extfieldsofstudy: Biology Physics

text:
Changes in chemichal characteristics of kombucha from various cultivars of snake fruit during fermentation

Kombucha snake fruit is a beverage of sugared snake fruit juice with a kombucha consortium called SCOBY (Symbiotic Culture of Bacteria and Yeast). This research was aimed to know the changes of chemical characteristics of kombucha from various cultivars of snake fruit during fermentation. This research used Randomized Block Design with 1 factor (salak Suwaru, salak Madura, salak Pondoh and salak Bali) and three replication. The data obtained were statistically evaluated by ANOVA test (Analysis of Variance) and continued by Fisher test to determine level of significant difference. The Effectiveness Index Test was used to select the best treatment. The results demonstrated that there were changes in the chemical characteristics of a decrease in pH, total sugar, and total soluble solids, as well as an increase in total acidity, total phenol and antioxidant activity significantly during fermentation. The best treatment was obtained on kombuchaof salak Suwaru cultivars with total acidity 1.64%, pH 3.22, total sugar 7.76%, total soluble solids 12.88 °Brix, total phenol 535.59 mg/L GAE and antioxidant activity 88.18%.

Introduction
Kombucha is a beverage of sugared tea fermented for 14 dayswith symbiotic consortium of acetic acid bacteria and yeasts called SCOBY. Acetobacter xylinum and various yeast (e.g. Saccharomyces , Zygosaccharomyces, Brettanomyces and Candida) have been identified in kombucha fermentation. Commonly, kombucha is made from black tea leaves as substrate [1]. Based on several previous researches it has been proven empirically that black tea kombucha has possesses functional properties such as antimicrobial, antioxidant, antidiabetic, antidislipidemic and other [1]. Besides of black tea, kombucha can be made from other substrates such asgrape, orange and blackcurrant [2].
Snake fruits (Sallacazalacca) is one of Indonesia's indigenous commoditieswhich contains fiber, vitamin A, B1, C, and high antioxidant activity [3]. Besides that, snake fruits have higher polyphenols compared to apples, oranges, mangosteen, and kiwi [3] [4]. Based on previous research revealed that Suwaru snake fruit which is fermented into kombucha can increase polyphenols and organic acids as well as antioxidant activity [5].
Indonesia have many snake fruit cultivars such as salak Suwaru (Malang, JawaTimur), salak Pondoh (Sleman, Yogyakarta), salak Madura (Bangkalan, Madura) and salak Bali (Karangasem, Bali). Each cultivar has unique characteristics. This research was aimed to know changes of chemical characteristic of kombucha from various cultivars of snake fruit during fermentation.

Experimental design
The experimental design used in this research is a randomized block design with one factor that consists of 4 levels and repeated 3 times to obtain 16 units of trial. Factors used are cultivars as a raw material for making kombucha namely: The independent variable in this research is various cultivars as a raw material. The dependent variables include pH, total acidity, total soluble solids, total sugar, total phenol and antioxidant activity. Kombucha were analysed on day 0 and 14 during fermentation.

Kombucha preparation
Kombucha were prepared according to previous research [5]. The snake fruits were peeled, washed, and cut into small sizes, from which 500 g was mixed with water (1:1, w/w), juiced (blended) and filtered (cheese cloth). Cane sugar were added 10% (w/v) in the snake fruit juice, pasterurized (Waterbath Memmert, Germany) at 65 °C for 30 min and cooled to ambient temperature before storing in a sterile jar. The sugared juices were inoculated with 10% (v/v) the liquid broth of kombucha starter aseptically.
The jar covered with clean cheese cloth and fixed with rubber bands. Fermentation was conducted under aseptic conditions, carried out by incubation at room temperature (28 ± 3 o C) for 14 days.

Kombucha analysis 2.4.1. Total acidity and pH analysis
Total acidity was measured by titration procedure [5], 10 mL of samples was taken and 2 or 3 drops of phenolphthalein indicator was added. It was then immediately titrated with 0.1 M NaOH till permanent colour appeared. pH samples were measured by pH meter (Hanna, Thermo Fischer Scientific, USA).

Total sugar and total soluble solid analysis
Total sugar was determined by the anthrone method according to previous research [5], 1 mL samples was transferred to a test tube and mixed with 5 mL anthrone reagent (0.05 g anthrone in 50 mL concentrated H 2 SO 4 ). The test tube were held at 100 °C for 12 min and cooled before measuring the absorbance at 630 nm in a spectrophotometer (Spectro 20D Plus, Labomed, USA) with a glucose solution as the standard. Total soluble solids of the samples were measured by refractometry (Atago handheld refractometer N-1E, Japan).

Total phenolic compound analysis
Total phenolic content was determined with the Folin-Ciocalteu reagent with reference to previous research [5] using gallic acid as the standard. One millilitermethanolic extract of samples was placed into a test tube and vortexed (Nissin mixer N-20 M, USA) for 15 s with 1.5 mL Folin-Ciocalteau reagent, and allowed to stand at room temperature for 5 min, before adding 1.5 mL of 0.57 M Na 2 CO 3 and incubated for 90 min at room temperature. Absorbance was measured at 750 nm using the spectrophotometer, with the same mixture except the sample extract was replaced by methanol as the blank. Total phenolic content was expressed as mg GAE (Gallic Acid Equivalent)/L.

Antioxidant activity analysis
Antioxidant activity was measured in using the DPPH radical scavenging activity method reference toprevious research [6] with slight modification, 100 µL samples diluted with 3 ml of ethanol 96%, then 1 ml of 0.2 mM DPPH was added and homogenized. The reaction mixture was vortexed and left to stand at dark room for 30 min and the absorbance for the sample (Abs sample) was measured using UV-VIS spectrophotometer (Shimadzu, UV-1601, Japan) at 517 nm against buffer blank. Controls were made by replacing sample with aqua demin. Antioxidant capacity is expressed as % DPPH radical scavenging ability by the formula [1 -(Abs sample/Abs Control)] x 100%.

Statistical Analysis
All the data were expressed as mean ± standard deviation (SD) for 3 repetition. The statistical significance was evaluated by one-way analysis of variance (ANOVA) followed by Fisher test (Stat View) using MiniTab Ver.16.0. Statistical significance was accepted at p < 0.05.

Chemical characteristic of snake fruit kombucha
Kombucha fermentation process characterized by decreasing the substrate in the form of sucrose, as well as the improvement of fermentation products such as acids and exopolysaccharide (nata phase). Table 1 shows that there were an increase in total acidity which is in line with the decrease in pH, total sugar and TSS. Based on the results of variance analysis, it is known that there were cultivar different on changes in total acidity, pH, total sugar and total soluble solids. Salak Pondoh kombucha had the highest change values. The increased in total acidity that occurs during the fermentation process is caused by changes of glucose by bacteria and yeast during the fermentation process to produce organic acids, especially  [1]. Kombucha fermentation process starts from the process of hydrolysis of sucrose to glucose and fructose by Acetobacterxylinum. In the pentose phosphate pathway, glucose is converted by the enzyme glucokinase to glucose-6-phosphate (G6P), then G6P is converted to glucose-1phosphate (G1P) with the help of phosphoglucomutase enzyme and converted back to UridinDiphosphate (UDP) with pyrophosphorylase enzyme until it is converted to cellulose with the help of cellulose synthase enzymes. The result of cellulose formation is what will be seen as a pellicle on the surface of the fermentation medium [7].
Besides producing cellulose, the metabolic process of Acetobacterxylinum will also produce primary metabolites in the form of acetic acid [1] and also other organic acids including gluconic acid, glucoronic acid [1], malic acid, tartaric acid, citric acid, butyrate and lactic acid [5]. While yeast (Saccharomyces cereviseae) during the fermentation process will convert glucose and fructose to alcohol and CO2 through the process of glycolysis [1]. Furthermore, CO2 will react with water to form carbonic acid. Meanwhile, the alcohol produced will be oxidized by Acetobacterxylinum to acetaldehyde and then into acetic acid [1]. The accumulation of organic acids formed during the fermentation process will affect the pH value. The higher the total acid formed, the lower the pH value, this occurs because the acid in the kombucha will release protons (H + ) so that the pH value decreases. The decreased total sugar and total soluble solids occurs during the fermentation process along with the increased in total acidity. This is because sugar in the fermentation medium is used as a carbon source for the growth of microorganism cells, in addition to the metabolic processes that produce cellulose and metabolites in the form of certain organic acids [1]. Total soluble solids value is a measure of the content of a combination of all substances (inorganic and organic) dissolved in food. Some decreases the value of total soluble solids during the fermentation process other than due to the reduced total sugar can also be caused by the deposition of protein, pectin, pigments and other minerals. This also happened in this research.

