), and those of S15 and S18 were fine (Grade 4), except for that of S1-S3, S6, S9, S10, S12 and S13 as moderate (Grade 5) due to their much lower or higher contents. ALQFM provides a reliable and feasible strategy to qualitatively and quantitatively assess TCM/HM fingerprints simultaneously.
Correlation between average linear quantitative similarity and quantitative analysis. In "Compounds content analysis" section, the compounds content in the GE samples were accurately quantitated using chemical reference substances. However, available chemical reference substances and more time were required for the quantitative analysis. Even if quantitation is feasible when the chemical reference substances  As discussed in "HPLC fingerprint analysis" section, P L is an important parameter for quantifying all fingerprint components in the sample fingerprint. The relationship between P L and the quantitative content of the six compounds was further explored. The P 6C values (y, average of six component percentages, Table 1) were, respectively, plotted vs. the P L values (x, P L −203 nm, P L −220 nm, P L −250 nm, P L −280 nm, P L −344 nm and P L -fusion, Table 2) as shown in Supporting Information Fig. S2. Linear regression shown that the correlation coefficients (r) were all above 0.5435, especially the correlation coefficient between P 6C and P L -fusion, reached an excellent value of 0.8487. This indicated that P L was basically consistent with the quantitative results for the six investigated compounds. Consequently, due to the economic, reliability, feasibility and simplicity advantages of quantifiable fingerprints for HM quality control, which has the potential to replace multi-component quantification.

Hierarchical clustering analysis.
To investigate the internal characteristics of GE samples from different sources, HCA 44 , a powerful multivariate analysis technique, was performed on HPLC fingerprints. HCA was performed using HemI statistics sofware (Heatmap Illustrator, Version 1.0). For the 30 GE samples, the quality grade difference between the fusion and 220 nm results were all within two grades (Supporting Information Fig. S3). Therefore, 220 nm fingerprint was the closest one to the fusion fingerprint and reflected more compound information than any other wavelengths from both qualitative and quantitative aspects. In this study, HCA was performed according to the peak areas of the 39 co-possessing peaks of 30 GE samples at 220 nm. Subsequently, between-groups linkage method and squared Euclidean distance was used as average linkage and a metric to evaluate 30 GE samples similarity. A hierarchical cluster heat-map (Fig. 4) was obtained to represent the dissimilarity (between the different groups) or similarity (within the same group) between 30 GE samples. Two main clusters were produced (Samples S1-S10 collected from Manufacturer A, Shanxi province and S11-S20, S21-S30 collected from Manufacturer B, C, Xinjiang province). The distance between samples in the different cluster was farther than the distance between samples in the same cluster, suggesting that the internal quality characterized by HPLC Sample 203 nm 220 nm 250 nm 280 nm 344 nm Fusion    17,41,42 . These results are consistent with the results of the quantitative fingerprint analysis, indicating that HCA only performs simple classification of samples, and the quantitative fingerprint analysis could provide a more accurate, feasible and reliable evaluation of TCM/HM. Subsequently, a simple and intuitive comparison of the chemical fingerprints (Fig. 3) involved comparing the color changes between the 39 co-possessing peaks in Fig. 4, which might be related to their different biological activities. In particular, the six investigated compounds showed strong color reactions. Thence, in the next part, antioxidant activity of the GE sample was studied.
Antioxidant activity. Antioxidant activity assay based on FIA. Antioxidant activity has been demonstrated to be an effective means of evaluating the biological activity of GE and related products in vitro 45,46 . To determine the total antioxidant capacity of GE samples, DPPH assays were performed by using the method introduced by Mrazek et al. 36 with slightly modification. In this study, the total antioxidant activities of the GE samples were assessed by the on-line UV spectroscopic DPPH method, where ascorbic acid equivalent (ASAE) values were measured as shown in Table 1. The results indicated that a majority of the GE samples were found to possess excellent antioxidant activities with an ASAE value above 0.2000 mM; however, S6, S9, S10 and S19 showed lower ASAE values (<0.2000 mM), indicating poor antioxidant activities. In addition, the ASAE values among different GE samples ranged from 0.1365 mM (S6) to 0.2809 mM (S12), showing a 2.06-fold difference in antioxidant activity. By observing chemical fingerprints and evaluation results, the difference in antioxidant activity was not caused by a simple change in the content of one certain component. Therefore, it is necessary to establish a model to investigate the relationship between antioxidant activity and chemical fingerprint.

Relationship between HPLC fingerprints and antioxidant activities.
A correlation model between the antioxidant activities and HPLC fingerprints was established to discover potential constituents with antioxidant capacity. PLS [47][48][49] , carried out using SIMCA-P 13.0 software (Umetrics, Sweden), was constructed by the ASAE values as the response matrix Y, and the HPLC fingerprints at 220 nm as the descriptor matrix X to investigate the spectrum-effect relationship. Based on the score plot centered on the data mean (Fig. 5A), outliers (S6 and S18) were identified and eliminated when constructing the final mathematical model. After excluding the outliers, the rest 28 samples were divided randomly into training and test sets (  , the more relevant for variable classification. Therefore, the six investigated compounds showed a strong antioxidant activity. In particular, the three largest variables (VIP value > 1.5) responsible for positive coefficient with antioxidant activity were the change in peak 7 (VIP value = 1.6928), peak 21 (VIP value = 1.6148) and LQA (VIP value = 1.5607) concentration (Fig. 5D).

Conclusion
To evaluate the quality consistency of GE samples, this study established a multi-prong approach including quantitative fingerprint evaluation (ALQFM), chemometric methods (HCA) and antioxidant activity assay. In quantitative fingerprint evaluation, all the GE samples showed similar S L and α; however, P L were able to identify the differences among the different samples due to the variations in the chemical contents. Moreover, P L was highly correlated with the content of the six investigated compounds, indicating that ALQFM had the potential to replace quantitative analysis to quantify complex HM systems. HCA had the ability to distinguish GE samples from different sources; however, the active ingredients in GE samples could not be clearly indicated. Therefore, with the help of chemometric approaches (PLS), fingerprint-efficacy relationship obtained by the rapid spectroscopic DPPH method was established for exploring the possible anti-oxidant active components in GE sample. The strategy proposed in this study provides a powerful, effective and practical method to evaluate the quality consistency of GE samples.


extfieldsofstudy: Medicine Biology

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

text:
PCR-Based Detection of Cryptosporidium spp. and Enterocytozoon bieneusi in Farm-Raised and Free-Ranging Geese (Anser anser f. domestica) From Hainan Province of China: Natural Infection Rate and the Species or Genotype Distribution

Cryptosporidium spp. and Enterocytozoon bieneusi are two important zoonotic pathogens that can infect humans and a broad range of animal hosts. However, few studies have been conducted to study infection of the two pathogens in domestic geese until now. The aims of the present study were to determine the prevalence of natural infection, and the species or genotype distribution of Cryptosporidium and E. bieneusi in farm-raised and free-ranging geese from Hainan Province of China. In total, 266 fecal samples of geese were collected (142 farm-raised and 124 free-ranging geese). Cryptosporidium spp. and E. bieneusi were identified by nested PCR and sequencing analysis of the SSU rRNA and the ITS region of the rRNA genes. A total of 4.1% (12/226) of the geese were positive for Cryptosporidium spp., with 0.7% identified in the farm-raised geese and 7.0% in the free-ranging geese. Two bird-adapted species/genotypes were identified: C. baileyi (n = 1) and Cryptosporidium goose genotype I (n = 11). Meanwhile, E. bieneusi was found in 13.9% (37/266) of geese, with 8.9% identified in the farm-raised and 21.8% in the free-ranging geese. Eleven genotypes of E. bieneusi were identified constituted with six known genotypes: D (n = 13), I (n = 5), CHG2 (n = 1), CHG3 (n = 5), and CHG5 (n = 1), and five novel genotypes named HNE-I to V (one each). All of the genotypes identified in the geese here belonged to zoonotic Groups 1 or 2. This study is the first to demonstrate the presence of Cryptosporidium spp. and E. bieneusi in domestic geese from Hainan, China, and provides baseline data that will be useful for controlling and preventing these pathogens in goose farms. The geese infected with E. bieneusi, but not with Cryptosporidium, should be considered potential public health threats.

INTRODUCTION
Cryptosporidium spp. and Enterocytozoon bieneusi are two obligate intracellular pathogens, which are common etiological agents of diarrhea in humans and animals around the globe (Fayer and Santin-Duran, 2014;Checkley et al., 2015). Both pathogens can cause death diarrhea in immunocompromised people, and are responsible for significant morbidity and mortality of children in developing countries (Matos et al., 2012;Khalil et al., 2018). Cryptosporidium and E. bieneusi can infect numerous vertebrate animal hosts, including mammals, birds, amphibians, reptiles, and fish (Santín and Fayer, 2011;Pumipuntu and Piratae, 2018). More importantly, the infective oocysts or spores of these two pathogens are ubiquitous in the environment. They are transmitted in humans, potentially through the fecal-oral route, either directly, via contact with infected humans or animals, or indirectly by ingesting food or water contaminated with the pathogens (Fayer and Santin-Duran, 2014;Xiao and Feng, 2017). Despite this knowledge, the contribution of each animal source to human infections is poorly understood.
Research conducted on the molecular epidemiology of Cryptosporidium has shown that it has a high diversity at the species level (Feng et al., 2018). To date, a total of 39 species, and more than 70 genotypes of Cryptosporidium have been described and 21 species and four genotypes out of these have been reported in humans Holubová et al., 2019). Many human-pathogenic species or genotypes have also been found in a variety of animal species, including farm animals, pets, and wildlife (Pumipuntu and Piratae, 2018). Similarly, E. bieneusi is a complex species of Microsporidia, and more than 500 ITS genotypes have been reported in humans and various animal (Li et al., 2019a). These genotypes can be placed into 11 distinct groups (named Groups 1-11) by phylogenetic analysis (Li et al., 2019b). More than 90% of the genotypes belong to Groups 1 or 2. Some of these genotypes are probably responsible for most zoonotic infections, and constitute a major risk for zoonotic or cross-species transmission because they have a large variety of hosts, including humans. The other nine groups (Groups 3-11) mainly include genotypes from specific hosts or wastewater, showing host adaption to some extent (Guo et al., 2014;Li et al., 2019b). The sources of contamination of Cryptosporidium spp. and E. bieneusi infection in humans can be clarified by genotyping the two pathogens in different hosts.
The majority of domesticated geese (Anser anser domesticus) descend from the Greylag goose (Anser anser). Geese are bred for meat, eggs, and feathers, and 95.3% of goose production in 2017 was in Asia (http://www.fao.org/faostat/en/#data/QL). The farming of geese has a long history in China. However, there are no available reports on identification and genotyping of Cryptosporidium in geese in China. Currently, only one study has evaluated E. bieneusi in geese, but the study included a small sample size and was limited to a very narrow geographical area of China (Zhao et al., 2016). The role of geese in the transmission of Cryptosporidium spp., and E. bieneusi remains unclear. The aims of the present study were to determine the prevalence of natural infection of Cryptosporidium and E. bieneusi in farm-raised and free-ranging geese from Hainan Province of China, to identify the genotype of Cryptosporidium and E. bieneusi isolates, and to assess the potential zoonotic transmission by homology and phylogenetic analysis.