Total phenolic compound and Antioxidant activity
Fermentation process in kombucha is known to be able to change bioactive components. Several previous researches revealed that there was an increase in the concentration of phenol [1], flavonoids and tannins [1,8] during fermentation. Based on Table 2, there was an increase in total phenols, tannins and flavonoids in all cultivars of snake fruit kombucha. The results of the analysis revealed that various types of snake fruit used as ingredients to make kombucha showed no significant differences in the parameters of changes in total phenol values and antioxidant activity. The increased of phenol during the fermentation process is suspected because there is a biotransformation process of phenol compounds by microorganisms in kombucha. In previous research revealed that bacteria and yeast in the kombucha consortium can produce various types of enzymes that function to break down phenol complex compounds into simple forms [1]. During fermentation process.several hydrolytic enzymes such as invertase, cellulase, amylase are produced [9] which are thought to be able to break various complex bonds between phenol compounds and the structure of the material network so as to increase the number of free phenols in fermentation media. Candida tropicalis which is one type of microorganism in kombucha culture is known to be able to break down various types of phenol compounds into simple forms [10]. Ferulic acid and cinnamic acid are a type of phenolic acid that is abundant in plants [11]. Saccharomyces cerevisiae is able to produce enzymes of cinnamic decarboxylase and vinyl reductase. Sinamic decarboxylase enzymes act to catalyze the decarboxylation process of cinnamic acid and ferulic acid to 4-vinylfenol and 4vinilguaikol. While the enzyme vinyl reductase acts to catalyze the reduction process of 4-vinylfenol and 4-vinilguaikol to 4-ethylphenol and 4-ethylguaicol [12].
The increase of phenol compounds in line with increase of antioxidant activity. This is supported by several previousresearches that have revealed that the content of phenol compounds will increase in line with the increase in antioxidant activity [8]. This is because bioactive compounds have a free ratio with hydrogen atoms from the aromatic hydroxyl group (-OH) they have [13].

Best treatment of snake fruit kombucha
The selection of the best treatment was carried out using the De Garmo / effectiveness index method [14] Based on this.it was known that the best results iskombucha of salak Suwaru cultivar with the following characteristics: total acid 1.64%. pH 3.22.total sugar 7.76%. Total soluble solids 12.88 o Brix.total phenol 535.59 mg / L GAE and antioxidant activity 88.18%.

Conclusion
The results demonstrated that there were changes in the chemical characteristics of a decrease in pH, total sugar, and total soluble solids, as well as an increase in total acidity, total phenol and antioxidant activity significantly during fermentation. The best treatment was obtained on kombucha of salak Suwaru cultivars with total acidity of 1.64%, pH of 3.22, total sugar of 7.76%, total soluble solids of 12.88 o Brix, total phenol of 535.59 mg/L GAE and antioxidant activity of 88.18%.


s2fieldsofstudy:
Agricultural And Food Sciences
Environmental Science

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

text:
PHYSICAL, CHEMICAL, AND BIOLOGICAL SOIL ATTRIBUTES UNDER ANALOG AGROFORESTRY SYSTEM AND PASTURE SITES

Analog agroforestry system uses native tree species to improve soil conditions and the microclimate of degraded areas. This study aimed to assess the impact of analog agroforestry on physical, chemical, and biological soil attributes. We tested the hypothesis that some of these attributes can be used as indicators of soil quality improvement compared to a managed pasture area. Two experimental sites were selected, an analog agroforestry site and a pasture site. In October 2016 (end of the dry season), soil samples were collected from the 0–5 and 5–10 cm depths and the soil fauna community was sampled using pitfall traps. The analog agroforestry system led to increased total abundance, total richness, mean richness, evenness, and diversity of the soil fauna community as well as higher gravimetric soil moisture, sand content, pH, calcium, magnesium, and sum of exchangeable bases, which are good indicators of soil quality. Adults of Coleoptera, Diptera, Gastropoda, Hymenoptera, Isopoda, Lepidoptera, Poduromorpha, Symphypleona, Pseudoscorpionida, Lepidoptera and larvae of Coleoptera, Diptera, Lepidoptera, and Neuroptera were the most abundant taxonomic groups in the analog agroforestry system.

INTRODUCTION
Soil management practices, including the choice of plant cover, can positively or negatively influence the physical, chemical, and biological attributes of soil (LOURENTE et al., 2007;CAMARA et al., 2012;BARETTA et al., 2014;CABRERA-DÁVILA et al., 2017). Agroforestry systems, as compared with monocultures, have been shown to enhance soil quality, nutrient cycling, carbon sequestration, and biodiversity (FÁVERO et al., 2008). In agroforestry systems, trees and shrubs are cultivated in combination with agricultural crops and/or livestock production. A wide range of economic activities can be practiced using this system, contributing to the social, economic, and environmental sustainability of the agricultural sector (SCHEMBERGUE et al., 2017). These benefits can stimulate the adoption of agroforestry, especially in areas degraded by anthropic action (JOSE, 2012).
Agroforestry systems can be designed to mimic native forest structure and function. These systems are called analog agroforestry, analog forestry, or successional agroforestry. As the tree canopy becomes denser, some agricultural crops can no longer be cultivated. From this point on, natural regeneration may take place (FÁVERO et al., 2008), since tree species contribute to the improvement of soil conditions. Fabaceae species, for instance, contribute to natural regeneration because of their association with nitrogen-fixing bacteria. Fabaceae plants increase the performance (SOUZA; PIÑA-RODRIGUES, 2013) and soil fertility of analog agroforestry systems (DIAS et al., 2006) by producing leaf litter with low lignin/N ratio, which favors the release of nutrients to the soil (DUARTE et al., 2013). Cultivation of Fabaceae species has a positive effect on the diversity and density of the soil fauna community, including Oligochaeta, Coleoptera, Araneae, and Formicidae individuals, an important factor for nutrient cycling (DIAS et al., 2006).
Limited data are available on the impact of analog agroforestry on soil attributes of degraded areas. This study aimed to fill this research gap by comparing the physical, chemical, and biological attributes of soils under analog agroforestry and pasture and by identifying soil quality indicators for analog agroforestry systems.

MATERIAL AND METHODS
The study was conducted in an agroecological farm (Fazendinha Agroecológica Km 47), which is part of an integrated agroecological production system (SIPA) managed by EMBRAPA Agrobiology, PESAGRO Rio, and the Federal Rural University of Rio de Janeiro. The farm is located in the municipality of Seropédica (22°44′38″S 43°42′27″W, 26 m above sea level), Rio de Janeiro, Brazil. The climate is classified as Aw, characterized by dry winters and wet summers, according to the Köppen climate classification (ALVARES et al., 2013). The average annual rainfall is 1,213 mm, occurring mainly between November and March. The average annual temperature is 23.9 °C (CARVALHO et al., 2011), and the original vegetation is Semideciduous Tropical Forest (CORRÊA NETO et al., 2014).
Two sites were studied: a pasture with Red Yellow Acrisol and an analog agroforestry system with haplic Planosol. Pannicum maximum and Brachiaria brizantha are grown in the pasture site, which surrounds the analog agroforest. The analog agroforestry site (6000 m 2 , 200 × 30 m) was used for pasture (Panicum maximum) until February 2005, when the analog agroforestry system was implemented (MARTINS et al., 2019). The land was plowed and mechanically graded, and seeds and seedlings of exotic forest species and Atlantic Forest species were planted (Table 1). In April 2005, banana seedlings (Musa paradisiaca) were planted and fertilized with 3 L of tanned bovine manure and 100 g of potassium sulfate per planting hole, and pineapple seedlings (Ananas comosus) were planted and fertilized with 1 L of manure and 150 g of phosphorite per meter of furrow. Cassava (Manihot esculenta) seedlings were planted in unfertilized furrows, and tree seedlings (Albizia lebbeck, Schizolobium parahyba, Albizia saman, Pterogyne nitens, Acacia angustissima, Trichilia hirta, Senna macranthera, Piptadenia gonoacantha, Mimosa artemisiana, Colubrina glandulosa, Enterolobium contortisiliquum, Lonchocarpus guilleminianus, Morus nigra, Eugenia uniflora, Inga semialata, Syzygium cumini, Schinus terebinthifolius, Guazuma ulmifolia, Sparattosperma leucanthum, Bixa orellana, Syagrus romanzoffiana, and Chorisia speciosa) were planted in rows with cassava, without fertilization. Fabaceae seedlings were inoculated with nitrogen-fixing bacteria and arbuscular mycorrhizal fungi (Rhizophagus clarus and Gigaspora margarita). In December 2005, tree seeds were mixed with manure and broadcast in furrows or holes.
In January 2009, invasive grasses and spontaneous herbaceous plants were removed by hoeing and 50% of the canopy of trees with a diameter at breast height (DBH) greater than 4 cm was pruned to increase light penetration. Pruned biomass was minced and left on the soil. In April 2009, 200 Eritrin sp. cuttings and 25 Tectona grandis seedlings were planted. A year later, in January 2010, invasive grasses were removed by hoeing and 10-15% of the tree canopy (>4 cm DBH) was pruned. Acacia angustissima individuals who were fallen, cracked, or infested with Struthanthus flexicaulis were removed. The system was enriched by planting 120 Euterpe edulis seedlings and 20 seedlings of each of the following tree species: Apuleia leiocarpa, Erythroxylum pulchrum, Cedrela fissilis, and Plathymenia foliosa. In April 2010, 60 Spondias sp. seedlings were planted. Between April 2008 and May 2010, the spontaneous occurrence of Eriotheca candolleana, Erythroxylum pulchrum, Anadenanthera sp., Mimosa bimucronata, and Eugenia brasiliensis was observed.
Soil sampling and soil fauna extraction were carried out in October 2016 (end of the dry season), when tree species were predominant in the area and there were no more short-cycle crops. Soil temperature and moisture content were determined in 0-5 cm depth soil samples. We determined soil fertility and texture analysis (clay, silt, and sand contents) in 0-5 and 5-10 cm depth samples.
We randomly installed ten 500 mL plastic pitfall traps (17 cm height and 9.7 cm diameter) in each site. Traps were buried in the ground with the rim at surface level, 10 m apart from each other, and were filled with about 100 mL of a 3% acetylsalicylic acid solution containing a few drops of detergent. Traps were left in the field for seven consecutive days. Then, the contents were sieved (0.0053 mm mesh) and stored in 10 mL bottles containing 70% alcohol. Samples were transferred to a Petri dish with distilled water, and captured individuals were quantified and categorized into taxonomic groups (Class, Order, Family). Total abundance (individuals day -1 trap -1 ), relative abundance (%), total richness (total number of taxa), mean richness (richness calculated among the replications), Pielou's evenness index, and Shannon's diversity index were estimated.
Soil moisture content (0-5 cm depth) and soil temperature (0-5 cm depth) were determined by the gravimetric method (DONAGEMA et al., 2011) and using a geothermometer, respectively, in 10 random sample points. At 10 random points, we determined the soil temperature (0-5 cm deep) using a geothermometer and the soil moisture content (0-5 cm deep) by the gravimetric method (DONAGEMA et al., 2011). Soil pH in water, N, P, K, Ca, Mg, and Na contents, sum of bases, extractable acidity, and soil texture fractions (DONAGEMA et al., 2011) were determined in 10 samples of 0-5 and 5-10 cm depth soil. Each sample was a composite of three samplings.
Soil physicochemical characteristics, total and relative abundance, and mean richness data were subjected to Levene's test of variance homogeneity. Means were compared by Student's t-test or Mann-Whitney nonparametric test. Pearson correlations were calculated between physicochemical soil attributes (0-5 cm depth) and mean richness, total abundance, and relative abundance of the 10 major taxonomic groups. significance was set at P < 0.05 for all statistical analyses, and analyses were carried out using Statistica version 8.0. Soil physicochemical data were subjected to principal component analysis (PCA), followed by hierarchical clustering using Ward's criterion. Multivariate analyses were carried out using PAST version 2.17c.
Soil attributes Analog agroforestry system Pasture 0-5 cm 5-10 cm 0-5 cm 5-10 cm Sand 700.80 ( PCA extracted two principal components (PC1 and PC2), which together accounted for about 94% of the total variance in the dataset. PC1 explained 64.35% of the variance and PC2 29.40% (Figure 2a). The two experimental sites and different soil layers were clearly separated in the PCA biplot. The pasture site was located on the positive side of the PC1 axis, whereas the analog agroforestry system site was located on the negative side. Soil layers appear on different sides of the PC2 axis, the 0-5 cm layer in the positive region and the 5-10 cm layer in the negative region. The 0-5 cm soil layer was associated with more chemical soil parameters than the 5-10 cm layer for both sites (Figure 2a). In the agroforestry site, the 0-5 cm soil layer was associated with higher Ca, Mg, and pH, and the 5-10 cm soil layer with higher sand content. In the pasture site, the 0-5 cm soil layer was associated with higher N, P, K, TOC, and extractable acidity, and the 5-10 cm layer was associated with higher silt content.
Hierarchical cluster analysis identified two large groups (Figure 2b). The first was formed by agroforest soil samples collected from the 0-5 and 5-10 cm layers, which were within 20 distance units of each other, and pasture soil samples collected at the 5-10 cm depth, located about 100 units away. The second group contained only pasture soil samples collected from the 0-5 cm layer. The two groups were about 540 distance units apart.
These results indicate that there is a large dissimilarity between the two experimental sites, due to soil chemical attributes in the 0-5 cm layer.
Soil fauna abundance and mean richness showed a significant positive correlation with soil sand content, pH, and magnesium and a significant negative correlation with soil temperature, potassium, and extractable acidity at the 0-5 cm depth (Tables 5 and 6). Table 5. Pearson's correlation between total abundance (Ab), mean richness (Rm), and relative abundance of the 10 most abundant taxonomic groups of the soil fauna community and gravimetric soil moisture (Ug), temperature (T), contents of sand, clay, silt, total organic carbon (TOC), nitrogen (N), and available phosphorus (P) at the 0-5 cm depth in analog agroforestry and pasture sites in Seropédica, Rio de Janeiro, Brazil. Tabela 5. Valores de coeficiente de correlação de Pearson entre a abundância total (Ab), riqueza média (Rm) e a abundância dos 10 grupos taxonômicos mais representativos da comunidade da fauna do solo, e a umidade gravimétrica (Ug), temperatura do solo (T), conteúdos de areia, argila, silte, carbono orgânico total (TOC), nitrogênio e fósforo disponível na camada de 0-5 cm, nas áreas de sistema agroflorestal regenerativo análogo e pastagem, Seropédica, RJ, Brasil. At least half of the 10 most abundant taxonomic groups presented a significant positive correlation with soil sand content and pH, and presented a significant negative correlation with soil temperature and extractable acidity at the 0-5 cm depth (Tables 5 and 6). Soil sodium levels showed no significant correlation with fauna community composition. Table 6. Pearson's correlation between total abundance (Ab), mean richness (Rm), and relative abundance of the 10 most abundant taxonomic groups of the soil fauna community and soil pH, calcium (Ca), magnesium (Mg), potassium (K), sodium (Na), sum of bases (SB), and extractable acidity (H + Al) in the 0-5 cm layer in analog agroforestry system and pasture sites in Seropédica, Rio de Janeiro, Brazil. Coleoptera, Isopoda, Poduromorpha, Symphypleona, and Diptera presented a significant positive correlation with soil sand content, pH, magnesium, and sum of bases. On the other hand, these taxonomic groups presented a significant negative correlation with soil temperature and H + Al (Tables 5 and 6). There was no clear correlation between the presence of Acari, Araneae, Diplopoda, and Entomobryomorpha and soil physical and chemical attributes. Formicidae was the only group that did not show a significant correlation with the soil attributes.

DISCUSSION
Total and relative abundance, richness, evenness, and diversity of the soil fauna community were higher in the analog agroforestry system site. This site also had a larger number of taxonomic groups (Coleoptera, Diptera, Gastropoda, Hymenoptera, Isopoda, Lepidoptera, Poduromorpha, Symphypleona, Pseudoscorpionida, and Lepidoptera adults and Coleoptera, Diptera, Lepidoptera, and Neuroptera larvae), probably because of its higher soil moisture content and lower soil temperature compared with the pasture site, where fewer taxonomic groups were observed (Araneae, Archaeognatha, Diplopoda, Entomobryomorpha, Formicidae, and Phasmatodea).
Milder soil microclimatic conditions, which favor the diversity and complexity of the soil fauna community (CAMARA et al., 2012;POMPEO et al., 2016), occurred in agroforest soil, even though the soil had a higher content of sand than pasture soil. It seems that microclimatic conditions were not greatly influenced by differences in soil type (Red Yellow Acrisol in the pasture site and haplic Planosol in the agroforestry site). Moisture retention is generally lower in soils with high sand contents (ANDRADE; STONE, 2011). Therefore, leaf litter was the key factor for the good soil microclimatic conditions in the analog agroforestry site. A similar result was observed in an agroforestry site in Cuba: total abundance and richness of the soil fauna community were higher than that of a pasture site because of the soil cover provided by plant material (CABRERA-DÁVILA et al., 2017). The abundant and heterogeneous litter observed in the analog agroforestry site may also have provided a greater variety of food resources for the soil fauna community (CAMARA et al., 2012;POMPEO et al., 2016).
The higher calcium and magnesium levels observed in analog agroforest system soil were probably due to plant litter, as this site was not fertilized with agricultural lime. Phosphorus and potassium contents were higher in pasture soil because of mineral and organic (cattle urine and feces) fertilization. Higher TOC levels were observed in pasture soil as a consequence of the constant deposition of organic material (QASEM, 1992). In a study carried out in Rio Doce Valley, Minas Gerais, Brazil, agroforest soil had higher pH, magnesium content, and sum of bases, whereas pasture soil had higher TOC content (FÁVERO et al., 2008).
Soil chemical attributes were associated with the 0-5 cm soil layer in both areas. Contact with plant debris and the high activity of decomposers in this layer contribute to soil fertility, which usually decreases with depth, regardless of soil type (CEZAR et al., 2015;MARTINS et al., 2015).
There was a significant and positive correlation of total abundance and richness with sand content, pH, and magnesium levels. The soil fauna community, therefore, is positively influenced by soil management practices that lead to increased soil pH and magnesium contents (LOURENTE et al., 2007;BARETTA et al., 2014). High soil pH is a reflection of the availability of specific ions in the soil solution, which interfere with the structure of the soil fauna community (POMPEO et al., 2016). Soils with high sand content have increased aeration, facilitating the movement of soil fauna. FLORESTA, Curitiba, PR, v. 50, n. 1, p. 887 -896, jan/mar 2020. Camara, R. et.al. ISSN eletrônico 1982 10.5380/rf.v50 i1.57476 895 Total abundance and richness presented a significant and negative correlation with soil temperature, potassium, and extractable acidity. Temperature is one of the main factors affecting the metabolism of soil fauna and, consequently, their spatial activity and distribution (POMPEO et al., 2016). Richness and abundance are negatively affected by high extractable acidity (BARETTA et al., 2014). Lourente et al. (2007), analyzing soil fauna in Maracaju, Mato Grosso do Sul, Brazil, found that Formicidae abundance was not significantly correlated with physicochemical parameters of soils under different types of management, such as conventional farming, no-till farming, pasture, eucalyptus and native forest, and silvopasture.