Ethics Statement
Before beginning work on the present study, we contacted the farm owners and obtained their permission to have their animals involved. Written informed consent was obtained from the owners for the participation of their animals in this study. The protocol was also reviewed and approved by the Ethics Committee of Hainan Medical University.

Collection of Fecal Specimens
During the period from March to July of 2019, a total of 266 fresh fecal specimens (∼10 g of each) were collected from 142 farmraised and 124 free-ranging geese from three farm: Chengmai (n = 67), Ding'an (n = 45), and Lingshui (n = 30) cities and two areas (Chengmai city) in Hainan Province of China (Figure 1 and Table 1). The farms of geese were selected based only on the owners' willingness to participate and the accessibility of animals for sampling. All of the fecal specimens were collected from the ground immediately after defecation using a sterile disposable latex glove. Each individual sample was then placed in a labeled, sterile bag. To avoid duplicate sampling, only one fecal specimen was collected from each animal. None of the animals had apparent clinical signs at the time of sampling. Samples were obtained from 10% of the total number of geese in each farm or area. All of the specimens were transported to the laboratory in a cooler with ice packs (<24 h) and stored at −20 • C until processing (<1 w).

DNA Extraction
Each of the feces samples was thoroughly mixed with 40 mL of distilled water, and the liquid was then concentrated by centrifugation at 1,500 g for 10 min. Genomic DNA was directly extracted from ∼200 mg of each processed fecal specimen using a QIAamp DNA stool mini kit (QIAgen, Hilden, Germany), according to the manufacturer-recommended procedures. Then, 200 µL of extracted DNA from each sample was transferred into Eppendorf tubes, and stored at −20 • C until PCR amplification.

PCR Amplification
Cryptosporidium in the fecal specimens was identified by nested PCR amplification of a SSU rRNA gene fragment of ∼830 bp. The primers and the cycle parameters were designed by Xiao et al. (1999). Meanwhile, all DNA preparations were analyzed for the presence of E. bieneusi by amplifying an ∼390 bp region of the rRNA gene of E. bieneusi. The primers and the cycle parameters were designed by Buckholt et al. (2002). TaKaRa Taq DNA Polymerase (TaKaRa Bio Inc., Tokyo, Japan) was used for all PCR amplifications. PCR amplifications were performed with positive controls (rat-derived Cryptosporidium rat genotype IV DNA for Cryptosporidium spp. and rat-derived genotype Peru 8 DNA for E. bieneusi) and negative controls (2 µL distilled water). All of the secondary PCR products were subjected to electrophoresis in a 1.5% agarose gel, and were visualized by staining the gel with GelRed (Biotium Inc., Hayward, CA).

Nucleotide Sequencing and Analyzing
All of the Cryptosporidium and E. bieneusi positive PCR products were sent to Sangon Biotech Co. Ltd. (Shanghai, China), for sequencing, which all of the samples were sequenced in both directions. The species or genotypes of Cryptosporidium and the genotypes of E. bieneusi were identified by comparing the nucleotide sequences obtained with each other and with published GenBank sequences using the Basic Local Alignment Search Tool (BLAST) (https://blast.ncbi.nlm.nih.gov/Blast.cgi) and ClustalX 1.83 (http://www.clustal.org/).

Phylogenetic Analysis
To confirm the genogroup designation and to assess the genetic relationships of novel ITS genotypes of E. bieneusi obtained, Bayesian inference (BI) and the Monte Carlo Markov Chain (MCMC) method were used to construct phylogenetic trees in MrBayes v 3.2.6 (http://mrbayes.sourceforge.net/). Fig Tree  v 1.4.4 (http://tree.bio.ed.ac.uk/software/fifigtree/) was used to visualize and edit the maximum clade credibility tree generated by these analyses. Posterior probability values were estimated based on 1,000,000 generations with four simultaneous tree building chains, with trees being saved every 100th generation. A 50% majority rule consensus tree for each analysis was constructed based on the final 75% of trees generated by BI.

Statistical Analysis
Data entry and analysis were performed using Social Sciences (SPSS) 19.0 software. The statistical significance of differences in infection proportions was generally evaluated by Pearson's Chi-square test. The significant level of all tests was: p = 0.05.

Nucleotide Sequence Accession Numbers
Representative nucleotide sequences obtained in the study were deposited in the GenBank database under accession numbers MN472907 to MN472911 for E. bieneusi; MN461548 and MN461549 for Cryptosporidium.

Cryptosporidium Species/Genotypes Identified in Geese
All of the 12 Cryptosporidium-positive specimens were successfully sequenced at the SSU rRNA locus. Using sequence analysis, C. baileyi (n = 1) and Cryptosporidium goose genotype I (n = 11) were identified. The C. baileyi sequence obtained had 100% homology with a sequence (JX548296) obtained in chickens in Zhejiang, China. All of the 11 sequences of Cryptosporidium goose genotype I were identical, and had not previously been reported, although they had only one base different from the sequence (AY120912) found in an isolate of Canada geese from the USA. In the present study, Cryptosporidium goose genotype I showed predominance and it was found in one farm-raised goose and 10 free-ranging geese. While, C. baileyi was only found in a free-ranging goose ( Table 1).

Genetic Characterizations and Genotypic Distribution of E. bieneusi in Geese
Sequencing analysis of the 37 E. bieneusi isolates in this study showed that 11 different representative sequences were identified, with a total of 33 polymorphic sites observed (Figure 2). Six of 11 representative sequences had been previously reported, and were identical to the genotypes D, I, BEB6, CHG3, CHG5, and CHG2. However, the other five ITS gene sequences (MN472907 to MN472911) had not been previously reported, and were named genotypes HNE-I to HNE-V. HNE-I and HNE-IV had 99.18 and 99.59% homology with the genotypes CHG5 (KP262365) and CHG2 (KT235708), respectively, while genotypes HNE-II, HNE-III and HNE-V had 99.59, 98.35, and 99.59% homology with genotype CHG3 (MH822618), respectively.
Out of the 11 genotypes, genotype D was the most prevalent, with a prevalence of 57.3% (13/37), followed by genotype I, CHG3 and CHG5, which each had a prevalence of 28.0% (5/37), BEB6 with a prevalence of 4.9% (3/37), and then the remaining six genotypes, CHG2 and HNE-I to V, which each had a prevalence of 1.2% (1/37) ( Table 1). Genotypes D, I, BEB6, CHG2, and HNE-I were only found in free-ranging geese, and genotypes HNE-II to V were only found in farm-raised geese, while genotypes CHG3 and CHG5 were found in both farmraised and free-ranging geese. The distributions of E. bieneusi   genotypes in animals characterized by feeding mode was shown in Table 1.

Phylogenetic Relationship of E. bieneusi Genotypes
In the phylogenetic analysis tree, genotype D was classified in Group 1, and the genotypes I, BEB6, CHG2, CHG3, CHG5, and HNE-I to V were in Group 2 (Figure 3).