CONCLUSIONS
The analyzes carried out allow us to conclude that: • Some physical, chemical, and biological soil attributes can be used as indicators of soil quality in analog agroforestry system and pasture sites. • The total abundance, total richness, mean richness, evenness, and diversity of the soil fauna community, as well as gravimetric soil moisture, sand content, pH, calcium, magnesium, and sum of bases were higher in the soil under analog agroforestry system when compared to the pasture site. • In soil under pasture, we observed higher values of temperature, extractable acidity, available phosphorus, exchangeable potassium, and TOC content in relation to the analog agroforestry system site. • The 0-5 cm soil layer was associated with more chemical soil attributes than the 5-10 cm layer for both experimental sites. • Adults of Coleoptera, Diptera, Gastropoda, Hymenoptera, Isopoda, Lepidoptera, Poduromorpha, Symphypleona, Pseudoscorpionida, and Lepidoptera and larvae of Coleoptera, Diptera, Lepidoptera, and Neuroptera were most abundant in soil under analog agroforest system. • Araneae, Archaeognatha, Diplopoda, Entomobryomorpha, Formicidae, and Phasmatodea were predominantly found in soil under pasture. • The total abundance and mean richness of the soil fauna groups presented a significant positive correlation with soil sand content, pH, and magnesium content and a significant negative correlation with soil temperature, potassium content, and extractable acidity.


s2fieldsofstudy:
Agricultural And Food Sciences
Biology

text:
Turopolje Pig (Turopoljska svinja)

Turopolje pig is a fatty-type pig breed created during the Middle Ages in Turopolje region in Central Croatia. Due to its modest demands, resilience and good adaptation to outdoor rearing, the Turopolje pig has been an important food source for the local population for centuries. However, with the transition from extensive to intensive pig production in the middle of the twentieth century, this autochthonous pig breed almost disappeared. Currently, despite the state support, Turopolje pig is still endangered, with a population of only 116 sows and 14 boars. Hence, to preserve Turopolje pig breed in a more sustainable way, the breed needs to be more economically exploited and scientifically explored. Thus, the aim of this chapter is to present history and current status of Turopolje pig breed, its exterior phenotypic characteristics, geographical location, production system and main products. Moreover, a collection and review of available literature data (available until August 2017) on reproductive and productive traits, including growth performance, carcass traits and meat and fat qualities of Turopolje pig breed, were carried out. Although studies on Turopolje pig are scarce, the present review gives the first comprehensive insight into this still untapped local breed of pigs investigated in the project TREASURE.

History and current status of the breed (census)
Turopolje pig is a native Croatian breed, created during the early Middle Ages in Turopolje region near Zagreb in Central Croatia. It is a medium-sized, primitive, fatty-type pig breed. As it developed over a long period of time, the breed perfectly adapts to its natural environment, primarily continental climate conditions and lowland forest ecosystems. Due to the modest demands, resistance and good adaptation to local marsh pastures and oak and beech forests, the Turopolje pig breed for centuries has been an important food source for the local population. However, the rapid penetration of imported lean pigs in the second half of the twentieth century, as well as the ban of forest grazing, significantly reduced the interest in this breed. The result was an emerging decrease of the population size, and since 1996, the Turopolje pig breed is under the state protection. Unfortunately, despite the support the Turopolje pig breed is still endangered, and the renewal of the population has been very slow. Census of Turopolje pig breed is presented in Figure 1. Presently, there are only 12 registered farms of Turopolje pigs with about 116 breeding sows and 14 boars in the latest available status (August 2016 [1]). In the past, the meat of Turopolje pig was considered better than meat of other pig breeds [2], but today its use is sporadic and almost completely replaced with the meat of modern pig breeds and hybrids. However, as a part of the current trends in the protection of local breeds and their sustainable farming systems, it becomes justified to review the breeding of Turopolje pig breed for production of meat and local meat products. Renovation of traditional link between breed and its products and their technological and marketing development may, by itself, represent the best way for recovery and long-term preservation of Turopolje pig breed on economically sustainable base.

Exterior phenotypic characteristics
The Turopolje pig breed morphology information is summarized in Table 1. It is a medium-size breed with distinctive sporadic black spots on a white or gray coat, mostly curly hair and drooping, half-folded ears (Figures 2 and 3). Head is medium long with slightly concave profile and sturdy snout, which ensures a good

Geographical distribution and production system
Turopolje refers to a plain extending over a 45-km-long and 23-km-wide alluvial plateau, occupying an area of about 600 km 2 , with an average altitude of 110 m above sea level. It is located between Posavina (wetland plains along the Sava River) in the north and the Vukomeričke gorice (low altitude hills) in the south. The Odra River flows through it with the Lomnica tributary. Characterized by lowland oak forests, periodically flooded pastures and continental climate, Turopolje has always been suitable for outdoor livestock production, especially pig breeding. In the past Turopolje pig breed spread from Turopolje to Sisak and Draganić, later to the parts of Slavonija and Podravina and all the way to the south-western parts of Hungary. However, with the transition from extensive to intensive pig production in the mid of twentieth century, its farming drastically reduced and the breed almost disappeared. Today, Turopolje pig is reared only in a few localities, mainly in Turopolje forest and Nature Park Lonjsko Polje (Figure 4), where traditional way of pig farming has been maintained. Basically, it comprises a low-input technology of animal housing and feeding in a fully outdoor system on pasture at local forests and marsh meadows. Pigs are provided with only a simple shelter, water and some supplemented feed (e.g., 0.5-2 kg  of corn per animal daily), while the majority of animal's diet is supplied from natural resources (e.g., acorn, grass, worms, snails, shellfish, etc.). Finishing at high-grain diet, prior to slaughter is usual. Indoor housing and intensive production systems are rarely practiced.

Organizations for breeding, monitoring and conservation
The Association "Plemenita Opčina Turopoljska" (Universitatis nobilium Campi Turopolya) is the responsible breeding organization for Turopolje pig breed, assisted by Croatian Agricultural Agency, which monitors the population and keeps herd books ( Table 2). Conservation of Turopolje pig breed started once Croatia signed Convention on Biological Diversity (CBD) in 1997, and breed was added to the FAO list of endangered breeds in category of regional breeds [3]. After CBD ratification a national biodiversity strategy was established, including an action plan for the conservation of endangered breeds. Since then Turopolje pig breed is under the state of renewal and in situ protection. Funds for conservation are provided by the state. Ilica 101, 10,000 Zagreb, Croatia http://www.hpa.hr/sektori/ sektor-za-razvoj-stocarskeproizvodnje/odjel-za-svinjogojstvo/ izvorne-pasmine/

Growth performance
Basic data on growth performance obtained in this review are presented in Tables 4 and 5. In Turopolje pig breed, studies provided only growth rate in period of lactation and the overall growth rate for the whole fattening stage (defined as overall). It should also be noted that majority of collected studies simulated practical conditions of the production systems used and that only a smaller part of the studies actually aimed at evaluating the breed potential for growth. The average daily gain in Turopolje pigs during lactation is 101 g/day [7], which is less than expected in modern pig breeds. Also, an average value obtained for the overall fattening stage is characterized by a considerably slower growth rate (429 g/day [10][11][12]) than modern pig breeds. In the context of the evaluation of growth performance, it is also of interest to observe the extreme values, because it can be assumed that the maximum figures exhibit the growth potentials of Turopolje pigs in ad libitum conditions of feeding (≈ 556 g/day in the overall fattening stage [12]).
In considered studies, the information on feed intake and feed nutritional value were scarce, which limits the evaluation of growth potential. Average daily feed intake reported was around 2.0 kg/day in the overall fattening period [11,12].