DISCUSSION
The first report on goose cryptosporidiosis was published in 1974, and identified parasites in five 14-day-old goslings from Iowa, USA (Proctor and Kemp, 1974). Since then, only two reports on Cryptosporidium infections in domestic geese have been published. In one study, Cryptosporidium infection was detected in 44 (59%) of goslings aged 8-35 days (Richter et al., 1994).
In the other study, Cryptosporidium infection was investigated in geese experimentally infected with Usutu virus using situhybridization, and showed that 89% of conjunctival tissue samples and 88% of bursal tissue samples of these geese were Cryptosporidium-positive (Chvala et al., 2006). Furthermore, Cryptosporidium was also reported in Canada geese in two studies conducted in the USA, with infection rates of 6.8 and 23.4% (Jellison et al., 2004;Zhou et al., 2004). For E. bieneusi, only one study has been reported in geese from Heilongjiang, China with a 30.8% (8/26) infection rate (Zhao et al., 2016). In the present study, the prevalence of Cryptosporidium spp. and E. bieneusi in geese were 4.1% (12/226) and 13.9% (37/266), respectively. The infection rates of both Cryptosporidium and E. bieneusi were higher in free-ranging geese than in farmraised geese, with 7.0% for Cryptosporidium and 21.8% for E. bieneusi in free-ranging geese, and 0.7% for Cryptosporidium and 8.9% for E. bieneui in farm-raised geese. The higher infection rates of Cryptosporidium and E. bieneusi in freeranging geese could be explained by the fact that farmed geese have better hygiene, whereas free-ranging geese have a FIGURE 3 | Bayesian phylogenetic analysis of Enterocytozoon bieneusi ITS sequences. Phylogenetic relationship of E. bieneusi genotypes identified here and other known genotypes deposited in GenBank was inferred by a Bayesian phylogenetic analysis of ITS sequences based on genetic distance by the Bayesian inference (BI) FIGURE 3 | and the Monte Carlo Markov Chain (MCMC) method. The statistically significant posterior probabilities are indicated at branches. Each sequence is identified by its accession number, host origin, and genotype designation. The E. bieneusi genotype CSK2 (KY706128) from white kangaroo was used as the outgroup. The empty squares and the squares filled in black indicate known and novel genotypes identified in this study, respectively.
wide range of space for activity, and access to a variety of water sources. There have been a few studies on the identity of Cryptosporidium spp. in geese, which have identified the occurrence of three species, including human pathogens C. hominis and C. parvum, and the avian species C. baileyi (Graczyk et al., 1998;Zhou et al., 2004;Chvala et al., 2006;Jellison et al., 2009). Meanwhile, six Cryptosporidium genotypes have also been found in geese, including four goose-specific genotypes named goose genotype I to IV, and the zoonotic pathogen muskrat genotype I, as well as Cryptosporidium duck genotype and C. hominis-like genotype (Zhou et al., 2004). However, only one study has characterized Cryptosporidium spp. in domestic geese, and only C. baileyi was found in those animals (Chvala et al., 2006). While, non-genotyped cryptosporidia have been detected in the swan goose and the black swan (Rohela et al., 2005). In the present study, C. baileyi and Cryptosporidium goose genotype I was identified in the domestic geese. C. baileyi was first identified in chickens (Current et al., 1986). Evidence has shown that C. baileyi can infect a broad range of birds with a wide geographic distribution (Nakamura and Meireles, 2015). Although C. baileyi has been identified in one immunodeficient patient, this species should not be considered as a true zoonotic agent since this patient was immunodeficient, and no other reports exist (Ditrich et al., 1991). Cryptosporidium goose genotype I has been commonly found in Canada geese, and has also been found in aquatic birds and peafowl (Jellison et al., 2004;Zhou et al., 2004;Cano et al., 2016;Feng et al., 2019). To date, no human cases of cryptosporiosis caused by Cryptosporidium goose genotype I have been identified. As only a small number of isolates of Cryptosporidium goose genotype I were isolated, the host specificity of the genotype is not yet fully understood. The source of this genotype infection and its transmission dynamics now require further investigation to elucidate the cross-species transmission potential of Cryptosporidium goose genotype I in geese and other birds in China.
One study revealed the presence of three genotypes (BEB6, Peru 6, and CHN-B3) of E. bieneusi in geese from Heilongjiang, China (Zhao et al., 2016). BEB6 and Peru 6 are known humanpathogenic genotypes, and genotype CHN-B3 belongs to Group 1, and therefore has a potential for zoonotic transmission (Zhao et al., 2016). In the present study, 11 E. bieneui genotypes were identified, including six known genotypes (D, I, BEB6, CHG3, CHG5, and CHG2) and five novel genotypes (HNE-I to HNE-V). Of these, genotype D, I, and BEB6 have been found in humans, and genotypes CHG2, CHG3, and CHG5 were commonly found in goats and sheep in China (Shi et al., 2016;Chen et al., 2018;Yang et al., 2018;Li et al., 2019a). Out of the 11 genotypes identified in the present study, genotype D is the most frequently detected in humans, and has been found in both HIV-positive patients and HIV-negative individuals from America, Europe, Asia, and Africa (Matos et al., 2012). Genotype D appears to have a wide host range as it has also been isolated from a large variety of animals including cattle, cats, horses, dogs, and some wild animals (macaques, muskrats, raccoons, beavers, foxes, and gorillas) as well as in birds, such as pigeons and falcons (Zhao et al., 2014;Li et al., 2019a). This genotype was the most common genotype found in geese in the present study, with a prevalence of 57.3% (13/37). The results above suggest that domestic geese infected with genotype D may transmit it to other animals and humans. Genotypes I and BEB6 are commonly found in cattle as well as in children from Shanghai and Changchun of China (Zhang et al., 2011;Wang et al., 2013;Zhao et al., 2015). Thus, the geese infected with those genotypes also have a potential to cause environmental pollution and human infection. To date, Genotypes CHG2 and CHG3 have been found in goats, sheep, and cattle Shi et al., 2016;Yang et al., 2018;Li W. C. et al., 2019;Udonsom et al., 2019), and genotype CHG5 was only found in goat (Shi et al., 2016). This was the first report of genotypes CHG2, CHG3, and CHG5 in geese indicating that those genotypes have an extensive host range. The five novel genotypes were included in Group 2. To date, the potential of genotypes CHG2, CHG3, and CHG5 and the five novel genotypes (HNG-I and HNG-II) to cause disease in humans or other livestock is unknown. Their host adaptation and potential role in the zoonotic transmission of E. bieneusi infection now requires further exploration in more systematic molecular epidemiological investigations of E. bieneusi in a larger number of hosts.

CONCLUSION
The present study is the first to demonstrate the occurrence and molecular characterizations of Cryptosporidium and E. bieneusi in farm-raised and free-ranging geese from the Hainan Province of China. Two bird-adapted species (C. baileyi) or genotypes (Cryptosporidium goose genotype I) of Cryptosporidium were identified. Thus, there is a lower risk of zoonotic transmission of Cryptosporidium between geese and humans in the areas investigated. However, all of the 11 genotypes of E. bieneusi were belonged to Groups 1 or 2, which are considered potentially zoonotic. Additionally, the three zoonotic E. bieneusi genotypes (D, I, and BEB6) were found in 56.8% of the geese that were tested. These results suggest that the geese infected with these genotypes of E. bieneusi have the risk of zoonotic potential and pose a threat to human health.

DATA AVAILABILITY STATEMENT
The datasets generated for this study can be found in the Representative nucleotide sequences obtained in the study were deposited in the GenBank database under accession numbers MN472907 to MN472911 for E. bieneusi; MN461548 and MN461549 for Cryptosporidium.

AUTHOR CONTRIBUTIONS
YS and GL conceived and designed the experiments. WZ, HZ, and TM performed the experiments. WZ analyzed the data and wrote the paper. JC contributed the reagents materials analysis tools. YS and GL critically revised the manuscript. All authors read and approved the final version of the manuscript.

FUNDING
This work was supported by the National Science and Technology Major Program of China (No. 2018ZX10713001-004 to YS), the Open Subject of Key Laboratory of Parasite and Vector Biology, MOPH (WSBKFKT-201802 to WZ), the Innovation Research Team Project of Hainan Natural Science Foundation (2018CXTD340 to GL), and the National Natural Science Foundation of China (Nos. 81672072 and 81760378 to GL). The funders had no role in study design, data collection and analysis, the decision to publish, or preparation of the manuscript.


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Bacterial community composition and diversity of two different forms of an organic residue of bioenergy crop

The use of residue of sugarcane ethanol industry named vinasse in fertirrigation is an established and widespread practice in Brazil. Both non-concentrated vinasse (NCV) and concentrated vinasse (CV) are used in fertirrigation, particularly to replace the potassium fertilizer. Although studies on the chemical and organic composition of vinasse and their impact on nitrous oxide emissions when applied in soil have been carried out, no studies have evaluated the microbial community composition and diversity in different forms of vinasse. We assessed the bacterial community composition of NCV and CV by non-culturable and culturable approaches. The non-culturable bacterial community was assessed by next generation sequencing of the 16S rRNA gene and culturable community by isolation of bacterial strains and molecular and biochemical characterization. Additionally, we assessed in the bacterial strains the presence of genes of nitrogen cycle nitrification and denitrification pathways. The microbial community based on 16S rRNA sequences of NCV was overrepresented by Bacilli and Negativicutes while CV was mainly represented by Bacilli class. The isolated strains from the two types of vinasse belong to class Bacilli, similar to Lysinibacillus, encode for nirK gene related to denitrification pathway. This study highlights the bacterial microbial composition particularly in CV what residue is currently recycled and recommended as a sustainable practice in sugarcane cultivation in the tropics.

INTRODUCTION
Sugarcane is a bioenergy sustainable crop used to bioethanol production and is considered a sustainable biofuel (De Souza et al., 2014), especially because it can reduce the greenhouse gas (GHG) emissions when compared to fossil fuel (Boddey et al., 2008;Galdos et al., 2010). Brazil is one of the largest producers of sugarcane with a cultivated area of 10 million hectares and ethanol production of 11-28 million m 3 (UNICA (União da Insdústria de Cana-de-açúcar), 2014; CONAB, 2017). However, some management practices may misbalance this sustainable strategy as ethanol production generates many agro and industry-residues such as sugarcane-straw, bagasse, molasses, filter cake and huge volumes of the organic pollutants vinasse (one L ethanol: 10-15 L vinasse) (Prado, Caione & Campos, 2013).
The sugarcane residue recycling practice follows the legal rules of the Brazilian environmental regulations (CETESB, 2014). The residue vinasse generated during the ethanol production is disposed in soil as organic fertilizer. Vinasse is rich in nutrients, especially in potassium (∼3,000 mg L -1 ) and has high organic loads (biochemical oxygen demand and chemical oxygen demand) and pH of 4-5 (Fuess & Garcia, 2014;De Oliveira et al., 2015). Due to vinasse chemical composition, it is a valuable organic residue to be recycled to increase soil quality and plant productivity. Besides the alternative of vinasse application as organic fertilizer in sugarcane plantations, vinasse is concentrated by evaporation without losses of nutrients and organic matter. In addition, the high water content in vinasse may cause soil and groundwater contamination. Thus, nowadays both non-concentrated vinasse (NCV) and concentrated vinasse (CV) are widely used in fertirrigation, particularly to replace the potassium fertilizer.
Despite the advantages of vinasse application on the field, vinasse fertilization can increase GHGs emissions mainly nitrous oxide (N 2 O), which emission factor can reach up to 3% of N applied in soil (Pitombo et al., 2016;Siqueira Neto et al., 2016;Lourenço et al., 2018aLourenço et al., , 2018b. Vinasse fertilization, as organic residue and a source of nutrients, alters the soil bacterial community composition and function of different microbial groups (Suleiman et al., 2018), which can affect the key biogeochemical processes, in particular nitrification and denitrification. In recent studies we have identified (Pitombo et al., 2016;Cassman et al., 2018) that bacterial members belonging to Firmicutes phylum present in vinasse are potential denitrifiers contributing to N 2 O emissions.
While for many agriculture and industrial residues (e.g., municipal wastewater, swine manure) literature on microorganisms present in the organic residues is available (Suleiman et al., 2016), the knowledge of vinasse microbes is restricted. Ethanol industry does not occur in sterile conditions and the material originated from sugarcane-ethanol production include mainly different genus of Firmicutes phyla and Acetobacter (Alphaproteobacteria) associated with this industrial process (Costa et al., 2015;Brexó & Sant'Ana, 2017). Furthermore, the microbial communities in different batches of vinasses are known of having low alpha diversity with core genus of Lactobacillus and with the presence of potential genes for denitrification but not nitrification in the vinasse metagenomes (Cassman et al., 2018;Lourenço et al., 2018c).
Current researches revealed that fertirrigation with CV and NCV impacts the N 2 O emissions (Pitombo et al., 2016;Cassman et al., 2018;Lourenço et al., 2018a). The knowledge about vinasse microbiome can decipher important ecological and environmental issues as a potential invasion of these microbes in the resident soil microbial community, especially CV for which there is no information about the bacterial community diversity. We hypothesize that (1)NCV and CV harbor different bacterial communities and (2) both vinasses isolated microbes have potential genes related to denitrification process. Therefore, this study aimed to evaluate the (i) bacterial community present in NCV and CV by next generation sequencing of 16S rRNA gene amplicon, (ii) isolation of bacteria from both vinasse types and (iii) molecular and biochemical characterization of the strains as potential denitrifier sources.

MATERIAL AND METHODS
Vinasse chemical composition, total DNA extraction and 16S rRNA gene amplification  Table S1. For total DNA extraction, a total of 90 mL from each replicate of concentrated and NCVs were harvested and centrifuged at 2,000Âg for 5 min. A 250 mg pellet of each replicate was used for total DNA extraction using kit PowerSoil kit (MoBio Laboratories, Inc., Carlsbad, CA, USA) according to manufacture. The DNA quantity and quality were determined by spectrophotometer NanoDrop 1000 (Thermo Scientific, Waltham, MA, USA).
The microbial community was determined based on V4 region of the 16S rRNA gene sequencing. The 16S rRNA was amplified by archaeal/bacterial primers 515F (5′-GTGCCA GCMGCCGCGGTAA-3′) and 806R (5′-GGACTACVSGGGTATCTAAT-3′). The 25 mL 25 PCR contained five mL of FastStart High Fidelity taq Enzyme, 10Â FastStart High Fidelity buffer containing 18 mM MgCl2 (Roche Diagnostics Ltd., Burgess Hill, UK), 0.2 mM of each dNTP (Promega UK Ltd., de Southampton, UK) and 0.1M of each primer. Each PCR had one mL DNA of each sample. The PCR conditions were 95 C for 5 mi., followed 35 cycles at 95 C for 30 s, 50 C for 30 s and 72 C for 1 min, with a final extension at 72 C for 10 min. The PCRs were in triplicates and amplified in a termocycler C1000 (Bio-Rad, Hemel Hempstead, UK). The PCR products were visualized on 1.5% agarose gel in TBE buffer. The PCRs were purified by QIAquick kit (Qiagen, Hilden, Germany), quantified with Quant-iT Broad-Range DNA Assay Kit (Invitrogen, Carlsbad, CA, USA) in conjunction with the BioTek Synergy HT microplate reader and combined in equimolar ratios. The 16S rRNA amplicons were sequenced using Ion TorrentTM semiconductor technology chemistry for unidirectional sequencing of the amplicon libraries. Barcoded primers were used to multiplex the amplicon pools in order to be sequenced together and separated afterward. Template preparation was performed using Ion OneTouch 2 System and Ion PGM Template OT2 400 Kit, and sequencing using Ion PGM Sequencing 400 on Ion PGM System using Ion 318 Chip v2.
The sequences were analyzed by Mothur version 1.33.2 (Schloss, 2010) combined with Snakemaker (Koster & Rahmann, 2012). First, multiplexed reads were filtered for quality and assigned to samples by matching to barcode sequences. Second, the reads were trimmed including one mismatch to the barcode and two mismatches to the primer, eight maximum homopolymer, minimum length of 250 bp, maximum length of 290 and quality score >25. Then, the sequences were aligned using the Silva reference database (Quast et al., 2013) template, pre-clustered to eliminate sequences outside of desired range alignment and potentially chimeric sequences were removed. Sequences were classified using Silva rRNA database (release SSU_Ref_119) with a confidence threshold of 80% and the sequences classified as chloroplasts and mitochondria were removed. The data were then analyzed in R (R Development Core Team, 2005) using Phyloseq package (McMurdie & Holmes, 2013). The sequences are available at the European Nucleotide Archive (https://www.ebi.ac.uk/ena/) under the study accession no. PRJEB30243. Samples were then, rarefied to determine the alpha diversity and principal coordinate analysis (PCoA) based on beta diversity (Supplemental Methods). Homogeneity of multivariate dispersion was tested by PERMDISP (Anderson, 2006) to determine if the community in different vinasses was shaped by a stochastic or a deterministic processes and the analysis was performed in calypso software (Zakrzewski et al., 2017).

Bacteria isolation, molecular and biochemical characterization
A volume of 100 mL of each replicate of NCV and CV were plated on MRS (Man, Rogos and Sharpe, Difco Ò ) medium and incubated at 37 C for 48 h. The pure colonies were characterized by Gram staining test. The presence of different enzymes and different organic compounds as carbon sources of the isolated bacteria were determined by API 20 NE test (BioMérieux AS, Lyon, França) according to manufacture.
The DNA of each isolated bacteria was extracted using PowerSoil kit (MoBio laboratories, Inc., Carlsbad, CA, USA) for molecular identification by sequencing the 16S rRNA gene. The 16S rRNA gene was amplified with 27f (5′AGAGTTTGATCMTGGCTCAG3′) and 1100r (5′AGGGTTGGGGTGGTTG3′) primers using the PCR conditions described in Lane et al. (1985). The PCR products were purified by Gel Band Purification Kit (GE Healthcare, Chicago, IL, USA) and sequenced (Macrogen Inc., Seoul, Korea). The strains 16S rRNA sequences were blast against Genbank (http://www.ncbi.nlm.gov/GenBank) sequences. The 16S rRNA gene sequences (>85% identity) were downloaded from NCBI and aligned with the six strains 16S rRNA gene sequences using ClustalW in MEGA7 (Kumar, Stecher & Tamura, 2016). All the sequences were edited and aligned. A neighbor-joining tree (Saitou & Nei, 1987) was created to examine the phylogenetic relationships between the six strains and the sequences from NCBI using as outgroup an Enterobacter ludwigii sequence as show in Fig. 1. Distances were computed using the Maximum Composite Likelihood method and a bootstrap test with 1,000 replicates was conducted (Felsenstein, 1985). We used the Interactive Tree of Life (Letunic & Bork, 2016) to visualize the tree.

RESULTS
Vinasse microbial diversity and core microbiome A total of 49,595 16S rRNA sequences were obtained for eight vinasse samples (four CV and four NCV) with average of 6,199, minimum of 3,688 and maximum of 9,496 sequences. Because differences in aand β-diversities between NCV and CV can arise from differences in similarity, differences in dispersion or both, a separate test of dispersion using PERMDISP was used to detect the nature of such differences. The PERMDISP analysis revealed no significant difference in dispersion, that is, homogeneity of variance, suggesting that differences in alpha-and beta-diversities were largely driven by dissimilarity rather than dispersion (Fig. S1, p > 0.05). The alpha-diversity was higher in NCV than in the CV based on Shannon's and Simpson's indexes, Chao and for observed OTUs, despite being non-significant only for richness calculations (Fig. S2, p > 0.05). PCoA plots also showed that microbial communities grouped into two clusters (Fig. 2, Permanova R ¼ 0.9, p < 0.05). The first two principal coordinates, PC1 and PC2, explained 94% and 2% of the data variation, respectively, clearly separating the communities of NCV and CV.
Both NCV and CV showed dominance of phylum Firmicutes with 95% and 99%, respectively (Fig. 3A). However, at class taxonomic level, the distribution of the bacterial groups was different in NCV and CV (Fig. 3B). In NCV, the most abundant class was Negativicutes (50%), followed by Bacilli (38%) while in CV Bacilli corresponded to almost 100% of the total relative abundance. At genus level, NCV was represented by Megasphaera (43%), followed by Lactobacillus (40%) and Mitsuokella (18%) while CV was overrepresented by mainly Lactobacillus (Fig. 3C).

Bacteria isolation from vinasses
Five strains (EK-V1, EK-V2, EK-V3, EK-V4 and EK-V5) were obtained from NCV and one strain (EK-V6) from CV. The phylogenetic tree based on 16S rRNA complete gene sequences of the strains showed two main distinct clusters (Fig. 1A). In cluster 1 are EK-V5 and EK-V4 strains that grouped with Lysinibacillus fusiformes and in cluster 2 are EK-V2, EK-V3, EK-V1 and EK-V6 strains. The PCR results of the N cycle genes of the six strains showed amplification only for nirK of strains EK-V1 and EK-V6 (Fig. 1B). The Gram staining test showed that all strains are Gram positive. By API 20 NE test, the strains EK-V1, EK-V3 and EK-V6 are capable to reduce nitrate to nitrite and hydrolyze arginine; strains EK-V1 and EK-V6 are capable to metabolize urea; protease and B-galactosidase are metabolized only by EK-V1 strain (Fig. 1B). Regarding to organic compost assimilation only strain EK-V2 showed activity to glucosamine, while the same strain EK-V2 and EK-V4 were able to assimilate malate; the strains EK-V2, EK-V3 and EK-V4 were capable to assimilate citrate.