Body composition and carcass traits
Basic data obtained in this review with some of the most commonly encountered carcass traits that could be compared are presented in Table 6. In considered studies, pigs of Turopolje breed were slaughtered at approximately 437 days of age (140-679 days [5,[10][11][12][13]) and average 96 kg live weight [5,10,12,13]. Dressing yield was around 80% [5,10,12,13] 1 ADG in a period of lactation regardless of how long it was. 2 ADG in a period of fattening is reported as the overall growth rate for the whole studied period ( from approximately 30 kg body weight until slaughter).     [5,[10][11][12][13]). The backfat thickness values were measured at the position of withers averaged 57 mm [10,12], at the level of the last rib 37 mm [5,10,12] and at the level of gluteus medius muscle 34 mm [11,12]. Muscularity was measured as loin eye area averaged 23 cm 2 [11] and as muscle thickness above gluteus medius 48 mm [11,12].

Meat quality
Basic data obtained in this review with some of the most commonly encountered meat and fat quality traits measured in longissimus muscle that could be found are presented in Table 7. In the studies reporting meat quality of Turopolje pigs, pH measured in longissimus muscle at 45 min and 24 h post-mortem were around 6.1 and 5.68, respectively [11,12]. The intramuscular fat content ranged from 2.2 to 5.8 (3.7% in average [5,[11][12][13], and color measured in CIE L*, a* and b* color space was 44.6, 19.3 and 5.7 for L, a* and b* [12]. SFA, MUFA and PUFA content of intramuscular fat in longissimus muscle in the considered studies were around 38, 51 and 11%, whereas SFA, MUFA and PUFA content of back fat tissue were approximately 38, 49 and 13%, respectively [5,12].

Use of breed and main products
Resilient and capable of foraging, Turopolje pig breed has always been able to survive in free range, which makes it particularly suitable for low-input, extensive production systems. Its use today represents a potential alternative to intensive farming, and it should be intended primarily for production of pork meat and products of premium quality. Meat is darker and redder in color than in standard pork, with fine muscular texture, which seems to be characteristic for this breed [4,9]. There is a higher level of accumulation of fat tissue, especially in the subcutaneous area, and between the muscles. Meat of Turopolje pigs in today's gastronomy is mainly used in special occasions for the preparation of various local food specialties (e.g., "turopoljska kotlovina", goulash, various pork roasts- Figure 5). It is also suitable for processing in typical meat products (e.g., dry-cured ham- Figure 6, bacon, dry-fermented sausages, etc.), which are highly appreciated by local consumers but for now rarely available in the market. In 2017, the breeding association "Plemenita Opčina Turopoljska" applied for the registration of fresh meat from Turopolje pig with the protected designation of origin (PDO) label, and the procedure is underway at national level.


extfieldsofstudy: Physics Biology

text:
The Effect of Plant Growth Promotion Rhizobacteria Inoculation To Agronomic Traits of Aromatic Rice (Oryza sativa CV. Inpago Unsoed 1)

The aim of this research was to study the effect of Plant Growth Promotion Rhizobacteria to improve agronomic traits of rice plant. The research was held in Agronomy and Horticulture Laboratory from September 2017 until March 2018. The research was arranged with randomized block design with three replications the treatment consisted of 9 isolates of PGPR and control. The observed variables including plant height, leaf area, number of tillers, leaf greenness, root dry weight, plant dry weight, total roots length, number of productive tillers, panicle length, number of grains per panicle, weight of 1000 seeds and grain yield. The result showed that inoculation of PGPR gave the effect on number tillers, plant height, but did not gave the effect on rice yield. Isolate R11 was the the best isolates that gave the effect on rice plant growth.

Introduction
Rice is the main food crops as a source of carbohydrates, protein, and vitamins for the people of Indonesia. As a source of vitamins, rice is capable of a source of niacin, riboflavin with vitamin content ranging from 27-32% [1] The increase in population has spurred the increase in demand and the level of national rice consumption. Indonesia ranks 5th world with rice consumption per capita reaching 132 kg [2]. Fulfillment of national rice needs is pursued through the intensification program with very intensive agrochemical inputs, and lately it has led to the levelling-off symptons in rice production. This condition is a weakness of intensive agriculture so sustainability is very limited due to soil sickness which causes pests in the soil, disturbances in physico-chemical physical properties, and autotoxicity [3] An environmentally friendly technology approach in rice production can be carried out with the application of bioameliorant through the application of useful organic manure and beneficial microorganism that can increase growth and health of plants. The use of bacteria or often called Plant Growth Promotion Rhizobacteria (PGPR) can increase plant growth through nitrogen fixation activities, nutrient solubilization, antibiotic production and production of growth regulators. [4] reported that application of bioameliorant combined with a consortium of bacteria and Trichoderma sp. has increased rice productivity and induced systemic resistance of the rice plant to brown spot, sheath rice blight and bacterial leaf blight diseases.
The strategy for obtaining adaptive PGPR and being able to stimulate rice plant growth is carried out by isolating it from plant rhizosphere so that bacteria indigenous to paddy fields will be obtained. [5] stated that application rhizobacteria as biofertilizers have potencial as biofertilizer to replace chemical fertilizers and pesticides for rice production. Various PGPR have been isolated from paddy soil such as Rhizobium sp. LM-5, Herbaspirillum sp., Burkholderia sp., Pseudacidovorax sp., Azospirillum sp. [6,7]. [8] reported that Bacillus megaterium and Arthrobacter chlorophenolicus showed positive result in N 2 fixation and phosphate solubilization. Inoculation of Azotobacter chroococcum, and Azpspirillum brasilense in rice production gave significant effect on plant growth attributes, yield and also saving of 50 percent of chemical fertilizer [9]. The aims of this research was to study the effect of indigenous PGPR on rice growth attributes and yield.

Materials and Methods
Pots experiment was conducted in Green House of Experimental Farm, Agriculture Faculty of Jenderal Soedirman University Purwokerto from September 2017 until January 2018. Inceptisol soil was used as growth medium.
The experimental design was a randomized completely block design with three replications. The treatments were 9 the isolates of PGPR from rice rhizosphere and control without inoculation of PGPR. The strains of PGPR were used in this research consisted of 9 isolates of PGPR and control. Before the application, PGPR was grown in NB medium (Himedia). One ose of isolate was strike into NB medium and then shaking for 72 hours with 120 rpm. Rice seeds was sterillization by using ethanol for 1 minute and soaking with sterile aquades. Rice seeds was germinated in petridish. Rice seedling was transplated at 21 days after sowing. Rice seedling were inoculated by soaking of seedling in to PGPR solution for 5 minutes, and then planted with 2 seedling per polybag. Fertilizer application consisted of urea 50 kg ha -1 , Super Phosphate (SP-36) 150 kg ha -1 , and KCl 150 kg ha -1 .
The observation variables were plant height, number of tillers, leaf area [10], plant biomassa, leaf greenness (measured with SPAD-502 Plus Chlorophyll meter, Conica-Minolta), number of productive tillers, panicle lenght, number of grains per panicle, 1000 grains weight, grains yield (at 14 % of water contents). The data were analysed by ANOVA (SAS 9.1), if the result significant different was continued by Duncan Multiple Range Test at 95% confidence level.

Effect of PGPR inoculation on rice plant growth
Plant Growth Promotion Rhizobacteria as useful microorganisms for the growth of rice plants can affect plant growth through colonization in root areas. The ability to colonize and dominate the rhizosphere will have mutually beneficial interactions between plants and microbes so that plant growth increases. The treatment of inoculation through soaking the roots of rice seedlings showed a significant effect on plant growth through plant height and the number of tillers per clump in the maximum vegetative phase Inoculation with isolate R04 showed the highest plant height reached 80.76 cm ( Figure 1). PGPR inoculation can stimulate the growth of very large plant heights. Increased plant height ranged from 14.81 -26.23 percent to control. This condition indicates that PGPR inoculation in rice plants can increase vegetative growth well. This is also seen in the variable number of tillers per clump. The number of tillers of rice plants increased in the provision of PGPR inoculation compared to without inoculation. The increase in the number of tillers increased by 113 percent against the control without PGPR inoculation. The highest number of total tillers was generated in the R08 isolate inoculation treatment of 12.42 tillers, although there were no significant differences with the inoculations of P10 and R01 isolates 12 and 12.33 tillers per clump respectively (Figure 2).