DISCUSSION
Organic fertilizers are usually complementary to inorganic fertilizers supplying the majority of plant nutrients needs. Thus, organic fertilizers are used in agriculture to improve the soil structure and stability in addition to enhancing the yield and, in particular, the quality of plants (Chang et al., 2010;Marzouk & Kassem, 2011). Vinasse organic fertilizer, for example, meets the specifications for organic farming with a high fertilizing value; it represents a considerable source of potassium but it also provides significant levels of phosphorus and nitrogen taken up by sugarcane plant (Christofoletti et al., 2013). Because of the large volumes of vinasse produced, concentration of vinasse by evaporation is an alternative to reduce the volume and avoid long transportation and soil compaction in the sugarcane fields (Christofoletti et al., 2013;De Carvalho et al., 2011). Our results showed that the process of vinasse concentration decreases bacterial diversity and change the microbial structure but still harbors bacteria with potential contribution to N 2 O emissions, based on the isolation of the bacteria strain EK-V6, which possess nirK (Fig. 1B). The strain EK-V1, isolated from NCV also possesses nirK gene. This result suggests that strains EK-V1 and EK-V6 (in NCV and CV) can participate in one of the stages of nitrogen transformation in vinasse, more specifically the transformation of NO 2into NO. Moreover, the strains EK-V1 and EK-V6 are able to produce arginine, essential aminoacid to produce NO 3-, as well as produce urease enzyme related with urea hydrolysis (Hibbs, Vavrin & Taintor, 1987;Zhou et al., 2019). The heating process to concentrate vinasse reaches 115 C (Carvalho & Silva, 2010), which drastically decreased Megasphaera and Mitsuokella genera present in NCV (Fig. 3C), confirming our hypothesis that NCV and CV harbor different bacterial community. In fact, CV harbors mainly Lactobacillus genus (Fig. 3C) and the PCoA plots (Fig. 2) are in accordance with this information, showing that there is a possible selection of this genus in CV associated with the evaporation method. We found for both NCV and CV the dominance of phylum Firmicutes (>90%). Actinobacteria and Bacteroidetes were only present in NCV. Within Firmicutes phylum are bacterial members capable of fermenting various organic substrates and forming spores. Previously, these bacteria group found to be abundant in the ethanol industry process (Costa et al., 2015). Aerobic and anaerobic microbial processes are options for treating vinasse. The vinasses are produced by similar industrial fermentation processes based on the growth of microorganisms on molasses derived from sugarcane. Anaerobic degradation of organic material (biomass), for example, involves decomposition of bacteria under humid condition in the absence of molecular oxygen where different organisms of genera Actinobacteria, Proteobacteria, Bacteroidetes and Firmicutes are selected in the different stages of industrial fermentation (Deublein & Steinhauser, 2011;Ray & Bhunia, 2013). Heat-resistant endospores is a specific property of the members of the phylum Firmicutes found in different classes as Bacilli, Clostridia, Erysipelotrichia and Negativicutes, which all encode similar sets of core sporulation proteins (Galperin, 2013). In NCV, the most abundant class was Negativicutes (50%), followed by Bacilli (38%) both belong to Firmicutes while in CV Bacilli corresponded to almost 100% of the total relative abundance.
The application of vinasse on sugarcane fields has negative environmental aspects related to GHG emissions when applied in conjunction with inorganic nitrogen (Lourenço et al., 2018b(Lourenço et al., , 2018d. NCV increases more N 2 O fluxes in the soil than CV (Pitombo et al., 2016). Based on our results, the microbes present in both vinasses, concentrated and non-concentrated, encode genes for denitrification, mainly nirK, suggesting the potential capacity of these isolates to contribute to the N 2 O emissions by denitrification when vinasse is applied into soil. Interestingly, three strains from CV (EK-V1 and EK-V3) and NCV (EK-V6) are able to reduce nitrate to nitrite. This step has emerged as an alternative route to the classical enzymatic NO and N 2 O formation.
One issue that should be considered is the substantial amount of vinasse potentially being flushed into soil microbiome in sugarcane cropland. Vinasse may affect the resident microbial activity and relative abundance of specific taxonomic groups in sugarcane-cultivated soils by introducing labile nutrients and exogenous microbes. Traditionally, most studies on biological invasions have focused on invasive plants and animals (Elton, 1958;Mooney & Hobbs, 2000), while only a few considered the effects of invasive microbes, except the study of Lourenço et al. (2018c) with NCV. Previous field and mesocosm experiments showed that vinasse increased abundances of Bacillaceae, Micrococcaceae, Hyphomicrobiaceae and Nitrospiraceae families (Pitombo et al., 2016;Navarrete et al., 2015) with functions related to spore-producing microorganisms overrepresented. For instance, Pitombo et al. (2016), Suleiman et al. (2018) and Lourenço et al. (2018d) observed an increase in the abundance of Lactobacillaceae in treatments with vinasse, but after 14 days, the relative abundance decreased and was similar to the treatments without vinasse showing that vinasse-exogenous microbes are unable to survive in the soil conditions after certain period. Cassman et al. (2018) identified vinasse-exogenous microbes bacteria that survived the selective bottleneck of the bioethanol production with Lactobacillus (Phylum Firmicutes) being the core genus present in the vinasse input.
The broad functional groups of Gram-positive bacteria dominated in both NCV and CV, over Gram-negative bacteria. Gram-positive bacteria are generally divided into the Actinobacteria and the Firmicutes (Hugget & O'Grady, 2014). This phenomenon is likely due to major differences in the cell envelope between Gram-negatives and Gram-positives. Gram-negative bacteria are the smallest and tend to be more sensitive to disturbances while Gram-positive bacteria are larger, have a thicker cell wall, a negative charge on the outer surface, and tend to resist stress (Mai-Prochnow et al., 2016). Furthermore, the ability of Gram-positive organisms to sporulation may allow them to withstand industrial fermentation process disturbance. The bacterial groups found in this study, including Gram-positive bacteria with low GC as Bacillus, Clostridium, Enterococcus, Lactobacillus and Lactococcus, which execute the steps of hydrolysis and acidogenesis, were comparable to investigations done in anaerobic digesters (Oude Elferink et al., 1998;Kröber et al., 2009;Sarti et al., 2010).
The isolated strains of this study metabolized different substrates related to different functions. For example, strains EK-V1 and EK-V6 were capable to reduce nitrate to nitrite, hydrolyze arginine and to metabolize urea. Nitrate-nitrite-nitric oxide reductive pathway has emerged as an alternative route to the classical enzymatic NO formation by oxidation of L-arginine with molecular oxygen (Lundberg, Weitzberg & Gladwin, 2008;Bryan & Loscalzo, 2013). This microbial denitrifies present in the soil, possess nitrate reducing mechanisms, maybe responsible for the loss of nitrate (NO 3 -) and production of the potent GHG, N 2 O. Urea hydrolysis to NH 4 + and CO 2 may also take place by microbial uptake (Hoult & McGarity, 1986;Pettit et al., 1976). This could be an indication of microbial activity that makes vinasse an option with available ammonium for soil fertilization since urease activity plays an important role in the regulation of N supply to plant after urea fertilization (Fazekašová, 2012). Proteolysis, for instance, is an important process in N-cycling because is considered to be a rate-limiting step during N mineralization in soils due to the much slower primary phase of protease activities during N mineralization compared with amino acids mineralization (Jan et al., 2009). For Betagalactosidase, probably less bioavailable carbon was present in CV as glycosidase activity facilitates the breakdown of low-molecular-weight carbohydrates and produces the end product-glucose, important in terrestrial C cycling by providing necessary energy for proliferation of microorganisms (Eivazi & Tabatabai, 1990). Glutamine is well known important amino acid in nitrogen metabolism and can be produced by direct fermentation with certain bacteria (Nabe et al., 1980;Nakanishi, 1980). Furthermore, Parnaudeau et al. (2008) reported that sugarcane vinasse contains significant amount of sucrose, oxalate, lactate, malate and pyruvate, which are ready metabolites to be fed to the tricarboxylic acid cycle during the alcoholic fermentation (Bhattacharyya et al., 2012). All these characteristics are related to the bacterial strains isolated from NCV and CV. The phylogenetic analyses based on 16S rRNA gene sequences revealed strains EK-V4 and EK-V5 similar to Lysinibacillus fusiformis a species recognized as plant growth promoter (Marasco et al., 2012). The present data indicate that these strains isolated from vinasse could be tested for production of secondary metabolites as well as sugarcane growth-promoting bacteria.
In conclusion, this study shows that process of vinasse concentration reduces the bacterial community diversity. There is the predominance of Firmicutes for both vinasse types capable of fermenting various organic substrates and forming spores. The broad functional groups of Gram-positive bacteria dominated in both NCV and CV, suggest that microbes resist to heating process of vinasse concentration. The strains in both vinasses can metabolize substrates related to the nitrogen cycle by encoding genes for denitrification, mainly nirK that might contribute to the N 2 O emissions when vinasse is applied into soil.


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Available plant nutrients in soil as influenced by planting methods and herbicidal treatments

Abstract Rice (Oryza sativa L.)-wheat (Triticum aestivum L.) is the predominant cropping system of North Indian region. Due to continuous following of rice-wheat cropping system every year, weed infestation particularly in wheat, has emerged a major problem resulting in reduced wheat yield and nutrient mining. Integration of suitable planting methods, along with effective weed control measures, can reduce the weed infestation and nutrient mining from the soil and can enhance available plant nutrients in the soil. To evaluate the influence of different planting techniques and weed control practices in wheat on available plant nutrients in soil, a field study was conducted at the department of Agronomy, Punjab Agricultural University, Ludhiana (India) for two consecutive years. The treatments comprised of five planting techniques: conventional tillage, zero till sowing without rice stubbles, zero till sowing in standing rice stubbles , zero till sowing after partial burning of rice stubbles and bed planting and five weed control treatments i.e. clodinafop 60 g/ha, clodinafop 60 g/ha fb 2, 4-D 0.5 kg/ha, sulfosulfuron 25 g/ha, mesosulfuron + iodosulfuron 12 g/ha and unweeded (control). The experiment was conducted in split plot design with planting methods in the main plot and herbicidal treatments in the sub plot with three replications. The results of the study showed that zero till sowing of wheat in standing rice stubbles observed significantly higher soil organic carbon, available nitrogen, phosphorus and potassium than conventional till wheat sowing after removal of rice residues. Although partial burning of rice stubbles also showed positive trend in soil organic carbon, available nitrogen, phosphorus and potassium but retort was less distinct than rice stubbles without burning. Further, zero tillage alone also showed improvement in soil organic carbon and available nitrogen, phosphorus and potassium over conventional tillage. Application of herbicides did not diverge soil organic carbon, but significantly improved the available nitrogen, phosphorus and potassium content in soil than the unweeded (control).

Introduction
Wheat (Triticum aestivum L.) is one of the major cereal crops grown in the world. India has reached the prestigious position in the world in wheat production due to the innovation of high yielding dwarf genotypes, improved fertilization plant protection measures and irrigation facilities coupled with scientific research. Rice (Oryza sativa L.)-wheat is the predominant cropping system of Punjab, India. Due to following same rice-wheat cropping system every year, wheat is particularly infested by diverse weed flora including both grass and broadleaf weeds, causing yield reduction of 15-40 percent depending upon category and strength of their incursion (Jat et al. 2004). Uptake of nutrients by weeds is comparatively faster and larger than crops, resulting in nutrient mining and reduction in available plant nutrients in soil. Integration of suitable planting methods and herbicides can effectively manage weeds. Different planting methods creates different micro-climatic conditions which may not favor the weed germination and growth. Sowing of wheat under zero till conditions reduced the infestation of grass weeds, whereas, the population of broadleaf weeds was enhanced (Brar and Walia 2007). Similarly, bed planning of wheat providing another type of ecology reduced the infestation and nutrient uptake by weeds (Brar and Walia 2009). In the same way, weeds behaved differently under different load of surface rice residues (Brar and Walia 2010). Regarding the chemical control of weeds, isoproturon and 2, 4-D were most commonly https://doi.org/10.1515/opag-2019-0031 received July 28, 2018;accepted December 13, 2018 Abstract: Rice (Oryza sativa L.)-wheat (Triticum aestivum L.) is the predominant cropping system of North Indian region. Due to continuous following of rice-wheat cropping system every year, weed infestation particularly in wheat, has emerged a major problem resulting in reduced wheat yield and nutrient mining. Integration of suitable planting methods, along with effective weed control measures, can reduce the weed infestation and nutrient mining from the soil and can enhance available plant nutrients in the soil. To evaluate the influence of different planting techniques and weed control practices in wheat on available plant nutrients in soil, a field study was conducted at the department of Agronomy, Punjab Agricultural University, Ludhiana (India) for two consecutive years. The treatments comprised of five planting techniques: conventional tillage, zero till sowing without rice stubbles, zero till sowing in standing rice stubbles , zero till sowing after partial burning of rice stubbles and bed planting and five weed control treatments i.e. clodinafop 60 g/ha, clodinafop 60 g/ha fb 2, 4-D 0.5 kg/ ha, sulfosulfuron 25 g/ha, mesosulfuron + iodosulfuron 12 g/ha and unweeded (control). The experiment was conducted in split plot design with planting methods in the main plot and herbicidal treatments in the sub plot with three replications. The results of the study showed that zero till sowing of wheat in standing rice stubbles observed significantly higher soil organic carbon, available nitrogen, phosphorus and potassium than conventional till wheat sowing after removal of rice residues. Although partial burning of rice stubbles also showed positive trend in soil organic carbon, available nitrogen, phosphorus and potassium but retort was less distinct than rice stubbles without burning. Further, zero tillage alone also showed used herbicides for the control of grass and broad leaf weeds, respectively. However, their continuous use has either resulted in shift in weed flora or emergence of resistance strains in some species (Yadav et al. 1996). Management of weeds become a major concern due to resistance development in Phalaris minor against the most commonly used herbicide isoproturon (Malik and Singh 1995) and increased infestation of broadleaf weeds. This necessitate the use of new herbicide formulation alone or in combination for the control of diverse weed flora of wheat to avoid conpicious shift in weed flora. Many new herbicides molecules have been synthesized which are quite promising against P. minor and broad leaf weeds, but their behavior can vary under different planting methods. The organic carbon associated with the ash of burnt rice straw has been found to be highly absorptive of herbicides (Walia et al. 1999). In another way, the applied herbicide to wheat crop can be intercepted by the standing stubbles of rice. So, the behavior of herbicides may vary under different planting methods of wheat. In view of the above complications, the current investigation was planned to assess the available nutrients in soil under different planting methods and weed control treatments.

Materials and Methods
To evaluate the response of planting techniques and weed management methods on available plant nutrients in soil, a field experiment was conducted during 2004-05 and 2005-06 at the experimental farm of the department of Agronomy, Punjab Agricultural University, Ludhiana, Punjab, India. The physico-chemical analysis of the soil from the experimental field before the start of the experiment (Table 1) showed that the soil was loamy sand in texture with nearly normal in-soil reaction (7.3) and electrical conductivity (0.26 dS/m). The soil was low in available nitrogen with 230 kg/ha, but it was medium in organic carbon with 4.2 g/kg, available phosphorus with 18.6 kg/ha and potassium with 150 kg/ha. Figures  1 and 2 presented the meteorological data recorded at Meteorological Observatory of Punjab Agricultural University, Ludhiana during both the cropping seasons. Figure 1 showed the range of maximum temperature between 13.2 to 37.6°C whereas minimum temperature ranged between 5.3 to 17.4°C during 2004-05. Similarly, Figure 2 depicted the range of the maximum temperature between 16.8 to 35.2°C and minimum temperature between 3.1 to 18.8°C during cropping season 2005-06. However, the maximum and minimum temperature was recorded in the months of April and January, respectively during both the growing seasons. A total rainfall of 186.9 mm and 55.2 mm was recorded during 2004-05 and 2005-06 crop growing seasons, respectively. The experiment was conducted in split plot design with three replications. Five planting techniques viz conventional tillage, zero till sowing without rice stubbles, zero till sowing in standing rice stubbles ,zero till sowing after partial burning of rice stubbles and bed planting were assigned in the main plots and five weed control treatments, clodinafop 60 g/ha, clodinafop 60 g/ha fb 2, 4-D 0.5 kg/ha, sulfosulfuron 25 g/ ha, mesosulfuron + iodosulfuron 12 g/ha and unweeded (control), were arranged in sub plots.
In case of conventional tillage and bed planting, after the harvest of paddy crop, field was prepared by ploughing twice with disc harrow, and then once with cultivator and finally by planking. Again, two ploughings followed by planking were given after pre-sowing irrigation to prepare a fine seed bed. In case of zero till plots, wheat was directly sown with zero till drill after harvesting the rice; without stubbles, in 1.0 to 1.5′ standing stubbles and after partial burning of rice stubbles as per the treatments. In case of bed planting treatment, 67.5 cm wide (37.5 cm bed top and 30 cm furrow) beds were prepared with bed planter. The sowing of wheat was done with tractor drawn conventional drill/zero till/bed planter (2 row per bed) as per treatment during last week of October and first week of November during 2004 and 2005, respectively. Nitrogen (125 kg ha -1 ) was applied in the form of urea as broadcast in two equal splits, half before sowing and remaining half after first irrigation (25 days after sowing). P 2 O 5 (60 kg ha -1 ) was drilled in the form of diammonium phosphate (DAP) at the time of sowing. Post-emergence application of herbicides; clodinafop 60 g/ha, sulfosulfuron 25 g/ha and mesosulfuron + iodosulfuron 12.0 g/ha was done 35 days after sowing, whereas, 2, 4-D (sodium salt) 0.5 kg/ha was applied one week thereafter. Other crop raising practices were followed as per recommended package of practices. After harvesting the wheat crop in the month of April, the soil samples were collected for the determination of organic carbon, available nitrogen, available phosphorus and available potassium from two depths viz., 0-15 cm and 15-30 cm. The soil samples were dried under shade, ground and passed through 2 mm sieve before analysis. Organic carbon was estimated using Walkley and Black's rapid titration method (Walkley and Black 1934), available nitrogen was determined by modified alkaline potassium permanganate method as given by Subbiah and Asija (1956), available phosphorus was determined as designated by Olsen et al. (1954) and available potassium was extracted with neutral normal ammonium acetate solution as prescribed by Jackson (1967) and determined by flame photometer. The data was analyzed at 5% level of significance by following the statistical procedure prescribed by Cochran and Cox (1967) using package CPCS-1 developed by Cheema and Singh (1991).

Ethical approval:
The conducted research is not related to either human or animal use.