Figure 3. Effect PGPR inoculatin on leaf greenness of rice
Inoculation of PGPR in rice has not given a significant effect on the variable greenness of leaves, leaf area, and root length. In the greenness of the leaves, it was seen that the greenish value of the leaves ranged from 30.12 to 32.14 obtained in the inoculation of S03 isolates. The greenish value of leaves is one of the factors that influence C assimilation activity, where the main constituent of leaf properties is the chlorophyll pigment. Chlorophyll acts as a reaction center for photosynthesis. Chlorophyll levels are more influenced by leaf N levels. Inoculation has no effect on leaf greennes due to the supplai of N derived from inorganic fertilizer or soil which have been able to supply sufficient N plants. In conditions of N nutrient adequacy, the activity of soil microorganisms such as fixation activities will be disrupted, and plant chlorophyll is highly influenced by N nutrients derived from inorganic fertilizers [11].
PGPR inoculation has an effect on increasing leaf area. PGPR inoculation can increase leaf area to 91.10 percent compared to control. The higher leaf area reached in the treatment of PGPR isolates J04 and R08 reached 838.15 cm2 and 823.54 cm2 respectively (Figure 4). The increase in leaf area of the plant has to do with the increase in the number of tillers in the PGPR inoculation treatment. The ability of PGPR to colonize roots so that they can utilize root exudates and produce fitohormones, especially IAA, can increase root length so that nutrient uptake of plants increases.
The data show that the treatment of various PGPR isolates was able to increase the total root length to 94.56 percent compared to control. The rice plants treated with PGPR inoculation had an average root length of 2509.54 cm, while the root length of the control plants only reached 1289.88 cm. The longest root length of rice plants was achieved in the inoculation treatment with R08 isolates reaching 3209.64 cm ( Figure 5). PGPR affects the root growth of rice plants with an increase outside the root surface and root lenght.
[12] stated that the content of fitohormones such as IAA had a positive effect on plant growth and development such as root growth so as to increase the uptake of water and mineral absorption from nutrient-rich pool of soil. Inoculation of bacteria was able to stimulate the growth of rooting of wheat plants where an increase the number of root tips and branches was 60 and 68 percent respectively.

The Effect of PGPR inoculation on yield and yield components of rice.
The yield of rice plants in general is determined by variations in yield components such as the number of productive tillers, panicle length, and the weight of 1000 seeds. The results showed that inoculation bacteria had no effect on the variable number of productive tillers, panicle length, and weight of 1000 seeds ( Table 1).
The number of tillers in the generative phase will decrease from the total number of tillers formed in the vegetative phase. Nutritional status plays a role in determining the small number of productive tillers. Availability of nutrients from inorganic fertilizers both in the treatment of PGPR and control caused no differences effect in the variable number of tillers, panicle length, and weight of 1000 seeds. The results showed that inoculation of bacteria did not provide significant differences on rice yields. The grain yield per clump in the inoculation bacteria treatment was able to reach an average of 12.27 g, while in control plants it only produced an average of 8.45 g per clump. This indicates an increase in yield of 45.19 percent towards control. The highest yield was obtained from the isolate R11 treatment reached 12.94 g per clump, followed by the treatment of isolates P10, R08, and J04 capable of producing grain of 12.57, 12.32, and 12.32 g per clump respectively ( Figure 6).

Conclusions
Inoculation of indigenous PGPR was able to increase the growth of rice plants, especially plant height, and the number of total tillers, however, the treatment of PGPR inoculation has not been able to increase the yield of aromatic rice (Oryza sativa cv. Inpago UNSOED 1). The isolate R11 treatment gave the highest grain yield of 12.94 g per clump.


text:
DEVELOPMENT AND VALIDATION OF ANALYTICAL METHOD FOR QUANTIFICATION OF ACETIC ACID CONTENT IN AMLODIPINE BESYLATE

Objective: To develop and validate a simple and accurate cost-effective titrimetric method according to International Conference Harmonization (ICH) guidelines for acetic acid content in Amlodipine Besylate.
Methods: The titration based on general acid-base reaction to form water and salt. Sodium hydroxide act as a strong base and titrated against weak acid (acetic acid). Phenolphthalein used as an indicator and colorless to pink is the endpoint. Sodium hydroxide is standardized with primary standard potassium hydrogen phthalate.
Results: The method was linear in the range of 0.75 to 30.25 μg/ml with a correlation coefficient 0.9999. Limit of detection (LOD) and limit of quantitation (LOQ) value were found to be 0.61 and 1.85 μg/ml, respectively. The percentage recovery (98.20–99.97%) and percentage relative standard deviation (%RSD) is less than 2% within the acceptable limit of ICH guidelines. The robustness and ruggedness results were excellent. Method is accurate and precise, no interference from excipients.
Conclusion: A new analytical titrimetric method was developed and validated as per ICH guidelines for the determination of acetic acid content in amlodipine. This proposed method applied for routine analysis of acetic acid content in bulk and pharmaceutical formulations of amlodipine besylate.

Fig. 1: Structure of amlodipine
Acetic acid (CH3COOH) is an important component of vinegar and act as mild chelating agent. The other name of acetic acid are methane carboxylic acid, ethylic acid and ethanoic acid. Acetaldehyde used for the preparation of acetic acid, followed by catalytic oxidation. During this synthesis, two byproducts, formaldehyde and formic acid were formed. The chemical exposures can make irritation in nose, cough and throat. The other symptoms are considered headache, vomiting, nausea, eye pain and impaired vision [3][4][5][6]. The acetic acid content was amperometrically determined in fermentation broths [7], museum cabinets with ion chromatography [8], fruits juices and drinks with high performance liquid chromatography [9], during hydrothermal treatment of birch wood utilizing gas chromatography [10], pectin samples with gas chromatography-mass spectrophotometry [11] and amlodipine besylate using gas chromatography [12].
Analytical method can be used for routine analysis when it fulfills certain performance criteria. Once the analytical method is advent, it is necessary to decide its suitability for the intended purpose, defined as method validation. Several international organizations and regulatory authorities, the namely international union of pure and applied chemistry, international laboratory accreditation conference, western european laboratory accreditation cooperation, an international conference on harmonization and international organization for standardization are involved to develop and modify the criteria of validation. The important validation parameters are accuracy, precision, selectivity, specificity, limits of detection and quantitation, robustness and ruggedness. However, when a method is validated, the role of statistical analysis cannot be ignored. It is the only way to get the most conclusive results from the mathematical data during the analysis.
The main reason of impurities presents in the final products because of raw materials, intermediates, solvents as well as byproducts during synthetic process. It may be organic impurities or residual solvents. The presence of residual solvents affects the efficacy of drug products. The ICH guidelines showed disadvantages of residual solvent available in the final product and limited it in terms of safety [13][14][15][16][17]. Due to its toxicity behavior [18], it was necessary to adopt a new simple and cost-effective method for the determination of acetic acid. The titrimetric method [19][20][21] are low cost and easily available in academic and research laboratory. The proposed method was developed and validated for the determination of acetic acid content in pharmaceutical formulations for amlodipine besylate.
• Phenolphthalein was purchased from Sigma Aldrich, USA.
• Ethanol was purchased from Carlo Erba Reagents, France.
• All chemicals were of analytical grade.

Procedure Standardization
The sodium hydroxide solution standardized with primary standard potassium hydrogen phthalate. 40.84 mg KHP transferred into a 250 ml erlenmeyer flask and added 20 ml distilled water to dissolve. Two drops of phenolphthalein (0.1%) used as indicator. Titration with sodium hydroxide continued until pink color changed to colorless. The replicate analyses repeated for two more times to get the average volume of sodium hydroxide, used to calculate the exact molar concentration of sodium hydroxide.

General
The acetic acid in the form of solution transferred 250 ml conical flask. Two drops of phenolphthalein indicator added to the flask and titrated with sodium hydroxide (0.01 M) until the color of the solution changed from pink to colorless and recorded the volume [22]. Different amount of acetic acid and volume of NaOH applied to construct a calibration curve and adopted a linear equation, which followed the linearity law. The unknown concentration/amount of acetic acid quantified in amlodipine besylate using the linear calibration curve.

Pharmaceutical formulations
To determine acetic acid content in pharmaceutical dosage form (Amlopine5, Amlor, Exforge label claim: 5 mg amlodipine per tablet/capsule), two tablets grinded and finely powdered using mortar and pestle. Then the powder placed into a 100 volumetric flask containing 50 ml water and sonicated for 5 min, then diluted upto the mark with distilled water. The solution filtered using 0.45 μm filter (Millipore, Milford). A 20 ml otest solution used for titration with standard NaOH (0.01 M) solution in the presence phenolphthalein indicator. The same procedure performed with other pharmaceutical formulations of amlodipine besylate to determine acetic acid content.

Specificity
The system suitability test will confirm the ability of the proposed method to determine the analyte accurately in a sample matrix in the presence of other components.

Accuracy
The closeness between the standard values with experimental values found during the analysis. The percentage recovery was important parameter related to accuracy.

Precision
The closeness between all of the results of replicate analysis were determined for the proposed method. There is no relation with the true value under stipulated conditions.

Limit of detection
Limit of detection indicates the point how the uncertainty of our results associate with the measured value. The LOD value was not necessary to quantify but this value was the lowest concentration in the sample matrix to be detected. LOD =3.3×So/b Where So and b are standard deviation and slope of the standard calibration curve, respectively.

Limit of quantitation
Limit of quantitation is the highest acceptable precision with lowest concentration of analyte in the sample matrix and quantified.

Linearity
The concentration of analyte was directly proportional to the results of the analysis within a given range.

Linear range
The peak areas of derivatives formaldehyde standard were directly proportional to the volume of sample over the concentration range. A known confidence level can be established by utilizing the linear calibration model.

Ruggedness
Small changes in the environment conducted experiments and model of the instrument means little variation with operating conditions as compared to the normal proposed method of analysis.

Robustness
The proposed analytical method varied with an acceptable limit. The results were unaffected by small changes in the parameters.