Organic Carbon
Soil organic carbon is the backbone of soil fertility. The perusal of data regarding soil organic carbon (Table 2) revealed that retention of rice residues as stubbles and less soil disturbance (zero tillage) showed positive trend in soil organic carbon. Zero till sowing with standing rice stubbles recorded highest soil organic carbon, whereas, conventional tillage after removing the rice residues recoded least soil organic carbon. The significantly higher soil organic carbon was observed in zero till sowing in standing rice stubbles in 0-15 cm soil layer, than bed planting and conventional tillage during both years of study. Among the zero till plots, although zero till sowing in standing rice stubbles recorded highest organic carbon content but it was statistically at par with other zero till sown plots with no rice residues and partial burnt residues. Less variation was observed in organic carbon at 15-30 cm soil layer, but zero tillage systems were better than conventional tillage and bed planting, but the differences were not significant.
Among the weed control treatments, soil organic carbon content did not show any significant difference during both the years at both the depths (0-15 cm and 15-30 cm) due to different weed control treatments (Table  2). However, herbicide treated plots; mesosulfuron + iodosulfuron 12.0 g/ha, sulfosulfuron 25 g/ha, clodinafop 60 g/ha f.b. 2, 4-D 0.5 kg/ha and clodinafop 60 g/ha showed slight improvement in soil organic content than unweeded control plots.

Available Nitrogen
Comparing all the planting techniques used, the data (Table 2) showed that the highest available nitrogen was recorded with zero till sowing in standing rice stubbles and lowest with conventional tillage without any rice residue treatment. During first year of study, zero till sowing in standing rice stubbles recorded significantly higher available nitrogen in soil than conventional tillage treatment at both 0-15 cm and 15-30 cm soil depths. During second year, both zero till sowing in standing rice stubbles and zero till sowing after partial of stubbles recorded significantly higher available nitrogen content in soil than conventional tillage at both the soil depths (0-15 cm and 15-30 cm). Further, zero till sowing treatments with or without rice stubbles and bed planting treatment were statistically at par with each other at both the soil depths during both the years.
In the weed control treatments, mesosulfuron + iodosulfuron 12.0 g/ha, sulfosulfuron 25 g/ha, clodinafop 60 g/ha f.b. 2, 4-D 0.5 kg/ha observed significantly higher available nitrogen than clodinafop 60 g/ha alone and unweeded control treatments ( Table 2). The trend of available nitrogen in soil was similar during both the growing seasons at both 0-15 cm and 15-30 cm soil depths.

Available Phosphorus
Available phosphorus in soil was significantly different with different planting techniques during both the years at both the soil depths. Soil samples analyzed after the harvest of wheat crop (Table 3) depicted that zero till sowing of wheat recorded highest available phosphorus in soil at both the soil depths during both the years. At 0-15 cm soil depth, alone zero till sowing of wheat in standing stubbles during first year and both zero till sowing of wheat in standing stubbles as well as after partial burning during second year registered significantly higher available phosphorus content in soil than conventional tillage treatment. All the zero till and bed planting treatments were statistically at par with each other. However, at 15-30 cm soil depth, zero till sowing of wheat in standing stubbles, the partial burning and bed planting treatments were statistically at par with each other and observed significantly higher available phosphorus conventional tillage during both years of study. Improvement in available phosphorus in soil was conspicuous where rice residues were retained at the time of sowing of wheat crop. Regarding weed control treatments, at 0-15 cm soil layer, available phosphorus content was significantly higher in mesosulfuron + iodosulfuron 12.0 g/ha, sulfosulfuron 25 g/ha and clodinafop 60 g/ha f.b. 2, 4-D 0.5 kg/ha than clodinafop 60 g/ha and unweeded control. Among all the weed control treatments, unweeded control observed the least available phosphorus content during both the years (Table 3). However, the variation among treatments was less at 15-30 cm soil depth as compared to 0-15 cm soil depth, whereas trend was same as that of 0-15 cm soil layer during both the years.

Available potassium
A thorough review of the data from Table 3, depicted that available potassium content in soil was again highest for both the soil depths (0-15 cm and 15-30 cm), during both the years under zero till sowing in standing rice stubbles, but this time closely followed by zero till sowing after partial burning of rice stubbles and lowest again with conventional tillage. Zero till sowing in standing rice stubbles and after partial burning of rice stubbles recorded significantly higher available potassium content in soil than conventional tillage treatment. Further, zero till sowing in standing rice stubbles recorded significantly higher potassium content than zero till sowing without rice stubbles at 0-15 cm soil depth for the first year and at both 0-15 cm and 15-30 cm soil depth for the second year. Zero till sowing of wheat without rice residues showed numerical improvement in available potassium over conventional tillage.
Different weed control treatments also significantly influenced available potassium content in soil during both the years at both the soil depths (Table 3). Mesosulfuron + iodosulfuron 12.0 g/ha showed the highest available potassium and the minimum values were observed in unweeded control treatment. Mesosulfuron + iodosulfuron 12.0 g/ha, sulfosulfuron 25 g/ha and clodinafop 60 g/ha f.b. 2, 4-D 0.5 kg/ha recorded significantly higher available potassium content in soil than unweeded control. Further, mesosulfuron + iodosulfuron 12.0 g/ha showed significantly higher available potassium content than clodinafop 60 g/ha alone.

Organic Carbon
Zero till sowing in standing rice stubbles resulted in higher soil organic carbon content in 0-15 cm and 15-30 cm soil layers than conventional tillage and bed planting during both growing seasons (Table 2). Higher soil organic carbon content in zero till plots with retention of rice stubbles might be due to addition of organic matter of rice stubbles, whereas, in conventional tillage plots, rice residues were removed which resulted in least organic matter in soil. Further, higher organic carbon content in zero till plots than conventional till and bed planting techniques might be due to less soil disturbance in zero till plots leading to lesser decomposition of crop residues. The results of the study are consistent with the results of Arshad et al. (1999), Das et al. (2003), Kumar and Yadav (2005), and Saikia et al. (2017).
Among the weed control treatments, herbicide treated plots showed improvement in soil organic carbon content than unweeded control plots during both the growing seasons at both the soil layers of 0-15 cm and 15-30 cm ( Table 2). This might be due to higher root biomass of crop plants produced in the herbicide treated plots than unweeded plots.

Available Nitrogen
Zero till sowing in standing rice stubbles and after partial burning of stubbles showed positive trend in available nitrogen content in soil than conventional tillage at both the soil depths of 0-15 cm and 15-30 cm during both the years ( Table 2). The higher available nitrogen content in zero till sowing with rice stubbles and partial burnt stubbles might be due to full or partial crop mass added which resulted in higher available nitrogen after decomposition of rice stubbles. Further, suppression of weeds in rice stubbles might have resulted in less nutrient uptake by weeds, resulting in more available nitrogen in soil. The findings are in agreement with the results of Das et al. (2003), Kharub et al. (2004), Kachroo et al. (2006) and Saikia et al. (2017).
Among the weed control treatments, all the herbicide treated plots viz., mesosulfuron + iodosulfuron 12.0 g/ ha, sulfosulfuron 25 g/ha, clodinafop 60 g/ha f.b. 2, 4-D 0.5 kg/ha and clodinafop 60 g/ha registered higher available nitrogen content in soil than unweeded control which recorded lowest available nitrogen during both the

Available potassium
Sowing of wheat under zero till condition in standing rice stubbles and after partial burning of rice stubbles showed higher available potassium content in soil than conventional tillage treatment without rice residues during both the year of experimentation at both 0-15 cm and 15-30 cm soil depth. Major part of the potassium uptake by rice plant remains in the rice residues after harvesting the rice grains. Higher potassium content in soil in the zero till sowing of wheat with full or partial burnt stubbles might be due to addition of crop residues. Zero till sowing of wheat without rice residues showed numerical improvement in available potassium over conventional tillage as zero till sowing of wheat favors lesser weed infestation as compared to conventional tillage. Das et al. (2003), Kharub et al. (2004) and Kachroo et al. (2006) also reported higher potassium content in soil where crop residues were added as compared to residue removal situations. Similarly, low available potassium content was also reported under conventional tillage system as compared to zero tillage treatment (Singh (1985); Matowo et al. (1999); Saikia et al. (2017).
During both the years of experimentation, at both 0-15 cm and 15-30 cm soil depths, all the herbicide application treatments like mesosulfuron + iodosulfuron 12.0 g/ha, sulfosulfuron 25 g/ha, clodinafop 60 g/ha f.b. 2, 4-D 0.5 kg/ha and clodinafop 60 g/ha registered higher available potassium content in soil than unweeded control (Table 3), probably due to lesser potassium uptake by weeds. Alone clodinafop 60 g/ha resulted in lower potassium content in soil than other herbicide application treatments probably due to lesser weed control efficiency of clodinafop than other herbicides. Brar and Walia (2008) also reported lesser nutrient uptake by weeds in herbicide application plots than untreated plot.

Conclusion
In the present study, analysis of soil samples taken after the harvest of wheat crop from both 0-15 cm and 15-30 cm soil depths indicated that zero till sowing of wheat in standing rice stubbles found significantly higher organic carbon, available nitrogen, phosphorus and potassium in soil than conventional till sown wheat after the removal of rice residues. Partial burning of rice stubbles also showed year (Table 3). This lowest nitrogen content in unweeded control treatment might be due to more nitrogen uptake by weeds. Similarly, lower available nitrogen content with clodinafop 60 g/ha alone might be due to the reason that clodinafop only controls grass weeds not the broad leaf weeds resulting in more nutrient uptake by weeds as compared to other herbicide application treatments. Brar and Walia (2008) also reported higher total nitrogen uptake by crop + weeds in unweeded control than herbicide treated plots.