System suitability
The system suitability test was performed for the proposed method by utilizing 25 μg/ml standard acetic acid solution. The same concentration titrated six times with NaOH and recorded the volume. The percentage relative standard deviation (%RSD) was calculated and found it is in the acceptable limit of ICH guideline.

Linearity and range
The linearity was compliance with the regression plots in the concentration range of 0.75-30.25 μg/ml with a correlation coefficient (r 2 ) of 0.9999. The linear graph between concentrations of CH3COOH and volume of NaOH given in fig. 2. The linearity range, slope, intercept, linear regression equation, limit of detection, limit of quantitation summarized in table 1 and indicated good linearity over the working concentration ranges.

LOD and LOQ
The standard deviation (So), calculated between concentration of acetic acid (µg/ml) and its respective NaOH (ml) using the linearity data. The LOD and LOQ values evaluated depend on slope (b) of the straight line. The values were 0.61 and 1.85 (µg/ml) respectively (table 1). The precision of LOD value stidied, since 0.75 µg/ml gave NaOH volume 1.3 ml, therefore carried out precision with 0.5 µg/ml, which would give NaOH volume 1 ml, lowest volume had the ability to neutralize the acid content in normal conditions. The % RSD of acetic acid solution (0.5 µg/ml) 16.2% with five replicate titrated volume of NaOH and meet the acceptance criteria (NMT 20%). The % RSD was calculated 8.85 and 17.25 % with 1.90 and 1.0 μg/ml respectively. Therefore, %RSD is very low for 1.90 µg/ml compared to 1.0 µg/ml. The % RSD value for 1.0 µg/ml was very close to the acceptance limit of 20%. Therefore, the LOD and LOQ of the method were found to be 0.5 and 1.0 µg/ml respectively.

Robustness
The robustness study carried out in different laboratories. The system suitability investigated and results were accepted within the limit. The % RSD (0.582-1.70 %) were calculated and tabulated in table 3.

Ruggedness
Ruggedness studies of the proposed method performed by selecting three concentration levels within the linearity range. The test result was expressed in terms of %RSD, applied the same procedure by two analyst using different burettes. The %RSD values were less than 2 % for the developed method. These results showed excellent ruggedness value of the method (table 4).

Solution stability
The solutions kept for seven days and performed the analysis every day. The % RSD was calculated with five replicate values of the same concentration. It was found that the solutions were stable and suitable for the analysis after 7 d because calculated % RSD values were in the range of ICH limit (2%).

Acetic acid content in pharmaceutical formulations
The formulation samples were titrated with standard NaOH solution. No color change and endpoint were not detected. Therefore, acetic acid content are not available with the present pharmaceutical formulations of amlodipine besylate and result is similar to developed gas chromatographic method [12].

CONCLUSION
The analytical method for the estimation of acetic acid in amlodipine besylate has been successfully validated. The proposed method for pharmaceutical formulation does not require any cleanup procedure for the analysis,. It has a wider linear dynamic range with good accuracy and precision. It is a simple and accurate time-consuming method, whereas there is no official method for its determination. The %RSD value was obtained, accurate and within the acceptable limit of ICH guidelines. Thus the present method is satisfactorily a better method for the determination of acetic acid content in the pharmaceutical dosage form of amlodipine besylate

AUTHORS CONTRIBUTIONS
SK Manirul Haque: Formulated the study, helped in literature searches, wrote the first draft, gave the answer of all reviewers comment and approved the final version to be submitted.
Ayman Ahmad: Managed literature survey, performed all experiments, collected data and approved the final version to be submitted.


extfieldsofstudy: Mathematics Medicine

text:
Identification and classification of honey’s authenticity by attenuated total reflectance Fourier-transform infrared spectroscopy and chemometric method

Background and Aim: The authentication of honey is important to protect industry and consumers from such adulterated honey. However, until now, there has been no guarantee of honey’s authenticity, especially in Indonesia. The classification of honey is based on the bee species (spp.) that produces it. The study used honey from sting bee Apis spp. and stingless bee Tetragonula spp. based on the fact that the content off honey produced between them has differences. Authenticating honey with currently available rapid detection methods, such as 13C nuclear magnetic resonance analysis, is costly. This study aimed to develop an inexpensive, fast, precise, and accurate classification method for authenticating honey. Materials and Methods: In this study, we use attenuated total reflectance Fourier-transform infrared (ATR-FTIR) spectroscopy with wavelengths ranging between 550 and 4000 cm−1 as an alternative analysis method, which is relatively less expensive. The spectra of authentic and fake honey samples were obtained using ATR-FTIR and plotted using chemometric discriminant analysis. The authentic honey samples were acquired from a local Indonesian breeder of honey bees, while the fake honey samples were made from a mixture of water, sugar, sodium bicarbonate, and authentic honey. Data were collected using Thermo Scientific’s OMNIC FTIR software and processed using Thermo Scientific’s TQ Analyst software. Results: Our method effectively classified the honey as authentic or fraudulent based on the FTIR spectra. To authenticate the honey, we formed two classes: Real honey and fake honey. The wavelengths that can best differentiate between these two classes correspond to four regions: 1600-1700 cm−1; 1175-1540 cm−1; 940-1175 cm−1; and 700-940 cm−1. Similarly, for classification purpose, we formed two classes: Apis spp. and Tetragonula spp. The wavelength region that can best classify the samples as belonging to the Apis spp. or Tetragonula spp. class is explicitly within the range of 1600-1700 cm−1. Conclusion: This study successfully demonstrated a method to rapidly and accurately classify and authenticate honey. ATR-FTIR is a useful tool to test the authenticity of honey.

Introduction
Honey is a complex compound derived from a process called nectar synthesis, in which honey bees collect nectar from plants [1]. Honey has well-known therapeutic potential, including wound healing and infection prevention [2]. Honey is very famous for its potential therapeutic role in the treatment of disease by phytochemical, antimicrobial, anti-inflammatory, and antioxidant properties [3]. There are three types of honey bees in Indonesia: Giant honey bees (Apis dorsata), beekeeping honey bees (Apis cerana and Apis mellifera), and stingless bees Melipona [2]. The content of honey produced by Apis spp. and stingless bee has some differences. Honey produced by Apis spp. has a sugar content of 62-70% and a water content of 14.86-17.53% [4]. Honey produced by stingless bee has a sugar content of 44.08% and a water content of 30%-35%. Due to their small size, stingless bee has a low honey yield per colony; thus, the cost of honey derived from stingless bees is much higher than that of honey derived from other bee species [5]. Many people consume honey due to the health benefits it provides [6], and the consumption of honey as a natural supplement has been on the rise over the past few decades. Unfortunately, the supply of honey in nature cannot meet this demand. According to the Ministry of Environment and Forestry in Indonesia, the demand for honey in Indonesia in 2015 reached 7500 tons/year, whereas the supply only reached 5000 tons/year. Exploitation of this supply-demand problem has led to the manufacture of adulterated and fake honey through the addition of other food ingredients [7]. For example, honey has been deliberately diluted with high-fructose corn syrup -an inexpensive sweetener that has been linked to diabetes. Adulation of honey not only deceives health-conscious consumers but also destabilizes economic markets by introducing unfair competition.
A rapid, sensitive, inexpensive, and accurate method to detect the authenticity of honey is critically needed to address this problem. However, currently available rapid detection methods do not provide a level of accuracy sufficient to perform authenticity validation [8]. Moreover, many of these methods have low levels of precision [9]. The authenticity of the botanical origin of bee products is typically determined by organoleptic sensory analysis, physicochemical methods, and pollen analysis [7]. The authenticity of the geographical region of origin is determined by melissopalynological characterization methods [7]. However, these analyses require specialized expertise and are time-consuming [7]. In our experiment, the authenticity of honey was tested using gas chromatography (GC) to analyze the presence of ethanol and carbon dioxide (CO 2 ) [10]. Real honey should contain oxygen (O 2 ) but not CO 2 . Hydrogen peroxide, a compound naturally found in honey, is unstable and decomposes to O 2 and water (H 2 O). One case of the fake honey found that they use sodium bicarbonate (NaHCO 3 ) to produce bubble (like fresh natural honey), which produces CO 2 [10].
To analyze and authenticate honey samples, we developed an innovative method based on attenuated total reflectance Fourier-transform infrared (ATR-FTIR) spectroscopy and chemometric discriminant analysis. The advantage of this approach is that it relies on the fact that every chemical compound has a unique and specific IR spectrum. Thus, the obtained spectra are representative of the characteristics of an organic sample as a whole [11]. FTIR spectroscopy can be used to non-destructively and rapidly obtain biochemical fingerprints of samples [12]. The crystal used in ATR cells is made from zinc selenide (ZnSe), and its low solubility in water and very high refractive index enable more precise measurements [13]. Moreover, the ATR-FTIR method has several advantages -it is relatively inexpensive, provides rapid quantification, does not damage the sample, eliminates the need for sample preparation, and requires only a small sample amount to perform the measurements [14].
This study aimed to develop an inexpensive, fast, precise, and accurate classification method for authenticating honey.