Available Phosphorus
The data presented in Table 3 showed higher available phosphorous in zero till sowing of wheat in standing stubbles as well as after partial burning than conventional tillage treatment during both the growing seasons at both the soil depths of 0-15 cm and 15-30 cm. Improvement in available phosphorus in soil was conspicuous where rice residues were retained at the time of sowing of wheat crop. Zero till sowing of wheat with retention of full or partial burnt stubbles added crop biomass, which might have resulted in higher phosphorus content in soil after decomposition of rice residues. Further, higher phosphorus content in zero till sown and bed planting treatments than conventional tillage treatment might be due to lower weed infestation resulting in lesser nutrient mining by weeds. The research findings are in agreement with the findings of Mishra (1984), Das et al. (2003), Kharub et al. (2004), Kachroo et al. (2006) and Saikia et al. (2017).
Regarding weed control treatments, the higher available phosphorus content in mesosulfuron + iodosulfuron 12.0 g/ha, sulfosulfuron 25 g/ha, clodinafop 60 g/ha f.b. 2, 4-D 0.5 kg/ha and clodinafop 60 g/ha as compared to unweeded control at both the soil depths of 0-15 and 15-30 cm during both the growing seasons (Table 3) might be due to less total biomass (crop + weeds) production in herbicide application treatments resulting in lower cumulative phosphorus uptake by crop and weeds. However, as application of alone clodinafop 60 g/ha controls only grass weeds, thus resulting in more nutrient mining and ultimately lower available phosphorus content in soil. Brar and Walia (2008) also reported higher total phosphorus uptake by crop and weeds in unweeded control plots than herbicide treated plots. improvement in organic carbon, available nitrogen and potassium in soil but response was less pronounced than rice stubbles without burning. Furthermore, simply zero till plots showed positive trend in organic carbon and available nitrogen, phosphorus and potassium in soil. Different herbicide application treatments although did not exhibit any difference in soil organic carbon, but significantly improved the available nitrogen, phosphorus and potassium level in soil by reducing nutrient mining by weeds than untreated control.


extfieldsofstudy:
Physics
Environmental Science

text:
The Application of Municipal Waste Compost to Improve the Physical Properties of Soil and Palm Oil Production in Silinda District, Serdang Bedagai

This research had been done in Agricultural faculty of north Sumatera university, medan on april until oktober 2009. The aim of this research are studied The Application of Municipal Waste Compost to Improve the Physical Properties of Soil and Palm Oil Production in Silinda District, Serdang Bedagai. This research was designed by 2 factors and 4 replications. The first factor are uses a separate plot design (RPT) with 2 factors and 4 replications as follows: Main plot consists of 2 levels of treatment, namely:T1: 5 years of planting, T2: 20 years of planting. Child Plots consist of 3 levels of treatment, namely: K1: Without Conservation Measures + Without Giving Compost, K2: Concave Plate + Compost, K3:, Individual Rorak + Compost, and numbers of reports: 4 replications (each planting). This result showed that the application of Municipal Waste Compost not significant to the Physical Properties such as,bulkdensity,porosity, permeability.

Introduction
Oil palm has an important role for the national economy, especially providing employment and as a source of state income [1]. The area of oil palm plantations in the North Sumatra province of Serdang Bedagai District in 2014 reached 12.7 million ha / year with fresh fruit bunches production of 40.89 million tons / ha / year so that it can be said that one area with low oil palm production if compared with the production of fresh fruit bunches in Deli Serdang district which reached 42.8 million tons / ha / year [2].
Palm oil grows in podsolic, latosol, gray hydromorphic, alluvial or regosol types. The optimum pH value is 5.0-5.5. Palm oil requires loose, fertile, flat soil well drained and has a deep solum layer without padas [3]. The topographic conditions of oil palm plantations should be no more than 25%, meaning that the difference in height between two points is 100 m not more than 25 m. The problem of farming in sloping areas is the erosion that is getting bigger if it is not accompanied by conservation techniques [4]. Erosion is very detrimental to land productivity because in a short time the fertile topsoil will disappear. Soil damage due to loss of nutrients can be improved by adding the right fertilizer, but if the damage is caused by loss of production and hydrological functions then repairing it takes a long time.
Conservation is the management of natural resources or the whole environment of an ecosystem to prevent over-utilization, pollution or neglect for the preservation of natural resources [5]. Soil conservation is an effort to keep the land productive or repair damaged land due to erosion to make it better [6]. The steepness of the slope can increase the amount of surface flow, but it also increases the transport energy of water. The number of soil grains splashed down by the collision of rain grains will  [7]. This is due to the greater gravity due to the increasingly sloping surface of the ground from the horizontal plane, so that the more eroded topsoil. The amount of erosion per unit area becomes 2.0-2.5 times more if the slope of the land surface is twice as steep.
Organic matter is an important ingredient in creating soil fertility both in physical, chemical and biological terms [8]. Organic matter is a soil aggregate that is unmatched. About half of the cation exchange capacity (CEC) comes from organic material. It is a source of plant nutrients. Besides that organic matter is the energy source of most soil organisms. In playing these roles organic matter is very much determined by the source and its composition, because of the smooth decomposition and the results of the docomposition itself. The benefits of organic matter in the soil are: Increase the content of organic matter, macro nutrients, micro nutrients, proteins, organic acids and colloids in the soil. Improve soil structure, increase soil in storing water, increase soil in cation exchange capacity, reducing phosphate fixation by Al and Fe on the soil, increasing the activity of biology or microorganisms in the soil such as bacteria, fungi, earthworms and algae, reducing bulk density,improve crop quality [9]. Addition of organic material from manure and plant remnants or the results of planting such as Mucuna sp. can improve soil physical properties such as available water pores, aggregate stability index, and soil density. Giving organic material both from plant debris and deliberately planted does not cause problems for farmers. Based on the problems stated above, the authors are interested in conducting a study entitled the application of municipal waste compost to improve the physical properties and production of oil palm on sloping land

This study uses a separate plot design (RPT) with 2 factors and 4 replications as follows:
Main plot consists of 2 levels of treatment, namely Yijk: Observation on the first experimental unit that obtained a combination of planting year treatment level i from factor a and treatment of conservation method level j of factor b μ: Actual Average Value (population average) ρk: Additive effect from group k αi: Additive effect of i-level of factor A βj: Additive effect of j-level of factor B (αβ) ij: Additive effect of i-level of factor A and j-level of factor B yik: The random effect of the main plot that appears at the first level of factor A in the k-group is often called the main plot error Furthermore, the data was analyzed by Variant analysis on each parameter measured and tested further for real treatment using Duncan's Multiple Range Test at the 5% level.

Location survey research
Preliminary survey (Location assessment) at the location of smallholder plantations in Pagarmanik Village, Silinda Subdistrict, Serdang Bedagai District, North Sumatra Province The method used in this study was to analyze the area of suitable research carried out by analyzing soil physics.

Preparation of municipal waste
Compost of municipal solid waste is obtained / purchased from Community Self-Help Groups (KSM) Pondok Miri Asri which provides large-scale compost and direct production with the application of Organic material used is Compost Fertilizer, with the composition of Domestic Waste Compost (Municipal Waste) + Cow / Lamb Manure + Blotong + Water Cattle Art and Laundry with a ratio of 5: 5: 5: 1.

Stage of Activity in the Field
Work begins with a preliminary survey, namely by conducting a field orientation research such as taking coordinates. After the preliminary survey, followed by the implementation of the main survey with the main objective, composite soils were sampled. The taking of soil samples is carried out zig zag at a depth of 0-30 cm then compiled from several locations, so that some soil samples are obtained. Provide as many as two plastic bags (one for soil chemical analysis and one for soil biological analysis) at each observation point, then put the soil sample into plastic by grouping each treatment on a conventional disk, concave disks, composted individual patterns, the contour pattern composted and labeled the field in each soil samples. Every soil taken from soil sampling can be air dried to be examined in the laboratory which includes the chemical and biological properties of the soil found in the land characteristics table. This research was carried out using methods of applying organic materials and soil analysis in the Laboratory and processing data.

Application of municipal waste compost on oil palm cultivation
Excavations between plants were made by using a hoe 60 cm wide and 30 cm deep, according to the treatment. The excavated soil is placed at the edge of the excavation hole to make it easier to close the hole. Prepared organic material (municipal waste compost) After the excavation hole has been prepared, then fill the excavation hole with the organic material provided. After the excavation hole is filled with organic material according to the treatment, it can make a mark or brand in each treatment. For the rorak dimension it is adjusted to the amount of organic material that will be applied with a maximum depth of 30 cm half of the root zone of oil palm The vertical mulch of a dish with 2 treatments is a mechanical conservation technique, that is, evenly distributed in a dish with a certain treatment (conventional) and without treatment, namely a land dish left in its original state (TM). All treatments were repeated 3 times at each different planting year both in plants that produced 1 that ranged from 3-4 years old and in plants that produced 2 that ranged from 7-8 years with a distance per each replicate of 1 row plants as a separator repeating one another.

Bulk density
The results of the statistical analysis showed that the effect of the conservation method was not significant, and that both interactions did not significantly influence bulk density. To find out the average of each observation is presented in table 1. In Table 1, it can be seen that the treatment of conservation methods did not significantly affect bulk density. The highest bulk density value was obtained in the treatment on conventional disk treatment (k1), that is, 0.76 and followed by individual behavior treatment (k3), that is, 0.75 and the lowest in conventional treatment (k2) is 0.67.

Porosity
The results of the statistical analysis show that the effect of the improvement of the conservation method has no significant effect, and both interactions do not significantly affect permeability. To find out the average of each observation is presented in Table 2. In table 2 it can be seen that the treatment of conservation methods has no significant effect on porosity. The highest porosity value was obtained in the treatment of the concave disk + compost (k2) treatment, that is, 73.83 and followed by individual rorak treatment (k3), namely, 72.06 and the lowest in conventional treatment (k1), namely 70.33

Permeability
The results of the statistical analysis show that the effect of the improvement of the conservation method has no significant effect, and both interactions do not significantly affect permeability. To find out the average of each observation is presented in Table 3. In table 3, it can be seen that the treatment of conservation methods has no significant effect on permeability. The highest permeability value was obtained in the treatment of the concave disk + compost (k2) treatment, that is, 11.5 and followed by the individual treatment pattern (k3), that is, 10.81 and the lowest in conventional treatment (k1) which was 10.43