Ethical approval
This in vitro study did not need ethical approval from the University Ethics Committee.

FTIR samples
For this study, we used a total of 85 samples consisting of 58 samples of real honey and 27 samples of fake (adulterated) honey. Real honey was collected from different geographical regions of Indonesia and represented various floral origins. Most of the samples were collected directly from primary honey producers.
The samples of real honey were produced by A. cerana (n=5), A. mellifera (n=19), A. dorsata (n=17), Tetragonula spp. (n=10) (stingless bee), and other stingless bee species (n=7). The 27 fake honey samples were made by mixing real honey with water, sucrose, and NaHCO 3 . Honey samples were grouped as either real or fake for identification purposes. For classification purposes, the honey samples were labeled as Apis spp. and Tetragonula spp.

Instrumentation and samples analysis
Spectra from all samples were collected with Nicolet iS5 FTIR spectrometer ( Thermo Fisher Scientific Inc., Waltham, MA, USA) equipped with an iD3 ATR accessory component. OMNIC software version 9 (Thermo Fisher Scientific Inc., Waltham, MA, USA) was used for spectral data acquisition. Samples were placed on a diamond/ ZnSe crystal plate (Thermo Fisher Scientific Inc., Waltham, MA, USA) and scanned at room temperature from 550 to 4000 cm −1 for a 16 scan time with a resolution of 16 cm −1 . Measurements for each sample were replicated 3 times, and the resulting identical spectra were analyzed. This process was done to evaluate the absorbance value accuracy, which could be affected by sample homogeneity. Propanol was used to clean the diamond between each sample measurement.

Chemometrics
Discriminant analysis with TQ Analyst software (Thermo Fisher Scientific Inc., Waltham, MA, USA) was performed to classify the samples based on spectral differences. In this work, discriminant analysis was performed for the determination of spectral differentiation. In this work, discriminant analysis was conducted on ATR-FTIR spectra with the following wavelength ranges: 2800-3000 cm −1 , 1600-1700 cm −1 , 1175-1540 cm −1 , 940-1175 cm −1 , and 700-940 cm −1 .

ATR-FTIR analysis
Figure-1 shows a real honey ATR-FTIR spectrum, which is divided into five specific regions. The band assignments and corresponding modes of vibration are shown in Table-1, based on Gok, 2014 [15]. The ATR-FTIR spectrum for real honey in the 550-4000 cm −1 spectral region is shown in Figure-2.

Discriminant analysis
The different spectral region was applied to discriminant analysis, as shown in Figure-3. For identification purpose, the samples are divided into two groups: Real honey and fake honey. The spectra of real honey and fake honey are indicated by the square and triangle symbols, respectively. The calculated result of selected regions for identification purposes (real vs. fake honey samples) is shown in Table-2. As shown in Figure-3a, the spectrum of fake honey fell within the spectrum of real honey because the spectral region covered the whole area (the 500-4000 cm −1 region). The performance index for Figure-3a was 88.7, and there were seven samples that were misclassified. In Figure-3b, there are two regions separating real honey (square symbols) and fake honey (triangle symbols). The results are shown in Figure-3b -in which the performance index is 91.8   and no samples are misclassified -represent the best results following many trials. The spectral differences correspond to four regions: 1600-1700 cm −1 , 1175-1540 cm −1 , 940-1175 cm −1 , and 700-940 cm −1 . As shown in Table-2, the best performance index is obtained when we use regions 2-5. For classification purposes, the samples were divided into two classes: Apis spp. and Tetragonula spp. The spectra of honey from Apis spp. and Tetragonula spp. are indicated by the square and triangle symbols, respectively. Figure-4a and b are scatter plots of the discriminant analysis when the performance index is 88.2 and 95.4, respectively. In Figure-4a, we can see that a spectrum was misclassified (red circle), whereas no spectra were misclassified in Figure- Table-3. The best performance index for the classification of honey is 95.4 and no samples were misclassified when we use region 2 only.
The purpose of the trial is to precisely find where the spectral region differs. There are significant spectral differences between honey which are produced by Apis spp. and Tetragonula spp.

Discussion
Ethanol in small quantities is a natural component of pure honey, and it is equivalent to <1% of the sugar content of honey [16]. Ethanol is produced by bacterial metabolism in the honey stomach of honey bees. Freshly harvested honey has a higher ethanol concentration due to the fermentation process in the honey bee stomach, and this concentration decreases overtime with evaporation. Previous study established that honey is considered a fermented food product due to the lactic acid bacteria (LAB) involved in the production process; a novel bacteria flora composed of LAB of the genera Lactobacillus and Bifidobacterium, which originated in the honey stomach of honey bees, was discovered [17]. The honey stomach represents an optimal niche for LAB because it is filled with nectar sugar and nutrients, and it operates at a fairly optimal temperature of 35°C in the hive [17,18].
Because the concentration of ethanol in honey depends on when the honey was harvested, some fake honey samples can contain ethanol while others contain no ethanol. Therefore, ethanol GC cannot be used as a valid method to test the authenticity of honey.
Testing of CO 2 content revealed that honey from Apis spp. does not contain CO 2 , while honey from Tetragonula spp. does contain CO 2 , as characterized by a peak at a retention time of 2 min. This testing  indicates that the honey samples produced by Apis spp. are original (naturally produced) because they do not contain CO 2 . Honey produced by Tetragonula spp. contains a small amount of CO 2 (0.100%). It is possible that Tetragonula spp. have a metabolic pathway that produces CO 2 , so the characteristics of the honey produced by these bees need to be further investigated. Because research on honey produced by Tetragonula spp. is very limited, it is difficult to control the quality of this honey as compared with the honey of A. mellifera, a more widely studied bee species [19].
The presence of ethanol and CO 2 using GC methods cannot be used to identify the authenticity of honey. The results of this study showed the potential power of ATR-FTIR spectroscopy as an automated and highly sensitive method to differentiate between real and fake honey samples and between Apis spp. and Tetragonula spp. [20]. In this study, ATR-FTIR spectroscopy was used to compare honey samples based on their spectral differences in the 550-4000 cm −1 region. The crystal used in the ATR cells is made from materials that have a low solubility in water and a very high refractive index [21].
The discriminant analysis method successfully classified the honey samples based on their ATR-FTIR spectra [22]. There are four wavelength ranges that can best distinguish between the real and fake honey samples: 1600-1700 cm −1 , 1175-1540 cm −1 , 940-1175 cm −1 , and 700-940 cm −1 . For classification of the honey samples, the wavelength range of 1600-1700 cm −1 can best differentiate between Apis spp. and Tetragonula spp. Our proposed method is straightforward and suitable for the large-scale industrial monitoring of honey samples.
The discriminant analysis result shown the spectral differences correspond to four regions: 1600-1700 cm −1 , 1175-1540 cm −1 , 940-1175 cm -1 , and 700-940 cm −1 . The best performance index is obtained when we use regions 2-5. While the trials for regions 1-5 have the same scores as the performance index, region 1 can be ignored because it is a region of group frequency. The group frequency region of 2800-3000 cm −1 shows the absorption of C-C and C-H compounds; thus, this region can be ignored because it is common among all of the organic compounds.
The region of 800-1500 cm −1 corresponds to the absorption zones of the three major sugar  b a constituents of honey: Fructose, glucose, and sucrose. The 750-900 cm −1 region is the anomeric region and is characteristic of the saccharide configurations. The bands in the 904-1153 cm −1 region are assigned to C-O and C-C stretching modes, and those around 1199-1474 cm −1 are due to the bending modes of O-C-H, C-C-H, and C-O-H angles. Negative bands were observed within the 1618-3635 cm −1 region. These bands are due to a lower water concentration in the honey sample compared with the reference employed and the fact that water presents an O-H stretching overtone at the corresponding wavelengths [23]. For classification purposes in the result shown, the best performance index for the classification of honey is 95.4, and no samples were misclassified when we use region 2 only. The bands in the region of 1600-1700 cm −1 had been previously assigned as amide I protein vibrations. Proteins are minor component in honey; however, they are used in detecting adulteration [24]. The previous studies revealed that pollen proteins could be used as a marker for taxonomic classification of honey. The bands appearing in the region of 1600-1700 cm −1 originated as a result of carbonyl group (C=O) and C≡C stretching, and this region was found to be related to phenolic molecules [25]. Phenolic compounds are linked to the biological origins of the nectar and pollen, and the species of the honey-producing bees [26][27][28]. However, water molecules show strong absorption between 1640 and 1650 cm −1 , so the discrimination in this region can be explained by the difference in protein and moisture content, and water-carbohydrate interactions between sample groups [15].
Our several studies have been associated with bioactive compounds from stingless bee and Apis spp. honey with many other medicinal effects, as it was shown to have anti-inflammatory, antioxidant, antibacterial, and antidiabetic activity [29][30][31].

Conclusion
We suggest a method to rapidly and accurately classify and authenticate honey using ATR-FTIR spectroscopy and chemometric method. This method successfully demonstrated to differentiate the authenticity and classification of honey based on the honey's spectrum.